Patent Grant
9017942
Analysis of specific cells can give insight into a variety of diseases. These analyses can provide non-invasive tests for detection, diagnosis and prognosis of diseases such as cancer or fetal disorders, thereby eliminating the risk of invasive diagnosis. Regarding fetal disorders, current prenatal diagnosis, such as amniocentesis and chorionic villus sampling (CVS), are potentially harmful to the mother and to the fetus. The rate of miscarriage for pregnant women undergoing amniocentesis is increased by 0.5-1%, and that figure is slightly higher for CVS. Because of the inherent risks posed by amniocentesis and CVS, these procedures are offered primarily to older women, e.g., those over 35 years of age, who have a statistically greater probability of bearing children with congenital defects. As a result, a pregnant woman at the age of 35 has to balance an average risk of 0.5-1% to induce an abortion by amniocentesis against an age related probability for trisomy 21 of less than 0.3%.
Regarding prenatal diagnostics, some non-invasive methods have already been developed to screen for fetuses at higher risk of having specific congenital defects. For example, maternal serum alpha-fetoprotein, and levels of unconjugated estriol and human chorionic gonadotropin can be used to identify a proportion of fetuses with Down's syndrome. However, these tests suffer from many false positive. Similarly, ultrasonography is used to determine congenital defects involving neural tube defects and limb abnormalities, but such methods are limited to time periods after fifteen weeks of gestation and are present unreliable results.
The presence of fetal cells within the blood of pregnant women offers the opportunity to develop a prenatal diagnostic that replaces amniocentesis and thereby eliminates the risk of today's invasive diagnosis. However, fetal cells represent a small number of cells against the background of a large number of maternal cells in the blood which make the analysis time consuming and prone to error.
With respect to cancer diagnosis, early detection is of paramount importance. Cancer is a disease marked by the uncontrolled proliferation of abnormal cells. In normal tissue, cells divide and organize within the tissue in response to signals from surrounding cells. Cancer cells do not respond in the same way to these signals, causing them to proliferate and, in many organs, form a tumor. As the growth of a tumor continues, genetic alterations may accumulate, manifesting as a more aggressive growth phenotype of the cancer cells. If left untreated, metastasis, the spread of cancer cells to distant areas of the body by way of the lymph system or bloodstream, may ensue. Metastasis results in the formation of secondary tumors at multiple sites, damaging healthy tissue. Most cancer death is caused by such secondary tumors. Despite decades of advances in cancer diagnosis and therapy, many cancers continue to go undetected until late in their development. As one example, most early-stage lung cancers are asymptomatic and are not detected in time for curative treatment, resulting in an overall five-year survival rate for patients with lung cancer of less than 15%. However, in those instances in which lung cancer is detected and treated at an early stage, the prognosis is much more favorable.
The methods of the present invention allow for the detection of fetal cells and fetal abnormalities when fetal cells are mixed with a population of maternal cells, even when the maternal cells dominate the mixture. In addition, the methods of the present invention can also be utilized to detect or diagnose cancer.
The present invention relates to methods for the detection of fetal cells or cancer cells in a mixed sample. In one embodiment, the present invention provides methods for determining fetal abnormalities in a sample comprising fetal cells that are mixed with a population of maternal cells. In some embodiments, determining the presence of fetal cells and fetal abnormalities comprises labeling one or more regions of genomic DNA in each cell from a mixed sample comprising at least one fetal cell with different labels wherein each label is specific to each cell. In some embodiments, the genomic DNA to be labeled comprises one or more polymorphisms, particularly STRs or SNPs
In some embodiments, the methods of the invention allow for simultaneously detecting the presence of fetal cells and fetal abnormalities when fetal cells are mixed with a population of maternal cells, even when the maternal cells dominate the mixture. In some embodiments, the sample is enriched to contain at least one fetal and one non fetal cell, and in other embodiments, the cells of the enriched population can be divided between two or more discrete locations that can be used as addressable locations. Examples of addressable locations include wells, bins, sieves, pores, geometric sites, slides, matrixes, membranes, electric traps, gaps, obstacles or in-situ within a cell or nuclear membrane.
In some embodiments, the methods comprise labeling one or more regions of genomic DNA in each cell in the enriched sample with different labels, wherein each label is specific to each cell, and quantifying the labeled DNA regions. The labeling methods can comprise adding a unique tag sequence for each cell in the mixed sample. In some embodiments, the unique tag sequence identifies the presence or absence of a DNA polymorphism in each cell from the mixed sample. Labels are added to the cells/DNA using an amplification reaction, which can be performed by PCR methods. For example, amplification can be achieved by multiplex PCR. In some embodiments, a further PCR amplification is performed using nested primers for the genomic DNA region(s).
In some embodiments, the DNA regions can be amplified prior to being quantified. The labeled DNA can be quantified using sequencing methods, which, in some embodiments, can precede amplifying the DNA regions. The amplified DNA region(s) can be analyzed by sequencing methods. For example, ultra deep sequencing can be used to provide an accurate and quantitative measurement of the allele abundances for each STR or SNP. In other embodiments, quantitative genotyping can be used to declare the presence of fetal cells and to determine the copy numbers of the fetal chromosomes. Preferably, quantitative genotyping is performed using molecular inversion probes.
The invention also relates to methods of identifying cells from a mixed sample with non-maternal genomic DNA and identifying said cells with non-maternal genomic DNA as fetal cells. In some embodiments, the ratio of maternal to paternal alleles is compared on the identified fetal cells in the mixed sample.
In one embodiment, the invention provides for a method for determining a fetal abnormality in a maternal sample that comprises at least one fetal and one non fetal cell. The sample can be enriched to contain at least one fetal cell, and the enriched maternal sample can be arrayed into a plurality of discrete sites. In some embodiments, each discrete site comprises no more than one cell.
In some embodiments, the invention comprises labeling one or more regions of genomic DNA from the arrayed samples using primers that are specific to each DNA region or location, amplifying the DNA region(s), and quantifying the labeled DNA region. The labeling of the DNA region(s) can comprise labeling each region with a unique tag sequence, which can be used to identify the presence or absence of a DNA polymorphism on arrayed cells and the distinct location of the cells.
The step of determining can comprise identifying non-maternal alleles at the distinct locations, which can result from comparing the ratio of maternal to paternal alleles at the location. In some embodiments, the method of identifying a fetal abnormality in an arrayed sample can further comprise amplifying the genomic DNA regions. The genomic DNA regions can comprise one or more polymorphisms e.g. STRs and SNPs, which can be amplified using PCR methods including multiplex PCR. An additional amplification step can be performed using nested primers.
The amplified DNA region(s) can be analyzed by sequencing methods. For example, ultra deep sequencing can be used to provide an accurate and quantitative measurement of the allele abundances for each STR or SNP. In other embodiments, quantitative genotyping can be sued to declare the presence of fetal cells and to determine the copy numbers of the fetal chromosomes. Preferably, quantitative genotyping is performed using molecular inversion probes.
In one embodiment, the invention provides methods for diagnosing a cancer and giving a prognosis by obtaining and enriching a blood sample from a patient for epithelial cells, splitting the enriched sample into discrete locations, and performing one or more molecular and/or morphological analyses on the enriched and split sample. The molecular analyses can include detecting the level of expression or a mutation of gene disclosed in
In some embodiments, the sample can be enriched for epithelial cells by at least 10,000 fold, and the diagnosis and prognosis can be provided prior to treating the patient for the cancer. Preferably, the blood samples are obtained from a patient at regular intervals such as daily, or every 2, 3 or 4 days, weekly, bimonthly, monthly, hi-yearly or yearly.
In some embodiments, the step of enriching a patient's blood sample for epithelial cells involves flowing the sample through a first array of obstacles that selectively directs cells that are larger than a predetermined size to a first outlet and cells that are smaller than a predetermined size to a second outlet. Optionally, the sample can be subjected to further enrichment by flowing the sample through a second array of obstacles, which can be coated with antibodies that selectively bind to white blood cells or epithelial cells. For example, the obstacles of the second array can be coated with anti-EpCAM antibodies.
Splitting the sample of cells of the enriched population can comprises splitting the enriched sample to locate individual cells at discrete sites that can be addressable sites. Examples of addressable locations include wells, bins, sieves, pores, geometric sites, slides, matrixes, membranes, electric traps, gaps, obstacles or in-situ within a cell or nuclear membrane.
In some embodiments there are provided kits comprising devices for enriching the sample and the devices and reagents needed to perform the genetic analysis. The kits may contain the arrays for size-based separation, reagents for uniquely labeling the cells, devices for splitting the cells into individual addressable locations and reagents for the genetic analysis.
All publications and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference.
The present invention provides systems, apparatus, and methods to detect the presence of or abnormalities of rare analytes or cells, such as hematapoeitic bone marrow progenitor cells, endothelial cells, fetal cells, epithelial cells, or circulating tumor cells in a sample of a mixed analyte or cell population (e.g., maternal peripheral blood samples).
I. Sample Collection/Preparation
Samples containing rare cells can be obtained from any animal in need of a diagnosis or prognosis or from an animal pregnant with a fetus in need of a diagnosis or prognosis. In one example, a sample can be obtained from animal suspected of being pregnant, pregnant, or that has been pregnant to detect the presence of a fetus or fetal abnormality. In another example, a sample is obtained from an animal suspected of having, having, or an animal that had a disease or condition (e.g. cancer). Such condition can be diagnosed, prognosed, monitored and therapy can be determined based on the methods and systems herein. Animal of the present invention can be a human or a domesticated animals such as a cow, chicken, pig, horse, rabbit, dogs, cat, or goat. Samples derived from an animal or human can include, e.g., whole blood, sweat, tears, ear flow, sputum, lymph, bone marrow suspension, lymph, urine, saliva, semen, vaginal flow, cerebrospinal fluid, brain fluid, ascites, milk, secretions of the respiratory, intestinal or genitourinary tracts fluid.
To obtain a blood sample, any technique known in the art may be used, e.g. a syringe or other vacuum suction device. A blood sample can be optionally pre-treated or processed prior to enrichment. Examples of pre-treatment steps include the addition of a reagent such as a stabilizer, a preservative, a fixant, a lysing reagent, a diluent, an anti-apoptotic reagent, an anti-coagulation reagent, an anti-thrombotic reagent, magnetic property regulating reagent, a buffering reagent, an osmolality regulating reagent, a pH regulating reagent, and/or a cross-linking reagent.
When a blood sample is obtained, a preservative such an anti-coagulation agent and/or a stabilizer is often added to the sample prior to enrichment. This allows for extended time for analysis/detection. Thus, a sample, such as a blood sample, can be enriched and/or analyzed under any of the methods and systems herein within 1 week, 6 days, 5 days, 4 days, 3 days, 2 days, 1 day, 12 hrs, 6 hrs, 3 hrs, 2 hrs, or 1 hr from the time the sample is obtained.
In some embodiments, a blood sample can be combined with an agent that selectively lyses one or more cells or components in a blood sample. For example, fetal cells can be selectively lysed releasing their nuclei when a blood sample including fetal cells is combined with deionized water. Such selective lysis allows for the subsequent enrichment of fetal nuclei using, e.g., size or affinity based separation. In another example platelets and/or enucleated red blood cells are selectively lysed to generate a sample enriched in nucleated cells, such as fetal nucleated red blood cells (fnRBC's), maternal nucleated blood cells (mnBC), epithelial cells and circulating tumor cells. fnRBC's can be subsequently separated from mnBC's using, e.g., antigen-i affinity or differences in hemoglobin
When obtaining a sample from an animal (e.g., blood sample), the amount can vary depending upon animal size, its gestation period, and the condition being screened. In some embodiments, up to 50, 40, 30, 20, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 mL of a sample is obtained. In some embodiments, 1-50, 2-40, 3-30, or 4-20 mL of sample is obtained. In some embodiments, more than 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100 mL of a sample is obtained.
To detect fetal abnormality, a blood sample can be obtained from a pregnant animal or human within 36, 24, 22, 20, 18, 16, 14, 12, 10, 8, 6 or 4 weeks of gestation.
II. Enrichment
A sample (e.g. blood sample) can be enriched for rare analytes or rare cells (e.g. fetal cells, epithelial cells or circulating tumor cells) using one or more any methods known in the art (e.g. Guetta, E M et al. Stem Cells Dev, 13(1):93-9 (2004)) or described herein. The enrichment increases the concentration of rare cells or ratio of rare cells to non-rare cells in the sample. For example, enrichment can increase concentration of an analyte of interest such as a fetal cell or epithelial cell or CTC by a factor of at least 2, 4, 6, 8, 10, 20, 50, 100, 200, 500, 1,000, 2,000, 5,000, 10,000, 20,000, 50,000, 100,000, 200,000, 500,000, 1,000,000, 2,000,000, 5,000,000, 10,000,000, 20,000,000, 50,000,000, 100,000,000, 200,000,000, 500,000,000, 1,000,000,000, 2,000,000,000, or 5,000,000,000 fold over its concentration in the original sample. In particular, when enriching fetal cells from a maternal peripheral venous blood sample, the initial concentration of the fetal cells may be about 1:50,000,000 and it may be increased to at least 1:5,000 or 1:500. Enrichment can also increase concentration of rare cells in volume of rare cells/total volume of sample (removal of fluid). A fluid sample (e.g., a blood sample) of greater than 10, 15, 20, 50, or 100 mL total volume comprising rare components of interest, and it can be concentrated such that the rare component of interest into a concentrated solution of less than 0.5, 1, 2, 3, 5, or 10 mL total volume.
Enrichment can occur using one or more types of separation modules. Several different modules are described herein, all of which can be fluidly coupled with one another in the series for enhanced performance.
In some embodiments, enrichment occurs by selective lysis as described above.
In one embodiment, enrichment of rare cells occurs using one or more size-based separation modules. Examples of size-based separation modules include filtration modules, sieves, matrixes, etc. Examples of size-based separation modules contemplated by the present invention include those disclosed in International Publication No. WO 2004/113877. Other size based separation modules are disclosed in International Publication No. WO 2004/0144651.
In some embodiments, a size-based separation module comprises one or more arrays of obstacles forming a network of gaps. The obstacles are configured to direct particles as they flow through the array/network of gaps into different directions or outlets based on the particle's hydrodynamic size. For example, as a blood sample flows through an array of obstacles, nucleated cells or cells having a hydrodynamic size larger than a predetermined certain size such as a cutoff or predetermined size, e.g., 8 microns, are directed to a first outlet located on the opposite side of the array of obstacles from the fluid flow inlet, while the enucleated cells or cells having a hydrodynamic size smaller than a predetermined size, e.g., 8 microns, are directed to a second outlet also located on the opposite side of the array of obstacles from the fluid flow inlet.
An array can be configured to separate cells smaller or larger than a predetermined size by adjusting the size of the gaps, obstacles, and offset in the period between each successive row of obstacles. For example, in some embodiments, obstacles or gaps between obstacles can be up to 10, 20, 50, 70, 100, 120, 150, 170, or 200 microns in length or about 2, 4, 6, 8 or 10 microns in length. In some embodiments, an array for size-based separation includes more than 100, 500, 1,000, 5,000, 10,000, 50,000 or 100,000 obstacles that are arranged into more than 10, 20, 50, 100, 200, 500, or 1000 rows. Preferably, obstacles in a first row of obstacles are offset from a previous (upstream) row of obstacles by up to 50% the period of the previous row of obstacles. In some embodiments, obstacles in a first row of obstacles are offset from a previous row of obstacles by up to 45, 40, 35, 30, 25, 20, 15 or 10% the period of the previous row of obstacles. Furthermore, the distance between a first row of obstacles and a second row of obstacles can be up to 10, 20, 50, 70, 100, 120, 150, 170 or 200 microns. A particular offset can be continuous (repeating for multiple rows) or non-continuous. In some embodiments, a separation module includes multiple discrete arrays of obstacles fluidly coupled such that they are in series with one another. Each array of obstacles has a continuous offset. But each subsequent (downstream) array of obstacles has an offset that is different from the previous (upstream) offset. Preferably, each subsequent array of obstacles has a smaller offset that the previous array of obstacles. This allows for a refinement in the separation process as cells migrate through the array of obstacles. Thus, a plurality of arrays can be fluidly coupled in series or in parallel, (e.g., more than 2, 4, 6, 8, 10, 20, 30, 40, 50). Fluidly coupling separation modules (e.g., arrays) in parallel allows for high-throughput analysis of the sample, such that at least 1, 2, 5, 10, 20, 50, 100, 200, or 500 mL per hour flows through the enrichment modules or at least 1, 5, 10, or 50 million cells per hour are sorted or flow through the device.
In some embodiments, a size-based separation module comprises an array of obstacles configured to direct cells larger than a predetermined size to migrate along a line-of-sight within the array (e.g. towards a first outlet or bypass channel leading to a first outlet), while directing cells and analytes smaller than a predetermined size to migrate through the array of obstacles in a different direction than the larger cells (e.g. towards a second outlet). Such embodiments are illustrated in part in
A variety of enrichment protocols may be utilized although gentle handling of the cells is needed to reduce any mechanical damage to the cells or their DNA. This gentle handling also preserves the small number of fetal or rare cells in the sample. Integrity of the nucleic acid being evaluated is an important feature to permit the distinction between the genomic material from the fetal or rare cells and other cells in the sample. In particular, the enrichment and separation of the fetal or rare cells using the arrays of obstacles produces gentle treatment which minimizes cellular damage and maximizes nucleic acid integrity permitting exceptional levels of separation and the ability to subsequently utilize various formats to very accurately analyze the genome of the cells which are present in the sample in extremely low numbers.
In some embodiments, enrichment of rare cells (e.g. fetal cells, epithelial cells or circulating tumor cells (CTCs)) occurs using one or more capture modules that selectively inhibit the mobility of one or more cells of interest. Preferable a capture module is fluidly coupled downstream to a size-based separation module. Capture modules can include a substrate having multiple obstacles that restrict the movement of cells or analytes greater than a predetermined size. Examples of capture modules that inhibit the migration of cells based on size are disclosed in U.S. Pat. Nos. 5,837,115 and 6,692,952.
In some embodiments, a capture module includes a two dimensional array of obstacles that selectively filters or captures cells or analytes having a hydrodynamic size greater than a particular gap size (predetermined size), International Publication No. WO 2004/113877.
In some cases a capture module captures analytes (e.g., cells of interest or not of interest) based on their affinity. For example, an affinity-based separation module that can capture cells or analytes can include an array of obstacles adapted for permitting sample flow through, but for the fact that the obstacles are covered with binding moieties that selectively bind one or more analytes (e.g., cell populations) of interest (e.g., red blood cells, fetal cells, epithelial cells or nucleated cells) or analytes not-of-interest (e.g., white blood cells). Arrays of obstacles adapted for separation by capture can include obstacles having one or more shapes and can be arranged in a uniform or non-uniform order. In some embodiments, a two-dimensional array of obstacles is staggered such that each subsequent row of obstacles is offset from the previous row of obstacles to increase the number of interactions between the analytes being sorted (separated) and the obstacles.
Binding moieties coupled to the obstacles can include e.g., proteins (e.g., ligands/receptors), nucleic acids having complementary counterparts in retained analytes, antibodies, etc. In some embodiments, an affinity-based separation module comprises a two-dimensional array of obstacles covered with one or more antibodies selected from the group consisting of anti-CD71, anti-CD235a, anti-CD36, anti-carbohydrates, anti-selectin, anti-CD45, anti-GPA, anti-antigen-i, anti-EpCAM, anti-E-cadherin, and anti-Muc-1.
In some embodiments, a capture module utilizes a magnetic field to separate and/or enrich one or more analytes (cells) based on a magnetic property or magnetic potential in such analyte of interest or an analyte not of interest. For example, red blood cells which are slightly diamagnetic (repelled by magnetic field) in physiological conditions can be made paramagnetic (attributed by magnetic field) by deoxygenation of the hemoglobin into methemoglobin. This magnetic property can be achieved through physical or chemical treatment of the red blood cells. Thus, a sample containing one or more red blood cells and one or more white blood cells can be enriched for the red blood cells by first inducing a magnetic property in the red blood cells and then separating the red blood cells from the white blood cells by flowing the sample through a magnetic field (uniform or non-uniform).
For example, a maternal blood sample can flow first through a size-based separation module to remove enucleated cells and cellular components (e.g., analytes having a hydrodynamic size less than 6 μms) based on size. Subsequently, the enriched nucleated cells (e.g., analytes having a hydrodynamic size greater than 6 μms) white blood cells and nucleated red blood cells are treated with a reagent, such as CO2, N2, or NaNO2, that changes the magnetic property of the red blood cells' hemoglobin. The treated sample then flows through a magnetic field (e.g., a column coupled to an external magnet), such that the paramagnetic analytes (e.g., red blood cells) will be captured by the magnetic field while the white blood cells and any other non-red blood cells will flow through the device to result in a sample enriched in nucleated red blood cells (including fetal nucleated red blood cells or fnRBC's). Additional examples of magnetic separation modules are described in U.S. application Ser. No. 11/323,971, filed Dec. 29, 2005 entitled “Devices and Methods for Magnetic Enrichment of Cells and Other Particles” and U.S. application Ser. No. 11/227,904, filed Sep. 15, 2005, entitled “Devices and Methods for Enrichment and Alteration of Cells and Other Particles”.
Subsequent enrichment steps can be used to separate the rare cells (e.g. fnRBC's) from the non-rare cells maternal nucleated red blood cells. In some embodiments, a sample enriched by size-based separation followed by affinity/magnetic separation is further enriched for rare cells using fluorescence activated cell sorting (FACS) or selective lysis of a subset of the cells.
In some embodiments, enrichment involves detection and/or isolation of rare cells or rare DNA (e.g. fetal cells or fetal DNA) by selectively initiating apoptosis in the rare cells. This can be accomplished, for example, by subjecting a sample that includes rare cells (e.g. a mixed sample) to hyperbaric pressure (increased levels of CO2; e.g. 4% CO2). This will selectively initiate apoptosis in the rare or fragile cells in the sample (e.g. fetal cells). Once the rare cells (e.g. fetal cells) begin apoptosis, their nuclei will condense and optionally be ejected from the rare cells. At that point, the rare cells or nuclei can be detected using any technique known in the art to detect condensed nuclei, including DNA gel electrophoresis, in situ labeling of DNA nick using terminal deoxynucleotidyl transferase (TdT)-mediated dUTP in situ nick labeling (TUNEL) (Gavrieli, Y., et al. J. Cell Biol. 119:493-501 (1992)), and ligation of DNA strand breaks having one or two-base 3′ overhangs (Taq polymerase-based in situ ligation). (Didenko V., et al. J. Cell Biol. 135:1369-76 (1996)).
In some embodiments ejected nuclei can further be detected using a size based separation module adapted to selectively enrich nuclei and other analytes smaller than a predetermined size (e.g. 6 microns) and isolate them from cells and analytes having a hydrodynamic diameter larger than 6 microns. Thus, in one embodiment, the present invention contemplated detecting fetal cells/fetal DNA and optionally using such fetal DNA to diagnose or prognose a condition in a fetus. Such detection and diagnosis can occur by obtaining a blood sample from the female pregnant with the fetus, enriching the sample for cells and analytes larger than 8 microns using, for example, an array of obstacles adapted for size-base separation where the predetermined size of the separation is 8 microns (e.g. the gap between obstacles is up to 8 microns). Then, the enriched product is further enriched for red blood cells (RBC's) by oxidizing the sample to make the hemoglobin puramagnetic and flowing the sample through one or more magnetic regions. This selectively captures the RBC's and removes other cells (e.g. white blood cells) from the sample. Subsequently, the fnRBC's can be enriched from nuiRBC's in the second enriched product by subjecting the second enriched product to hyperbaric pressure or other stimulus that selectively causes the fetal cells to begin apoptosis and condense/eject their nuclei. Such condensed nuclei are then identified/isolated using e.g. laser capture microdissection or a size based separation module that separates components smaller than 3, 4, 5 or 6 microns from a sample. Such fetal nuclei can then by analyzed using any method known in the art or described herein.
In some embodiments, when the analyte desired to be separated (e.g., red blood cells or white blood cells) is not ferromagnetic or does not have a potential magnetic property, a magnetic particle (e.g., a bead) or compound (e.g., Fe3+) can be coupled to the analyte to give it a magnetic property. In some embodiments, a bead coupled to an antibody that selectively binds to an analyte of interest can be decorated with an antibody elected from the group of anti CD71 or CD75. In some embodiments a magnetic compound, such as Fe3+, can be couple to an antibody such as those described above. The magnetic particles or magnetic antibodies herein may be coupled to any one or more of the devices herein prior to contact with a sample or may be mixed with the sample prior to delivery of the sample to the device(s). Magnetic particles can also be used to decorate one or more analytes (cells of interest or not of interest) to increase the size prior to performing size-based separation.
Magnetic field used to separate analytes/cells in any of the embodiments herein can uniform or non-uniform as well as external or internal to the device(s) herein. An external magnetic field is one whose source is outside a device herein (e.g., container, channel, obstacles). An internal magnetic field is one whose source is within a device contemplated herein. An example of an internal magnetic field is one where magnetic particles may be attached to obstacles present in the device (or manipulated to create obstacles) to increase surface area for analytes to interact with to increase the likelihood of binding. Analytes captured by a magnetic field can be released by demagnetizing the magnetic regions retaining the magnetic particles. For selective release of analytes from regions, the demagnetization can be limited to selected obstacles or regions. For example, the magnetic field can be designed to be electromagnetic, enabling turn-on and turn-off off the magnetic fields for each individual region or obstacle at will.
One or more of the enrichment modules herein (e.g., size-based separation module(s) and capture module(s)) may be fluidly coupled in series or in parallel with one another. For example a first outlet from a separation module can be fluidly coupled to a capture module. In some embodiments, the separation module and capture module are integrated such that a plurality of obstacles acts both to deflect certain analytes according to size and direct them in a path different than the direction of analyte(s) of interest, and also as a capture module to capture, retain, or bind certain analytes based on size, affinity, magnetism or other physical property.
In any of the embodiments herein, the enrichment steps performed have a specificity and/or sensitivity greater than 50, 60, 70, 80, 90, 95, 96, 97, 98, 99, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, 99.9 or 99.95% The retention rate of the enrichment module(s) herein is such that ≧50, 60, 70, 80, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 99.9% of the analytes or cells of interest (e.g., nucleated cells or nucleated red blood cells or nucleated from red blood cells) are retained. Simultaneously, the enrichment modules are configured to remove ≧50, 60, 70, 80, 85, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 99.9% of all unwanted analytes (e.g., red blood-platelet enriched cells) from a sample.
Any of the enrichment methods herein may be further supplemented by splitting the enriched sample into aliquots or sub-samples. In some embodiments, an enriched sample is split into at least 2, 5, 10, 20, 50, 100, 200, 500, or 1000 sub-samples. Thus when an enriched sample comprises about 500 cells and is split into 500 or 1000 different sub-samples, each sub-sample will have 1 or 0 cells.
In some cases a sample is split or arranged such that each sub-sample is in a unique or distinct location (e.g. well). Such location may be addressable. Each site can further comprise a capture mechanism to capture cell(s) to the site of interest and/or release mechanism for selectively releasing cells from the site of interest. In some cases, the well is configured to hold a single cell.
III. Sample Analysis
In some embodiments, the methods herein are used for detecting the presence or conditions of rare cells that are in a mixed sample (optionally even after enrichment) at a concentration of up to 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, 5% or 1% of all cells in the mixed sample, or at a concentration of less than 1:2, 1:4, 1:10, 1:50, 1:100, 1:200, 1:500, 1:1000, 1:2000, 1:5000, 1:10,000, 1:20,000, 1:50,000, 1:100,000, 1:200,000, 1:1,000,000, 1:2,000,000, 1:5,000,000, 1:10,000,000, 1:20,000,000, 1:50,000,000 or 1:100,000,000 of all cells in the sample, or at a concentration of less than 1×10−3, 1×10−4, 1×10−5, 1×10−6, or 1×10−7 cells/μL of a fluid sample. In some embodiments, the mixed sample has a total of up to 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30, 40, 50, or 100 rare cells (e.g. fetal cells or epithelial cells).
Enriched target cells (e.g., fnRBC) may be “binned” prior to further analysis of the enriched cells (
Binning may be preceded by positive selection for target cells including, but not limited to, affinity binding (e.g. using anti-CD71 antibodies). Alternately, negative selection of non-target cells may precede binning. For example, output from a size-based separation module may be passed through a magnetic hemoglobin enrichment module (MHEM) which selectively removes WBCs from the enriched sample by attracting magnetized hemoglobin-containing cells.
For example, the possible cellular content of output from enriched maternal blood which has been passed through a size-based separation module (with or without further enrichment by passing the enriched sample through a MHEM) may consist of: 1) approximately 20 fnRBC; 2) 1,500 mnRBC; 3) 4,000-40,000 WBC; 4) 15×106 RBC. If this sample is separated into 100 bins (PCR wells or other acceptable binning platform), each bin would be expected to contain: 1) 80 negative bins and 20 bins positive for one fnRBC; 2) 150 mnRBC; 3) 400-4,000 WBC; 4) 15×104 RBC. If separated into 10,000 bins, each bin would be expected to contain: 1) 9,980 negative bins and 20 bins positive for one fnRBC; 2) 8,500 negative bins and 1,500 bins positive for one mnRBC; 3)<1-4 WBC; 4) 15×102 RBC. One of skill in the art will recognize that the number of bins may be increased or decreased depending on experimental design and/or the platform used for binning. Reduced complexity of the binned cell populations may facilitate further genetic and/or cellular analysis of the target cells by reducing the number of non-target cells in an individual bin.
Analysis may be performed on individual bins to confirm the presence of target cells (e.g. fnRBC) in the individual bin. Such analysis may consist of any method known in the art including, but not limited to, FISH, PCR, STR detection, SNP analysis, biomarker detection, and sequence analysis (
For example, a peripheral maternal venous blood sample enriched by the methods herein can be analyzed to determine pregnancy or a condition of a fetus (e.g., sex of fetus or aneuploidy). The analysis step for fetal cells may further involves comparing the ratio of maternal to paternal genomic DNA on the identified fetal cells.
IV. Fetal Biomarkers
In some embodiments fetal biomarkers may be used to detect and/or isolate fetal cells, after enrichment or after detection of fetal abnormality or lack thereof. For example, this may be performed by distinguishing between fetal and maternal nRBCs based on relative expression of a gene (e.g., DYS1, DYZ, CD-71, ε- and ζ-globin) that is differentially expressed during fetal development. In preferred embodiments, biomarker genes are differentially expressed in the first and/or second trimester. “Differentially expressed,” as applied to nucleotide sequences or polypeptide sequences in a cell or cell nuclei, refers to differences in over/under-expression of that sequence when compared to the level of expression of the same sequence in another sample, a control or a reference sample. In some embodiments, expression differences can be temporal and/or cell-specific. For example, for cell-specific expression of biomarkers, differential expression of one or more biomarkers in the cell(s) of interest can be higher or lower relative to background cell populations. Detection of such difference in expression of the biomarker may indicate the presence of a rare cell (e.g., fnRBC) versus other cells in a mixed sample (e.g., background cell populations). In other embodiments, a ratio of two or more such biomarkers that are differentially expressed can be measured and used to detect rare cells.
In one embodiment, fetal biomarkers comprise differentially expressed hemoglobins. Erythroblasts (nRBCs) are very abundant in the early fetal circulation, virtually absent in normal adult blood and by having a short finite lifespan, there is no risk of obtaining fnRBC which may persist from a previous pregnancy. Furthermore, unlike trophoblast cells, fetal erythroblasts are not prone to mosaic characteristics.
Yolk sac erythroblasts synthesize ε-, ζ- γ-and α-globins, these combine to form the embryonic hemoglobins. Between six and eight weeks, the primary site of erythropoiesis shifts from the yolk sac to the liver, the three embryonic hemoglobins are replaced by fetal hemoglobin (HbF) as the predominant oxygen transport system, and ε- and ζ-globin production gives way to γ-, α- and β-globin production within definitive erythrocytes (Peschle et al., 1985). HbF remains the principal hemoglobin until birth, when the second globin switch occurs and β-globin production accelerates.
Hemoglobin (Hb) is a heterodimer composed of two identical α globin chains and two copies of a second globin. Due to differential gene expression during fetal development, the composition of the second chain changes from ε globin during early embryonic development (1 to 4 weeks of gestation) to γ globin during fetal development (6 to 8 weeks of gestation) to β globin in neonates and adults as illustrated in (Table 1).
In the late-first trimester, the earliest time that fetal cells may be sampled by CVS, fnRBCs contain, in addition to α globin, primarily ε and γ globin. In the early to mid second trimester, when amniocentesis is typically performed, fnRBCs contain primarily γ globin with some adult β globin. Maternal cells contain almost exclusively α and β globin, with traces of γ detectable in some samples. Therefore, by measuring the relative expression of the ε, γ and β genes in RBCs purified from maternal blood samples, the presence of fetal cells in the sample can be determined. Furthermore, positive controls can be utilized to assess failure of the FISH analysis itself.
In various embodiments, fetal cells are distinguished from maternal cells based on the differential expression of hemoglobins β, γ or ε. Expression levels or RNA levels can be determined in the cytoplasm or in the nucleus of cells. Thus in some embodiments, the methods herein involve determining levels of messenger RNA (mRNA), ribosomal RNA (rRNA), or nuclear RNA (nRNA).
In some embodiments, identification of fnRBCs can be achieved by measuring the levels of at least two hemoglobins in the cytoplasm or nucleus of a cell. In various embodiments, identification and assay is from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15 or 20 fetal nuclei. Furthermore, total nuclei arrayed on one or more slides can number from about 100, 200, 300, 400, 500, 700, 800, 5000, 10,000, 100,000, 1,000,000, 2,000,000 to about 3,000,000. In some embodiments, a ratio for γ/β or ε/β is used to determine the presence of fetal cells, where a number less than one indicates that a fnRBC(s) is not present. In some embodiments, the relative expression of γ/β or ε/β provides a fnRBC index (“FNI”), as measured by γ or ε relative to β. In some embodiments, a FNI for γ/β greater than 5, 10, 15, 20, 25, 30, 35, 40, 45, 90, 180, 360, 720, 975, 1020, 1024, 1250 to about 1250, indicate that a fnRBC(s) is present. In yet other embodiments, a FNI for γ/β of less than about 1 indicates that a fnRBC(s) is not present. Preferably, the above FNI is determined from a sample obtained during a first trimester. However, similar ratios can be used during second trimester and third trimester.
In some embodiments, the expression levels are determined by measuring nuclear RNA transcripts including, nascent or unprocessed transcripts. In another embodiment, expression levels are determined by measuring mRNA, including ribosomal RNA. There are many methods known in the art for imaging (e.g., measuring) nucleic acids or RNA including, but not limited to, using expression arrays from Affymetrix, Inc. or Illumina, Inc.
RT-PCR primers can be designed by targeting the globin variable regions, selecting the amplicon size, and adjusting the primers annealing temperature to achieve equal PCR amplification efficiency. Thus TaqMan probes can be designed for each of the amplicons with well-separated fluorescent dyes, Alexa Fluor®-355 for ε, Alexa Fluor®-488 for γ, and Alexa Fluor-555 for β. The specificity of these primers can be first verified using ε, γ, and β cDNA as templates. The primer sets that give the best specificity can be selected for further assay development. As an alternative, the primers can be selected from two exons spanning an intron sequence to amplify only the mRNA to eliminate the genomic DNA contamination.
The primers selected can be tested first in a duplex format to verify their specificity, limit of detection, and amplification efficiency using target cDNA templates. The best combinations of primers can be further tested in a triplex format for its amplification efficiency, detection dynamic range, and limit of detection.
Various commercially available reagents are available for RT-PCR, such as One-step RT-PCR reagents, including Qiagen One-Step RT-PCR Kit and Applied Biosytems TaqMan One-Step RT-PCR Master Mix Reagents kit. Such reagents can be used to establish the expression ratio of ε, γ, and β using purified RNA from enriched samples. Forward primers can be labeled for each of the targets, using Alexa fluor-355 for ε, Alexa fluor-488 for γ, and Alexa fluor-555 for β. Enriched cells can be deposited by cytospinning onto glass slides. Additionally, cytospinning the enriched cells can be performed after in situ RT-PCR. Thereafter, the presence of the fluorescent-labeled amplicons can be visualized by fluorescence microscopy. The reverse transcription time and PCR cycles can be optimized to maximize the amplicon signal:background ratio to have maximal separation of fetal over maternal signature. Preferably, signal:background ratio is greater than 5, 10, 50 or 100 and the overall cell loss during the process is less than 50, 10 or 5%.
V. Fetal Cell Analysis
Aneuploidy means the condition of having less than or more than the normal diploid number of chromosomes. In other words, it is any deviation from euploidy. Aneuploidy includes conditions such as monosomy (the presence of only one chromosome of a pair in a cell's nucleus), trisomy (having three chromosomes of a particular type in a cell's nucleus), tetrasomy (having four chromosomes of a particular type in a cell's nucleus), pentasomy (having five chromosomes of a particular type in a cell's nucleus), triploidy (having three of every chromosome in a cell's nucleus), and tetraploidy (having four of every chromosome in a cell's nucleus). Birth of a live triploid is extraordinarily rare and such individuals are quite abnormal, however triploidy occurs in about 2-3% of all human pregnancies and appears to be a factor in about 15% of all miscarriages. Tetraploidy occurs in approximately 8% of all miscarriages. (http://www.emedicine.com/med/topic3241.htm).
In step 400, a sample is obtained from an animal, such as a human. In some embodiments, animal or human is pregnant, suspected of being pregnant, or may have been pregnant, and, the systems and methods herein are used to diagnose pregnancy and/or conditions of the fetus (e.g. trisomy). In some embodiments, the animal or human is suspected of having a condition, has a condition, or had a condition (e.g., cancer) and, the systems and methods herein are used to diagnose the condition, determine appropriate therapy, and/or monitor for recurrence.
In both scenarios a sample obtained from the animal can be a blood sample e.g., of up to 50, 40, 30, 20, or 15 mL. In some cases multiple samples are obtained from the same animal at different points in time (e.g. before therapy, during therapy, and after therapy, or during 1st trimester, 2nd trimester, and 3rd trimester of pregnancy).
In optional step 402, rare cells (e.g., fetal cells or epithelial cells) or DNA of such rare cells are enriched using one or more methods known in the art or described herein. For example, to enrich fetal cells from a maternal blood sample, the sample can be applied to a size-base separation module (e.g., two-dimensional array of obstacles) configured to direct cells or particles in the sample greater than 8 microns to a first outlet and cells or particles in the sample smaller than 8 microns to a second outlet. The fetal cells can subsequently be further enriched from maternal white blood cells (which are also greater than 8 microns) based on their potential magnetic property. For example, N2 or anti-CD71 coated magnetic beads is added to the first enriched product to make the hemoglobin in the red blood cells (maternal and fetal) paramagnetic. The enriched sample is then flowed through a column coupled to an external magnet. This captures both the fnRBC's and mnRBC's creating a second enriched product. The sample can then be subjected to hyperbaric pressure or other stimulus to initiate apoptosis in the fetal cells. Fetal cells/nuclei can then be enriched using microdissection, for example. It should be noted that even an enriched product can be dominated (>50%) by cells not of interest (e.g. maternal red blood cells). In some cases an enriched sample has the rare cells (or rare genomes) consisting of up to 0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, or 50% of all cells (or genomes) in the enriched sample. For example, using the systems herein, a maternal blood sample of 20 mL from a pregnant human can be enriched for fetal cells such that the enriched sample has a total of about 500 cells, 2% of which are fetal and the rest are maternal.
In step 404, the enriched product is split between two or more discrete locations. In some embodiments, a sample is split into at least 2, 10, 20, 50, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3,000, 4,000, 5000, or 10,000 total different discrete sites or about 100, 200, 500, 1000, 1200, 1500 sites. In some embodiments, output from an enrichment module is serially divided into wells of a 1536 microwell plate (
Examples of discrete locations which could be used as addressable locations include, but are not limited to, wells, bins, sieves, pores, geometric sites, slides, matrixes, membranes, electric traps, gaps, obstacles, or in-situ within a cell or nuclear membrane. In some embodiments, the discrete cells are addressable such that one can correlate a cell or cell sample with a particular location.
Examples of methods for splitting a sample into discrete addressable locations include, but are not limited to, fluorescent activated cell sorting (FACS) (Sherlock, J V et al. Ann. Hum. Genet. 62 (Pt. 1): 9-23 (1998)), micromanipulation (Sarnura, O., Ct al Hum. Genet. 107(1):28-32 (2000)) and dilution strategies (Findlay, I. et al. Mol. Cell. Endocrinol. 183 Suppl 1: 55-12 (2001)). Other methods for sample splitting cell sorting and splitting methods known in the art may also be used. For example, samples can be split by affinity sorting techniques using affinity agents (e.g. antibodies) bound to any immobilized or mobilized substrate (Sarnura O., et al., Hum. Genet. 107(1):28-32 (2000)). Such affinity agents can be specific to a cell type e.g. RBC's fetal cells epithelial cells including those specifically binding EpCAM, antigen-i, or CD-71.
In some embodiments, a sample or enriched sample is transferred to a cell sorting device that includes an array of discrete locations for capturing cells traveling along a fluid flow. The discrete locations can be arranged in a defined pattern across a surface such that the discrete sites are also addressable. In some embodiments, the sorting device is coupled to any of the enrichment devices known in the art or disclosed herein. Examples of cell sorting devices included are described in International Publication No. WO 01/35071. Examples of surfaces that may be used for creating arrays of cells in discrete addressable sites include, but are not limited to, cellulose, cellulose acetate, nitrocellulose, glass, quartz or other crystalline substrates such as gallium arsenide, silicones, metals, semiconductors, various plastics and plastic copolymers, cyclo-olefin polymers, various membranes and gels, microspheres, beads and paramagnetic or supramagnetic microparticles.
In some embodiments, a sorting device comprises an array of wells or discrete locations wherein each well or discrete location is configured to hold up to 1 cell. Each well or discrete addressable location may have a capture mechanism adapted for retention of such cell (e.g. gravity, suction, etc.) and optionally a release mechanism for selectively releasing a cell of interest from a specific well or site (e.g. bubble actuation). Figure B illustrates such an embodiment.
In step 406, nucleic acids of interest from each cell or nuclei arrayed are tagged by amplification. Preferably, the amplified/tagged nucleic acids include at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 90, 90 or 100 polymorphic genomic DNA regions such as short tandem repeats (STRs) or variable number of tandem repeats (“VNTR”). When the amplified DNA regions include one or more STR/s/, the STR/s/ are selected for high heterozygosity (variety of alleles) such that the paternal allele of any fetal cell is more likely to be distinct in length from the maternal allele. This results in improved power to detect the presence of fetal cells in a mixed sample and any potential of fetal abnormalities in such cells. In some embodiment, STR(s) amplified are selected for their association with a particular condition. For example, to determine fetal abnormality an STR sequence comprising a mutation associated with fetal abnormality or condition is amplified. Examples of STRs that can be amplified/analyzed by the methods herein include, but are not limited to D2151414, D2151411, D2151412, D21511 MBP, D135634, D135631, D185535, AmgXY and XHPRT. Additional STRs that can be amplified/analyzed by the methods herein include, but are not limited to, those at locus F13B (1:q31-q32); TPDX (2:p23-2pter); FIBRA (FGA) (4:q28); CSFIPO (5:q33.3-q34); F13A (6; p24-p25); THOI (11:p15-15.5); VWA (12:p12-pter); CDU (12p12-pter); D1451434 (14:q32.13); CYAR04 (p450) (15:q21.1) D21511 (21:q11-q21) and D2251045 (22:q12.3). In some cases, STR loci are chosen on a chromosome suspected of trisomy and on a control chromosome. Examples of chromosomes that are often trisomic include chromosomes 21, 18, 13, and X. In some cases, 1 or more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, or 20 STRs are amplified per chromosome tested (Samura, O. et al., Olin. Chem. 47(9):1622-6 (2001)). For example amplification can be used to generate amplicons of up to 20, up to 30, up to 40, up to 50, up to 60, up to 70, up to 80, up to 90, up to 100, up to 150, up to 200, up to 300, up to 400, up to 500 or up to 1000 nucleotides in length. Di-, tri-, tetra-, or penta-nucleotide repeat STR loci can be used in the methods described herein.
To amplify and tag genomic DNA region(s) of interest, PCR primers can include: (i) a primer element, (ii) a sequencing element, and (iii) a locator element.
The primer element is configured to amplify the genomic DNA region of interest (e.g. STR). The primer element includes, when necessary, the upstream and downstream primers for the amplification reactions. Primer elements can be chosen which are multiplexable with other primer pairs from other tags in the same amplification reaction (e.g. fairly uniform melting temperature, absence of cross-priming on the human genome, and absence of primer-primer interaction based on sequence analysis). The primer element can have at least 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 40 or 50 nucleotide bases, which are designed to specifically hybridize with and amplify the genomic DNA region of interest.
The sequencing element earl be located on the 5′ end of each primer element or nucleic acid tag. The sequencing element is adapted to cloning and/or sequencing of the amplicons. (Marguiles, M, Nature 437 (7057): 376-80) The sequencing element can be about 4, 6, 8, 10, 18, 20, 28, 36, 46 or 50 nucleotide bases in length.
The locator element (also known as a unique tag sequence), which is often incorporated into the middle part of the upstream primer, can include a short DNA or nucleic acid sequence between 4-20 bp in length (e.g., about 4, 6, 8, 10, or 20 nucleotide bases). The locator element makes it possible to pool the amplicons from all discrete addressable locations following the amplification step and analyze the amplicons in parallel. In some embodiments each locator element is specific for a single addressable location.
Tags are added to the cells/DNA at each discrete location using an amplification reaction. Amplification can be performed using PCR or by a variety of methods including, but not limited to, singleplex PCR, quantitative PCR, quantitative fluorescent PCR (QF-PCR), multiplex fluorescent PCR (MF-PCR), real time PCR(RT-PCR), single cell PCR, restriction fragment length polymorphism PCR(PCR-RFLP), PCR-RFLP/RT-PCR-RFLP, hot start PCR, nested PCR, in situ polonony PCR, in situ rolling circle amplification (RCA), bridge PCR, picotiter PCR, multiple strand displacement amplification (MDA), and emulsion PCR. Other suitable amplification methods include the ligase chain reaction (LCR), transcription amplification, self-sustained sequence replication, selective amplification of target polynucleotide sequences, consensus sequence primed polymerase chain reaction (CP-PCR), arbitrarily primed polymerase chain reaction (AP-PCR), degenerate oligonucleotide-primed PCR (DOP-PCR) and nucleic acid based sequence amplification (NABSA). Additional examples of amplification techniques using PCR primers are described in, U.S. Pat. Nos. 5,242,794, 5,494,810, 4,988,617 and 6,582,938.
In some embodiments, a further PCR amplification is performed using nested primers for the one or more genomic DNA regions of interest to ensure optimal performance of the multiplex amplification. The nested PCR amplification generates sufficient genomic DNA starting material for further analysis such as in the parallel sequencing procedures below.
In step 408, genomic DNA regions tagged/amplified are pooled and purified prior to further processing. Methods for pooling and purifying genomic DNA are known in the art.
In step 410, pooled genomic DNA/amplicons are analyzed to measure, e.g. allele abundance of genomic DNA regions (e.g. STRs amplified). In some embodiments such analysis involves the use of capillary gel electrophoresis (CGE). In other embodiments, such analysis involves sequencing or ultra deep sequencing.
Sequencing can be performed using the classic Sanger sequencing method or any other method known in the art.
For example, sequencing can occur by sequencing-by-synthesis, which involves inferring the sequence of the template by synthesizing a strand complementary to the target nucleic acid sequence. Sequence-by-synthesis can be initiated using sequencing primers complementary to the sequencing element on the nucleic acid tags. The method involves detecting the identity of each nucleotide immediately after (substantially real-time) or upon (real-time) the incorporation of a labeled nucleotide or nucleotide analog into a growing strand of a complementary nucleic acid sequence in a polymerase reaction. After the successful incorporation of a label nucleotide, a signal is measured and then nulled by methods known in the art. Examples of sequence-by-synthesis methods are described in U.S. Application Publication Nos. 2003/0044781, 2006/0024711, 2006/0024678 and 2005/0100932. Examples of labels that can be used to label nucleotide or nucleotide analogs for sequencing-by-synthesis include, but are not limited to, chromophores, fluorescent moieties, enzymes, antigens, heavy metal, magnetic probes, dyes, phosphorescent groups, radioactive materials, chemiluminescent moeities, scattering or fluorescent nanoparticles, Raman signal generating moieties, and electrochemical detection moieties. Sequencing-by-synthesis can generate at least 1,000, at least 5,000, at least 10,000, at least 20,000, 30,000, at least 40,000, at least 50,000, at least 100,000 or at least 500,000 reads per hour. Such reads can have at least 50, at least 60, at least 70, at least 80, at least 90, at least 100, at least 120 or at least 150 bases per read.
Another sequencing method involves hybridizing the amplified genomic region of interest to a primer complementary to it. This hybridization complex is incubated with a polymerase, ATP sulfurylase, luciferase, apyrase, and the substrates luciferin and adenosine 5′ phosphosulfate. Next, deoxynucleotide triphosphates corresponding to the bases A, C, G, and T (U) are added sequentially. Each base incorporation is accompanied by release of pyrophosphate, converted to ATP by sulfurylase, which drives synthesis of oxyluciferin and the release of visible light. Since pyrophosphate release is equimolar with the number of incorporated bases, the light given off is proportional to the number of nucleotides adding in any one step. The process is repeated until the entire sequence is determined.
Yet another sequencing method involves a four-color sequencing by ligation scheme (degenerate ligation), which involves hybridizing an anchor primer to one of four positions. Then an enzymatic ligation reaction of the anchor primer to a population of degenerate nonamers that are labeled with fluorescent dyes is performed. At any given cycle, the population of nonamers that is used is structure such that the identity of one of its positions is correlated with the identity of the fluorophore attached to that nonamer. To the extent that the ligase discriminates for complementarily at that queried position, the fluorescent signal allows the inference of the identity of the base. After performing the ligation and four-color imaging, the anchor primer:nonamer complexes are stripped and a new cycle begins. Methods to image sequence information after performing ligation are known in the art.
Preferably, analysis involves the use of ultra-deep sequencing, such as described in Marguiles et al., Nature 437 (7057): 376-80 (2005). Briefly, the amplicons are diluted and mixed with beads such that each bead captures a single molecule of the amplified material. The DNA molecule on each bead is then amplified to generate millions of copies of the sequence which all remain bound to the bead. Such amplification can occur by PCR. Each bead can be placed in a separate well, which can be a (optionally addressable) picoliter-sized well. In some embodiments, each bead is captured within a droplet of a PCR-reaction-mixture-in-oil-emulsion and PCR amplification occurs within each droplet. The amplification on the bead results in each bead carrying at least one million, at least 5 million, or at least 10 million copies of the original amplicon coupled to it. Finally, the beads are placed into a highly parallel sequencing by synthesis machine which generates over 400,000 reads (˜100 bp per read) in a single 4 hour run.
Other methods for ultra-deep sequencing that can be used are described in Hong, S. et al. Nat. Biotechnol. 22(4):435-9 (2004); Bennett, B. et al. Pharmacogenomics 6(4):373-82 (2005); Shendure, P. et al. Science 309 (5741):1728-32 (2005).
The role of the ultra-deep sequencing is to provide an accurate and quantitative way to measure the allele abundances for each of the STRs. The total required number of reads for each of the aliquot wells is determined by the number of STRs, the error rates of the multiplex PCR, and the Poisson sampling statistics associated with the sequencing procedures.
In one example, the enrichment output from step 402 results in approximately 500 cells of which 98% are maternal cells and 2% are fetal cells. Such enriched cells are subsequently split into 500 discrete locations (e.g., wells) in a microtiter plate such that each well contains 1 cell. PCR is used to amplify STR's (˜3-10 STR loci) on each chromosome of interest. Based on the above example, as the fetal/maternal ratio goes down, the aneuploidy signal becomes diluted and more loci are needed to average out measurement errors associated with variable DNA amplification efficiencies from locus to locus. The sample division into wells containing ˜1 cell proposed in the methods described herein achieves pure or highly enriched fetal/maternal ratios in some wells, alleviating the requirements for averaging of PCR errors over many loci.
In one example, let ‘f’ be the fetal/maternal DNA copy ratio in a particular PCR reaction. Trisomy increases the ratio of maternal to paternal alleles by a factor 1+f12. PCR efficiencies vary from allele to allele within a locus by a mean square error in the logarithm given by σallele2, and vary from locus to locus by σlocus2, where this second variance is apt to be larger due to differences in primer efficiency. Na is the loci per suspected aneuploid chromosome and Nc is the control loci. If the mean of the two maternal allele strengths at any locus is ‘m’ and the paternal allele strength is ‘p,’ then the squared error expected is the mean of the ln(ratio(m/p)), where this mean is taken over N loci is given by 2(σallele2)/N. When taking the difference of this mean of ln(ratio(m/p)) between a suspected aneuploidy region and a control region, the error in the difference is given by
σdiff2=2(σallele2)/Na+2(σallele2)/Nc (1)
For a robust detection of aneuploidy we require
3σdiff<f/2.
For simplicity, assuming Na=Nc=N in Equation 1, this gives the requirement
6σallele/N1/2<f/2, (3)
or a minimum N of
N=144(σallele/f)2 (4)
In the context of trisomy detection, the suspected aneuploidy region is usually the entire chromosome and N denotes the number of loci per chromosome. For reference, Equation 3 is evaluated for N in the following Table 2 for various values of σallele and f.
Since sample splitting decreases the number of starting genome copies which increases σallele at the same time that it increases the value of f in some wells, the methods herein are based on the assumption that the overall effect of splitting is favorable; i.e., that the PCR errors do not increase too fast with decreasing starting number of genome copies to offset the benefit of having some wells with large f. The required number of loci can be somewhat larger because for many loci the paternal allele is not distinct from the maternal alleles, and this incidence depends on the heterozygosity of the loci. In the case of highly polymorphic STRs, this amounts to an approximate doubling of N.
The role of the sequencing is to measure the allele abundances output from the amplification step. It is desirable to do this without adding significantly more error due to the Poisson statistics of selecting only a finite number of amplicons for sequencing. The rms error in the ln(abundance) due to Poisson statistics is approximately (Nreads)−1/2. It is desirable to keep this value less than or equal to the PCR error σallele. Thus, a typical paternal allele needs to be allocated at least (σallele)−2 reads. The maternal alleles, being more abundant, do not add appreciably to this error when forming the ratio estimate for m/p. The mixture input to sequencing contains amplicons from Nloci loci of which roughly an abundance fraction f/2 are paternal alleles. Thus, the total required number of reads for each of the aliquot wells is given approximately by 2Nloci(f σallele2). Combining this result with Equation 4, it is found a total number of reads over all the wells given approximately by
Nreads=288Nwellsf3. (5)
When performing sample splitting, a rough approximation is to stipulate that the sample splitting causes f to approach unity in at least a few wells. If the sample splitting is to have advantages, then it must be these wells which dominate the information content in the final result. Therefore, Equation (5) with f=1 is adopted, which suggests a minimum of about 300 reads per well. For 500 wells, this gives a minimum requirement for ˜150,000 sequence reads. Allowing for the limited heterozygosity of the loci tends to increase the requirements (by a factor of ˜2 in the case of STRs), while the effect of reinforcement of data from multiple wells tends to relax the requirements with respect to this result (in the baseline case examined above it is assumed that ˜10 wells have a pure fetal cell). Thus the required total number of reads per patient is expected to be in the range 100,000-300,000.
In step 412, wells with rare cells/alleles (e.g., fetal alleles) are identified. The locator elements of each tag can be used to sort the reads (˜200,000 sequence reads) into ‘bins’ which correspond to the individual wells of the microtiter plates (˜500 bins). The sequence reads from each of the bins (˜400 reads per bin) are then separated into the different genomic DNA region groups, (e.g. STR loci,) using standard sequence alignment algorithms. The aligned sequences from each of the bins are used to identify rare (e.g., non-maternal) alleles. It is estimated that on average a 15 ml blood sample from a pregnant human will result in ˜10 bins having a single fetal cell each.
The following are two examples by which rare alleles can be identified. In a first approach, an independent blood sample fraction known to contain only maternal cells can be analyzed as described above in order to obtain maternal alleles. This sample can be a white blood cell fraction or simply a dilution of the original sample before enrichment. In a second approach, the sequences or genotypes for all the wells can be similarity-clustered to identify the dominant pattern associated with maternal cells. In either approach, the detection of non-maternal alleles determines which discrete location (e.g. well) contained fetal cells. Determining the number of bins with non-maternal alleles relative to the total number of bins provides an estimate of the number of fetal cells that were present in the original cell population or enriched sample. Bins containing fetal cells are identified with high levels of confidence because the non-maternal alleles are detected by multiple independent polymorphic DNA regions, e.g. STR loci.
In step 414, condition of rare cells or DNA is determined. This can be accomplished by determining abundance of selected alleles (polymorphic genomic DNA regions) in bin(s) with rare cells/DNA. In some embodiments, allele abundance is used to determine aneuploidy, e.g. chromosomes 13, 18 and 21. Abundance of alleles can be determined by comparing ratio of maternal to paternal alleles for each genomic region amplified (e.g., ˜12 STR's). For example, if 12 STRs are analyzed, for each bin there are 33 sequence reads for each of the STRs. In a normal fetus, a given STR will have 1:1 ratio of the maternal to paternal alleles with approximately 16 sequence reads corresponding to each allele (normal diallelic). In a trisomic fetus, three doses of an STR marker will be detected either as three alleles with a 1:1:1 ratio (trisomic triallelic) or two alleles with a ratio of 2:1 (trisomic diallelic). (Adinolfi, P. et al., Prenat. Diagn, 17(13):1299-311 (1997)). In rare instances all three alleles may coincide and the locus will not be informative for that individual patient. In some embodiments, the information from the different DNA regions on each chromosome are combined to increase the confidence of a given aneuploidy call. In some embodiments, the information from the independent bins containing fetal cells can also be combined to further increase the confidence of the call.
In some embodiments allele abundance is used to determine segmental anuepolidy. Normal diploid cells have two copies of each chromosome and thus two alleles of each gene or loci. Changes in the allele abundance for a particular chromosomal region may be indicative of a chromosomal rearrangement, such as a deletion, duplication or translocation event. In some embodiments, the information from the different DNA regions on each chromosome are combined to increase the confidence of a given segmental aneuploidy call. In some embodiments, the information from the independent bins containing fetal cells can also be combined to further increase the confidence of the call.
The determination of fetal trisomy can be used to diagnose conditions such as abnormal fetal genotypes, including, trisomy 13, trisomy 18, trisomy 21 (Down syndrome) and Klinefelter Syndrome (XXY). Other examples of abnormal fetal genotypes include, but are not limited to, aneuploidy such as, monosomy of one or more chromosomes (X chromosome monosomy, also known as Turner's syndrome), trisomy of one or more chromosomes (13, 18, 21, and X), tetrasomy and pentasomy of one or more chromosomes (which in humans is most commonly observed in the sex chromosomes, e.g. XXXX, XXYY, XXXY, XYYY, XXXXX, XXXXY, XXXYY, XYYYY and XXYYY), triploidy (three of every chromosome, e.g. 69 chromosomes in humans), tetraploidy (four of every chromosome, e.g. 92 chromosomes in humans) and multiploidy. In some embodiments, an abnormal fetal genotype is a segmental aneuploidy. Examples of segmental aneuploidy include, but are not limited to, 1p36 duplication, dup(17)(p11.2p11.2) syndrome, Down syndrome, Pelizaeus-Merzbacher disease, dup(22)(q11.2q11.2) syndrome, and cat-eye syndrome. In some cases, an abnoiival fetal genotype is due to one or more deletions of sex or autosomal chromosomes, which may result in a condition such as Cri-du-chat syndrome, Wolf-Hirschhorn, Williams-Beuren syndrome, Charcot-Marie-Tooth disease, Hereditary neuropathy with liability to pressure palsies, Smith-Magenis syndrome, Neurofibromatosis, Alagille syndrome, Velocardiofacial syndrome, DiGeorge syndrome, Steroid sulfatase deficiency, Kallmann syndrome, Microphthalmia with linear skin defects, Adrenal hypoplasia, Glycerol kinase deficiency, Pelizaeus-Merzbacher disease, Testis-determining factor on. Y, Azospermia (factor a), Azospermia (factor b), Azospermia (factor c), or 1p36 deletion. In some embodiments, a decrease in chromosomal number results in an XO syndrome.
In one embodiment, the methods of the invention allow for the determination of maternal or paternal trisomy. In some embodiments, the methods of the invention allow for the determination of trisomy or other conditions in fetal cells in a mixed maternal sample arising from more than one fetus.
In another aspect of the invention, standard quantitative genotyping technology is used to declare the presence of fetal cells and to determine the copy numbers (ploidies) of the fetal chromosomes. Several groups have demonstrated that quantitative genotyping approaches can be used to detect copy number changes (Wang, Moorhead et al. 2005). However, these approaches do not perform well on mixtures of cells and typically require a relatively large number of input cells (˜10,000). The current invention addresses the complexity issue by performing the quantitative genotyping reactions on individual cells. In addition, multiplex PCR and DNA tags are used to perform the thousands of genotyping reaction on single cells in highly parallel fashion.
An overview of this embodiment is illustrated in
In step 500, a sample (e.g., a mixed sample of rare and non-rare cells) is obtained from an animal or a human. See, e.g., step 400 of
In step 502, the sample is enriched for rare cells (e.g., fetal cells) by any method known in the art or described herein. See, e.g., step 402 of
In step 504, the enriched product is split into multiple distinct sites (e.g., wells). See, e.g., step 404 of
In step 506, PCR primer pairs for amplifying multiple (e.g., 2-100) highly polymorphic genomic DNA regions (e.g., SNPs) are added to each discrete site or well in the array or microtiter plate. For example, PCR primer pairs for amplifying SNPs along chromosome 13, 18, 21 and/or X can be designed to detect the most frequent aneuoploidies. Other PCR primer pairs can be designed to amplify SNPs along control regions of the genome where aneuploidy is not expected. The genomic loci (e.g., SNPs) in the aneuploidy region or aneuploidy suspect region are selected for high polymorphism such that the paternal alleles of the fetal cells are more likely to be distinct from the maternal alleles. This improves the power to detect the presence of fetal cells in a mixed sample as well as fetal conditions or abnormalities. SNPs can also be selected for their association with a particular condition to be detected in a fetus. In some cases, one or more than one, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, or 100 SNPs are analyzed per target chromosome (e.g., 13, 18, 21, and/or X). The increase number of SNPs interrogated per chromosome ensures accurate results. PCR primers are chosen to be multiplexible with other pairs (fairly uniform melting temperature, absence of cross-priming on the human genome, and absence of primer-primer interaction based on sequence analysis). The primers are designed to generate amplicons 10-200, 20-180, 40-160, 60-140 or 70-100 bp in size to increase the performance of the multiplex PCR.
A second of round of PCR using nested primers may be performed to ensure optimal performance of the multiplex amplification. The multiplex amplification of single cells is helpful to generate sufficient starting material for the parallel genotyping procedure. Multiplex PCT can be performed on single cells with minimal levels of allele dropout and preferential amplification. See Sherlock, J., et al. Ann. Hum. Genet. 61 (Pt 1): 9-23 (1998); and Findlay, I., et al. Mol. Cell. Endocrinol. 183 Suppl. 1: S5-12 (2001).
In step 508, amplified polymorphic DNA region(s) of interest (e.g., SNPs) are tagged e.g., with nucleic acid tags. Preferably, the nucleic acid tags serve two roles: to determine the identity of the different SNPs and to determine the identity of the bin from which the genotype was derived. Nucleic acid tags can comprise primers that allow for allele-specific amplification and/or detection. The nucleic acid tags can be of a variety of sizes including up to 10 base pairs, 10-40, 15-30, 18-25 or ˜22 base pair long.
In some embodiments, a nucleic acid tag comprises a molecular inversion probe (MIP). Examples of MIPs and their uses are described in Hardenbol, P., et al., Nat. Biotechnol. 21(6):673-8 (2003); Hardenbol, P., et al., Genome Res. 15(2):269-75 (2005); and Wang, Y., et al., Nucleic Acids Res. 33(21):e183 (2005).
In one embodiment, a nucleic acid tag comprises a unique property, such as a difference in mass or chemical properties from other tags. In another embodiments a nucleic acid tag comprises a photoactivatable label, so that it crosslinks where it binds. In another embodiment a nucleic acid tag can be used as a linker for ultra deep sequencing. In another embodiment a nucleic acid tag can be used as a linker for arrays. In another embodiment a nucleic acid tag comprises a unique fluorescent label, (Such as FAM, JOE, ROX, NED, HEX, SYBR, PET, TAMRA, VIC, CY-3, CY-5, dR6G, DS-33, LIZ, DS-02, dR110, and Texas Red) which can be used to differentiate individual DNA fragments. In another embodiment a nucleic acid tag can serve as primer or hybridization site for a probe, to facilitate signal amplification or detection from a single cell by using a tractable marker. In some embodiments the labeled nucleic acid tag can be analyzed using a system coupled to a light source, such as an ABI 377, 310, 3700 or any other system which can detect fluorescently labeled DNA.
In step 510, the tagged amplicons are pooled together for further analysis.
In step 512, the genotype at each polymorphic site is determined and/or quantified using any technique known in the art. In one embodiment, genotyping occurs by hybridization of the MIP tags to a microarray containing probes complementary to the sequences of each MIP tag. See U.S. Pat. No. 6,858,412.
Using the example described above with the MIP probes, the 20,000 tags are hybridized to a single tag array containing complementary sequences to each of the tagged MIP probes. Microarrays (e.g. tag arrays) can include a plurality of nucleic acid probes immobilized to discrete spots (e.g., defined locations or assigned positions) on a substrate surface. For example, a microarray can have at least 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 500, 1,000, 5,000, 10,000, 15,000, 20,000, 30,000, 40,000, 50,000, 60,000, 70,000, 80,000, 90,000, or 100,000 different probes complementary to MIP tagged probes. Methods to prepare microarrays capable to monitor several genes according to the methods of the invention are well known in the art. Examples of microarrays that can be used in nucleic acid analysis that may be used are described in U.S. Pat. No. 6,300,063, U.S. Pat. No. 5,837,832, U.S. Pat. No. 6,969,589, U.S. Pat. No. 6,040,138, U.S. Pat. No. 6,858,412, US Publication No. 2005/0100893, US Publication No. 2004/0018491, US Publication No. 2003/0215821 and US Publication No. 2003/0207295.
In step 516, bins with rare alleles (e.g., fetal alleles) are identified. Using the example described above, rare allele identification can be accomplished by first using the 22 bp tags to sort the 20,000 genotypes into 500 bins which correspond to the individual wells of the original microtiter plates. Then, one can identify bins containing non-maternal alleles which correspond to wells that contained fetal cells. Determining the number bins with non-maternal alleles relative to the total number of its provides an accurate estimate of the number of fnRBCs that were present in the original enriched cell population. When a fetal cell is identified in a given bin, the non-maternal alleles can be detected by 40 independent SNPS s which provide an extremely high level of confidence in the result.
In step 518, a condition such as trisomy is determined based on the rare cell polymorphism. For example, after identifying the ˜10 bins that contain fetal cells, one can determine the ploidy of chromosomes 13, 18, 21 and X of such cells by comparing the ratio of maternal to paternal alleles for each of ˜10 SNPs on each chromosome (X, 13, 18, 21). The ratios for the multiple SNPs on each chromosome can be combined (averaged) to increase the confidence of the aneuploidy call for that chromosome. In addition, the information from the ˜10 independent bins containing fetal cells can also be combined to further increase the confidence of the call.
As described above, an enriched maternal sample with 500 cells can be split into 500 discrete locations such that each location contains one cell. If ten SNPs are analyzed in each of four different chromosomes, forty tagged MIP probes are added per discrete location to analyze forty different SNPs per cell. The forty SNPs are then amplified in each location using the primer element in the MIP probe as described above. All the amplicons from all the discrete locations are then pooled and analyzed using quantitative genotyping as describe above. In this example a total of 20,000 probes in a microarray are required to genotype the same 40 SNPs in each of the 500 discrete locations (4 chromosomes×10 SNPs×500 discrete locations).
The above embodiment can also be modified to provide for genotyping by hybridizing the nucleic acid tags to bead arrays as are commercially available by Illumina, Inc. and as described in U.S. Pat. Nos. 7,040,959; 7,035,740; 7033,754; 7,025,935, 6,998,274; 6, 942,968; 6,913,884; 6,890,764; 6,890,741; 6,858,394; 6,846,460; 6,812,005; 6,770,441; 6,663,832; 6,620,584; 6,544,732; 6,429,027; 6,396,995; 6,355,431 and US Publication Application Nos. 20060019258; 20050266432; 20050244870; 20050216207; 20050181394; 20050164246; 20040224353; 20040185482; 20030198573; 20030175773; 20030003490; 20020187515; and 20020177141; as well as Shen, R., et al. Mutation Research 573 70-82 (2005).
An overview of the use of nucleic acid tags is described in
In any of the embodiments herein, preferably, more than 1000, 5,000, 10,000, 50,000, 100,000, 500,000, or 1,000,000 SNPs are interrogated in parallel.
In another aspect of the invention, illustrated in part by
Cancers such as breast, colon, liver, ovary, prostate, and lung as well as other tumors exfoliate epithelial cells into the bloodstream. The presence of an increased number epithelial cells is associated with an active tumor or other neoplastic condition, tumor progression and spread, poor response to therapy, relapse of disease, and/or decreased survival over a period of several years. Therefore, enumerating and/or analyzing epithelial cells and CTC's in the bloodstream can be used to diagnose, prognose, and/or monitor neoplastic conditions.
In step 600, a sample is obtained from an animal such as a human. The human can be suspected of having cancer or cancer recurrence or may have cancer and is in need of therapy selection. The sample obtained is a mixed sample comprising normal cells as well as one or more CTCs, epithelial cells, endothelial cells, stem cells, or other cells indicative of cancer. In some cases, the sample is a blood sample. In some cases multiple samples are obtained from the animal at different points in time (e.g., regular intervals such as daily, or every 2, 3 or 4 days, weekly, bimonthly, monthly, bi-yearly or yearly. In step 602, the mixed sample is then enriched for epithelial cells or CTC's or other cell indicative of cancer. Epithelial cells that are exfoliated from solid tumors have been found in very low concentrations in the circulation of patients with advanced cancers of the breast, colon, liver, ovary, prostate, and lung, and the presence or relative number of these cells in blood has been correlated with overall prognosis and response to therapy. These epithelial cells which are in fact CTCs can be used as an early indicator of tumor expansion or metastasis before the appearance of clinical symptoms.
CTCs are generally larger than most blood cells. Therefore, one useful approach for obtaining CTCs in blood is to enrich them based on size, resulting in a cell population enriched in CTCs. Another way to enrich CTCs is by affinity separation, using antibodies specific for particular cell surface markers may be used. Useful endothelial cell surface markers include CD105, CD106, CD144, and CD 146; useful tumor endothelial cell surface markers include TEM1, TEM5, and TEM8 (see, e.g., Carson-Walter et al., Cancer Res. 61; 6649-6655 (2001)); and useful mesenchymal cell surface markers include CD133. Antibodies to these or other markers may be obtained from, e.g., Chemicon, Abeam, and R&D Systems.
In one example, a size-based separation module that enriches CTC's from a fluid sample (e.g., blood) comprises an array of obstacles that selectively deflect particles having a hydrodynamic size larger than 10 urn into a first outlet and particles having a hydrodynamic size smaller than 10 μm into a second outlet is used to enrich epithelial cells and CTC's from the sample.
In step 603, the enriched product is split into a plurality of discrete sites, such as microwells. Exemplary microwells that can be used in the present invention include microplates having 1536 wells as well as those of lesser density (e.g., 96 and 384 wells). Microwell plate design contemplated herein include those have 14 outputs that can be automatically dispensed at the same time, as well as those with 16, 24, or 32 outputs such that e.g., 32 outputs can be dispenses simultaneously.
Dispensing of the cells into the various discrete sites is preferably automated. In some cases, about 1, 5, 10, or 15 μL of enriched sample is dispensed into each well. Preferably, the size of the well and volume dispensed into each well is such that only 1 cell is dispensed per well and only 1-5 or less than 3 cells can fit in each well.
An exemplary array for sample splitting is illustrated in
In some embodiments, such as those illustrated in
In some cases, the array of wells can be a micro-electro-mechanical system (MEMS) such that it integrates mechanical elements, sensors, actuators, and electronics on a common silicon substrate through microfabrication technology. Any electronics in the system can be fabricated using integrated circuit (IC) process sequences (e.g., CMOS, Bipolar, or BICMOS processes), while the micromechanical components are fabricated using compatible micromachining processes that selectively etch away parts of the silicon wafer or add new structural layers to form the mechanical and electromechanical devices. One example of a MEMS array of wells includes a MEMS isolation element within each well. The MEMS isolation element can create a flow using pressure and/or vacuum to increase pressure on cells and particles not of interest to escape the well through the well opening. In any of the embodiments herein, the array of wells can be coupled to a microscope slide or other substrate that allows for convenient and rapid optical scanning of all chambers (i.e. discrete sites) under a microscope. In some embodiments, a 1536-well microtiter plate is used for enhanced convenience of reagent addition and other manipulations.
In some cases, the enriched product can be split into wells such that each well is loaded with a plurality of leukocytes (e.g., more than 100, 200, 500, 1000, 2000, or 5000). In some cases, about 2500 leukocytes are dispensed per well, while random wells will have a single epithelial CTC or up to 2, 3, 4, or 5 epithelial cells or CTC's. Preferably, the probability of getting a single epithelial cell or CTC into a well is calculated such that no more than 1 CTC is loaded per well. The probability of dispensing CTC's from a sample into wells can be calculated using Poisson statistics. When dispensing a 15 mL sample into 1536 wellplate at 10 μL per well, it is not until the number of CTC's in the sample is >100 that there is more than negligible probability of two or more CTC's being loaded into the sample well.
In step 604, rare cells (e.g. epithelial cells or CTC's) or rare DNA is detected and/or analyzed in each well.
In some embodiments, detection and analysis includes enumerating epithelial cells and/or CTC's. CTCs typically have a short half-life of approximately one day, and their presence generally indicates a recent influx from a proliferating tumor. Therefore, CTCs represent a dynamic process that may reflect the current clinical status of patient disease and therapeutic response. Thus, in some embodiments, step 604 involves enumerating CTC and/or epithelial cells in a sample (array of wells) and determining based on their number if a patient has cancer, severity of condition, therapy to be used, or effectiveness of therapy administered.
In some cases, the method herein involve making a series of measurements, optionally made at regular intervals such as one day, two days, three days, one week, two weeks, one month, two months, three months, six months, or one year, one may track the level of epithelial cells present in a patient's bloodstream as a function of time. In the case of existing cancer patients, this provides a useful indication of the progression of the disease and assists medical practitioners in making appropriate therapeutic choices based on the increase, decrease, or lack of change in epithelial cells, e.g., CTCs, in the patient's bloodstream. For those at risk of cancer, a sudden increase in the number of cells detected may provide an early warning that the patient has developed a tumor. This early diagnosis, coupled with subsequent therapeutic intervention, is likely to result in an improved patient outcome in comparison to an absence of diagnostic information.
In some cases, more than one type of cell (e.g., epithelial, endothelial, etc.) can be enumerated and a determination of a ratio of numbers of cells or profile of various cells can be obtained to generate the diagnosis or prognosis.
Alternatively, detection of rare cells or rare DNA (e.g. epithelial cells or CTC's) can be made by detecting one or more cancer biomarkers, e.g., any of those listed in
In some cases single cell analysis techniques are used to analyze individual cells in each well. For example, single cell PCR may be performed on a single cell in a discrete location to detect one or more mutant alleles in the cell (Thornhill A R, J. Mol. Diag; (4) 11-29 (2002)) or a mutation in a gene listed in
In some cases, morphological analyses are performed on the cells in each well. Morphological analyses include identification, quantification and characterization of mitochondrial DNA, telomerase, or nuclear matrix proteins. Parrella et al., Cancer Res. 61:7623-7626 (2001); Jones et al., Cancer Res. 61:1299-1304 (2001); Fliss et al., Science 287:2017-2019 (2000); and Soria et al., Clin. Cancer Res. 5:971-975 (1999). In particular, in some cases, the molecular analyses involves determining whether any mitoehrondial abnormalities or whether perinuclear compartments are present. Carew et al., Mol. Cancer. 1:9 (2002); and Wallace, Science 283:1482-1488 (1999).
A variety of cellular characteristics may be measured using any technique known in the art, including: protein phosphorylation, protein glycosylation, DNA methylation (Das et al., J. Clin. Oncol. 22:4632-4642 (2004)), microRNA levels (He et al., Nature 435:828-833 (2005), Lu et al., Nature 435:834-838 (2005), O'Donnell et al., Nature 435:839-843 (2005), and Calin et al., N. Engl. J. Med. 353:1793-1801 (2005)), cell morphology or other structural characteristics, e.g., pleomorphisms, adhesion, migration, binding, division, level of gene expression, and presence of a somatic mutation. This analysis may be performed on any number of cells, including a single cell of interest, e.g., a cancer cell.
In one embodiment, the cell(s) (such as fetal, maternal, epithelial or CTCs) in each well are lysed and RNA is extracted using any means known in the art. For example, The Quiagen RNeasy™ 96 bioRobot™ 8000 system can be used to automate high-throughput isolation of total RNA from each discrete site. Once the RNA is extracted reverse transcriptase reactions can be performed to generate cDNA sequences, which can then be used for performing multiplex PCR reactions on target genes. For example, 1 or more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, or 20 target genes can be amplified in the same reaction. When more than one target genes are used in the same amplification reaction, primers are chosen to be multiplexable (fairly uniform melting temperature, absence of cross-priming on the human genome, and absence of primer-primer interaction based on sequence analysis) with other pairs of primers. Multiple dyes and multi-color fluorescence readout may be used to increase the multiplexing capacity. Examples of dyes that can be used to label primers for amplification include, but are not limited to, chromophores, fluorescent moieties, enzymes, antigens, heavy metal, magnetic probes, dyes, phosphorescent groups, radioactive materials, chemiluminescent moeities, scattering or fluorescent nanoparticles, Raman signal generating moieties, and electrochemical detection moieties.
In another embodiment, fetal or maternal cells or nuclei are enriched using one or more methods disclosed herein. Preferably, fetal cells are enriched by flowing the sample through an array of obstacles that selectively directs particles or cells of different hydrodynamic sizes into different outlets such that fetal cells and cells larger than fetal cells are directed into a first outlet and one or more cells or particles smaller than the rare cells are directed into a second outlet.
Total RNA or poly-A mRNA is then obtained from enriched cell(s) (fetal or maternal cells) using purification techniques known in the art. Generally, about 1 μg-2 μg of total RNA is sufficient. Next, a first-strand complementary DNA (cDNA) is synthesized using reverse transcriptase and a single T7-oligo(dT) primer. Next, a second-strand cDNA is synthesized using DNA ligase, DNA polymerase, and RNase enzyme. Next, the double stranded cDNA (ds-cDNA) is purified.
In another embodiment, total RNA is extracted from enriched cells (fetal cells or maternal cells). Next a, two one-quarter scale Message Amp II reactions (Ambion, Austin, Tex.) are performed for each RNA extraction using 200 ng of total RNA. MessageAmp is a procedure based on antisense RNA (aRNA) amplification, and involves a series of enzymatic reactions resulting in linear amplification of exceedingly small amounts of RNA for use in array analysis. Unlike exponential RNA amplification methods, such as NASBA and RT-PCR, aRNA amplification maintains representation of the starting mRNA population. The procedure begins with total or poly(A) RNA that is reverse transcribed using a primer containing both oligo(dT) and a T7 RNA polymerase promoter sequence. After first-strand synthesis, the reaction is treated with RNase H to cleave the mRNA into small fragments. These small RNA fragments serve as primers during a second-strand synthesis reaction that produces a double-stranded cDNA template.
In some embodiments, cDNAs, which are reverse transcribed from mRNAs obtained from fetal or maternal cells, are tagged and sequenced. The type and abundance of the cDNAs can be used to determine whether a cell is a fetal cell (such as by the presence of Y chromosome specific transcripts) or whether the fetal cell has a genetic abnormality (such as aneuploidy, abundance or type of alternative transcripts or problems with DNA methylation or imprinting).
In one embodiment, PCR amplification can be performed on genes that are expressed in epithelial cells and not in normal cells, e.g., white blood cells or other cells remaining in an enriched product. Exemplary genes that can be analyzed according to the methods herein include EGFR, EpCAM, GA733-2, MUC-1, HER-2, Claudin-7 and any other gene identified in
For example, analysis of the expression level or pattern of such a polypeptide or nucleic acid, e.g., cell surface markers, genomic DNA, mRNA, or microRNA, may result in a diagnosis or prognosis of cancer.
In some embodiments, cDNAs, which are reverse transcribed from mRNAs obtained from fetal or maternal cells, are tagged and sequenced. The type and abundance of the cDNAs can be used to determine whether a cell is a fetal cell (such as by the presence of Y chromosome specific transcripts) or whether the fetal cell has a genetic abnormality (such as anueploidy, or problems with DNA methylation or imprinting).
In some embodiments, analysis step 604 involves identifying cells from a mixed sample that express genes which are not expressed in the non-rare cells (e.g. EGFR or EpCAM). For example, an important indicator for circulating tumor cells is the presence/expression of EGFR or EGF at high levels wherein non-cancerous epithelial cells will express EGFR or EGF at smaller amounts if at all.
In addition, for lung cancer and other cancers, the presence or absence of certain mutations in EGFR can be associated with diagnosis and/or prognosis of the cancer as well and can also be used to select a more effective treatment (see, e.g., International Publication WO 2005/094357). For example, many non-small cell lung tumors with EGFR mutations respond to small molecule EGFR inhibitors, such as gefitinib (Iressa; AstraZeneca), but often eventually acquire secondary mutations that make them drug resistant. In some embodiments, one can determine a therapy treatment for a patient by enriching epithelial cells and/or CTC's using the methods herein, splitting sample of cells (preferably so no more than 1 CTC is in a discrete location), and detecting one or more mutations in the EGFR gene of such cells. Exemplary mutations that can be analyzed include those clustered around the ATP-binding pocket of the EGFR TK domain, which are known to make cells susceptible to gefitinib inhibition. Thus, presence of such mutations supports a diagnosis of cancer that is likely to respond to treatment using gefitinib.
Many patients who respond to gefitinib eventually develop a second mutation, often a methionine-to-threonine substitution at position 790 in exon 20 of the TK domain. This type of mutation renders such patients resistant to gefitinib. Therefore, the present invention contemplates testing for this mutation as well to provide further diagnostic information.
Since many EGFR mutations, including all EGFR mutations in NSC lung cancer reported to date that are known to confer sensitivity or resistance to gefitinib, lie within the coding regions of exons 18 to 21, this region of the EGFR gene may be emphasized in the development of assays for the presence of mutations. Examples of primers that can be used to detect mutations in EGFR include those listed in
In step 605, a determination is made as to the condition of a patient based on analysis made above. In some cases the patient can be diagnosed with cancer or lack thereof. In some cases, the patient can be prognosed with a particular type of cancer. In cases where the patient has cancer, therapy may be determined based on the types of mutations detected.
In another embodiment, cancer cells may be detected in a mixed sample (e.g. circulating tumor cells and circulating normal cells) using one or more of the sequencing methods described herein. Briefly, RNA is extracted from cells in each location and converted to cDNA as described above. Target genes are then amplified and high throughput ultra deep sequencing is performed to detect a mutation expression level associated with cancer.
VI. Computer Executable Logic
Any of the steps herein can be performed using computer program product that comprises a computer executable logic recorded on a computer readable medium. For example, the computer program can use data from target genomic DNA regions to determine the presence or absence of fetal cells in a sample and to determine fetal abnormalit(ies) in cells detected. In some embodiments, computer executable logic uses data input on STR or SNP intensities to determine the presence of fetal cells in a test sample and determine fetal abnormalities and/or conditions in said cells.
The computer program may be specially designed and configured to support and execute some or all of the functions for determining the presence of rare cells such as fetal cells or epithelial/CTC's in a mixed sample and abnormalities and/or conditions associated with such rare cells or their DNA including the acts of (i) controlling the splitting or sorting of cells or DNA into discrete locations (ii) amplifying one or more regions of genomic DNA e.g. trisomic region(s) and non-trisomic region(s) (particularly DNA polymorphisms such as STR and SNP) in cells from a mixed sample and optionally control sample, (iii) receiving data from the one or more genomic DNA regions analyzed (e.g. sequencing or genotyping data); (iv) identifying bins with rare (e.g. non-maternal) alleles, (v) identifying bins with rare (e.g. non-maternal) alleles as bins containing fetal cells or epithelial cells, (vi) determining number of rare cells (e.g. fetal cells or epithelial cells) in the mixed sample, (vii) detecting the levels of maternal and non-maternal alleles in identified fetal cells, (viii) detecting a fetal abnormality or condition in said fetal cells and/or (ix) detecting a neoplastic condition and information concerning such condition such as its prevalence, origin, susceptibility to drug treatment(s), etc. In particular, the program can fit data of the quantity of allele abundance for each polymorphism into one or more data models. One example of a data model provides for a determination of the presence or absence of aneuploidy using data of amplified polymorphisms present at loci in DNA from samples that are highly enriched for fetal cells. The determination of presence of fetal cells in the mixed sample and fetal abnormalities and/or conditions in said cells can be made by the computer program or by a user.
In one example, let ‘f’ be the fetal/maternal DNA copy ratio in a particular PCR reaction. Trisomy increases the ratio of maternal to paternal alleles by a factor 1+f/2. PCR efficiencies vary from allele to allele within a locus by a mean square error in the logarithm given by σallele2, and vary from locus to locus by σlocus2, where this second variance is apt to be larger due to differences in primer efficiency. Na is the loci per suspected aneuploid chromosome and Nc is the control loci. If the mean of the two maternal allele strengths at any locus is ‘m’ and the paternal allele strength is then the squared error expected is the mean of the ln(ratio(m/p)), where this mean is taken over N loci is given by 2(σallele2)/N. When taking the difference of this mean of ln(ratio(m/p)) between a suspected aneuploidy region and a control region, the error in the difference is given by
σdiff2=2(σallele2)/Na+2(σallele2)Nc (1)
For a robust detection of aneuploidy we require
3σdiff<f/2.
For simplicity, assuming Na=Nc=N in Equation 1, this gives the requirement
6σallele/N1/2<f/2, (3)
or a minimum N of
N=144(σallele/f)2 (4)
In the context of trisomy detection, the suspected aneuploidy region is usually the entire chromosome and N denotes the number of loci per chromosome. For reference, Equation 3 is evaluated for N in Table 2 for various values of σallele and f.
The role of the sequencing is to measure the allele abundances output from the amplification step. It is desirable to do this without adding significantly more error due to the Poisson statistics of selecting only a finite number of amplicons for sequencing. The rms error in the in(abundance) due to Poisson statistics is approximately (Nreads)−1/2. It is desirable to keep this value less than or equal to the PCR error σallele. Thus, a typical paternal allele needs to be allocated at least (σallele)−2 reads. The maternal alleles, being more abundant, do not add appreciably to this error when forming the ratio estimate for m/p. The mixture input to sequencing contains amplicons from Nloci loci of which roughly an abundance fraction f/2 are paternal alleles. Thus, the total required number of reads for each of the aliquot wells is given approximately by 2Nloci/(f σallele2). Combining this result with Equation 4, it is found a total number of reads over all the wells given approximately by Nreads=288 Nwells f3. Thus, the program can determine the total number of reads that need to be obtained for determining the presence or absence of aneuploidy in a patient sample.
The computer program can work in any computer that may be any of a variety of types of general-purpose computers such as a personal computer, network server, workstation, or other computer platform now or later developed. In some embodiments, a computer program product is described comprising a computer usable medium having the computer executable logic (computer software program, including program code) stored therein. The computer executable logic can be executed by a processor, causing the processor to perform functions described herein. In other embodiments, some functions are implemented primarily in hardware using, for example, a hardware state machine. Implementation of the hardware state machine so as to perform the functions described herein will be apparent to those skilled in the relevant arts.
In one embodiment, the computer executing the computer logic of the invention may also include a digital input device such as a scanner. The digital input device can provide an image of the target genomic DNA regions (e.g. DNA polymorphism, preferably STRs or SNPs) according to method of the invention. For instance, the scanner can provide an image by detecting fluorescent, radioactive, or other emissions; by detecting transmitted, reflected, or scattered radiation; by detecting electromagnetic properties or characteristics; or by other techniques. Various detection schemes are employed depending on the type of emissions and other factors. The data typically are stored in a memory device, such as the system memory described above, in the form of a data file.
In one embodiment, the scanner may identify one or more labeled targets. For instance, in the genotyping analysis described herein a first DNA polymorphism may be labeled with a first dye that fluoresces at a particular characteristic frequency, or narrow band of frequencies, in response to an excitation source of a particular frequency. A second DNA polymorphisms may be labeled with a second dye that fluoresces at a different characteristic frequency. The excitation sources for the second dye may, but need not, have a different excitation frequency than the source that excites the first dye, e.g., the excitation sources could be the same, or different, lasers.
In one embodiment, a human being may inspect a printed or displayed image constructed from the data in an image file and may identify the data (e.g. fluorescence from microarray) that are suitable for analysis according to the method of the invention. In another embodiment, the information is provided in an automated, quantifiable, and repeatable way that is compatible with various image processing and/or analysis techniques.
Another aspect of the invention is kits which permit the enrichment and analysis of the rare cells present in small qualities in the samples. Such kits may include any materials or combination of materials described for the individual steps or the combination of steps ranging from the enrichment through the genetic analysis of the genomic material. Thus, the kits may include the arrays used for size-based separation or enrichment, labels for uniquely labeling each cell, the devices utilized for splitting the cells into individual addressable locations and the reagents for the genetic analysis. For example, a kit might contain the arrays for size-based separation, unique labels for the cells and reagents for detecting polymorphisms including STRs or SNPs, such as reagents for performing PCR.
While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention. It is intended that the following claims define the scope of the invention and that methods and structures within the scope of these claims and their equivalents be covered thereby.
Dimensions: 100 mm×28 mm×1 mm
Array design: 3 stages, gap size=18, 12 and 8 μm for the first, second and third stage, respectively.
Device fabrication: The arrays and channels were fabricated in silicon using standard photolithography and deep silicon reactive etching techniques. The etch depth is 140 μm. Through holes for fluid access are made using KOH wet etching. The silicon substrate was sealed on the etched face to form enclosed fluidic channels using a blood compatible pressure sensitive adhesive (9795, 3M, St Paul, Minn.).
Device packaging: The device was mechanically mated to a plastic manifold with external fluidic reservoirs to deliver blood and buffer to the device and extract the generated fractions.
Device operation: An external pressure source was used to apply a pressure of 2.0 PSI to the buffer and blood reservoirs to modulate fluidic delivery and extraction from the packaged device.
Experimental conditions: Human fetal cord blood was drawn into phosphate buffered saline containing Acid Citrate Dextrose anticoagulants. 1 mL of blood was processed at 3 mL/hr using the device described above at room temperature and within 48 hrs of draw. Nucleated cells from the blood were separated from enucleated cells (red blood cells and platelets), and plasma delivered into a buffer stream of calcium and magnesium-free Dulbecco's Phosphate Buffered Saline (14190-144, Invitrogen, Carlsbad, Calif.) containing 1% Bovine Serum Albumin (BSA) (A8412-100ML, Sigma-Aldrich, St Louis, Mo.) and 2 mM EDTA (15575-020, Invitrogen, Carlsbad, Calif.).
Measurement techniques: Cell smears of the product and waste fractions (
Performance: Fetal nucleated red blood cells were observed in the product fraction (
The device and process described in detail in Example 1 were used in combination with immunomagnetic affinity enrichment techniques to demonstrate the feasibility of isolating fetal cells from maternal blood.
Experimental conditions: blood from consenting maternal donors carrying male fetuses was collected into K2EDTA vacutainers (366643, Becton Dickinson, Franklin Lakes, N.J.) immediately following elective termination of pregnancy. The undiluted blood was processed using the device described in Example 1 at room temperature and within 9 his of draw. Nucleated cells from the blood were separated from enucleated cells (red blood cells and platelets), and plasma delivered into a buffer stream of calcium and magnesium-free Dulbecco's Phosphate Buffered Saline (14190-144, Invitrogen, Carlsbad, Calif.) containing 1% Bovine Serum Albumin (BSA) (A8412-100ML, Sigma-Aldrich, St Louis, Mo.). Subsequently, the nucleated cell fraction was labeled with anti-CD71 microbeads (130-046-201, Miltenyi Biotech Inc., Auburn, Calif.) and enriched using the MiniMACS™ MS column (130-042-201, Miltenyi Biotech Inc., Auburn, Calif.) according to the manufacturer's specifications. Finally, the CD71-positive fraction was spotted onto glass slides.
Measurement techniques: Spotted slides were stained using fluorescence in situ hybridization (FISH) techniques according to the manufacturer's specifications using Vysis probes (Abbott Laboratories, Downer's Grove, Ill.). Samples were stained from the presence of X and Y chromosomes. In one case, a sample prepared from a known Trisomy 21 pregnancy was also stained for chromosome 21.
Performance: Isolation of fetal cells was confirmed by the reliable presence of male cells in the CD71-positive population prepared from the nucleated cell fractions (
Confirmation of the presence of a male fetal cell in an enriched sample is performed using qPCR with primers specific for DYZ, a marker repeated in high copy number on the Y chromosome. After enrichment of fhRBC by any of the methods described herein, the resulting enriched fnRBC are binned by dividing the sample into 100 PCR wells. Prior to binning, enriched samples may be screened by FISH to determine the presence of any fnRBC containing an aneuploidy of interest. Because of the low number of fnRBC in maternal blood, only a portion of the wells will contain a single fnRBC (the other wells are expected to be negative for fnRBC). The cells are fixed in 2% Paraformaldehyde and stored at 4° C. Cells in each bin are pelleted and resuspended in 5 PBS plus 1 μl 20 mg/ml Proteinase K (Sigma #P-2308). Cells are lysed by incubation at 65° C. for 60 minutes followed by inactivation of the Proteinase K by incubation for 15 minutes at 95° C. For each reaction, primer sets (DYZ forward primer TCGAGTGCATTCCATTCCG; DYZ reverse primer ATGGAATGGCATCAAACGGAA; and DYZ Taqman Probe 6FAM-TGGCTGTCCATTCCA-MGBNFQ), TaqMan Universal PCR master mix, No AmpErase and water are added. The samples are run and analysis is performed on an ABI 7300: 2 minutes at 50° C., 10 minutes 95° C. followed by 40 cycles of 95° C. (15 seconds) and 60° C. (1 minute). Following confirmation of the presence of male fetal cells, further analysis of bins containing fnRBC is performed. Positive bins may be pooled prior to further analysis.
Maternal blood is processed through a size-based separation module, with or without subsequent MHEM enhancement of fnRBCs. The enhanced sample is then subjected to FISH analysis using probes specific to the aneuploidy of interest (e.g., trisomy 13, trisomy 18, and XYY). Individual positive cells are isolated by “plucking” individual positive cells from the enhanced sample using standard micromanipulation techniques. Using a nested PCR protocol, STR marker sets are amplified and analyzed to confirm that the FISH-positive aneuploid cell(s) are of fetal origin. For this analysis, comparison to the maternal genotype is typical. An example of a potential resulting data set is shown in Table 3. Non-maternal alleles may be proven to be paternal alleles by paternal genotyping or genotyping of known fetal tissue samples. As can be seen, the presence of paternal alleles in the resulting cells, demonstrates that the cell is of fetal origin (cells #1, 2, 9, and 10). Positive cells may be pooled for further analysis to diagnose aneuploidy of the fetus, or may be further analyzed individually.
Maternal blood is processed through a size-based separation module, with or without subsequent MHEM enhancement of fnRBCs. The enhanced sample is then subjected to FISH analysis using probes specific to the aneuploidy of interest (e.g., triploidy 13, triploidy 18, and XYY). Samples testing positive with FISH analysis are then binned into 96 microtiter wells, each well containing 15 μl of the enhanced sample. Of the 96 wells, 5-10 are expected to contain a single fnRBC and each well should contain approximately 1000 nucleated maternal cells (both WBC and mnRBC). Cells are pelleted and resuspended in 5 μl PBS plus 1 μl 20 mg/ml Proteinase K (Sigma #P-2308). Cells are lysed by incubation at 65° C. for 60 minutes followed by a inactivation of the Proteinase K by 15 minute at 95° C.
In this example, the maternal genotype (BB) and fetal genotype (AB) for a particular set of SNPs is known. The genotypes A and B encompass all three SNPs and differ from each other at all three SNPs. The following sequence from chromosome 7 contains these three SNPs (rs7795605, rs7795611 and rs7795233 indicated in brackets, respectively):
In the first round of PCR, genomic DNA from binned enriched cells is amplified using primers specific to the outer portion of the fetal-specific allele A and which flank the interior SNP (forward primer ATGCAGCAAGGCACAGACTACG; reverse primer AGAGGGGAGAGAAATGGGTCATT). In the second round of PCR, amplification using real time SYBR Green PCR is performed with primers specific to the inner portion of allele A and which encompass the interior SNP (forward primer CAAGGCACAGACTAAGCAAGGAGAG; reverse primer GGCAAAATTTTCATAGGGGAGAGAAATGGGTCATT).
Expected results are shown in
Fetal cells or nuclei can be isolated as described in the enrichment section or as described in example 1. Quantitative genotyping can then be used to detect chromosome copy number changes.
Perform multiplex PCR and nested PCR: PCR primer pairs for multiple (40-100) highly polymorphic SNPs can then be added to each well in the microtiter plate. For example, SNPs primers can be designed along chromosomes 13, 18, 21 and X to detect the most frequent aneuploidies, and along control regions of the genome where aneuploidy is not expected. Multiple (˜10) SNPs would be designed for each chromosome of interest to allow for non-informative genotypes and to ensure accurate results. The SNPs listed in the Table below can be used to performed analysis and associated PCR primers can be designed as described below.
PCR primers would be chosen to be multiplexible with other pairs (fairly uniform melting temperature, absence of cross-priming on the human genome, and absence of primer-primer interaction based on sequence analysis). The primers would be designed to generate amplicons 70-100 bp in size to increase the performance of the multiplex PCR. The primers would contain a 22 bp tag on the 5′ which is used in the genotyping analysis. Multiplex PCR protocols can be performed as described in Findlay et al. Molecular Cell Endocrinology 183 (2001) S5-S12. Primer concentrations can vary from 0.7 pmoles to 60 pmoles per reaction. Briefly, PCRs are performed in a total volume of 25 μA per well, Taq polymerase buffer (Perkin-Elmer), 200 μM dNTPs, primer, 1.5 mM MgCl2 and 0.6 units AmpliTaq (Perkin-Elmer). After denaturation at 95° C. for 5 min, 41 cycles at 94, 60 and 72° C. for 45 s are performed in a MJ DNA engine thermal cycler. The amplification can be run with an annealing temperature different that 60° C. depending on the primer pair being amplified. Final extension can be for 10 min.
A second of round of PCR using nested primers may be performed to ensure optimal performance of the multiplex amplification. Two ul aliquot of each PCR reaction is diluted 40 fold (to 80 ul total) with nuclease free water from the PCR kit. A no template or negative control is generated to test for contamination. The amplification with the nested PCR primers is run with an annealing temperature of 60° C.-68° C. depending on the primer pair being amplified.
Genotyping sing MIP technology with bin specific tags: The Molecular Inversion Probe (MIP) technology developed by Affyinetrix (Santa Clara, Calif.) can genotype 20,000 SNPs or more in a single reaction. In the typical MIP assay, each SNP would be assigned a 22 bp DNA tag which allows the SNP to be uniquely identified during the highly parallel genotyping assay. In this example, the DNA tags serve two roles: (1) determine the identity of the different SNPs and (2) determine the identity of the well from which the genotype was derived. For example, a total of 20,000 tags would be required to genotype the same 40 SNPs in 500 wells different wells (4 chromosomes×10 SNPs×500 wells)
The tagged MIP probes would be combined with the amplicons from the initial multiplex single-cell PCR (or nested PCR) and the genotyping reactions would be performed. The probe/template mix would be divided into 4 tubes each containing a different nucleotide (e.g. G, A, T or C). Following an extension and ligation step, the mixture would be treated with exonuclease to remove all linear molecules and the tags of the surviving circular molecules would be amplified using PCR. The amplified tags form all of the bins would then be pooled and hybridized to a single DNA microarray containing the complementary sequences to each of the 20,000 tags.
Identify bins with non-maternal alleles (e.g. fetal cells): The first step in the data analysis procedure would be to use the 22 bp tags to sort the 20,000 genotypes into bins which correspond to the individual wells of the original microtiter plates. The second step would be to identify bins contain non-maternal alleles which correspond to wells that contained fetal cells. Determining the number bins with non-maternal alleles relative to the total number of bins would provide an accurate estimate of the number of fnRBCs that were present in the original enriched cell population. When a fetal cell is identified in a given bin, the non-maternal alleles would be detected by 40 independent SNPs which provide an extremely high level of confidence in the result.
Detect ploidy for chromosomes 13, 18, and 21: After identifying approximately 10 bins that contain fetal cells, the next step would be to determine the ploidy of chromosomes 13, 18, 21 and X by comparing ratio of maternal to paternal alleles for each of the 10 SNPs on each chromosome. The ratios for the multiple SNPs on each chromosome can be combined (averaged) to increase the confidence of the aneuploidy call for that chromosome. In addition, the information from the approximate 10 independent bins containing fetal cells can also be combined to further increase the confidence of the call.
Fetal cells or nuclei can be isolated as described in the enrichment section or as described in example 1. The enrichment process described in example 1 may generate a final mixture containing approximately 500 maternal white blood cells (WBCs), approximately 100 maternal nuclear red blood cells (mnBCs), and a minimum of approximately 10 fetal nucleated red blood cells (fnRBCs) starting from an initial 20 ml blood sample taken late in the first trimester. The output of the enrichment procedure would be divided into separate wells of a microliter plate with the number of wells chosen so no more than one cell or genome copy is located per well, and where some wells may have no cell or genome copy at all.
Perform multiplex PCR and Ultra-Deep Sequencing with bin specific tags: PCR primer pairs for highly polymorphic STR loci (multiple loci per chromosome of interest) are then added to each well in the microliter plate. The polymorphic STRs listed in the Table below can be used to performed analysis and associated PCR primers can be designed.
The primers for each STR will have two important features. First, each of the primers will contain a common ˜18 bp sequence on the 5′ end which is used for the subsequent DNA cloning and sequencing procedures. Second, each well in the microliter plate is assigned a unique ˜6 bp DNA tag sequence which is incorporated into the middle part of the upstream primer for each of the different STRs. The DNA tags make it possible to pool all of the STR amplicons following the multiplex PCR which makes it possible to analyze the amplicons in parallel more cost effectively during the ultra-deep sequencing procedure. DNA tags of length ˜6 bp provide a compromise between information content (4096 potential bins) and the cost of synthesizing primers.
Multiplex PCR protocols can be performed as described in Findlay et al. Molecular Cell Endocrinology 183 (2001) 85-S 12. Primer concentrations can vary from 0.7 pmoles to 60 pmoles per reaction. Briefly, PCRs are performed in a total volume of 25 μl per well, Taq polymerase buffer (Perkin-Elmer), 200 μM dNTPs, primer, 1.5 mM MgCl2 and 0.6 units AmpliTaq (Perkin-Elmer). After denaturation at 95° C. for 5 min, 41 cycles at 94, 60 and 72° C. for 45 s are performed in a MJ DNA engine thermal cycler. The amplification can be run with an annealing temperature different that 60° C. depending on the primer pair being amplified. Final extension can be for 10 min.
Following PCR, the amplicons from each of the wells in the microtiter plate are pooled, purified and analyzed using a single-molecule sequencing strategy as described in Margulies et al. Nature 437 (2005) 376-380. Briefly, the amplicons are diluted and mixed with beads such that each bead captures a single molecule of the amplified material. The DNA-carrying beads are isolated in separate 100 μm aqueous droplets made through the creation of a PCR-reaction-mixture-in-oil emulsion. The DNA molecule on each bead is then amplified to generate millions of copies of the sequence, which all remain bound to the bead. Finally, the beads are placed into a highly parallel sequencing-by-synthesis machine which can generate over 400,000 sequence reads (˜100 bp per read) in a single 4 hour run.
Ultra-deep sequencing provides an accurate and quantitative way to measure the allele abundances for each of the STRs. The total required number of reads for each of the aliquot wells is determined by the number of STRs and the error rates of the multiplex PCR and the Poisson sampling statistics associated with the sequencing procedures. Statistical models which may account for variables in amplification can be used to detect ploidy changes with high levels of confidence. Using this statistical model it can be predicted that ˜100,000 to 300,000 sequence reads will be required to analyze each patient, with ˜3 to 10 STR loci per chromosome. Specifically, ˜33 reads for each of 12 STRs in each of the individual wells of the microtiter plate will be read (33 reads×12 STRs per well×500 wells=200,000 reads).
Identify bins with non-maternal alleles (e.g. fetal cells): The first step in the data analysis procedure would be to use the 6 bp DNA tags to sort the 200,000 sequence reads into bins which correspond to the individual wells of the microtiter plates. The ˜400 sequence reads from each of the bins would then be separated into the different STR groups using standard sequence alignment algorithms. The aligned sequences from each of the bins would then be analyzed to identify non-maternal alleles. These can be identified in one of two ways. First, an independent blood sample fraction known to contain only maternal cells can be analyzed as described above. This sample can be a white blood cell fraction (which will contain only negligible numbers of fetal cells), or simply a dilution of the original sample before enrichment. Alternatively, the genotype profiles for all the wells can be similarity-clustered to identify the dominant pattern associated with maternal cells. In either approach, the detection of non-maternal alleles then determines which wells in the initial microtiter plate contained fetal cells. Determining the number bins with non-maternal alleles relative to the total number of bins provides an estimate of the number of fetal cells that were present in the original enriched cell population. Bins containing fetal cells would be identified with high levels of confidence because the non-maternal alleles are detected by multiple independent STRs.
Detect ploidy for chromosomes 13, 18, and 21: After identifying the bins that contained fetal cells, the next step would be to determine the ploidy of chromosomes 13, 18 and 21 by comparing the ratio of maternal to paternal alleles for each of the STRs. Again, for each bin there will be ˜33 sequence reads for each of the 12 STRs. In a normal fetus, a given STR will have 1:1 ratio of the maternal to paternal alleles with approximately 16 sequence reads corresponding to each allele (normal diallelic). In a trisomic fetus, three doses of an STR marker can be detected either as three alleles with a 1:1:1 ratio (trisomic triallelic) or two alleles with a ratio of 2:1 (trisomic diallelic). In rare instances all three alleles may coincide and the locus will not be informative for that individual patient. The information from the different STRs on each chromosome can be combined to increase the confidence of a given aneuploidy call. In addition, the information from the independent bins containing fetal cells can also be combined to further increase the confidence of the call.
Fetal cells or nuclei can be isolated as described in the enrichment section or as described in example 1 and 2. Sequencing methods can then be used to detect chromosome copy number changes.
Perform Multiplex PCR and Sequencing with Bin Specific Tags:
PCR primer pairs for highly polymorphic STR loci (multiple loci per chromosome of interest) can be added to each well in the microtiter plate. For example, STRs could be designed along chromosomes 13, 18, 21 and X to detect the most frequent aneuploidies, and along control regions of the genome where aneuploidy is not expected. Typically, four or more STRs should be analyzed per chromosome of interest to ensure accurate detection of aneuploidy.
The primers for each STR can be designed with two important features. First, each primer can contain a common ˜18 bp sequence on the 5′ end which can be used for the subsequent DNA cloning and sequencing procedures. Second, each well in the microtiter plate can be assigned a unique ˜6 bp DNA tag sequence which can be incorporated into the middle part of the upstream primer for each of the different STRs. The DNA tags make it possible to pool all of the STR amplicons following the multiplex PCR, which makes possible to analyze the amplicons in parallel during the ultra-deep sequencing procedure. Furthermore, nested PCR strategies for the STR amplification can achieve higher reliability of amplification from single cells.
Sequencing can be performed using the classic Sanger sequencing method or any other method known in the art.
For example, sequencing can occur by sequencing-by-synthesis, which involves inferring the sequence of the template by synthesizing a strand complementary to the target nucleic acid sequence. Sequence-by-synthesis can be initiated using sequencing primers complementary to the sequencing element on the nucleic acid tags. The method involves detecting the identity of each nucleotide immediately after (substantially real-time) or upon (real-time) the incorporation of a labeled nucleotide or nucleotide analog into a growing strand of a complementary nucleic acid sequence in a polymerase reaction. After the successful incorporation of a label nucleotide, a signal is measured and then nulled by methods known in the art. Examples of sequence-by-synthesis methods are described in U.S. Application Publication Nos. 2003/0044781, 2006/0024711, 2006/0024678 and 2005/0100932. Examples of labels that can be used to label nucleotide or nucleotide analogs for sequencing-by-synthesis include, but are not limited to, chromophores, fluorescent moieties, enzymes, antigens, heavy metal, magnetic probes, dyes, phosphorescent groups, radioactive materials, chemiluminescent moeities, scattering or fluorescent nanoparticles, Raman signal generating moieties, and electrochemical detection moieties. Sequencing-by-synthesis can generate at least 1,000, at least 5,000, at least 10,000, at least 20,000, 30,000, at least 40,000, at least 50,000, at least 100,000 or at least 500,000 reads per hour. Such reads can have at least 50, at least 60, at least 70, at least 80, at least 90, at least 100, at least 120 or at least 150 bases per read.
Another sequencing method involves hybridizing the amplified genomic region of interest to a primer complementary to it. This hybridization complex is incubated with a polymerase, ATP sulfurylase, luciferase, apyrase, and the substrates luciferin and adenosine 5′ phosphosulfate. Next, deoxynucleotide triphosphates corresponding to the bases A, C, G, and T (U) are added sequentially. Each base incorporation is accompanied by release of pyrophosphate, converted to ATP by sulfurylase, which drives synthesis of oxyluciferin and the release of visible light. Since pyrophosphate release is equimolar with the number of incorporated bases, the light given off is proportional to the number of nucleotides adding in any one step. The process is repeated until the entire sequence is determined.
Yet another sequencing method involves a four-color sequencing by ligation scheme (degenerate ligation), which involves hybridizing an anchor primer to one of four positions. Then an enzymatic ligation reaction of the anchor primer to a population of degenerate nonamers that are labeled with fluorescent dyes is performed. At any given cycle, the population of nonamers that is used is structure such that the identity of one of its positions is correlated with the identity of the fluorophore attached to that nonamer. To the extent that the ligase discriminates for complementarily at that queried position, the fluorescent signal allows the inference of the identity of the base. After performing the ligation and four-color imaging, the anchor primer:nonamer complexes are stripped and a new cycle begins.
Identify bins with non-maternal alleles (e.g. fetal cells): The first step in the data analysis procedure would be to use the 6 bp DNA tags to sort the 200,000 sequence reads into bins which correspond to the individual wells of the microtiter plates. The ˜400 sequence reads from each of the bins would then be separated into the different STR groups using standard sequence alignment algorithms. The aligned sequences from each of the bins would then be analyzed to identify non-maternal alleles. These can be identified in one of two ways. First, an independent blood sample fraction known to contain only maternal cells can be analyzed as described above. This sample can be a white blood cell fraction (which will contain only negligible numbers of fetal cells), or simply a dilution of the original sample before enrichment. Alternatively, the genotype profiles for all the wells can be similarity-clustered to identify the dominant pattern associated with maternal cells. In either approach, the detection of non-maternal alleles then determines which wells in the initial microtiter plate contained fetal cells. Determining the number bins with non-maternal alleles relative to the total number of bins provides an estimate of the number of fetal cells that were present in the original enriched cell population. Bins containing fetal cells would be identified with high levels of confidence because the non-maternal alleles are detected by multiple independent STRs.
Detect ploidy for chromosomes 13, 18, and 21: After identifying the bins that contained fetal cells, the next step would be to determine the ploidy of chromosomes 13, 18 and 21 by comparing the ratio of maternal to paternal alleles for each of the STRs. Again, for each bin there will be ˜33 sequence reads for each of the 12 STRs. In a normal fetus, a given STR will have 1:1 ratio of the maternal to paternal alleles with approximately 16 sequence reads corresponding to each allele (normal diallelic). In a trisomic fetus, three doses of an STR marker can be detected either as three alleles with a 1:1:1 ratio (trisomic tiallelic) or two alleles with a ratio of 2:1 (trisomic diallelic). In rare instances all three alleles may coincide and the locus will not be informative for that individual patient. The information from the different STRs on each chromosome can be combined to increase the confidence of a given aneuploidy call. In addition, the information from the independent bins containing fetal cells can also be combined to further increase the confidence of the call.
Microfluidic devices of the invention were designed by computer-aided design (CAD) and microfabricated by photolithography. A two-step process was developed in which a blood sample is first debulked to remove the large population of small cells, and then the rare target epithelial cells target cells are recovered by immunoaffinity capture. The devices were defined by photolithography and etched into a silicon substrate based on the CAD-generated design. The cell enrichment module, which is approximately the size of a standard microscope slide, contains 14 parallel sample processing sections and associated sample handling channels that connect to common sample and buffer inlets and product and waste outlets. Each section contains an array of microfabricated obstacles that is optimized to enrich the target cell type by hydrodynamic size via displacement of the larger cells into the product stream. In this example, the microchip was designed to separate red blood cells (RBCs) and platelets from the larger leukocytes and CTCs. Enriched populations of target cells were recovered from whole blood passed through the device. Performance of the cell enrichment microchip was evaluated by separating RBCs and platelets from white blood cells (WBCs) in normal whole blood (
Next, epithelial cells were recovered by affinity capture in a microfluidic module that is functionalized with immobilized antibody. A capture module with a single chamber containing a regular array of antibody-coated microfabricated obstacles was designed. These obstacles are disposed to maximize cell capture by increasing the capture area approximately four-fold, and by slowing the flow of cells under laminar flow adjacent to the obstacles to increase the contact time between the cells and the immobilized antibody. The capture modules may be operated under conditions of relatively high flow rate but low shear to protect cells against damage. The surface of the capture module was functionalized by sequential treatment with 10% silane, 0.5% gluteraldehyde, and avidin, followed by biotinylated anti-EpCAM. Active sites were blocked with 3% bovine serum albumin in PBS, quenched with dilute Tris HCl, and stabilized with dilute L-histidine. Modules were washed in PBS after each stage and finally dried and stored at room temperature. Capture performance was measured with the human advanced lung cancer cell line NCI-H1650 (ATCC Number CRL-5883). This cell line has a heterozygous 15 bp in-frame deletion in exon 19 of EGFR that renders it susceptible to gefitinib. Cells from confluent cultures were harvested with trypsin, stained with the vital dye Cell Tracker Orange (CMRA reagent, Molecular Probes, Eugene, Oreg.), resuspended in fresh whole blood, and fractionated in the microfluidic chip at various flow rates. In these initial feasibility experiments, cell suspensions were processed directly in the capture modules without prior fractionation in the cell enrichment module to debulk the red blood cells; hence, the sample stream contained normal blood red cells and leukocytes as well as tumor cells. After the cells were processed in the capture module, the device was washed with buffer at a higher flow rate (3 ml/hr) to remove the nonspecifically bound cells. The adhesive top was removed and the adherent cells were fixed on the chip with paraformaldehyde and observed by fluorescence microscopy. Cell recovery was calculated from hemacytometer counts; representative capture results are shown in Table 4. Initial yields in reconstitution studies with unfractionated blood were greater than 60% with less than 5% of non-specific binding.
Next, NCI-H1650 cells that were spiked into whole blood and recovered by size fractionation and affinity capture as described above were successfully analyzed in situ. In a trial run to distinguish epithelial cells from leukocytes, 0.5 ml of a stock solution of fluorescein-labeled CD45 pan-leukocyte monoclonal antibody were passed into the capture module and incubated at room temperature for 30 minutes. The module was washed with buffer to remove unbound antibody, and the cells were fixed on the chip with 1% paraformaldehyde and observed by fluorescence microscopy. As shown in
A design for preferred device embodiments of the invention is shown in
Using the methods of the invention, a diagnosis of the absence, presence, or progression of cancer may be based on the number of cells in a cellular sample that are larger than a particular cutoff size. For example, cells with a hydrodynamic size of 14 microns or larger may be selected. This cutoff size would eliminate most leukocytes. The nature of these cells may then be determined by downstream molecular or cytological analysis.
Cell types other than epithelial cells that would be useful to analyze include endothelial cells, endothelial progenitor cells, endometrial cells, or trophoblasts indicative of a disease state. Furthermore, determining separate counts for epithelial cells, e.g., cancer cells, and other cell types, e.g., endothelial cells, followed by a determination of the ratios between the number of epithelial cells and the number of other cell types, may provide useful diagnostic information.
A device of the invention may be configured to isolate targeted subpopulations of cells such as those described above, as shown in
Using a device of the invention, therefore, it is possible to isolate a subpopulation of cells from blood or other bodily fluids based on size, which conveniently allows for the elimination of a large proportion of native blood cells when large cell types are targeted. As shown schematically in
A blood sample from a cancer patient is processed and analyzed using the devices and methods of the invention, resulting in an enriched sample of epithelial cells containing CTCs. This sample is then analyzed to identify potential EGFR mutations. The method permits both identification of known, clinically relevant EGFR mutations as well as discovery of novel mutations. An overview of this process is shown in
Below is an outline of the strategy for detection and confirmation of EGFR mutations:
1) Sequence CTC EGFR mRNA
2) Confirm RNA Sequence Using CTC Genomic DNA
Further details for each step outlined above are as follows.
1) Sequence CTC EGFR mRNA
d) Use resultant cDNA to perform first and second PCR reactions for generating sequencing templates. cDNA from the reverse transcriptase reactions is mixed with DNA primers specific for the region of interest (
Purify the nested PCR amplicon and use as a sequencing template to sequence EGFR exons 18-21. Sequencing is performed by ABI automated fluorescent sequencing machines and fluorescence-labeled DNA sequencing ladders generated via Sanger-style sequencing reactions using fluorescent dideoxynucleotide mixtures. PCR products are purified using Qiagen QuickSpin columns, the Agencourt AMPure PCR Purification System, or PCR product purification kits obtained from other vendors. After PCR products are purified, the nucleotide concentration and purity is determined with a Nanodrop 7000 spectrophotometer, and the PCR product concentration is brought to a concentration of 25 ng/μl. As a quality control measure, only PCR products that have a UV-light absorbance ratio (A260/A280) greater than 1.8 are used for sequencing. Sequencing primers are brought to a concentration of 3.2 pmol/μl.
2) Confirm RNA sequence using CTC genomic DNA
a) Purify CTCs from blood sample. As above, CTCs are isolated using any of the size-based enrichment and/or affinity purification devices of the invention.
b) Purify genomic DNA (gDNA) from CTCs. Genomic DNA is purified using the Qiagen DNeasy Mini kit, the Invitrogen ChargeSwitch gDNA kit, or another commercial kit, or via the following protocol:
c) Amplify exons 18, 19, 20, and/or 21 via PCR reactions. Hot start nested PCR amplification is carried out as described above in step id, except that there is no nested round of amplification. The initial PCR step may be stopped during the log phase in order to minimize possible loss of allele-specific information during amplification. The primer sets used for expansion of EGFR exons 18-21 are listed in Table 6 (see also Paez et al., Science 304:1497-1500 (Supplementary Material) (2004)).
d) Use the resulting POR amplicon(s) in real-time quantitative allele-specific PCR reactions in order to confirm the sequence of mutations discovered via RNA sequencing. An aliquot of the PCR amplicons is used as template in a multiplexed allele-specific quantitative PCR reaction using TaqMan PCR 5′ Nuclease assays with an Applied Biosystems model 7500 Real Time PCR machine (
Probe and primer sets are designed for all known mutations that affect gefitinib responsiveness in NSCLC patients, including over 40 such somatic mutations, including point mutations, deletions, and insertions, that have been reported in the medical literature. For illustrative purposes, examples of primer and probe sets for five of the point mutations are listed in Table 7. In general, oligonucleotides may be designed using the primer optimization software program Primer Express (Applied Biosystems), with hybridization conditions optimized to distinguish the wild type EGFR DNA sequence from mutant alleles. EGFR genomic DNA amplified from lung cancer cell lines that are known to carry EGFR mutations, such as H358 (wild type), H1650 (15-bp deletion, Δ2235-2249), and H1975 (two point mutations, 2369 C→2573 T→G), is used to optimize the allele-specific Real Time PCR reactions. Using the TaqMan 5′ nuclease assay, allele-specific labeled probes specific for wild type sequence or for known EGFR mutations are developed. The oligonucleotides are designed to have melting temperatures that easily distinguish a match from a mismatch, and the Real Time PCR conditions are optimized to distinguish wild type and mutant alleles. All Real Time PCR reactions are carried out in triplicate.
Initially, labeled probes containing wild type sequence are multiplexed in the same reaction with a single mutant probe. Expressing the results as a ratio of one mutant allele sequence versus wild type sequence may identify samples containing or lacking a given mutation. After conditions are optimized for a given probe set, it is then possible to multiplex probes for all of the mutant alleles within a given exon within the same Real Time PCR assay, increasing the ease of use of this analytical tool in clinical settings.
A unique probe is designed for each wild type allele and mutant allele sequence. Wild-type sequences are marked with the fluorescent dye VIC at the 5′ end, and mutant sequences with the fluorophore FAM. A fluorescence quencher and Minor Groove Binding moiety are attached to the 3′ ends of the probes. ROX is used as a passive reference dye for normalization purposes. A standard curve is generated for wild type sequences and is used for relative quantitation. Precise quantitation of mutant signal is not required, as the input cell population is of unknown, and varying, purity. The assay is set up as described by ABI product literature, and the presence of a mutation is confirmed when the signal from a mutant allele probe rises above the background level of fluorescence (
To test whether EGFR mRNA is present in leukocytes, several PCR experiments were performed. Four sets of primers, shown in Table 8, were designed to amplify four corresponding genes:
Total RNAs of approximately 9×106 leukocytes isolated using a cell enrichment device of the invention (cutoff size 4 μm) and 5×106 H1650 cells were isolated by using RNeasy mini kit (Qiagen). Two micrograms of total RNAs from leukocytes and H1650 cells were reverse transcribed to obtain first strand cDNAs using 100 pmol random hexamer (Roche) and 200 U Superscript II (Invitrogen) in a 20 μl reaction. The subsequent PCR was carried out using 0.5 μl of the first strand cDNA reaction and 10 pmol of forward and reverse primers in total 25 μl of mixture. The PCR was run for 40 cycles of 95° C. for 20 seconds, 56° C. for 20 seconds, and 70° C. for 30 seconds. The amplified products were separated on a 1% agarose gel. As shown in
In order to determine the sensitivity of the assay described in Example 12, various quantities of input NSCLC cell line total RNA were tested, ranging from 100 pg to 50 ng. The results of the first and second EGFR PCR reactions (step id, Example 12) are shown in
Next, samples containing 1 ng of NCI-H1975 RNA were mixed with varying quantities of peripheral blood mononuclear cell (PBMC) RNA ranging from 1 ng to 1 μg and used in PCR reactions as before. As shown in
Table 8 lists the RNA yield in a variety of cells and shows that the yield per cell is widely variable, depending on the cell type. This information is useful in order to estimate the amount of target and background RNA in a sample based on cell counts. For example, 1 ng of NCL-H1975 RNA corresponds to approximately 100 cells, while 1 μg of PBMC RNA corresponds to approximately 106 cells. Thus, the highest contamination level in the above-described experiment, 1,000:1 of PBMC RNA to NCL-H1975 RNA, actually corresponds to a 10,000:1 ratio of PBMCs to NCL-H1975 cells. Thus, these data indicate that EGFR may be sequenced from as few as 100 CTCs contaminated by as many as 106 leukocytes.
Next, whole blood spiked with 1,000 cells/ml of Cell Tracker (Invitrogen)-labeled H1650 cells was run through the capture module chip of
This application is a continuation of and claims priority under 35 U.S.C. §120 to U.S. application Ser. No. 13/306,640, filed on Nov. 29, 2011, which is a continuation of U.S. application Ser. No. 12/230,628 (now U.S. Pat. No. 8,168,389), filed on Sep. 2, 2008, which is a continuation of and claims priority to U.S. application Ser. No. 11/763,421 (now U.S. Pat. No. 8,372,584), filed on Jun. 14, 2007, which claims the benefit of U.S. Provisional Application Ser. No. 60/804,819, filed on Jun. 14, 2006 and U.S. Provisional Application Ser. No. 60/820,778, filed on Jul. 28, 2006, the entire disclosures of which are incorporated herein by reference.
| Number | Name | Date | Kind |
|---|---|---|---|
| 3560754 | Kamentsky | Feb 1971 | A |
| 4508625 | Graham | Apr 1985 | A |
| 4675286 | Calenoff | Jun 1987 | A |
| 4683202 | Mullis | Jul 1987 | A |
| 4789628 | Nayak | Dec 1988 | A |
| 4800159 | Mullis et al. | Jan 1989 | A |
| 4886761 | Gustafson et al. | Dec 1989 | A |
| 4936465 | Zoeld | Jun 1990 | A |
| 4971904 | Luddy | Nov 1990 | A |
| 4977078 | Niimura et al. | Dec 1990 | A |
| 5153117 | Simons | Oct 1992 | A |
| 5215926 | Etchells, III et al. | Jun 1993 | A |
| 5296375 | Kricka et al. | Mar 1994 | A |
| 5300779 | Hillman et al. | Apr 1994 | A |
| 5302509 | Cheeseman | Apr 1994 | A |
| 5304487 | Wilding et al. | Apr 1994 | A |
| 5310674 | Weinreb et al. | May 1994 | A |
| 5427663 | Austin et al. | Jun 1995 | A |
| 5427946 | Kricka et al. | Jun 1995 | A |
| 5432054 | Saunders et al. | Jul 1995 | A |
| 5447842 | Simons | Sep 1995 | A |
| 5486335 | Wilding et al. | Jan 1996 | A |
| 5489506 | Crane | Feb 1996 | A |
| 5498392 | Wilding et al. | Mar 1996 | A |
| 5506141 | Weinreb et al. | Apr 1996 | A |
| 5529903 | Kübler et al. | Jun 1996 | A |
| 5541072 | Wang et al. | Jul 1996 | A |
| 5556773 | Youmo | Sep 1996 | A |
| 5587070 | Pall et al. | Dec 1996 | A |
| 5622831 | Liberti et al. | Apr 1997 | A |
| 5629147 | Asgari et al. | May 1997 | A |
| 5635358 | Wilding et al. | Jun 1997 | A |
| 5637469 | Wilding et al. | Jun 1997 | A |
| 5639669 | Ledley | Jun 1997 | A |
| 5641628 | Bianchi | Jun 1997 | A |
| 5646001 | Terstappen et al. | Jul 1997 | A |
| 5670325 | Lapidus et al. | Sep 1997 | A |
| 5676849 | Sammons et al. | Oct 1997 | A |
| 5707799 | Hansmann et al. | Jan 1998 | A |
| 5709943 | Coleman et al. | Jan 1998 | A |
| 5715946 | Reichenbach | Feb 1998 | A |
| 5726026 | Wilding et al. | Mar 1998 | A |
| 5750339 | Smith | May 1998 | A |
| 5766843 | Asgari et al. | Jun 1998 | A |
| 5770029 | Nelson et al. | Jun 1998 | A |
| 5798042 | Chu et al. | Aug 1998 | A |
| 5837115 | Austin et al. | Nov 1998 | A |
| 5840502 | Van Vlasselaer | Nov 1998 | A |
| 5842787 | Kopf-Sill et al. | Dec 1998 | A |
| 5843767 | Beattie | Dec 1998 | A |
| 5846708 | Hollis et al. | Dec 1998 | A |
| 5858649 | Asgari et al. | Jan 1999 | A |
| 5861253 | Asgari et al. | Jan 1999 | A |
| 5863502 | Southgate et al. | Jan 1999 | A |
| 5866345 | Wilding et al. | Feb 1999 | A |
| 5879624 | Boehringer et al. | Mar 1999 | A |
| 5879883 | Benson et al. | Mar 1999 | A |
| 5891651 | Roche et al. | Apr 1999 | A |
| 5906724 | Sammons et al. | May 1999 | A |
| 5928880 | Wilding et al. | Jul 1999 | A |
| 5944971 | Foote | Aug 1999 | A |
| 5952173 | Hansmann et al. | Sep 1999 | A |
| 5962234 | Golbus | Oct 1999 | A |
| 5962237 | Ts'o et al. | Oct 1999 | A |
| 5962332 | Singer et al. | Oct 1999 | A |
| 5972721 | Bruno et al. | Oct 1999 | A |
| 5993665 | Terstappen et al. | Nov 1999 | A |
| 5994057 | Mansfield | Nov 1999 | A |
| 5994517 | Ts'o et al. | Nov 1999 | A |
| 6007690 | Nelson et al. | Dec 1999 | A |
| 6008007 | Fruehauf et al. | Dec 1999 | A |
| 6008010 | Greenberger et al. | Dec 1999 | A |
| 6013188 | Terstappen et al. | Jan 2000 | A |
| 6030581 | Virtanen | Feb 2000 | A |
| 6036857 | Chen et al. | Mar 2000 | A |
| 6066449 | Ditkoff et al. | May 2000 | A |
| 6071394 | Cheng et al. | Jun 2000 | A |
| 6074827 | Nelson et al. | Jun 2000 | A |
| 6100029 | Lapidus et al. | Aug 2000 | A |
| 6124120 | Lizardi | Sep 2000 | A |
| 6129848 | Chen et al. | Oct 2000 | A |
| 6132607 | Chen et al. | Oct 2000 | A |
| 6143496 | Brown et al. | Nov 2000 | A |
| 6143576 | Buechler | Nov 2000 | A |
| 6150119 | Kopf-sill et al. | Nov 2000 | A |
| 6154707 | Livak et al. | Nov 2000 | A |
| 6156270 | Buechler | Dec 2000 | A |
| 6159685 | Pinkel et al. | Dec 2000 | A |
| 6176962 | Soane et al. | Jan 2001 | B1 |
| 6184029 | Wilding et al. | Feb 2001 | B1 |
| 6184043 | Fodstad et al. | Feb 2001 | B1 |
| 6186660 | Koph-Sill et al. | Feb 2001 | B1 |
| 6190870 | Schmitz et al. | Feb 2001 | B1 |
| 6197523 | Rimm et al. | Mar 2001 | B1 |
| 6200765 | Murphy et al. | Mar 2001 | B1 |
| 6210574 | Sammons et al. | Apr 2001 | B1 |
| 6210891 | Nyren et al. | Apr 2001 | B1 |
| 6210910 | Walt et al. | Apr 2001 | B1 |
| 6214558 | Shuber et al. | Apr 2001 | B1 |
| 6235474 | Feinberg | May 2001 | B1 |
| 6242209 | Ransom et al. | Jun 2001 | B1 |
| 6258540 | Lo et al. | Jul 2001 | B1 |
| 6265229 | Fodstad et al. | Jul 2001 | B1 |
| 6274337 | Parce et al. | Aug 2001 | B1 |
| 6277489 | Abbott et al. | Aug 2001 | B1 |
| 6280967 | Ransom et al. | Aug 2001 | B1 |
| 6300077 | Shuber et al. | Oct 2001 | B1 |
| 6344326 | Nelson et al. | Feb 2002 | B1 |
| 6361958 | Shieh et al. | Mar 2002 | B1 |
| 6365362 | Terstappen et al. | Apr 2002 | B1 |
| 6368871 | Christel et al. | Apr 2002 | B1 |
| 6372432 | Tocque et al. | Apr 2002 | B1 |
| 6376181 | Ramsey et al. | Apr 2002 | B2 |
| 6377721 | Walt et al. | Apr 2002 | B1 |
| 6383759 | Murphy et al. | May 2002 | B1 |
| 6387707 | Seul et al. | May 2002 | B1 |
| 6391559 | Brown et al. | May 2002 | B1 |
| 6394942 | Moon et al. | May 2002 | B2 |
| 6399364 | Reeve et al. | Jun 2002 | B1 |
| 6432630 | Blankenstein | Aug 2002 | B1 |
| 6440706 | Vogelstein et al. | Aug 2002 | B1 |
| 6444461 | Knapp et al. | Sep 2002 | B1 |
| 6454938 | Moon et al. | Sep 2002 | B2 |
| 6479299 | Parce et al. | Nov 2002 | B1 |
| 6488895 | Kennedy | Dec 2002 | B1 |
| 6511967 | Weissleder et al. | Jan 2003 | B1 |
| 6517234 | Koph-Sill et al. | Feb 2003 | B1 |
| 6540895 | Spence et al. | Apr 2003 | B1 |
| 6551841 | Wilding et al. | Apr 2003 | B1 |
| 6566101 | Shuber et al. | May 2003 | B1 |
| 6573082 | Choi et al. | Jun 2003 | B1 |
| 6576478 | Wagner et al. | Jun 2003 | B1 |
| 6582904 | Dahm | Jun 2003 | B2 |
| 6582969 | Wagner et al. | Jun 2003 | B1 |
| 6596144 | Regnier et al. | Jul 2003 | B1 |
| 6596545 | Wagner et al. | Jul 2003 | B1 |
| 6605454 | Barenburg et al. | Aug 2003 | B2 |
| 6613525 | Nelson et al. | Sep 2003 | B2 |
| 6618679 | Loehriein et al. | Sep 2003 | B2 |
| 6632619 | Harrison et al. | Oct 2003 | B1 |
| 6632652 | Austin et al. | Oct 2003 | B1 |
| 6632655 | Mehta et al. | Oct 2003 | B1 |
| 6637463 | Lei et al. | Oct 2003 | B1 |
| 6641997 | Mackinnon | Nov 2003 | B1 |
| 6645731 | Terstappen et al. | Nov 2003 | B2 |
| 6664056 | Lo et al. | Dec 2003 | B2 |
| 6664104 | Pourahmadi et al. | Dec 2003 | B2 |
| 6673541 | Klein et al. | Jan 2004 | B1 |
| 6674525 | Bardell et al. | Jan 2004 | B2 |
| 6685841 | Lopez et al. | Feb 2004 | B2 |
| 6689615 | Murto et al. | Feb 2004 | B1 |
| 6746503 | Benett et al. | Jun 2004 | B1 |
| 6753147 | Vogelstein et al. | Jun 2004 | B2 |
| 6783647 | Culbertson et al. | Aug 2004 | B2 |
| 6783928 | Hvichia et al. | Aug 2004 | B2 |
| 6815664 | Wang et al. | Nov 2004 | B2 |
| 6818184 | Fulwyler et al. | Nov 2004 | B2 |
| 6830936 | Anderson et al. | Dec 2004 | B2 |
| 6858439 | Xu et al. | Feb 2005 | B1 |
| 6875619 | Blackburn | Apr 2005 | B2 |
| 6893881 | Fodstad et al. | May 2005 | B1 |
| 6906182 | Ts'o et al. | Jun 2005 | B2 |
| 6911345 | Quake et al. | Jun 2005 | B2 |
| 6913697 | Lopez et al. | Jul 2005 | B2 |
| 6927028 | Dennis et al. | Aug 2005 | B2 |
| 6947583 | Ellis et al. | Sep 2005 | B2 |
| 6953668 | Israeli et al. | Oct 2005 | B1 |
| 6958245 | Seul et al. | Oct 2005 | B2 |
| 6960449 | Wang et al. | Nov 2005 | B2 |
| 7115709 | Gray et al. | Oct 2006 | B1 |
| 7150812 | Huang et al. | Dec 2006 | B2 |
| 7171975 | Moon et al. | Feb 2007 | B2 |
| 7190818 | Ellis et al. | Mar 2007 | B2 |
| 7192698 | Kinch et al. | Mar 2007 | B1 |
| 7198787 | Fodstad et al. | Apr 2007 | B2 |
| 7208275 | Gocke et al. | Apr 2007 | B2 |
| 7212660 | Wetzel et | May 2007 | B2 |
| 7220594 | Foster et al. | May 2007 | B2 |
| 7224839 | Zeineh | May 2007 | B2 |
| 7227002 | Kufer et al. | Jun 2007 | B1 |
| 7229838 | Foster et al. | Jun 2007 | B2 |
| 7250256 | Reinhard et al. | Jul 2007 | B2 |
| 7252976 | Lin et al. | Aug 2007 | B2 |
| 7258987 | Lamorte et al. | Aug 2007 | B2 |
| 7262177 | Ts'o et al. | Aug 2007 | B2 |
| 7262269 | Lam et al. | Aug 2007 | B2 |
| 7264972 | Foster | Sep 2007 | B2 |
| 7272252 | De La Torre-Bueno et al. | Sep 2007 | B2 |
| 7276170 | Oakey et al. | Oct 2007 | B2 |
| 7332277 | Dhallan | Feb 2008 | B2 |
| 7428325 | Douglass et al. | Sep 2008 | B2 |
| 7442506 | Dhallan | Oct 2008 | B2 |
| 7476363 | Unger et al. | Jan 2009 | B2 |
| 7645576 | Lo et al. | Jan 2010 | B2 |
| 7655399 | Cantor et al. | Feb 2010 | B2 |
| 7727720 | Dhallan et al. | Jun 2010 | B2 |
| 7783098 | Douglass et al. | Aug 2010 | B2 |
| 7838647 | Hahn et al. | Nov 2010 | B2 |
| 7888017 | Quake et al. | Feb 2011 | B2 |
| RE42315 | Lopez et al. | May 2011 | E |
| 8008018 | Quake et al. | Aug 2011 | B2 |
| 8137912 | Kapur et al. | Mar 2012 | B2 |
| 8195415 | Fan et al. | Jun 2012 | B2 |
| 20010007749 | Feinberg | Jul 2001 | A1 |
| 20010051341 | Lo et al. | Dec 2001 | A1 |
| 20010053958 | Ried et al. | Dec 2001 | A1 |
| 20020005354 | Spence et al. | Jan 2002 | A1 |
| 20020006621 | Bianchi | Jan 2002 | A1 |
| 20020009738 | Houghton et al. | Jan 2002 | A1 |
| 20020012930 | Rothberg et al. | Jan 2002 | A1 |
| 20020012931 | Waldman et al. | Jan 2002 | A1 |
| 20020016450 | Laugharn et al. | Feb 2002 | A1 |
| 20020019001 | Light | Feb 2002 | A1 |
| 20020028431 | Julien | Mar 2002 | A1 |
| 20020058332 | Quake et al. | May 2002 | A1 |
| 20020076825 | Cheng et al. | Jun 2002 | A1 |
| 20020086329 | Shvets et al. | Jul 2002 | A1 |
| 20020090741 | Jurgensen et al. | Jul 2002 | A1 |
| 20020098535 | Wang et al. | Jul 2002 | A1 |
| 20020106661 | Virtanen | Aug 2002 | A1 |
| 20020108859 | Wang et al. | Aug 2002 | A1 |
| 20020110835 | Kumar | Aug 2002 | A1 |
| 20020115163 | Wang et al. | Aug 2002 | A1 |
| 20020115164 | Wang et al. | Aug 2002 | A1 |
| 20020115201 | Barenburg et al. | Aug 2002 | A1 |
| 20020119469 | Shuber et al. | Aug 2002 | A1 |
| 20020123078 | Seul et al. | Sep 2002 | A1 |
| 20020123112 | Wang et al. | Sep 2002 | A1 |
| 20020132315 | Wang et al. | Sep 2002 | A1 |
| 20020132316 | Wang et al. | Sep 2002 | A1 |
| 20020137088 | Bianchi | Sep 2002 | A1 |
| 20020160363 | McDevitt et al. | Oct 2002 | A1 |
| 20020164816 | Quake | Nov 2002 | A1 |
| 20020164825 | Chen | Nov 2002 | A1 |
| 20020166760 | Prentiss et al. | Nov 2002 | A1 |
| 20020172987 | Terstappen et al. | Nov 2002 | A1 |
| 20030004402 | Hitt et al. | Jan 2003 | A1 |
| 20030013101 | Balasubramanian | Jan 2003 | A1 |
| 20030017514 | Pachmann et al. | Jan 2003 | A1 |
| 20030022207 | Balasubramanian et al. | Jan 2003 | A1 |
| 20030033091 | Opalsky et al. | Feb 2003 | A1 |
| 20030044388 | Dennis et al. | Mar 2003 | A1 |
| 20030044832 | Blankenstein | Mar 2003 | A1 |
| 20030072682 | Kikinis | Apr 2003 | A1 |
| 20030077292 | Hanash et al. | Apr 2003 | A1 |
| 20030082566 | Sylvan | May 2003 | A1 |
| 20030100102 | Rothberg et al. | May 2003 | A1 |
| 20030119077 | Ts'o et al. | Jun 2003 | A1 |
| 20030119724 | Ts'o et al. | Jun 2003 | A1 |
| 20030129676 | Terstappen et al. | Jul 2003 | A1 |
| 20030153085 | Leary et al. | Aug 2003 | A1 |
| 20030159999 | Oakey et al. | Aug 2003 | A1 |
| 20030165852 | Schueler et al. | Sep 2003 | A1 |
| 20030170631 | Houghton et al. | Sep 2003 | A1 |
| 20030170703 | Piper et al. | Sep 2003 | A1 |
| 20030175990 | Heyenga | Sep 2003 | A1 |
| 20030178641 | Blair et al. | Sep 2003 | A1 |
| 20030186255 | Williams et al. | Oct 2003 | A1 |
| 20030190602 | Pressman et al. | Oct 2003 | A1 |
| 20030199685 | Pressman et al. | Oct 2003 | A1 |
| 20030204331 | Whitney et al. | Oct 2003 | A1 |
| 20030206901 | Chen | Nov 2003 | A1 |
| 20030231791 | Torre-Bueno et al. | Dec 2003 | A1 |
| 20030232350 | Afar et al. | Dec 2003 | A1 |
| 20040005582 | Shipwash | Jan 2004 | A1 |
| 20040009471 | Cao | Jan 2004 | A1 |
| 20040018116 | Desmond et al. | Jan 2004 | A1 |
| 20040018509 | Bianchi | Jan 2004 | A1 |
| 20040018611 | Ward et al. | Jan 2004 | A1 |
| 20040023222 | Russell et al. | Feb 2004 | A1 |
| 20040043506 | Haussecker et al. | Mar 2004 | A1 |
| 20040048360 | Wada et al. | Mar 2004 | A1 |
| 20040053352 | Ouyang et al. | Mar 2004 | A1 |
| 20040063162 | Dunlay et al. | Apr 2004 | A1 |
| 20040072278 | Chou et al. | Apr 2004 | A1 |
| 20040077105 | Wu et al. | Apr 2004 | A1 |
| 20040096892 | Wang et al. | May 2004 | A1 |
| 20040121343 | Buechler et al. | Jun 2004 | A1 |
| 20040137452 | Levett et al. | Jul 2004 | A1 |
| 20040137470 | Dhallan | Jul 2004 | A1 |
| 20040142463 | Walker et al. | Jul 2004 | A1 |
| 20040144651 | Huang et al. | Jul 2004 | A1 |
| 20040166555 | Braff et al. | Aug 2004 | A1 |
| 20040171091 | Lesko et al. | Sep 2004 | A1 |
| 20040185495 | Schueler et al. | Sep 2004 | A1 |
| 20040197839 | Daniely et al. | Oct 2004 | A1 |
| 20040203037 | Lo et al. | Oct 2004 | A1 |
| 20040209299 | Pinter et al. | Oct 2004 | A1 |
| 20040214240 | Cao | Oct 2004 | A1 |
| 20040232074 | Peters et al. | Nov 2004 | A1 |
| 20040241707 | Gao et al. | Dec 2004 | A1 |
| 20040245317 | Larionov et al. | Dec 2004 | A1 |
| 20050003351 | Fejgin et al. | Jan 2005 | A1 |
| 20050014208 | Krehan et al. | Jan 2005 | A1 |
| 20050019792 | McBride et al. | Jan 2005 | A1 |
| 20050037388 | Antonarakis et al. | Feb 2005 | A1 |
| 20050042623 | Ault-Riche et al. | Feb 2005 | A1 |
| 20050042685 | Albert et al. | Feb 2005 | A1 |
| 20050049793 | Paterlini-Brechot | Mar 2005 | A1 |
| 20050061962 | Mueth et al. | Mar 2005 | A1 |
| 20050118591 | Tamak et al. | Jun 2005 | A1 |
| 20050129581 | McBride et al. | Jun 2005 | A1 |
| 20050142663 | Parthasarathy et al. | Jun 2005 | A1 |
| 20050145496 | Goodsaid et al. | Jul 2005 | A1 |
| 20050147977 | Koo et al. | Jul 2005 | A1 |
| 20050153329 | Hakansson et al. | Jul 2005 | A1 |
| 20050153342 | Chen | Jul 2005 | A1 |
| 20050158754 | Puffenberger et al. | Jul 2005 | A1 |
| 20050164241 | Hahn et al. | Jul 2005 | A1 |
| 20050170373 | Monforte | Aug 2005 | A1 |
| 20050175505 | Cantor et al. | Aug 2005 | A1 |
| 20050175981 | Voldman et al. | Aug 2005 | A1 |
| 20050175996 | Chen | Aug 2005 | A1 |
| 20050181353 | Rao et al. | Aug 2005 | A1 |
| 20050181463 | Rao et al. | Aug 2005 | A1 |
| 20050196785 | Quake et al. | Sep 2005 | A1 |
| 20050207940 | Butler et al. | Sep 2005 | A1 |
| 20050211556 | Childers et al. | Sep 2005 | A1 |
| 20050214855 | Wagner et al. | Sep 2005 | A1 |
| 20050221341 | Shimkets et al. | Oct 2005 | A1 |
| 20050221373 | Enzelberger et al. | Oct 2005 | A1 |
| 20050239101 | Sukumar et al. | Oct 2005 | A1 |
| 20050244843 | Chen et al. | Nov 2005 | A1 |
| 20050250111 | Xie et al. | Nov 2005 | A1 |
| 20050250155 | Lesko et al. | Nov 2005 | A1 |
| 20050250199 | Anderson et al. | Nov 2005 | A1 |
| 20050252773 | McBride et al. | Nov 2005 | A1 |
| 20050255001 | Padmanabhan et al. | Nov 2005 | A1 |
| 20050262577 | Guelly et al. | Nov 2005 | A1 |
| 20050266433 | Kapur et al. | Dec 2005 | A1 |
| 20050272103 | Chen | Dec 2005 | A1 |
| 20050282196 | Costa | Dec 2005 | A1 |
| 20050282220 | Prober et al. | Dec 2005 | A1 |
| 20050282293 | Cosman et al. | Dec 2005 | A1 |
| 20050287611 | Nugent et al. | Dec 2005 | A1 |
| 20060000772 | Sano et al. | Jan 2006 | A1 |
| 20060003312 | Blau et al. | Jan 2006 | A1 |
| 20060008807 | O'Hara et al. | Jan 2006 | A1 |
| 20060008824 | Ronaghi et al. | Jan 2006 | A1 |
| 20060019235 | Soen et al. | Jan 2006 | A1 |
| 20060024756 | Tibbe et al. | Feb 2006 | A1 |
| 20060046258 | Lapidus et al. | Mar 2006 | A1 |
| 20060051265 | Mohamed et al. | Mar 2006 | A1 |
| 20060051775 | Bianchi et al. | Mar 2006 | A1 |
| 20060060767 | Wang et al. | Mar 2006 | A1 |
| 20060072805 | Tsipouras et al. | Apr 2006 | A1 |
| 20060073125 | Clarke et al. | Apr 2006 | A1 |
| 20060094109 | Trainer | May 2006 | A1 |
| 20060121452 | Dhallan | Jun 2006 | A1 |
| 20060121624 | Huang et al. | Jun 2006 | A1 |
| 20060128006 | Gerhardt et al. | Jun 2006 | A1 |
| 20060134599 | Toner et al. | Jun 2006 | A1 |
| 20060160105 | Dhallan | Jul 2006 | A1 |
| 20060160150 | Seilhamer et al. | Jul 2006 | A1 |
| 20060160243 | Tang et al. | Jul 2006 | A1 |
| 20060183886 | Ts'o et al. | Aug 2006 | A1 |
| 20060205057 | Wayner et al. | Sep 2006 | A1 |
| 20060223178 | Barber et al. | Oct 2006 | A1 |
| 20060228721 | Leamon et al. | Oct 2006 | A1 |
| 20060252054 | Lin et al. | Nov 2006 | A1 |
| 20060252061 | Zabeau et al. | Nov 2006 | A1 |
| 20060252068 | Lo et al. | Nov 2006 | A1 |
| 20060252071 | Lo et al. | Nov 2006 | A1 |
| 20060252087 | Tang et al. | Nov 2006 | A1 |
| 20070015171 | Bianchi et al. | Jan 2007 | A1 |
| 20070017633 | Tonkovich et al. | Jan 2007 | A1 |
| 20070026381 | Huang et al. | Feb 2007 | A1 |
| 20070026413 | Toner et al. | Feb 2007 | A1 |
| 20070026414 | Fuchs et al. | Feb 2007 | A1 |
| 20070026415 | Fuchs et al. | Feb 2007 | A1 |
| 20070026416 | Fuchs | Feb 2007 | A1 |
| 20070026417 | Fuchs et al. | Feb 2007 | A1 |
| 20070026418 | Fuchs et al. | Feb 2007 | A1 |
| 20070026419 | Fuchs et al. | Feb 2007 | A1 |
| 20070026469 | Fuchs et al. | Feb 2007 | A1 |
| 20070037172 | Chiu et al. | Feb 2007 | A1 |
| 20070037173 | Allard et al. | Feb 2007 | A1 |
| 20070037273 | Shuler et al. | Feb 2007 | A1 |
| 20070037275 | Shuler et al. | Feb 2007 | A1 |
| 20070042238 | Kim et al. | Feb 2007 | A1 |
| 20070042339 | Toner et al. | Feb 2007 | A1 |
| 20070042360 | Afar et al. | Feb 2007 | A1 |
| 20070042368 | Zehentner-Wilkinson et al. | Feb 2007 | A1 |
| 20070048750 | Peck et al. | Mar 2007 | A1 |
| 20070054268 | Sutherland et al. | Mar 2007 | A1 |
| 20070054287 | Bloch | Mar 2007 | A1 |
| 20070059680 | Kapur et al. | Mar 2007 | A1 |
| 20070059683 | Barber et al. | Mar 2007 | A1 |
| 20070059716 | Balis et al. | Mar 2007 | A1 |
| 20070059718 | Toner et al. | Mar 2007 | A1 |
| 20070059719 | Grisham et al. | Mar 2007 | A1 |
| 20070059737 | Baker et al. | Mar 2007 | A1 |
| 20070059774 | Grisham et al. | Mar 2007 | A1 |
| 20070059781 | Kapur et al. | Mar 2007 | A1 |
| 20070059785 | Bacus et al. | Mar 2007 | A1 |
| 20070065845 | Baker et al. | Mar 2007 | A1 |
| 20070065858 | Haley | Mar 2007 | A1 |
| 20070071762 | Ts'o et al. | Mar 2007 | A1 |
| 20070072228 | Brauch | Mar 2007 | A1 |
| 20070072290 | Hvichia | Mar 2007 | A1 |
| 20070077578 | Penning et al. | Apr 2007 | A1 |
| 20070092444 | Benos et al. | Apr 2007 | A1 |
| 20070092881 | Ohnishi et al. | Apr 2007 | A1 |
| 20070092917 | Guyon | Apr 2007 | A1 |
| 20070099207 | Fuchs et al. | May 2007 | A1 |
| 20070099219 | Teverovskiy et al. | May 2007 | A1 |
| 20070099289 | Irimia et al. | May 2007 | A1 |
| 20070105105 | Clelland et al. | May 2007 | A1 |
| 20070105133 | Clarke et al. | May 2007 | A1 |
| 20070110773 | Asina et al. | May 2007 | A1 |
| 20070117158 | Coumans et al. | May 2007 | A1 |
| 20070122856 | Georges et al. | May 2007 | A1 |
| 20070122896 | Shuler et al. | May 2007 | A1 |
| 20070128655 | Obata | Jun 2007 | A1 |
| 20070131622 | Oakey et al. | Jun 2007 | A1 |
| 20070134658 | Bohmer et al. | Jun 2007 | A1 |
| 20070134713 | Cao | Jun 2007 | A1 |
| 20070135621 | Bourel et al. | Jun 2007 | A1 |
| 20070141587 | Baker et al. | Jun 2007 | A1 |
| 20070141588 | Baker et al. | Jun 2007 | A1 |
| 20070141717 | Carpenter et al. | Jun 2007 | A1 |
| 20070154928 | Mack et al. | Jul 2007 | A1 |
| 20070154960 | Connelly et al. | Jul 2007 | A1 |
| 20070160503 | Sethu et al. | Jul 2007 | A1 |
| 20070160974 | Sidhu et al. | Jul 2007 | A1 |
| 20070160984 | Huang et al. | Jul 2007 | A1 |
| 20070161064 | Kinch et al. | Jul 2007 | A1 |
| 20070166770 | Hsieh et al. | Jul 2007 | A1 |
| 20070170811 | Rubel | Jul 2007 | A1 |
| 20070172903 | Toner et al. | Jul 2007 | A1 |
| 20070178067 | Maier et al. | Aug 2007 | A1 |
| 20070178458 | O'Brien et al. | Aug 2007 | A1 |
| 20070178478 | Dhallan et al. | Aug 2007 | A1 |
| 20070187250 | Huang et al. | Aug 2007 | A1 |
| 20070196663 | Schwartz et al. | Aug 2007 | A1 |
| 20070196820 | Kapur et al. | Aug 2007 | A1 |
| 20070196840 | Roca et al. | Aug 2007 | A1 |
| 20070196869 | Perez et al. | Aug 2007 | A1 |
| 20070202106 | Palucka et al. | Aug 2007 | A1 |
| 20070202109 | Nakamura et al. | Aug 2007 | A1 |
| 20070202525 | Quake et al. | Aug 2007 | A1 |
| 20070202536 | Yamanishi et al. | Aug 2007 | A1 |
| 20070207351 | Christensen et al. | Sep 2007 | A1 |
| 20070207466 | Cantor et al. | Sep 2007 | A1 |
| 20070212689 | Bianchi et al. | Sep 2007 | A1 |
| 20070212698 | Bendele et al. | Sep 2007 | A1 |
| 20070212737 | Clarke et al. | Sep 2007 | A1 |
| 20070212738 | Haley et al. | Sep 2007 | A1 |
| 20070231851 | Toner et al. | Oct 2007 | A1 |
| 20070238105 | Barrett et al. | Oct 2007 | A1 |
| 20070259424 | Toner et al. | Nov 2007 | A1 |
| 20070264675 | Toner et al. | Nov 2007 | A1 |
| 20070275402 | Lo et al. | Nov 2007 | A1 |
| 20080020390 | Mitchell et al. | Jan 2008 | A1 |
| 20080023399 | Inglis et al. | Jan 2008 | A1 |
| 20080026390 | Stoughton et al. | Jan 2008 | A1 |
| 20080038733 | Bischoff et al. | Feb 2008 | A1 |
| 20080050739 | Stoughton et al. | Feb 2008 | A1 |
| 20080070792 | Stoughton et al. | Mar 2008 | A1 |
| 20080071076 | Hahn et al. | Mar 2008 | A1 |
| 20080090239 | Shoemaker et al. | Apr 2008 | A1 |
| 20080096216 | Quake | Apr 2008 | A1 |
| 20080096766 | Lee | Apr 2008 | A1 |
| 20080113350 | Terstappen | May 2008 | A1 |
| 20080113358 | Kapur et al. | May 2008 | A1 |
| 20080124721 | Fuchs | May 2008 | A1 |
| 20080138809 | Kapur et al. | Jun 2008 | A1 |
| 20080153090 | Lo et al. | Jun 2008 | A1 |
| 20080182261 | Bianchi | Jul 2008 | A1 |
| 20080193927 | Mann et al. | Aug 2008 | A1 |
| 20080213775 | Brody et al. | Sep 2008 | A1 |
| 20080220422 | Shoemaker et al. | Sep 2008 | A1 |
| 20080299562 | Oeth et al. | Dec 2008 | A1 |
| 20090029377 | Lo et al. | Jan 2009 | A1 |
| 20090087847 | Lo et al. | Apr 2009 | A1 |
| 20090170113 | Quake et al. | Jul 2009 | A1 |
| 20090170114 | Quake et al. | Jul 2009 | A1 |
| 20090280492 | Stoughton et al. | Nov 2009 | A1 |
| 20090291443 | Stoughton et al. | Nov 2009 | A1 |
| 20090317798 | Heid et al. | Dec 2009 | A1 |
| 20090317836 | Kuhn et al. | Dec 2009 | A1 |
| 20100094562 | Shohat et al. | Apr 2010 | A1 |
| 20100112575 | Fan et al. | May 2010 | A1 |
| 20100136529 | Shoemaker et al. | Jun 2010 | A1 |
| 20100169990 | Clarke et al. | Jul 2010 | A1 |
| 20100216151 | Lapidus et al. | Aug 2010 | A1 |
| 20100216153 | Lapidus et al. | Aug 2010 | A1 |
| 20100248358 | Yoshioka | Sep 2010 | A1 |
| 20100291572 | Stoughton et al. | Nov 2010 | A1 |
| 20110003293 | Stoughton et al. | Jan 2011 | A1 |
| 20120171666 | Shoemaker et al. | Jul 2012 | A1 |
| 20120171667 | Shoemaker et al. | Jul 2012 | A1 |
| Number | Date | Country |
|---|---|---|
| 0057907 | Aug 1982 | EP |
| 0637996 | Jul 1997 | EP |
| 0405972 | May 1999 | EP |
| 1221342 | Jul 2002 | EP |
| 1262776 | Dec 2002 | EP |
| 0994963 | May 2003 | EP |
| 0970365 | Oct 2003 | EP |
| 783694 | Nov 2003 | EP |
| 1262776 | Jan 2004 | EP |
| 1388013 | Feb 2004 | EP |
| 0920627 | May 2004 | EP |
| 1418003 | May 2004 | EP |
| 0739240 | Jun 2004 | EP |
| 1462800 | Sep 2004 | EP |
| 0919812 | Oct 2004 | EP |
| 1561507 | Aug 2005 | EP |
| 1328803 | Sep 2005 | EP |
| 1409727 | Nov 2005 | EP |
| 1272668 | Feb 2007 | EP |
| 1754788 | Feb 2007 | EP |
| 1757694 | Feb 2007 | EP |
| 1409745 | Apr 2007 | EP |
| 1754788 | Apr 2007 | EP |
| 1770171 | Apr 2007 | EP |
| 1313882 | May 2007 | EP |
| 1803822 | Jul 2007 | EP |
| 951645 | Aug 2007 | EP |
| 1813681 | Aug 2007 | EP |
| 1832661 | Sep 2007 | EP |
| 1757694 | Feb 2008 | EP |
| 2161347 | Mar 2010 | EP |
| 2161347 | Jun 2010 | EP |
| 1597353 | Nov 2010 | EP |
| 2004351309 | Dec 2004 | JP |
| WO 9006509 | Jun 1990 | WO |
| WO 9107660 | May 1991 | WO |
| WO 9116452 | Oct 1991 | WO |
| WO 9322053 | Nov 1993 | WO |
| WO 9322055 | Nov 1993 | WO |
| WO 9429707 | Dec 1994 | WO |
| WO 9509245 | Apr 1995 | WO |
| WO 9746882 | Dec 1997 | WO |
| WO 9800231 | Jan 1998 | WO |
| WO 9802528 | Jan 1998 | WO |
| WO 9810267 | Mar 1998 | WO |
| WO 9831839 | Jul 1998 | WO |
| WO 9857159 | Dec 1998 | WO |
| WO 9922868 | May 1999 | WO |
| WO 9938612 | Aug 1999 | WO |
| WO 9944064 | Sep 1999 | WO |
| WO 9961888 | Dec 1999 | WO |
| WO 0006770 | Feb 2000 | WO |
| WO 0037163 | Jun 2000 | WO |
| WO 0040750 | Jul 2000 | WO |
| WO 0062931 | Oct 2000 | WO |
| WO 0135071 | May 2001 | WO |
| WO 0137958 | May 2001 | WO |
| WO 0151668 | Jul 2001 | WO |
| WO 9961888 | Dec 2001 | WO |
| WO 0135071 | Feb 2002 | WO |
| WO 0212896 | Feb 2002 | WO |
| WO 0228523 | Apr 2002 | WO |
| WO 0230562 | Apr 2002 | WO |
| WO 0231506 | Apr 2002 | WO |
| WO 0244318 | Jun 2002 | WO |
| WO 02073204 | Sep 2002 | WO |
| WO 03003057 | Jan 2003 | WO |
| WO 03018757 | Mar 2003 | WO |
| WO 03019141 | Mar 2003 | WO |
| WO 03020974 | Mar 2003 | WO |
| WO 03020986 | Mar 2003 | WO |
| WO 03023057 | Mar 2003 | WO |
| WO 03031938 | Apr 2003 | WO |
| WO 03035894 | May 2003 | WO |
| WO 03035895 | May 2003 | WO |
| WO 03040064 | May 2003 | WO |
| WO 03044217 | May 2003 | WO |
| WO 03044224 | May 2003 | WO |
| WO 03048295 | Jun 2003 | WO |
| WO 03069421 | Aug 2003 | WO |
| WO 03018757 | Sep 2003 | WO |
| WO 03020974 | Sep 2003 | WO |
| WO 03078972 | Sep 2003 | WO |
| WO 02073204 | Oct 2003 | WO |
| WO 03044217 | Oct 2003 | WO |
| WO 03085379 | Oct 2003 | WO |
| WO 03003057 | Nov 2003 | WO |
| WO 03031938 | Nov 2003 | WO |
| WO 03093795 | Nov 2003 | WO |
| WO 03023057 | Dec 2003 | WO |
| WO 03069421 | Dec 2003 | WO |
| WO 03085379 | Dec 2003 | WO |
| WO 03035895 | Jan 2004 | WO |
| WO 03035894 | Mar 2004 | WO |
| WO 2004025251 | Mar 2004 | WO |
| WO 03019141 | Apr 2004 | WO |
| WO 2004029221 | Apr 2004 | WO |
| WO 2004029221 | May 2004 | WO |
| WO 2004037374 | May 2004 | WO |
| WO 2004044236 | May 2004 | WO |
| WO 03040064 | Jun 2004 | WO |
| WO 2004056978 | Jul 2004 | WO |
| WO 2004065629 | Aug 2004 | WO |
| WO 2004076643 | Sep 2004 | WO |
| WO 03093795 | Oct 2004 | WO |
| WO 2004037374 | Oct 2004 | WO |
| WO 2004088310 | Oct 2004 | WO |
| WO 2004025251 | Nov 2004 | WO |
| WO 2004101762 | Nov 2004 | WO |
| WO 2004113877 | Dec 2004 | WO |
| WO 2004101762 | Feb 2005 | WO |
| WO 2005023091 | Mar 2005 | WO |
| WO 2005028663 | Mar 2005 | WO |
| WO 2005042713 | May 2005 | WO |
| WO 2005043121 | May 2005 | WO |
| WO 2005047529 | May 2005 | WO |
| WO 2005047532 | May 2005 | WO |
| WO 2005023091 | Jun 2005 | WO |
| WO 2005049168 | Jun 2005 | WO |
| WO 2005058937 | Jun 2005 | WO |
| WO 2005061075 | Jul 2005 | WO |
| WO 2005068503 | Jul 2005 | WO |
| WO 2005049168 | Sep 2005 | WO |
| WO 2005084374 | Sep 2005 | WO |
| WO 2005084380 | Sep 2005 | WO |
| WO 2005085476 | Sep 2005 | WO |
| WO 2005085861 | Sep 2005 | WO |
| WO 2005098046 | Oct 2005 | WO |
| WO 2005108621 | Nov 2005 | WO |
| WO 2005108963 | Nov 2005 | WO |
| WO 2005109238 | Nov 2005 | WO |
| WO 2005028663 | Dec 2005 | WO |
| WO 2005098046 | Dec 2005 | WO |
| WO 2005116264 | Dec 2005 | WO |
| WO 2005118852 | Dec 2005 | WO |
| WO 2005121362 | Dec 2005 | WO |
| WO 2005085861 | Feb 2006 | WO |
| WO 2006010610 | Feb 2006 | WO |
| WO 2006020936 | Feb 2006 | WO |
| WO 2005118852 | Mar 2006 | WO |
| WO 2006023563 | Mar 2006 | WO |
| WO 2005121362 | Apr 2006 | WO |
| WO 2006041453 | Apr 2006 | WO |
| WO 2006043181 | Apr 2006 | WO |
| WO 2005109238 | Jun 2006 | WO |
| WO 2006010610 | Jun 2006 | WO |
| WO 2006043181 | Jun 2006 | WO |
| WO 2006076567 | Jul 2006 | WO |
| WO 2006078470 | Jul 2006 | WO |
| WO 2005043121 | Aug 2006 | WO |
| WO 2006020936 | Sep 2006 | WO |
| WO 2006076567 | Sep 2006 | WO |
| WO 2006078470 | Sep 2006 | WO |
| WO 2006097049 | Sep 2006 | WO |
| WO 2006100366 | Sep 2006 | WO |
| WO 2006104474 | Oct 2006 | WO |
| WO 2006108087 | Oct 2006 | WO |
| WO 2006108101 | Oct 2006 | WO |
| WO 2005042713 | Nov 2006 | WO |
| WO 2006023563 | Nov 2006 | WO |
| WO 2006120434 | Nov 2006 | WO |
| WO 2005084380 | Dec 2006 | WO |
| WO 2005116264 | Feb 2007 | WO |
| WO 2006104474 | Feb 2007 | WO |
| WO 2007020081 | Feb 2007 | WO |
| WO 2004076643 | Mar 2007 | WO |
| WO 2007024264 | Mar 2007 | WO |
| WO 2007028146 | Mar 2007 | WO |
| WO 2007030949 | Mar 2007 | WO |
| WO 2007033167 | Mar 2007 | WO |
| WO 2007034221 | Mar 2007 | WO |
| WO 2007035414 | Mar 2007 | WO |
| WO 2007035498 | Mar 2007 | WO |
| WO 2007035585 | Mar 2007 | WO |
| WO 2007035586 | Mar 2007 | WO |
| WO 2007024264 | Apr 2007 | WO |
| WO 2007036025 | Apr 2007 | WO |
| WO 2007038264 | Apr 2007 | WO |
| WO 2007041610 | Apr 2007 | WO |
| WO 2007044091 | Apr 2007 | WO |
| WO 2007044690 | Apr 2007 | WO |
| WO 2007048076 | Apr 2007 | WO |
| WO 2007030949 | May 2007 | WO |
| WO 2007034221 | May 2007 | WO |
| WO 2007050495 | May 2007 | WO |
| WO 2007053142 | May 2007 | WO |
| WO 2007053245 | May 2007 | WO |
| WO 2007053648 | May 2007 | WO |
| WO 2007053785 | May 2007 | WO |
| WO 2007059430 | May 2007 | WO |
| WO 2007062222 | May 2007 | WO |
| WO 2005058937 | Jun 2007 | WO |
| WO 2007035586 | Jun 2007 | WO |
| WO 2007067734 | Jun 2007 | WO |
| WO 2007048076 | Jul 2007 | WO |
| WO 2007053648 | Jul 2007 | WO |
| WO 2007075836 | Jul 2007 | WO |
| WO 2007075879 | Jul 2007 | WO |
| WO 2007076989 | Jul 2007 | WO |
| WO 2007079229 | Jul 2007 | WO |
| WO 2007079250 | Jul 2007 | WO |
| WO 2007080583 | Jul 2007 | WO |
| WO 2007082144 | Jul 2007 | WO |
| WO 2007082154 | Jul 2007 | WO |
| WO 2007082379 | Jul 2007 | WO |
| WO 2007050495 | Aug 2007 | WO |
| WO 2007075879 | Aug 2007 | WO |
| WO 2007087612 | Aug 2007 | WO |
| WO 2007089880 | Aug 2007 | WO |
| WO 2007089911 | Aug 2007 | WO |
| WO 2007090670 | Aug 2007 | WO |
| WO 2007092473 | Aug 2007 | WO |
| WO 2007092713 | Aug 2007 | WO |
| WO 2007098484 | Aug 2007 | WO |
| WO 2006100366 | Sep 2007 | WO |
| WO 2007100684 | Sep 2007 | WO |
| WO 2007101609 | Sep 2007 | WO |
| WO 2007033167 | Oct 2007 | WO |
| WO 2007038264 | Oct 2007 | WO |
| WO 2007044690 | Oct 2007 | WO |
| WO 2007053785 | Oct 2007 | WO |
| WO 2007059430 | Oct 2007 | WO |
| WO 2005084374 | Nov 2007 | WO |
| WO 2007035414 | Nov 2007 | WO |
| WO 2007035585 | Nov 2007 | WO |
| WO 2007044091 | Nov 2007 | WO |
| WO 2007053245 | Nov 2007 | WO |
| WO 2007089880 | Nov 2007 | WO |
| WO 2007126938 | Nov 2007 | WO |
| WO 2007132166 | Nov 2007 | WO |
| WO 2007132167 | Nov 2007 | WO |
| WO 2007082379 | Dec 2007 | WO |
| WO 2007098484 | Dec 2007 | WO |
| WO 2007062222 | Jan 2008 | WO |
| WO 2007100684 | Jan 2008 | WO |
| WO 2007075836 | Feb 2008 | WO |
| WO 2007132166 | Feb 2008 | WO |
| WO 2008017871 | Feb 2008 | WO |
| WO 2007089911 | May 2008 | WO |
| WO 2007132167 | May 2008 | WO |
| WO 2007028146 | Jun 2008 | WO |
| WO 2007067734 | Aug 2008 | WO |
| WO 2007126938 | Oct 2008 | WO |
| WO 2007082154 | Nov 2008 | WO |
| WO 2007087612 | Nov 2008 | WO |
| WO 2007092473 | Nov 2008 | WO |
| WO 2007082144 | Dec 2008 | WO |
| WO 2007092713 | Dec 2008 | WO |
| WO 2007079229 | Jan 2009 | WO |
| WO 2009013492 | Jan 2009 | WO |
| WO 2009013496 | Jan 2009 | WO |
| WO 2007080583 | Feb 2009 | WO |
| WO 2009019455 | Feb 2009 | WO |
| WO 2007079250 | Mar 2009 | WO |
| WO 2007041610 | Apr 2009 | WO |
| WO 2009019455 | Apr 2009 | WO |
| Entry |
|---|
| Zhang et al. Whole genome amplification from a single cell: Implications for genetic analysis. PNAS 89:5847-5851 (1992). |
| REPLI-g® Mini and Midi Kits pamphlet from Qiagen (Oct. 2005). |
| U.S. Appl. No. 11/825,677, filed Jul. 5, 2007, Lopez et al. |
| U.S. Appl. No. 11/909,959, filed Sep. 27, 2007, Duff. |
| U.S. Appl. No. 13/737,730, filed Jan. 9, 2013, Fuchs et al. |
| U.S. Appl. No. 60/704,067, filed Jul. 29, 2005, Huang et al. |
| U.S. Appl. No. 60/764,420, filed Feb. 2, 2005, Quake. |
| U.S. Appl. No. 60/949,227, filed Jul. 11, 2007, Kapur. |
| Adinolfi, et al. Gene Amplification to Detect Fetal Nucleated Cells in Pregnant Women. The Lancet. Aug. 5, 1989:328-329. |
| Adinolfi, et al. Rapid detection of aneuploidies by microsatellite and the quantitative fluorescent polymerase chain reaction. Prenat. Diagn. 1997; 17(13):1299-311. |
| Adinolfi, M. On a Non-Invasive Approach to Prenatel Diagnosis based on the detection of Fetal Nucleated Cells in Maternal Blood Samples. Prenatal Diagnosis. 1991;11:799-804. |
| Aggarwal, et al. A combinatorial approach to the selective capture of circulating malignant epithelial cells by peptide ligands. Biomaterials. Oct. 2005;26(30):6077-86. |
| Ahn, et al. A fully integrated micromachined magnetic particle separator. Journal of Microelectromechanical Systems. 1996; 5(3):151-158. |
| Allard, et al. Tumor cells circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases. Clin Cancer Res. Oct. 15, 2004;10(20):6897-904. |
| Allowed claims dated Dec. 9, 2010 for U.S. Appl. No. 11/701,686. |
| Andre, et al. (2000). “Lectin-Mediated Drug Targeting: Selection of Valency, Sugar Type (Gal/Lac), and Spacer Length for Cluster Glycosides as Parameters to Distinguish Ligand Binding to C-Type Asialoglycoprotein Receptors and Galectins” Pharmaceutical Research 2000 United States, vol. 17, No. 8, 2000, pp. 985-990. |
| Andrews, et al. Enrichment of fetal nucleated cells from maternal blood: model test system using cord blood. Prenatal Diagnosis. 1995; 15:913-919. |
| Applicant's Amendment and Response dated Jun. 17, 2009 to Non-Final Office Action of Jan. 28, 2009 re U.S. Appl. No. 11/701,686. |
| Applicant's Amendment and Response dated Jun. 24, 2010 to Office Action of Jan. 27, 2010 re U.S. Appl. No. 11/701,686. |
| Applicant's Amendment and Response dated Nov. 13, 2009 to Office Action of Sep. 11, 2009 re U.S. Appl. No. 11/701,686. |
| Applicant's response dated Jun. 10, 2011 to Office action dated Apr. 25, 2011 for U.S. Appl. No. 12/393,803. |
| Archer, et al. Cell Reactions to Dielectrophoretic Manipulation. Biochemical and Biophysical Research Communications. 1999;257:687-98. |
| Ariga, et al. Kinetics of fetal cellular and cell-free DNA in the maternal circulation during and after pregnancy: implications for noninvasive prenatal diagnosis. Transfusion. 2001; 41:1524-1530. |
| Arnould, et al. Agreement between chromogenic in situ hybridisation (CISH) and FISH in the determination of HER2 status in breast cancer. Br J Cancer. 2003; 88(10):1587-91. (Abstract only). |
| Babochkina, et al. Direct detection of fetal cells in maternal blood: a reappraisal using a combination of two different Y chromosome-specific FISH probes and a single X chromosome-specific probe. Arch Gynecol Obstet. Dec. 2005;273(3):166-9. (Abstract only). |
| Babochkina, T. I. Ph. D. Dissertation—Fetal cells in maternal circulation: Fetal cell separation and FISH analysis. University of Basel, Switzerland. Dec. 8, 2005. (123 pages). |
| Balko, et al. Gene expression patterns that predict sensitivity to epidermal growth factor receptor tyrosine kinase inhibitors in lung cancer cell lines and human lung tumors. BMC Genomics. Nov. 10, 2006;7:289 (14 pages). |
| Barrett, et al. Comparative genomic hybridization using oligonucleotide microarrays and total genomic DNA. Proc Natl Acad Sci U S A. 2004; 101(51):17765-70. |
| Basch, et al. Cell separation using positive immunoselective techniques. Journal of Immunological Methods. 1983;56:269-280. |
| Bauer, J. Advances in cell separation: recent developments in counterflow centrifugal elutriation and continuous flow cell separation. Journal of Chromatography. 1999;722:55-69. |
| Becker, et al. Fabrication of Microstructures With High Aspect Ratios and Great Structural Heights by Synchrotron Radiation Lithography, Galvanoforming, and Plastic Moulding (LIGA Process). Microelectronic Engineering. 1986;4:35-56. |
| Becker, et al. Planar quartz chips with submicron channels for two-dimensional capillary electrophoresis applications. J. Micromech Microeng.1998;9:24-28. |
| Beebe et al. Functional Hydrogel Structures for Autonomous Flow Control Inside Microfluidic Channels. Nature. 2000; 404:588-590. |
| Benincasa, et al. Cell Sorting by One Gravity SPLITT Fractionation. Analytical Chemistry. 2005; 77(16):5294-5301. |
| Bennett, et al. Toward the 1,000 dollars human genome. Pharmacogenomics. 2005; 6(4):373-82. |
| Berenson, et al. Cellular Immunoabsorption Using Monoclonal Antibodies. Transplantation.1984 ;38:136-143. |
| Berenson, et al. Positive selection of viable cell populations using avidin-biotin immunoadsorption. Journal of Immunological Methods. 1986;91:11-19. |
| Berg, H. C. Random Walks in Biology, Ch. 4. Princeton University Press. Princeton, NJ. 1993. pp. 48-64. |
| Berger, et al. Design of a microfabricated magnetic cell separator. Electrophoresis. Oct. 2001;22(18):3883-92. |
| Bianchi, et al. Isolation of fetal DNA from nucleated erythrocytes in maternal blood. Medical Sciences. 1990;87:3279-3283. |
| Bianchi, et al. Demonstration of fetal gene sequences in nucleated erythrocytes isolated from maternal blood. American Journal of Human Genetics. 1989;45:A252. |
| Bianchi, et al. Fetal gender and aneuploidy detection using fetal cells in maternal blood: analysis of NIFTY I data. Prenatal Diagnosis. 2002; 22:609-615. |
| Bianchi, et al. Fetal nucleated erythrocytes (FNRBC) in maternal blood: erythroid-specific antibodies improve detection. The American Journal of Human Genetics. Oct. 1992. Supplemental to vol. 51, No. 4: 996. |
| Bianchi, et al. Isolation of Male Fetal DNA from Nucleated Erythrocytes (NRBC) in Maternal Blood. The American Pediatric Society and Society for Pediatric Research, (1989) Mar. 1989; 818:139A. |
| Bianchi, et al. Possible Effects of Gestational Age on the Detection of Fetal Nucleated Erythrocytes in Maternal Blood. Prenatal Diagnosis. 1991;11:523-528. |
| Bignell, et al. High-resolution analysis of DNA copy number using oligonucleotide microarrays. Genome Research. 2004; 14(2):287-295. |
| Birner, et al. Evaluation of the United States Food and Drug Administration-approved scoring and test system of HER-2 protein expression in breast cancer. Clin Cancer Res. Jun. 2001;7(6):1669-75. |
| Blake, et al. Assessment of multiplex fluorescent PCR for screening single cells for trisomy 21 and single gene defects. Mol. Hum. Reprod. 1999; 5(12):1166-75. |
| Bode, et al. Mutations in the tyrosine kinase domain of the EGFR gene are rare in synovial sarcoma. Mod Pathol. Apr. 2006;19(4):541-7. |
| Boehm, et al. Analysis of Defective Dystrophin Genes with cDNA Probes: Rearrangement Polymorphism, Detection of Deletions in Carrier Females, and Lower Than Expected Frequency of Carrier Mothers in Isolated Cases of Delections. Pediatric Research. Apr. 1989: 139A-820. |
| Bohmer, et al. Differential Development of Fetal and Adult Haemoglobin Profiles in Colony Culture: Isolation of Fetal Nucleated Red Cells by Two-Colour Fluorescence Labelling. Br. J. Haematol. 1998; 103:351-60. |
| Braslavsky, et al. “Sequence information can be obtained from single DNA molecules,” PNAS, Apr. 2003, vol. 100, No. 7, 3960-3964. |
| Brison, et al. General Method for Cloning Amplified DNA by Differential Screening with Genomic Probes. Molecular and Cellular Biology. 1982;2:578-587. |
| Brody, et al. Deformation and Flow of Red Blood Cells in a Synthetic Lattice: Evidence for an Active Cytoskeleton. Biophys. J. 68:2224-2232 (1995). |
| Bustamante-Aragones, et al. Detection of a Paternally Inherited Fetal Mutation in Maternal Plasma by the Use of Automated Sequencing. Ann. N.Y. Acad. Sci. 1075: 108-117 (2006), pp. 108-117, XP-002652985. |
| Caggana, M. Microfabricated devices for sparse cell isolation. CNF Project #905-00. Cornell NanoScale Facility. 2003; pp. 38-39. |
| Caggana, M. Microfabricated devices for sparse cell isolation. CNF Project #905-00. Cornell NanoScale Facility. 2004-2005; pp. 32-33. |
| Calin, et al. A microRNA signature Associated with prognosis and progression in chronic lymphocytic leukemia. New England Journal of Medicine. 2005; 353:1793-1801. |
| Cappuzzo, et al. Epidermal growth factor receptor gene and protein and gefitinib sensitivity in non-small-cell lung cancer. J Natl Cancer Inst. May 4, 2005;97(9):643-55. |
| Cha, The utility of an erythroblast scoring system and gender-independent short tandem repeat (STR) analysis for the detection of aneuploid fetal cells in maternal blood. Prenat. Diagn. 2005; 25(7):586-91. |
| Chamberlain, et al. Deletion screening of the Duchenne muscular dystrophy locus via multiplex DNA amplification. Nucleic Acids Research. 1988;16:11141-11156. |
| Chan, et al. “DNA Mapping Using Microfluidic Stretching and Single-Molecule Detection of Fluorescent Site-Specific Tags,” Genome Research, 2004, vol. 14, 1137-1146. |
| Chan, et al. Size distributions of maternal and fetal DNA in maternal plasma. Clin Chem. Jan. 2004;50(1):88-92. |
| Chang, et al. Biomimetic technique for adhesion-based collection and separation of cells in a microfluidic channel. Lab Chip. 2005; 5:64-73. |
| Cheung, et al. Development and validation of a CGH microarray for clinical cytogenetic diagnosis. Genet Med. 2005; 7(6):422-32. |
| Chiu, et al. “Effects of Blood-Processing Protocols on Fetal and Total DNA Quantification in Maternal Plasma,” Clinical Chemistry, 2001, vol. 47, No. 9, 1607-1613. |
| Chiu, et al. Non-invasive prenatal assessment of trisomy 21 by multiplexed maternal plasma DNA sequencing: large scale validity study. BMJ. Jan. 11, 2011;342:c7401. doi: 10.1136/bmj.c7401. |
| Chiu, et al. Noninvasive prenatal diagnosis of fetal chromosomal aneuploidy by massively parallel genomic sequencing of DNA in maternal plasma. Proc Natl Acad Sci U S A. Dec. 23, 2008;105(51):20458-63. |
| Chiu, et al. Patterned Deposition of Cells and Proteins Onto Surfaces by Using Three-Dimensional Microfluidic Systems. Proceedings of the National Academy of Sciences of the United States of America. 2000; pp. 2408-2413. |
| Choesmel, et al. Enrichment methods to detect bone marrow micrometastases in breast carcinoma patients: clinical relevance. Breast Cancer Res. 2004;6(5):R556-569. |
| Choolani, et al. Characterization of First Trimester Fetal Erythroblasts for Non-Invasive Prenatal Diagnosis. Mol. Hum. Reprod. 2003; 9:227-35. |
| Chou, et al. A Microfabricated Device for Sizing and Sorting DNA Molecules. Proceedings of the National Academy of Sciences of the United States of America. 1999; pp. 11-13. |
| Chou, et al. Sorting by diffusion: An asymmetric obstacle course for continuous molecular separation. PNAS. 1999; 96(24):13762-13765. |
| Christel, et al. High aspect ratio silicon microstructures for nucleic acid extraction. Solid-state sensor and actuator workshop. Hilton Head, SC. Jun. 8-11, 1998; 363-366. |
| Christensen, et al. Fetal Cells in Maternal Blood: A Comparison of Methods for Cell Isolation and Identification. Fetal Diagn. Ther. 2005; 20:106-12. |
| Chueh, et al. Prenatal Diagnosis Using Fetal Cells from the Maternal Circulation. West J. Med. 159:308-311 (1993). |
| Chueh, et al. Prenatal Diagnosis Using Fetal Cells in the Maternal Circulation. Seminars in Perinatology. 1990;14:471-482. |
| Chueh, et al. The search for fetal cells in the maternal circulation. J Perinat Med. 1991;19:411-420. |
| Cirigliano, et al. “Clinical application of multiplex quantitative fluorescent polymerase chain reaction (QF-PCR) for the rapid prenatal detection of common chromosome aneuploidies,” Molecular Human Reproduction, 2001, vol. 7, No. 10, 1001-1006. |
| Claims mailed with RCE Response to Final Rejection dated Dec. 31, 2009 for U.S. Appl. No. 11/763,421, filed Jun. 14, 2007 (6 pages). |
| Clayton, et al. Fetal Erythrocytes in the Maternal Circulation of Pregnant Women. Obstetrics and Gynecology. 1964;23:915-919. |
| Collarini, et al. Comparison of methods for erythroblast selection: application to selecting fetal erythroblasts from maternal blood. Cytometry. 2001; 45:267-276. |
| Cremer, et al. Detection of chromosome aberrations in human interphase nucleus by visualization of specific target DNAs with radioactive and non-radioactive in situ hybridization techniques: diagnosis of trisomy 18 with probe L1.84. Human Genetics.1986;74:346-352. |
| Cremer, et al. Detection of chromosome aberaations in metaphase and interphase tumor cells by in situ hybridization using chromosome-specific library probes. Human Genetics.1988;80:235-246. |
| Cristofanilli, et al. Circulating tumor cells revisited. JAMA. 2010; 303(11):1092-1093. |
| Cristofanilli, et al. Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N Engl J Med. Aug. 19, 2004;351(8):781-91. |
| Das, et al. Dielectrophoretic segregation of different human cell types on microscope slides. Anal. Chem. 2005; 77:2708-2719. |
| De Alba, et al. Prenatal diagnosis on fetal cells obtained from maternal peripheral blood: report of 66 cases. Prenat Diagn. Oct. 1999;19(10):934-40. |
| De Kretser, et al. The Separation of Cell Populations using Monoclonal Antibodies attached to Sepharose. Tissue Antigens. 1980;16:317-325. |
| De Luca, et al. Detection of circulating tumor cells in carcinoma patients by a novel epidermal growth factor receptor reverse transcription-PCR assay. Clin Cancer Res. Apr. 2000;6(4):1439-44. |
| Delamarche, et al. Microfluidic Networks for Chemical Patterning of Substrates: Design and Application to Bioassays. Journal of the American Chemical Society. 1998; 120:500-508. |
| Delamarche, et al. Patterned Delivery of Immunoglobulins to Surfaces Using Microfluidic Networks. Science. 1997; 276:779-781. |
| Deng, et al. Enumeration and microfluidic chip separation of circulating fetal cells early in pregnancy from maternal blood. American Journal of Obstetrics & Gynecology. Dec. 2008 (vol. 199, Issue 6, p. S134). |
| Deshmukh, et al. Continuous Micromixer With Pulsatile Micropumps. Solid-State Sensor and Actuator Workshop. Hilton Head Island, South Carolina; Jun. 4-8, 2000:73-76. |
| Devotek. “Separation of RNA 8 DNA by Gel Filtration Chromatography,” Edvotek, 1987. 1-9. |
| Dhallan, et al. A non-invasive test for prenatal diagnosis based on fetal DNA present in maternal blood: a preliminary study. Lancet. Feb. 10, 2007;369(9560):474-81. |
| Di Naro, et al. Prenatal diagnosis of beta-thalassaemia using fetal erythroblasts enriched from maternal blood by a novel gradient. Mol Hum Reprod. 2000; 6(6):571-4. |
| Diehl, et al. Digital quantification of mutant DNA in cancer patients. Curr Opin Oncol. Jan. 2007;19(1):36-42. |
| Dilella, et al. Screening for Phenylketonuria Mutations by DNA Amplification with the Polymerase Chain Reaction. The Lancet. Mar. 5, 1988:497-499. |
| Dohm, et al. Substantial biases in ultra-short read data sets from high-throughput DNA sequencing. Nucleic Acids Research. 2008. 36: e105 doi: 10.1093\nark\gkn425. |
| Doyle, et al. Self-Assembled Magnetic Matrices for DNA Separation Chips. Science 295:2237 (2002). |
| Dragovich, et al. Anti-EGFR-targeted therapy for exophageal and gastric cancers: an evolving concept. Jornal of Oncology. 2009; vol. 2009, Article ID 804108. |
| Dressman, et al. “Transforming single DNA molecules into fluorescent magnetic particles for detection and enumeration of genetic variations.” PNAS, Jul. 2003, vol. 100. No. 15, 8817-8822. |
| Eigen, et al. Sorting Single Molecules: Application to Diagnostics and Evolutionary Biotechnology. Proceedings of the National Academy of Sciences of the United States of America. 1994; 91:5740-5747. |
| Emanuel, et al. Amplification of Specific Gene Products from Human Serum. GATA, 1993, vol. 10, No. 6, 144-146. |
| European office action dated Apr. 4, 2012 for Application No. 07784444.7. |
| European office action dated Jun. 26, 2012 for EP Application No. 11159371.1. |
| European office action dated Aug. 2, 2010 for Application No. 07784444.7. (6 pages). |
| European office action dated Dec. 18, 2012 for EP Application No. 11159371.1. |
| European Search Opinion dated Jul. 31, 2009 for EP07763674.4. |
| European Search Report Office action dated Dec. 21, 2010 for EP07763674.4. |
| European search report and search opinion dated Jan. 2, 2013 for EP Application No. 12175907.0. |
| European search report dated Nov. 9, 2009 for Application No. 7784442.1. |
| European search report dated Dec. 21, 2009 for Application No. 07798579.4. |
| European search report dated Dec. 22, 2009 for Application No. 07798580.2. |
| European search report dated Dec. 22, 2009 for Application No. 07784444.7. |
| European Search Report dated Jul. 31, 2009 for EP07763674.4. |
| Applicant's Response with Allowed Claims dated Dec. 2, 2010 issued in U.S. Appl. No. 11/701,686. |
| Pending Claims filed with the USPTO on Apr. 26, 2010 for U.S. Appl. No. 11/701,686. |
| Extended European Search Report for Application No. 11159371 dated Aug. 10, 2011, 10 pages. |
| Falcidia, et al. Fetal Cells in maternal blood: a six-fold increase in women who have undergone mniocentesis and carry a fetus with Down syndrome: a multicenter study. Neuropediatrics. 2004; 35(6):321-324. (Abstract only). |
| Fan, et al. Detection of aneuploidy with digital polymerase chain reaction. Anal Chem. Oct. 1, 2007; 79(19):7576-9. |
| Fan, et al. Highly parallel SNP genotyping. Cold Spring Harb. Symp. Quant. Biol. 2003; 68:69-78. |
| Fan, et al. Microfluidic digital PCR enables rapid prenatal diagnosis of fetal aneuploidy. Am J Obstet Gynecol. May 2009;200(5):543.e1-7. . . . |
| Fan, et al. Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood. Proc Natl Acad Sci U S A. Oct. 21, 2008;105(42):16266-71. |
| Fan, et al. Single cell degenerate oligonucleotide primer-PCR and comparative genomic hybridization with modified control reference. Journal of Ahejian University—Science A. 2001; 2(3):318-321. |
| Farber, et al. Demonstration of spontaneous XX/XY chimerism by DNA fingerprinting. Human Genetics. 1989;82:197-198. |
| Farooqui, et al. Microfabrication of Submicron Nozzles in Silicon Nitride. Journal of Microelectromechanical Systems. 1992; 1(2):86-88. |
| Feinberg, et al. A technique for radiolabeling DNA restriction endonuclease fragments to high specific activity. Anal Biochem. Jul. 1, 1983;132(1):6-13. |
| Fiedler, et al. Dielectrophoretic Sorting of Particles and Cells in a Microsystem. Analytical Chemistry. 1998; pp. 1909-1915. |
| Findlay, et al. Using MF-PCR to diagnose multiple defects from single cells: implications for PGD. Mol Cell Endocrinol. 2001; 183 Suppl 1:S5-12. |
| Freemantle, M. Downsizing Chemistry. Chemical analysis and synthesis on microchips promise a variety of potential benefits. Chemical & Engineering News. 1999; pp. 27-36. |
| Fu, et al. An integrated miscrofabricated cell sorter. Anal Chem. 2002;74:2451-2457. |
| Fu, et al. A Microfabricated Fluorescence-Activated Cell Sorter. Nature Biotechnology.1999; 17:1109-1111. |
| Fuhr, et al. Biological Application of Microstructures. Topics in Current Chemistry. 1997; 194:83-116. |
| Fullwood, et al. Next Generation DNA sequencin of paired-end tags (PET) for transcriptome and genome analyses. Genome Research. 2009. 19:521-532. |
| Furdui, et al. Immunomagnetic T cell capture from blood for PCR analysis using microfluidic systems. Lab Chip. Dec. 2004;4(6):614-8. |
| Ganshirt-Ahlert, et al. Magnetic cell sorting and the transferrin receptor as potential means of prenatal diagnosis from maternal blood. Am J Obstet Gynecol. 1992;166:1350-1355. |
| Ganshirt-Ahlert, et al. Noninvasive prenatal diagnosis: Triple density gradient, magnetic activated cell sorting and FISH prove to be an efficient and reproducible method for detection of fetal aneuploidies from maternal blood. The American Journal of Human Genetics. Oct. 1992. Supplemental to vol. 51, No. 4: 182. |
| GenomeWeb. Immunicon inks biomarker assay, lab services deal with merck serona. Available at C:\Documents and Settings\fc3\Local Settings\Temporary Internet Files\OLK35E\141896-1.htm. Accessed on Sep. 11, 2007. |
| Ghia, et al. Ordering of human bone marrow B lymphocyte precursors by single-cell polymerase chain reaction analyses of the rearrangement status of the immunoglobulin H and L chain gene loci. J Exp Med. Dec. 1, 1996;184(6):2217-29. |
| Giddings, J. C. Chemistry ‘Eddy’ Diffusion in Chromatography. Nature. 1959;184:357-358. |
| Giddings, J. C. Field-Flow Fractionation: Analysis of Macromolecular, Colloidal, and Particulate Materials. Science. 1993;260:1456-1465. |
| Gonzalez, et al. Multiple displacement amplification as a pre-polymerase chain reaction (pre-PCR) to process difficult to amplify samples and low copy number sequences from natural environments. Environ Microbiol. 2005; 7(7):1024-8. |
| Graham. Efficiency comparison of two preparative mechanisms for magnetic separation of erthrocytes from whole blood. J. Appl. Phys. 1981; 52:2578-2580. |
| Greaves, et al. Expression of the OKT Monoclonal Antibody Defined Antigenic Determinants in Malignancy. Int. J. Immunopharmac. 1981;3:283-299. |
| Guetta, et al. Analysis of fetal blood cells in the maternal circulation: challenges, ongoing efforts, and potential solutions. Stem Cells Dev. 2004;13(1):93-9. |
| Gunderson, et al. A genome-wide scalable SNP genotyping assay using microarray technology. Nat Genet. 2005; 37(5):549-54. |
| Hahn, et al. “Prenatal Diagnosis Using Fetal Cells and Cell-Free Fetal DNA in Maternal Blood: What is Currently Feasible?” Clinical Obstetrics and Gynecology, Sep. 2002, vol. 45, No. 3, 649-656. |
| Hahn, et al. Current applications of single-cell PCR. Cell. Mol. Life Sci. 2000; 57(1):96-105. Review. |
| Hamabe, et al. Molecular study of the Prader-Willi syndrome: deletion, RFLP, and phenotype analyses of 50 patients. Am J Med Genet. Oct. 1, 1991;41(1):54-63. |
| Han, et al. Separation of Long DNA Molecules in a Microfabricated Entropic Trap Array. Science. 2000;288:1026-1029. |
| Hardenbol, et al. Highly multiplexed molecular inversion probe genotyping: over 10,000 targeted SNPs genotyped in a single tube assay. Genome Res. 2005;15(2):269-75. |
| Hardenbol, et al. Multiplexed genotyping with sequence-tagged molecular inversion probes. Nat. Biotechnol. 2003; 21(6):673-8. |
| Hartmann, et al. Gene expression profiling of single cells on large-scale oligonucleotide arrays. Nucleic Acids Research. 2006; 34(21): e143. (11 pages). |
| Hatch, et al. A rapid diffusion immunoassay in a T-sensor. Nature Biotechnology. 2001; 19:461-465. |
| Herzenberg, et al. Fetal cells in the blood of pregnant women: Detection and enrichment by flourescence-activated cell sorting. Proc. Natl. Acad. Sci. 1979;76:1453-1455. |
| Holzgreve, et al. Fetal Cells in the Maternal Circulation. Journal of Reproductive Medicine. 1992;37:410-418. |
| Hong, et al. A nanoliter-scale nucleic acid processor with parallel architecture. Nat. Biotechnol. 2004; 22(4):435-9. |
| Hong, et al. Molecular biology on a microfluidic chip. Journal of Physics: Condensed Matter, 2006, vol. 18, S691-S701. |
| Hosono, et al. Unbiased whole-genome amplification directly from clinical samples. Genome Res. May 2003;13(5):954-64. |
| Hromadnikova, et al. “Quantitative analysis of DNA levels in maternal plasma in normal and Down syndrome pregnancies.” Bio Med Central, May 2002, 1-5. |
| http://www.fda.gov/cdrh/pma/pmasep98.html. Sep. 1998. |
| Huang, et al. A DNA prism for high-speed continuous fractionation of large DNA molecules. Nature Biotechnology. 2002;20:1048-1051. |
| Huang, et al. Continuous Particle Separation Through Deterministic Lateral Displacement. Science 304:987-90 (2004). |
| Huang, et al. Electric Manipulation of Bioparticles and Macromoledules on Microfabricated Electrodes. Analytical Chemistry. 2001; pp. 1549-1559. |
| Huang, et al. Role of Molecular Size in Ratchet Fractionation. 2002; 89(17):178301-1-178301-4. |
| Huh, et al. Gravity-driven microhydrodynamics-based cell sorter (microHYCS) for rapid, inexpensive, and efficient cell separation and size-profiling. 2nd Annual International IEEE-EMBS Special Topic Conference on Microtechnology in Medicine and Biology. Madison, Wisconsin USA; May 2-4, 2002:466-469. |
| Hviid T. In-Cell PCT method for specific genotyping of genomic DNA from one individual in a micture of cells from two individuals: a model study with specific relevance to prenatal diagnosis based on fetal cells in maternal blood. Molecular Diagnostics and Genetics. 2002; 48:2115-2123. |
| Hviid, T. In-cell polymerase chain reaction: strategy and diagnostic applications. Methods Mol Biol. 2006;336:45-58. |
| International preliminary report on patentability dated Oct. 29, 2008 for PCT/US2007/003209. |
| International search report and written opinion dated Mar. 16, 2010 for PCT Application No. US2009/57136. |
| International Search Report and Written Opinion dated Sep. 18, 2008 for PCT/US2007/003209, received Sep. 22, 2008. |
| International search report dated Jan. 16, 2008 for PCT Application No. US2007/71247. |
| International search report dated Jan. 25, 2008 for PCT Application No. US2007/71250. |
| International search report dated Nov. 15, 2007 for PCT Application No. US2007/71149. |
| International search report dated Nov. 26, 2007 for PCT Application No. US2007/71256. |
| International search report dated Feb. 25, 2008 for PCT Application No. US07/71148. |
| International search report dated Feb. 25, 2008 for PCT Application No. US2007/71248. |
| Iverson, et al. Detection and Isolation of Fetal Cells From Maternal Blood Using the Flourescence-Activated Cell Sorter (FACS). Prenatal Diagnosis 1981;1:61-73. |
| Jan, et al. Fetal Erythrocytes Detected and Separated from Maternal Blood by Electronic Fluorescent Cell Sorter. Texas Rep Biol Med.1973;31:575. |
| Jayasena, S. Aptamers: an emerging class of molecules that rival antibodies in diagnostics. Clin Chem. Sep. 1999 ;45(9):1628-50. |
| Jeon, et al. Generation of Solution and surface Gradients Using Microfluidic Systems. Langmuir. 2000, pp. 8311-8316. |
| Jiang, et al. Genome amplification of single sperm using multiple displacement amplification. Nucleic Acids Res. 2005; 33(10):e91. (9 pages). |
| Kamholz, et al. Quantitative Analysis of Molecular Interaction in a Microfluidic Channel: the T-Sensor. Analytical Chemistry. 1999; pp. 5340-5347. |
| Kan, et al. Concentration of Fetal Red Blood Cells From a Mixture of Maternal and Fetal Blood by Anti-i Serum—An Aid to Prenatal Diagnosis of Hemoglobinopathies. Blood. 1974; 43:411-415. |
| Kartalov et al.: “Microfluidic device reads up to four consecutive base pairs in DNA sequencing-by-synthesis.”, Nucleic Acids Research, 2004, vol. 32, No. 9, 2004, pp. 2873-2879, XP-002652987. |
| Kasakov, et al. Extracellular DNA in the blood of pregnant women. Tsitologiia. 1995;37(3):232-6. (English translation only). |
| Kenis, et al. Microfabrication Inside Capillaries Using Multiphase Laminar Flow Patterning. Science. 1999; 285:83-85. |
| Kim, et al. Polymer microstructures formed by moulding in capillaries. Nature. 1995;376:581-584. |
| Kimura, et al. Deletional mutant EGFR detected in circulating tumor-derived DNA from lung cancer patients treated with gefitinib. American Association for Cancer Research 96th Annual Meeting. Apr. 16-20, 2005. Abstract 479. |
| Kimura, et al. The DYRKIA gene, encoded in chromosome 21 Down syndrome critical region, bridges between (β-amyloid production and tau phosphorylation in Alzheimer disease. Human Molecular Genetics, Nov. 29, 2008, vol. 16, No. 1, 1523. |
| Klein, C. A. Single cell amplification methods for the study of cancer and cellular ageing. Mech. Ageing Dev. 2005; 126(1):147-51. |
| Klein, et al. Comparative genomic hybridization, loss of heterozygosity, and DNA sequence analysis of single cells. Proc Natl Acad Sci U S A. 1999; 96(8):4494-9. |
| Kobayashi, et al. EGFR mutation and resistance of non-small-cell lung cancer to gefitinib. N Engl J Med. Feb. 24, 2005;352(8):786-92. |
| Kogan, et al. An Improved Method for Prenatal Diagnosis of Genetic Diseases by Analysis of Amplified DNA Sequences, Application to Hemophilia A. The New England Journal of Medicine.1987;317:985-990. |
| Korenberg, et al. Down syndrome phenotypes: the consequences of chromosomal imbalance. PNAS 1994; 91:4997-5001. |
| Krabchi, et al. Quantification of all fetal nucleated cells in maternal blood between the 18th and 22nd weeks of pregnancy using molecular cytogenic techniques. Clin. Genet. 2001; 60:145-150. |
| Krivacic, et al. A rare-cell detector for cancer. PNAS. 2004;101:10501-10504. |
| Kulozik, et al. Fetal Cell in the Maternal Circulation: Detection by Direct AFP-Immunoflourescence. Human Genetics. 1982;62:221-224. |
| Kurg, et al. Arrayed primer extension: solid-phase four-color DNA resequencing and mutation detection technology. Genet Test. 2000;4(1):1-7. |
| Kutter et al. Royal Society of Chemistry Special Publications, 1005, pp. 130-132 Abstract. |
| Leutwyler, K. Mapping Chromosome 21. Available at http://www.scientificamerican.com/article.cfm?id=mapping-chromosome-21. Accessed Feb. 3, 2010. |
| Levett, et al. A large-scale evaluation of amnio-PCR for the rapid prenatal diagnosis of fetal trisomy. Ultrasound Obstet Gynecol. 2001; 17(2):115-8. |
| Li , et al. Transport, Manipulation, and Reaction of Biological Cells On-Chip Using Electrokinetic Effects. Analytical Chemistry., 1997; pp. 1564-1568. |
| Li, et al. Amplification and analysis of DNA sequences in single human sperm and diploid cells. Nature. 1988;335:414-417. |
| Li, et al. Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Research. Genome Res. Nov. 2008;18(11):1851-8. |
| Li, et al. Size separation of circulatory DNA in maternal plasma permits ready detection of fetal DNA polymorphisms. Clin Chem. Jun. 2004;50(6):1002-11. |
| Lichter , et al. Delineation of individual human chromosomes in metaphase and interphase cells by in situ suppression hyridization using recombinant DNA libraries. Hum Genet. 1988;80:224-234. |
| Liu, et al. Development and validation of a T7 based linear amplification for genomic DNA. BMC Genomics. 2003; 4(1):19. (11 pages). |
| Lo, et al. Detection of fetal RhD sequence from peripheral blood of sensitized RhD-negative pregnant women. British Journalof Haematology, 1994, vol. 87, 658-660. |
| Lo, et al. Detection of single-copy fetal DNA sequence from maternal blood. The Lancet, Jun. 16, 1990, vol. 335, 1463-1464. |
| Lo, et al. Digital PCR for the molecular detection of fetal chromosomal aneuploidy. PNAS. Aug. 7, 2007; 104(32):13116-13121. |
| Lo, et al. Fetal DNA in Maternal Plasma. Ann. N. Y. Acad. Sci, Apr. 2000, vol. 906, 141-147. |
| Lo, et al. Plasma placental RNA allelic ratio permits noninvasive prenatal chromosomal aneuploidy detection. Nat Med. Feb. 2007;13(2):218-23. |
| Lo, et al. Prenatal diagnosis: progress through plasma nucleic acids. Nature. Jan. 2007, vol. 8, 71-76. |
| Lo, et al. Prenatal sex determination by DNA amplification from material peripheral blood. The Lancet.Dec. 9, 1989:1363-1365. |
| Lo, et al. Presence of fetal DNA in maternal plasma and serum. The Lancet, Aug. 16, 1997, vol. 350, 485-487. |
| Lo, et al. Quantitative Analysis of Fetal NA in Maternal Plasma and Serum: Implications for Noninvasive Prenatal Diagnosis. Am J. Hum. Genet., 1998, vol. 62, 768-775. |
| Lo, Y. M. Noninvasive prenatal detection of fetal chromosomal aneuploidies by maternal plasma nucleic acid analysis: a review of the current state of the art. BJOG, 2009, vol. 116, 152-157. |
| Loken , et al. Flow Cytometric Analysis of Human Bone Marrow: I. Normal Erythroid Development. Blood. 1987;69:255-263. |
| Lun, et al. Microfluidics Digital PCR Reveals a Higher than Expected Fraction of Fetal DNA in Maternal Plasma. Clinical Chemistry, 2008, vol. 54, No. 10, 1664-1672. |
| Mahr, et al. Fluorescence in situ hybridization of fetal nucleated red blood cells. The American Journal of Human Genetics. Oct. 1992. Supplemental to vol. 51, No. 4: 1621. |
| Maloney et al. “Microchimerism of maternal origin persists into adult life,” J. Clin. Invest. 104:41-47 (1999). |
| Marcus, et al. Microfluidic Single-Cell mRNA Isolation and Analysis. American Chemical Society, Mar. 2006; 76:3084-3089. |
| Marcus, et al. Parallel Picoliter RT-PCR Assays Using Microfluidics. Analytical Chemistry, Feb. 1, 2006, vol. 78, No. 3, 956-958. |
| Margulies, et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature. 2005; 437:376-80. |
| Marks, et al. Epidermal growth factor receptor (EGFR) expression in prostatic adenocarcinoma after hormonal therapy: a fluorescence in situ hybridization and immunohistochemical analysis. The Prostate. 2008; 68:919-923. |
| Martin, et al. “A method for using serum or plasma as a source of NDA for HLA typing,” Human Immunology. 1992; 33:108-113. |
| Mavrou, et al. Identification of nucleated red blood cells in maternal circulation: A second step in screening for fetal aneuploidies and pregnancy complications. Prenat Diagn. 2007; 247:150-153. |
| McCabe, et al. DNA microextraction from dried blood spots on filter paper blotters: potential applications to newborn screening. Hum Genet.1987;75:213-216. |
| McCarley, et al. Patterning of surface-capture architectures in polymer-based microanalytical devices. In KUTTER, et al. Eds. Royal Society of Chemistry Special Publication. 2005;130-132. (Abstract only). |
| Mehrishi , et al. Electrophoresis of cells and the biological relevance of surface charge. Electrophoresis.2002;23:1984-1994. |
| Melville, et al. Direct magnetic separation of red cells from whole blood. Nature. 1975; 255:706. |
| Meng, et al., “Her-2 gene amplification can be acquired as breast cancer progresses,” PNAS, 101:9393-98 (2004). |
| Meng, et al.: “Design and Synthesis of a Photocleavable Fluorescent Nucleotide 3′-O-Allyl-dGTPPC-Bodipy-FL-510 as a Reversible Terminator for DNA Sequencing by Synthesis”, J. Org. Chem. 2006, 71, pp. 3248-3252, XP-002652986. |
| Mohamed, et al. A Micromachined Sparse Cell Isolation Device: Application in Prenatal Diagnostics. Nanotech 2006 vol. 2; 641-644. (Abstract only). |
| Mohamed, et al. Biochip for separating fetal cells from maternal circulation. J Chromatogr A. Aug. 31, 2007;1162(2):187-92. |
| Mohamed, et al. Development of a rare cell fractionation device: application for cancer detection. IEEE Trans Nanobioscience. 2004; 3(4): 251-6. |
| Moore, et al. Lymphocyte fractionation using immunomagnetic colloid and a dipole magnet flow cell sorter. J Biochem Biophys Methods. 1998;37:11-33. |
| Moorhead, et al. Optimal genotype determination in highly multiplexed SNP data. Eur. J. Hum. Genet. 2006;14(2):207-15. (published online Nov. 23, 2005). |
| Mueller , et al. Isolation of fetal trophoblast cells from peripheral blood of pregnant women. The Lancet. 1990;336:197-200. |
| Muller, et al. Moderately repeated DNA sequences specific for the short arm of the human Y chromosome are present in XX makes and reduced in copy number in an XY female. 1986;14:1325-1340. |
| Mullis, et al. Specific Enzymatic Amplification of DNA In Vitro: The Polymerase Chain Reaction. Cold Spring Harbor Symposia on Quantitative Biolgy 1986;51:263-273. |
| Murakami, et al. A novel single cell PCR assay: detection of human T lymphotropic virus type I DNA in lymphocytes of patients with adult T cell leukemia. Leukemia. Oct. 1998;12(10):1645-50. |
| Murthy, et al. Assessment of multiple displacement amplification for polymorphism discovery and haplotype determination at a highly polymorphic locus, MC1R. Hum. Mutat. 2005; 26(2):145-52. |
| Nagrath, et al. Isolation of rare circulating tumour cells in cancer patients by microchip technology. Nature. 2007; 450: 1235-1241 (with Supplemental pp. 1-10). |
| Nelson, et al. Genotyping Fetal DNA by Non-Invasive Means: Extraction From Maternal Plasma. Vox Sang. 2001;80:112-116. |
| Newcombe, R. G. Two-sided confidence intervals for the single proportion: comparison of seven methods. Statistics in Medicine. 1998; 17:857-872. |
| Ng, et al. “The Concentration of Circulating Corticotropin-releasing Hormone mRNA in Maternal Plasma Is Increased in Preeclampsia,” Clinical Chemistry, 2003, vol. 49, No. 5, 727-731. |
| Notice of Allowance and Issue Fee Due Dec. 9, 2010 issued in U.S. Appl. No. 11/701,686. |
| Notice of allowance dated Jul. 12, 2011 with allowed claims for U.S. Appl. No. 12/393,803. |
| Oakey et al. Laminar Flow-Based Separations at the Microscale. Biotechnology Progress. 2002; pp. 1439-1442. |
| Office action (Ex parte Quayle) dated May 13, 2011 for U.S. Appl. No. 11/763,421. |
| Office Action dated Jan. 12, 2009 for U.S. Appl. No. 11/763,133. |
| Office Action dated Jan. 27, 2010 for U.S. Appl. No. 11/701,686. |
| Office action dated Jan. 28, 2009 for U.S. Appl. No. 11/701,686. |
| Office action dated Feb. 4, 2010 for U.S. Appl. No. 11/067,102. |
| Office action dated Feb. 15, 2011 for U.S. Appl. No. 11/763,426. |
| Office action dated Mar. 4, 2009 for U.S. Appl. No. 11/228,454. |
| Office action dated Mar. 11, 2010 for U.S. Appl. No. 11/763,245. |
| Office action dated Mar. 29, 2011 for U.S. Appl. No. 11/763,245. |
| Office action dated Apr. 4, 2008 for U.S. Appl. No. 11/067,102. |
| Office action dated Apr. 13, 2009 for U.S. Appl. No. 11/067,102. |
| Office action dated Apr. 25, 2011 for U.S. Appl. No. 12/393,803 with pending claims. |
| Office action dated May 4, 2009 for U.S. Appl. No. 11/763,431. |
| Office action dated May 6, 2011 for U.S. Appl. No. 11/763,133. |
| Office action dated May 12, 2011 for U.S. Appl. No. 12/230,628. |
| Office action dated May 18, 2011 for U.S. Appl. No. 12/413,467. |
| Office action dated May 26, 2011 for U.S. Appl. No. 11/762,750. |
| Office action dated Jun. 4, 2012 for U.S. Appl. No. 11/762,747. |
| Office action dated Jun. 5, 2012 for U.S. Appl. No. 12/393,833. |
| Office action dated Jun. 14, 2010 for U.S. Appl. No. 11/763,426. |
| Office action dated Jun. 15, 2007 for U.S. Appl. No. 11/067,102. |
| Office action dated Jul. 9, 2012 for U.S. Appl. No. 11/762,750. |
| Office action dated Jul. 10, 2009 for U.S. Appl. No. 11/763,421. |
| Office action dated Jul. 26, 2011 for U.S. Appl. No. 11/763,245. |
| Office action dated Aug. 1, 2008 for U.S. Appl. No. 11/067,102. |
| Office action dated Aug. 27, 2010 for U.S. Appl. No. 11/762,747. |
| Office Action dated Sep. 8, 2010 for U.S. Appl. No. 11/701,686. |
| Office action dated Sep. 10, 2010 for U.S. Appl. No. 11/762,750. |
| Office Action dated Sep. 11, 2009 for U.S. Appl. No. 11/701,686. |
| Office action dated Sep. 14, 2012 for U.S. Appl. No. 12/393,833. |
| Office action dated Sep. 17, 2010 for U.S. Appl. No. 11/067,102. |
| Office action dated Oct. 24, 2011 for U.S. Appl. No. 11/762,747. |
| Office action dated Oct. 29, 2010 for U.S. Appl. No. 12/230,628. |
| Office action dated Nov. 3, 2009 for U.S. Appl. No. 11/763,133. |
| Office action dated Dec. 1, 2009 for U.S. Appl. No. 11/763,426. |
| Office action dated Dec. 2, 2008 for U.S. Appl. No. 11/762,747. |
| Office action dated Dec. 3, 2008 for U.S. Appl. No. 11/763,426. |
| Office action dated Dec. 31, 2009 for U.S. Appl. No. 11/763,421. |
| Office action dated Dec. 31, 2009 for U.S. Appl. No. 11/762,750. |
| Office action dated Mar. 3, 2009 for EP Application No. EP07763674.4. |
| Office action dated Sep. 23, 2009 for EP Application No. EP07763674.4. |
| Office action dated Sep. 23, 2009 for EP Application No. EP07763674.4 with pending claims. |
| Olson, et al. An In Situ Flow Cytometer for the Optical Analysis of Individual Particles in Seawater. Available at http://www.whoi.edu/science/B/Olsonlab/insitu2001.htm. Accessed Apr. 24, 2006. |
| Oosterwijk, et al. Prenatal diagnosis of trisomy 13 on fetal cells obtained from maternal blood after minor enrichment. Prenat Diagn. 1998;18(10):1082-5. |
| Ottesen,et al. Microfluidic Digital PCR Enables Multigene Analysis of Individual Environmental Bacteria. Science. Dec. 1, 2006; 314(5804):1464-1467. (Abstract only). |
| Owen, et al. High gradient magnetic separation of erythrocytes. Biophys. J. 1978; 22:171-178. |
| Pallavicini, et al. Analysis of fetal cells sorted from maternal blood using fluorescence in situ hybridization. The American Journal of Human Genetics. Oct. 1992. Supplemental to vol. 51, No. 4: 1031. |
| Parano, et al. Fetal Nucleated red blood cell counts in peripheral blood of mothers bearing Down Syndrome fetus. Neuropediatrics. 2001; 32(3):147-149. (Abstract only). |
| Parano, et al. Noninvasive Prenatal Diagnosis of Chromosomal Aneuploidies by Isolation and Analysis of Fetal Cells from Maternal Blood. Am. J. Med. Genet. 101:262-7 (2001). |
| Paterlini-Brechot, et al. Circulating tumor cells (CTC) detection: Clinical impact and future directions. Cancer Letter. 2007. (In press, 25 pages.) Available at www.sciencedirect.com. |
| Paul, et al. Single-molecule dilution and multiple displacement amplification for molecular haplotyping. Biotechniques. 2005; 38(4):553-4, 556, 558-9. |
| Pawlik, et al. Prodrug Bioactivation and Oncolysis of Diffuse Liver Metastases by a Herpes Simplex Virus 1 Mutant that Expresses the CYP2B1 Transgene. Cancer. 2002;95:1171-81. |
| Peixoto, et al. Quantification of multiple gene expression in individual cells. Genome Res. Oct. 2004;14(10A):1938-47. |
| Pending Claims and Preliminary Amendment filed Nov. 19, 2010 for U.S. Appl. No. 11/763,133. |
| Pending claims and preliminary amendment filed Dec. 10, 2010 for U.S. Appl. No. 11/763,245. |
| Pending claims filed with the USTPO on Apr. 26, 2010 for U.S. Appl. No. 11/067,102. |
| Peng, et al. Real-time detection of gene expression in cancer cells using molecular beacon imaging: new strategies for cancer research. Cancer Res. 2005; 65(5):1909-17. |
| Pertl, et al. “Fetal DNA in Maternal Plasma: Emerging Clinical Applications,” Obstetrics and Gynecology, Sep. 2001, vol. 98, No. 3, 483-490. |
| Petersen, et al. The Promise of Miniaturized Clinical Diagnostic Systems. IVD Technol. 4:43-49 (1998). |
| Pfaffl, et al. Relative expression software tool (REST) for group-wise comparison and statistical analysis of relative expression results in real-time PCR. Nucleic Acids Res. May 1, 2002;30(9):e36. |
| Pinkel, et al. Cytogenetic Analysis Using Quantitative, High-sensitivity, Fluorescence Hybridization. Genetics. 1986;83:2934-2938. |
| Pinkel, et al. Fluorescence in situ Hybridization with Human Chromosome-specific Libraries: Detection of Trisomy 21 and Translocations of Chromosome 4. Genetics.1988;85:9138-9142. |
| Pinkel, et al. Detection of structural chromosome abberations in metaphase in metaphase spreads and interphase nuclei by in situ hybridization high complexity probes which stain entire human chromosomes. The American Journal of Human Genetics. Sep. 1988. Supplemental to vol. 43, No. 3: 0471. |
| Pinzani, et al. Isolation by size of epithelial tumor cells in peripheral blood of patients with breast cancer: correlation with real-time reverse transcriptase-polymerase chain reaction results and feasibility of molecular analysis by laser microdissection. Hum Pathol. 2006; 37(6):711-8. |
| Pohl et al. Principle and applications of digital PCR. Expert Rev Mol Diagn. Jan. 2004;4(1):41-7. |
| Poon, et al. “Circulating fetal DNA in maternal plasma,” ClinicalChimica Acta, 2001, vol. 313, 151-155. |
| Potti, et al. Genomic signatures to guide the use of chemotherapeutics. Nat Med. 2006; 12(11):1294-1300. |
| Price, et al. Prenatal Diagnosis with Fetal Cells Isolated from Maternal Blood by Multiparameter Flow Cytometry. Am. J. Obstet. Gynecol. 1991; 165:1731-7. |
| Prieto, et al. Isolation of fetal nucleated red blood cells from maternal blood in normal and aneuploid pregnancies. Clin Chem Lab Med. Jul. 2002;40(7):667-72. |
| Product literature for GEM, a system for blood testing: GEM Premier 3000. Avaiable at http://www.ilus.com/premier—gem3000—iqm.asp. Accessed Apr. 24, 2006. |
| Purwosunu, et al. Clinical potential for noninvasive prenatal diagnosis through detection of fetal cells in maternal blood. Taiwan J Obstet Gynecol. Mar. 2006;45(1):10-20. |
| Raeburn, P. Fetal Cells Isolated in Women's Blood. Associated Press (Jul. 28, 1989) [electronic version]. |
| Rahil, et al. Rapid detection of common autosomal aneuploidies by quantitative fluorescent PCR on uncultured amniocytes, European Journal of Human Genetics, 2002, vol. 10, 462-466. |
| Request for Continued Examination by applicant with claim set dated Mar. 26, 2010 in Response to Final Office Action dated Nov. 3, 2009 for U.S. Appl. No. 11/763,133. |
| Request for Continued Examination by applicant with claim set dated Mar. 26, 2010 in Response to Final Office Action dated Dec. 1, 2009 for U.S. Appl. No. 11/763,426. |
| Response dated Nov. 24, 2010 to Office action dated Jun. 14, 2010 with Pending Claims for U.S. Appl. No. 11/763,426. |
| Response filed Dec. 26, 2012 with claims for U.S. Appl. No. 12/393,833. |
| Rickman, et al. Prenatal diagnosis by array-CGH. European Journal of Medical Genetics. 2005; 48:232-240. |
| Rolle, et al. Increase in number of circulating disseminated epithelia cells after surgery for non-small cell lung cancer monitored by MAINTRAC is a predictor for relapse: a preliminary report. World Journal of Surgical Oncology. 2005; 9 pages. |
| Ruan, et al. Identification of clinically significant tumor antigens by selecting phage antibody library on tumor cells in situ using laser capture microdissection. Molecular & Cellular Proteomics. 2006; 5(12): 2364-73. |
| Sakhnini, et al. Magnetic behavior of human erythrocytes at different hemoglobin states. Eur Biophys J. Oct. 2001;30(6):467-70. |
| Samura, et al. Diagnosis of trisomy 21 in fetal nucleated erythrocytes from maternal blood by use of short tandem repeat sequences. Clin. Chem. 2001; 47(9):1622-6. |
| Samura, et al. Female fetal cells in maternal blood: use of DNA polymorphisms to prove origin. Hum. Genet. 2000;107(1):28-32. |
| Sato, et al. Individual and Mass Operation of Biological Cells Using Micromechanical Silicon Devices. Sensors and Actuators. 1990;A21-A23:948-953. |
| Schaefer, et al. The Clinical Relevance of Nucleated Red Blood Cells counts. Sysmex Journal International. 2000; 10(2):59-63. |
| Schröder, et al. Fetal Lymphocytes in the Maternal Blood. The Journal of Hematolog:Blood. 1972;39:153-162. |
| Scoazec. J. Y. Tissue and cell imaging in situ: potential for applications in pathology and endoscopy. Gut. Jun. 2003; 52(Suppl 4): iv1-iv6. |
| Sehnert, et al. Optimal Detection of Fetal Chromosomal Abnormalities by Massively Parallel DNA Sequencing of Cell-Free Fetal DNA from Maternal Blood. Clin Chem. Apr. 25, 2011. [Epub ahead of print]. |
| Sequenom, Inc. and Sequenom Center for Molecular Medicine LLC's Patent L. R. 3-3 Preliminary Invalidity Contentions for U.S. Patent Nos. 7,888,017, 8,008,018 and 8,195,415 and Patent L. R. 3-4 Document Production, Verinata Health v. Sequenom, No. 12-00865 (N.D. Cal. 2012), dated Sep. 28, 2012. |
| Sequenom, Inc. and Sequenom Center for Molecular Medicine LLC's Patent L. R. 4-2 Preliminary Claim Constructions and Extrinsic Evidence, Verinata Health v. Sequenom, No. 12-00865 (N.D. Cal. 2012), dated Oct. 26, 2012. |
| Sethu, et al. Continuous Flow Microfluidic Device for Rapid Erythrocyte Lysis. Anal. Chem. 76:6247-6253 (2004). |
| Shen, et al. High-throughput SNP genotyping on universal bead arrays. Mutat. Res. 2005; 573:70-82. |
| Shendure, et al. Accurate multiplex polony sequencing of an evolved bacterial genome. Science. 2005; 309:1728-32. |
| Shendure, et al. Next-generation DNA sequencing. Nature. 2008; 26(10):1135-1145. |
| Sherlock, et al. Assessment of diagnostic quantitative fluorescent multiplex polymerase chain reaction assays performed on single cells. Ann. Hum. Genet. 1998; 62:9-23. |
| Sitar, et al. The Use of Non-Physiological Conditions to Isolate Fetal Cells from Maternal Blood. Exp. Cell. Res. 2005; 302:153-61. |
| Sohda, et al. The Proportion of Fetal Nucleated Red Blood Cells in Maternal Blood: Estimation by FACS Analysis. Prenat. Diagn. 1997; 17:743-52. |
| Solexa Genome Analysis System. 2006; 1-2. |
| Sparkes, et al. “New Molecular Techniques for the Prenatal Detection of Chromosomal Aneuploidy,” JOGC, Jul. 2008, No. 210, 617-621. |
| Stipp, D. IG Labs Licenses New Technology for Fetal Testing. The Wall Street Journal. Aug. 10, 1990:B5. |
| Stoecklein, et al. SCOMP is superior to degenerated oligonucleotide primed-polymerase chain reaction for global amplification of minute amounts of DNA from microdissected archival tissue samples. Am J Pathol. 2002; 161(1):43-51. |
| Stoughton, et al. Data-adaptive algorithms for calling alleles in repeat polymorphisms. Electrophoresis. 1997;18(1):1-5. |
| Sun, et al. Whole-genome amplification: relative efficiencies of the current methods. Leg Med. 2005; 7(5):279-86. |
| Sykes, et al. Quantitation of targets for PCR by use of limiting dilution. Biotechniques. Sep. 1992;13(3):444-9. |
| Tanaka, et al. “Genome-wide expression profiling of mid-gestation placenta and embryo using a 15,000 mouse developmental cDNA microarray,” PNAS, Aug. 2000, vol. 97, No. 16, 9127-9132. |
| Tettelin, et al. The nucleotide sequence of Saccharomyces cerevisiae chromosome VII. Nature. May 29, 1997 ;387(6632 Suppl):81-4. |
| Thomas, et al. Specific Binding and Release of Cells from Beads Using Cleavable Tettrametric Antibody Complexes. Journal of Immunological Methods 1989;120:221-231. |
| Tibbe, et al. Statistical considerations for enumeration of circulating tumor cells. Cytometry A. Mar. 2007;71(3):154-62. |
| Toner, et al. Blood-on-a-Chip. Annu. Rev. Biomed. Eng. 7:77-103, C1-C3 (2005). |
| Trask, et al. Detection of DNA Sequences and Nuclei in Suspension by In Situ Hybridization and Dual Beam Flow Cytometry. Science.1985;230:1401-1403. |
| Troeger, et al. Approximately half of the erythroblasts in maternal blood are of fetal origin. Mol Hum Reprod. 1999; 5(12):1162-5. |
| Tufan, et al., Analysis of Cell-Free Fetal DNA from Maternal Plasma and Serum Using a Conventional Multiplex PCR: Factors Influencing Success. 2005. Turk. J. Med. Sci. 35:85-92. |
| Uitto, et al. Probing the fetal genome: progress in non-invasive prenatal diagnosis. Trends Mol Med. Aug. 2003;9(8):339-43. |
| Van Raamsdonk, et al. Optimizing the detection of nascent transcripts by RNA fluorescence in situ hybridization. Nucl. Acids. Res. 2001; 29(8):e42. |
| Voelkerding, et al. Digital fetal aneuploidy diagnosis by next-generation sequencing. Clin Chem. Mar. 2010;56(3):336-8. |
| Vogelstein, et al. “Digital PCR.” Proc Natl. Acad Sci. USA, Aug. 1999, vol. 96., 9236-9241. |
| Voldberg, et al. Epidermal growth factor receptor (EGFR) and EGFR mutations, function and possible role in clinical trials. Ann Oncol. Dec. 1997;8(12):1197-206. |
| Voldman, et al. Holding Forces of Single-Particle Dielectrophoretic Traps. Biophysical Journal.2001;80:531-541. |
| Volkmuth, et al. DNA electrophoresis in microlithographic arrays. Nature. 1992; 358:600-602. |
| Volkmuth, et al. Observation of Electrophoresis of Single DNA Molecules in Nanofabricated Arrays. Presentation at joint annual meeting of Biophysical Society and the American Society for Biochemistry and Molecular Biology. Feb. 9-13, 1992. |
| Von Eggeling, et al. Determination of the origin of single nucleated cells in maternal circulation by means of random PCR and a set of length polymorphisms. Hum Genet. Feb. 1997;99(2):266-70. |
| Vona, et al. Enrichment, immunomorphological, and genetic characterization of fetal cells circulating in maternal blood. Am J Pathol. Jan. 2002;160(1):51-8. |
| Vona, et al. Isolation by size of epthelieal tumor cells. American Journal of Pathology. 2000; 156:57-63. |
| Voullaire, et al. Detection of aneuploidy in single cells using comparative genomic hybridization. Prenat Diagn. 1999; 19(9):846-51. |
| Vrettou, et al. Real-time PCR for single-cell genotyping in sickle cell and thalassemia syndromes as a rapid, accurate, reliable, and widely applicable protocol for preimplantation genetic diagnosis. Human Mutation. 2004; 23(5):513-21. |
| Wachtel, et al. Fetal Cells in the Maternal Circulation: Isolation by Multiparameter Flow Cytometry and Confirmation by Polymerase Chain Reaction. Human Reproduction. 1991;6:1466-1469. |
| Wang, et al. Allele quantification using molecular inversion probes (MIP). Nucleic Acids Research. 2005; 33(21); e183 (14 pages). |
| Wapner, et al. First-trimester screening for trisomies 21 and 18. N. Engl. J. Med. 2003; 349:1405-1413. |
| Warren, et al. Transcription factor profiling in individual hematopoietic progenitors by digital RT-PCR. PNAS. Nov. 21, 2006; 103(47):17807-17812. |
| Washizu, et al. Handling Biological Cells Utilizing a Fluid Integrated Circuit. IEEE Industry Applications Society Annual Meeting Presentations. Oct. 2-7, 1988;: 1735-40. |
| Washizu, et al. Handling Biological Cells Utilizing a Fluid Integrated Circuit. IEEE Transactions of Industry Applications. 1990; 26: 352-8. |
| Weigl, et al. Microfluidic Diffusion-Based Separation and Detection. Science. 1999; pp. 346-347. |
| White, et al. Digital PCR provides sensitive and absolute calibration for high throughput sequencing. BMC Genomics. Mar. 19, 2009;10:116. |
| Williams, et al. Comparison of cell separation methods to entrich the proportion of fetal cells in material blood samples. The American Journal of Human Genetics. Oct. 1992. Supplemental to vol. 51, No. 4: 1049. |
| Xiong, et al. “A simple, rapid, high-fidelity and cost-effective PCR-based two-step DNA synthesis method for long gene sequences,” Nucleic Acids Research, Apr. 19, 2004, vol. 32, No. 12, e98. |
| Xu, et al. Dielectrophoresis of human red cells in microchips. Electrophoresis.1999;20: 1829-1831. |
| Yang, et al. Prenatal diagnosis of trisomy 21 with fetal cells i maternal blood using comparative genomic hybridization. Fetal Diagn Ther. 2006; 21:125-133. |
| Yang, et al. Rapid Prenatal Diagnosis of Trisomy 21 by Real-time Quantitative Polymerase Chain Reaction with Amplification of Small Tandem Repeats and S100B in Chromosome 21. Yonsei Medical Journal, 2005, vol. 46, No. 2, 193-197. |
| Yu, et al. Objective Aneuploidy Detection for Fetal and Neonatal Screening Using Comparative Genomic Hybridization (CGH). Cytometry. 1997; 28(3): 191-197. (Absbract). |
| Zavala, et al. Genomic GC content prediction in prokaryotes from a sample of genes. Gene. Sep. 12, 2005;357(2):137-43. |
| Zborowski, et al. Red Blood Cell Magnetophoresis. Biophys. J. 84:2638-45 (2003). |
| Zhen, et al. Poly-FISH: a technique of repeated hybridizations that improves cytogenetic analysis of fetal cells in maternal blood. Prenat Diagn. 1998; 18(11):1181-5. |
| Zheng, et al. Fetal cell identifiers: results of microscope slide-based immunocytochemical studies as a function of gestational age and abnormality. Am J Obstet Gynecol. May 1999;180(5):1234-9. |
| Zhu, et al. Single molecule profiling of alternative pre-mRNA splicing. Science. Aug. 8, 2003;301(5634):836-8. |
| Zimmerman, et al. Novel real-time quantitative PCR test for trisomy 21. Jan 1, 2002. Clinical Chemistry, American Association for Clinical Chemistry. 48:(2) 362-363. |
| Zimmermann, Bernhard. “Molecular Diagnosis in Prenatal Medicine,” Ph.D. Thesis, 2004. |
| Zuska, P. Microtechnology Opens Doors to the Universe of Small Space, MD&DI Jan. 1997, p. 131. |
| Number | Date | Country | |
|---|---|---|---|
| 20130189688 A1 | Jul 2013 | US |
| Number | Date | Country | |
|---|---|---|---|
| 60820778 | Jul 2006 | US | |
| 60804819 | Jun 2006 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 13306640 | Nov 2011 | US |
| Child | 13835926 | US | |
| Parent | 12230628 | Sep 2008 | US |
| Child | 13306640 | US | |
| Parent | 11763421 | Jun 2007 | US |
| Child | 12230628 | US |
