Patent Application
20150057275
The invention relates to methods and materials for rapid detection of mutations for tumor genotyping.
The clinical management of cancer patients has traditionally relied on chemotherapeutic choices that are mostly dictated by pathologic tumor histology and organ of origin. In recent years, major efforts to define the molecular causes of cancer have revealed a wide number of genetic aberrations (Davies et al. (2005) Cancer Res 65, 7591-7595; Ding et al. (2008) Nature 455, 1069-1075; Greenman et al. (2007) Nature 446, 153-158; Rikova et al. (2007) Cell 131, 1190-1203; Sjoblom et al. (2006) Science 314, 268-274; Stephens et al. (2005) Nat Genet, 37 590-592; Thomas et al. (2007) Nat Genet 39, 347-351; Wood et al. (2007) Science 318, 1108-1113). A small subset of these defects, usually referred to as “drivers,” is frequently present across cancer types and appears to be essential for oncogenesis and tumor progression (Greenman et al. (2007) Nature 446, 153-158). A new generation of drugs has been developed to selectively target such cancer-promoting pathways (Druker et al. (2001) N Engl J Med 344, 1031-1037; Hanahan and Weinberg (2000) Cell, 100, 57-70; Weinstein, 2000) and hence, treatment dictated by genetic markers is starting to complement the more conventional therapeutic approaches.
The present invention is based, at least in part, on the discovery of a robust and highly sensitive tumor genotyping assay for real-time testing of tumors.
In one aspect, the invention features methods of providing a genetic profile of a tumor (e.g., a tumor cell from a lung, breast, colorectal, head and neck, or ovarian tumor, or any solid tumor or hematopoietic malignancy), the method comprising providing a sample comprising genomic DNA from a tumor cell and simultaneously determining the identity of one or more alleles listed in Table 3B for each of EGFR and KRAS plus one or more alleles from one or more of AKT1, APC, BRAF, CTNNB1, FLT3, IDH1, JAK2, KIT, MAP2K1, NOTCH1, NRAS, PIK3CA, PTEN, and TP53 in the genomic DNA, wherein the method comprises determining the identity of each allele using a single base extension reaction, thereby providing a genetic profile of the tumor.
In one embodiment, the methods described herein wherein the tumor cell is in a formalin-fixed paraffin-embedded biopsy sample.
In one embodiment, the methods described herein comprise determining the identity of about 6 to 9 alleles in a single reaction.
In one embodiment, the methods described herein comprise determining the identity of all alleles listed in Table 3B.
In one embodiment, the methods described herein comprise performing a plurality of reactions as set forth in Tables 8A and 8B.
In another aspect, the invention features methods of selecting an appropriate chemotherapy for a subject with cancer (e.g., lung cancer, breast cancer, colorectal cancer, head and neck cancer, ovarian cancer, any solid tumor or hematopoietic malignancy), the method comprising providing a sample comprising genomic DNA from a tumor cell from the subject; simultaneously determining the identity of one or more alleles listed in Table 3B for each of EGFR and KRAS plus one or more alleles from one or more of AKT1, APC, BRAF, CTNNB1, FLT3, IDH1, JAK2, KIT, MAP2K1, NOTCH1, NRAS, PIK3CA, PTEN, and TP53 in the genomic DNA, wherein the method comprises determining the identity of each allele using a single base extension reaction, to provide a genetic profile of the tumor; and selecting an appropriate chemotherapy based on the genetic profile of the tumor.
In one embodiment, if an EGFR 2369C>T, KRAS 34G>T, KRAS 34G>C, KRAS 34G>A, KRAS 35G>T, KRAS 35G>C, KRAS 35G>A, KRAS 37G>T, KRAS 37G>C, KRAS 37G>A, KRAS 38G>T, KRAS 38G>C, or KRAS 38G>A mutation is present, then a therapy comprising an EGFR inhibitor is not selected.
In one embodiment, the methods described herein comprise determining the identity of about 6 to 9 alleles in a single reaction.
In one embodiment, the methods described herein comprise determining the identity of all alleles listed in Table 3B.
In one embodiment, the methods described herein comprise performing a plurality of reactions as set forth in Tables 8A and 8B.
In one embodiment, the methods further comprise administering the selected chemotherapy (e.g., erlotinib or gefitinib) to the subject.
In one aspect, the invention features methods of determining a prognosis for a subject diagnosed with cancer (e.g., lung cancer, breast cancer, colorectal cancer, head and neck cancer, ovarian cancer, any solid tumor or hematopoietic malignancy), the method comprising providing a sample comprising genomic DNA from a tumor cell from the subject; simultaneously determining the identity of one or more alleles listed in Table 3B for each of EGFR and KRAS plus one or more alleles from one or more of AKT1, APC, BRAF, CTNNB1, FLT3, IDH1, JAK2, KIT, MAP2K1, NOTCH1, NRAS, PIK3CA, PTEN, and TP53 in the genomic DNA, wherein the method comprises determining the identity of each allele using a single base extension reaction, to provide a genetic profile of the tumor; and determining a prognosis for the subject based on the genetic profile of the tumor.
In one embodiment, the subject has a plurality of tumors and the method comprises determining the genetic profile of more than one tumor in the subject, wherein the presence of an identical profile in each tumor indicates that the cancer is metastatic (i.e., poor prognosis), and the presence of a different profile in each tumor indicates that the cancer is not metastatic (i.e., better prognosis). Further, a FTL3 2503G>T mutation indicates a poor prognosis in acute myeloid leukemia. All IDH1 mutations indicate better prognosis in glioblastoma.
In one embodiment, the methods described herein comprise determining the identity of about 6 to 9 alleles in a single reaction.
In one embodiment, the methods described herein comprise determining the identity of all alleles listed in Table 3B.
In one embodiment, the methods described herein comprise performing a plurality of reactions as set forth in Tables 8A and 8B.
In another aspect, the invention features kits comprising the primers listed in Table 7. In one embodiment, the primers are provided in a container in the combinations as listed in Tables 8A and 8B.
The term “single reaction” as used herein refers to a reaction occurring in a vessel, e.g., tube, well, area on an array, or other container, suitable for the purpose.
As used herein, an “allele” is one of a pair or series of genetic variants of a polymorphism at a specific genomic location. A “cancer susceptibility allele” is an allele that is associated with increased susceptibility of developing cancer.
As used herein, a “haplotype” is one or a set of signature genetic changes (polymorphisms) that are normally grouped closely together on the DNA strand, and are usually inherited as a group; the polymorphisms are also referred to herein as “markers.” A “haplotype” as used herein is information regarding the presence or absence of one or more genetic markers in a given chromosomal region in a subject. A haplotype can consist of a variety of genetic markers, including indels (insertions or deletions of the DNA at particular locations on the chromosome); single nucleotide polymorphisms (SNPs) in which a particular nucleotide is changed; microsatellites; and minisatellites.
The term “chromosome” as used herein refers to a gene carrier of a cell that is derived from chromatin and comprises DNA and protein components (e.g., histones). The conventional internationally recognized individual human genome chromosome numbering identification system is employed herein.
The term “gene” refers to a DNA sequence in a chromosome that codes for a product (either RNA or its translation product, a polypeptide). A gene contains a coding region and includes regions preceding and following the coding region (termed respectively “leader” and “trailer”). The coding region is comprised of a plurality of coding segments (“exons”) and intervening sequences (“introns”) between individual coding segments.
The term “probe” refers to an oligonucleotide. A probe can be single stranded at the time of hybridization to a target. As used herein, probes include primers, i.e., oligonucleotides that can be used to prime a reaction, e.g., a PCR reaction.
Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Methods and materials are described herein for use in the present invention; other, suitable methods and materials known in the art can also be used. The materials, methods, and examples are illustrative only and not intended to be limiting. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control.
Other features and advantages of the invention will be apparent from the following detailed description and figure, and from the claims.
Tables 1 to 9 appear at the end of this text before the drawings.
The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawings will be provided by the Office upon request and payment of the necessary fee.
FIGS. 14A to 14AG show the coding sequences (nucleic acid and corresponding amino acid) for AKT1, APC, BRAF, CTNNB1, EGFR, FLT3, IDH1, JAK2, KIT, KRAS, MAP2K1, NOTCH1, NRAS, PIK3CA, PTEN, and TP53.
The methods and materials described herein are based, at least in part, on the development of a robust and highly sensitive tumor genotyping assay for real-time testing of tumors, which can assist physicians in directing their cancer patients to the most appropriate targeted therapies.
While the clinical benefit observed with some targeted agents is encouraging, it is clear that for such strategies to be successful, it is necessary to identify the patient population carrying the genetic abnormalities targeted by each drug (McDermott et al. (2007) Proc Natl Acad Sci USA 104, 19936-19941; Sos et al. (2009) J Clin Invest 119, 1727-1740). In advanced non-small cell lung cancer (NSCLC), activating mutations in the region encoding the kinase domain of the epidermal growth factor receptor (EGFR) gene predict tumor sensitivity to the tyrosine kinase inhibitors (TKI) erlotinib and gefitinib (Lynch et al. (2004) N Engl J Med 350, 2129-2139; Paez et al. (2004) Science 304, 1497-1500; Pao et al. (2004) Proc Natl Acad Sci USA 101, 13306-13311; Sordella et al. (2004) Science 305, 1163-1167). Since NSCLC patients harboring EGFR mutations benefit from these specific inhibitors in the first-line setting compared to standard chemotherapy (Mok et al. (2009) N Engl J Med 361, 947-957), and only a small fraction of NSCLCs harbor these mutations, prospective screening for EGFR mutations at the time of diagnosis is becoming common practice (Sharma et al. (2007) Nat Rev Cancer 7, 169-181). Equally important is the identification of mutations that render tumors resistant to therapy. Activating mutations in KRAS predict resistance to EGFR TKI treatment in NSCLC (Pao et al. (2005b) PLoS Med 2, e17). In metastatic colorectal cancer, mutations in KRAS, BRAF, and PIK3CA are associated with resistance to treatment with monoclonal antibodies cetuximab and panitumumab, which target the extracellular domain of EGFR (Di Nicolantonio et al. (2008) J Clin Oncol 26, 5705-5712; Lievre et al. (2006) Cancer Res 66, 3992-3995; Sartore-Bianchi et al. (2009) Cancer Res, 69, 1851-1857). Similarly in breast cancer, oncogenic mutations in PIK3CA or low levels of PTEN expression may confer resistance to treatment with trastuzumab, a monoclonal antibody that targets the HER2/NEU receptor (Berns et al. (2007) Cancer Cell 12, 395-402).
Pharmacogenomics is the branch of pharmacology that deals with the influence of genetic variation on drug response in patients by correlating gene expression or single-nucleotide polymorphisms with a drug's efficacy or toxicity. As the repertoire of selective therapeutic compounds continues to expand, the need to evaluate larger numbers of genetic mutations is a major challenge (Chin and Gray (2008) Nature 452, 553-563). Pharmacogenomics aims to develop rational means to optimize drug therapy, with respect to a subject's genotype, to ensure maximum efficacy with minimal adverse effects. Such approaches promise the advent of “personalized medicine,” in which drugs and drug combinations are optimized for an individual's unique genetic makeup.
In addition to the dilemma of selecting the most relevant abnormalities, the tissue samples themselves pose many obstacles, including minute specimens derived from small core biopsies, poor quality fragmented nucleic acid due to formalin fixation and paraffin embedding (FFPE) required for histology-based diagnosis (Srinivasan et al. (2002) Am J Pathol 161, 1961-1971), and heterogeneous tumor samples comprised of normal tissue and cancerous cells which dilute the mutant alleles of interest. Thus, a clinical assay should: (1) be multiplexed, to maximize information retrieval from limited tissue; (2) perform well with FFPE-derived material; and (3) be very sensitive to detect low-level mutations. Additionally, the turn-around-time for the entire specimen processing and mutation detection platform should be fast, in order to integrate into the rapid pace of clinical decision making and impact patient management.
Provided herein are methods for providing a genetic profile of a tumor. The present disclosure also describes predictive biomarkers (SNP alleles) to classify a tumor, e.g., as resistant or sensitive to a chemotherapeutic drug. The tumor can be from a subject, e.g., a human or animal, such as laboratory animals, e.g., mice, rats, rabbits, or monkeys, or domesticated and farm animals, e.g., cats, dogs, goats, sheep, pigs, cows, horses, and birds.
The biomarkers and methods are also useful in selecting appropriate therapeutic modalities for subjects with certain conditions, e.g., cancer, e.g., lung cancer, breast cancer, colon cancer, pancreatic cancer, renal cancer, stomach cancer, liver cancer, bone cancer, leukemia, lymphoma, multiple myeloma, hematological cancer, neural tissue cancer, melanoma, thyroid cancer, ovarian cancer, testicular cancer, prostate cancer, cervical cancer, vaginal cancer, or bladder cancer. A subject with cancer can be identified using methods known in the art, e.g., based on detection of a tumor or neoplasm, or on the presence of one or more symptoms of the condition. Symptoms of cancer vary greatly and are well-known to those of skill in the art and include, without limitation, breast lumps, nipple changes, breast cysts, breast pain, weight loss, weakness, excessive fatigue, difficulty eating, loss of appetite, chronic cough, worsening breathlessness, coughing up blood, blood in the urine, blood in stool, nausea, vomiting, liver metastases, lung metastases, bone metastases, abdominal fullness, bloating, fluid in peritoneal cavity, vaginal bleeding, constipation, abdominal distension, perforation of colon, acute peritonitis (infection, fever, or pain), pain, vomiting blood, heavy sweating, fever, high blood pressure, anemia, diarrhea, jaundice, dizziness, chills, muscle spasms, colon metastases, lung metastases, bladder metastases, liver metastases, bone metastases, kidney metastases, pancreas metastases, difficulty swallowing, and the like.
Furthermore, after performing any of the methods for characterizing the drug sensitivity of a tumor, the tumor can be subjected to any of a variety of chemotherapeutic drugs, e.g., any of those described above. It is understood that such therapies would be administered to a tumor that had been found by such a method to have an increased sensitivity to the therapy.
A SNP occurs at a polymorphic site occupied by a single nucleotide, which is the site of variation between allelic sequences. The site is usually preceded by and followed by highly conserved sequences of the allele (e.g., sequences that vary in less than 1/100 or 1/1000 members of the populations). A SNP usually arises due to substitution of one nucleotide for another at the polymorphic site. A transition is the replacement of one purine by another purine or one pyrimidine by another pyrimidine. A transversion is the replacement of a purine by a pyrimidine or vice versa. Single nucleotide polymorphisms can also arise from a deletion of a nucleotide or an insertion of a nucleotide relative to a reference allele. Typically the polymorphic site is occupied by a base other than the reference base. For example, where the reference allele contains the base “T” at the polymorphic site, the altered allele can contain a “C”, “G” or “A” at the polymorphic site.
A series of SNP alleles have been identified that are associated with cancers (Tables 3A and 3B). Thus, the presence of one or more of these SNP alleles can be used to provide a genetic profile of a tumor and characterize the drug sensitivity of the tumor. The SNP genotypes (identified by their SNP site) are depicted in Tables 3A and 3B. Further information on the SNPs can be obtained from, for example, the COSMIC/Sanger Institute database that is accessible via the Internet.
In some embodiments, the allele(s) of at least one (e.g., at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 20, at least 30, at least 40, at least 50, at least 80, at least 100, at least 120, or at least 140) of the SNP sites depicted in Table 3B can be determined and/or used to characterize the drug sensitivity of the tumor.
Methods for detecting the presence of a SNP are known in the art and include, for example, those set forth in the accompanying Examples. The methods of detecting a SNP can be performed in formats that allow for rapid preparation, processing, and analysis of multiple samples (see below). The methods will be described primarily with SNAPSHOT®, although it will be understood by skilled practitioners that they may be adapted for use with other platforms, which may include standard Sanger sequencing, Sequenom MassARRAY, SNPStream and SNPlex technologies, among others. Further, a variety of reporter molecules can be used to determine the identity of an allele. For example, rather than fluorescent dideoxynucleotides, the single base extension reaction can be performed with oligonucleotides labeled with quantum dots; see, e.g., Sapsford et al. (2006) Sensors 6, 925-953. Alternatively, SNP detection can be performed by analysis of the molecular weight of the extension products using MALDI-TOFF mass spectrometry (Tang et al. (1999) Proc Natl Acad Sci USA 96:10016-20).
Suitable biological samples for the methods described herein include any biological fluid, cell, tissue, or fraction thereof, which includes analyte biomolecules of interest such as nucleic acid (e.g., DNA). A biological sample can be, for example, a specimen obtained from a human subject or can be derived from such a subject. For example, a sample can be a tissue section obtained by biopsy, or cells that are placed in or adapted to tissue culture. A biological sample can also be a biological fluid such as urine, blood, plasma, serum, saliva, semen, sputum, cerebral spinal fluid, tears, or mucus, or such a sample absorbed onto a paper or polymer substrate. A biological sample can be further fractionated, if desired, to a fraction containing particular cell types. For example, a blood sample can be fractionated into serum or into fractions containing particular types of blood cells such as red blood cells or white blood cells (leukocytes). If desired, a sample can be a combination of samples from a subject such as a combination of a tissue and fluid sample.
The biological samples can be obtained from a subject, e.g., a subject having a tumor. Any suitable methods for obtaining the biological samples can be employed, although exemplary methods include, e.g., phlebotomy, swab (e.g., buccal swab), or fine needle aspirate biopsy procedure. Non-limiting examples of tissues susceptible to fine needle aspiration include lymph node, lung, thyroid, breast, and liver. Samples can also be collected, e.g., by microdissection (e.g., laser capture microdissection (LCM) or laser microdissection (LMD)), bladder wash, smear (PAP smear), or ductal lavage.
Methods for obtaining and/or storing samples that preserve the activity or integrity of molecules (e.g., nucleic acids) in the sample are well known to those skilled in the art. For example, a biological sample can be further contacted with one or more additional agents such as appropriate buffers and/or inhibitors, including nuclease inhibitors, which preserve or minimize changes in the molecules (e.g., nucleic acids) in the sample. Such inhibitors include, for example, chelators such as ethylenediamine tetraacetic acid (EDTA) and ethylene glycol bis(P-aminoethyl ether) N,N,N1,N1-tetraacetic acid (EGTA). Appropriate buffers and conditions for isolating molecules are well known to those skilled in the art and can be varied depending, for example, on the type of molecule in the sample to be characterized (see, for example, Ausubel et al., Current Protocols in Molecular Biology (Supplement 47), John Wiley & Sons, New York (1999); Harlow and Lane, Antibodies: A Laboratory Manual (Cold Spring Harbor Laboratory Press (1988); Harlow and Lane, Using Antibodies: A Laboratory Manual, Cold Spring Harbor Press (1999); Tietz, Textbook of Clinical Chemistry, 3rd ed. Burtis and Ashwood, eds. W.B. Saunders, Philadelphia, (1999)). A sample also can be processed to eliminate or minimize the presence of interfering substances. For example, a biological sample can be fractionated or purified to remove one or more materials that are not of interest. Methods of fractionating or purifying a biological sample include, but are not limited to, chromatographic methods such as liquid chromatography, ion-exchange chromatography, size-exclusion chromatography, or affinity chromatography.
For use in the methods described herein, a sample can be in a variety of physical states. For example, a sample can be a liquid or solid, can be dissolved or suspended in a liquid, can be in an emulsion or gel, and can be absorbed onto a material.
Subjects of all ages can be affected by cancer. Therefore, a biological sample used in a methods described herein can be obtained from a subject (e.g., a human) of any age, including a child, an adolescent, or an adult, such as an adult having a tumor.
The methods and compositions described herein can be used to, e.g., (a) provide a genetic profile of a tumor and/or (b) characterize the drug sensitivity of a tumor. The profile can include information that indicates the presence or absence of one or more SNP genotypes depicted in Tables 3A and 3B.
The genetic profiles described herein can include information on the presence or absence of at least one or more (e.g., at least two or more, at least three or more, at least four or more, at least five or more, at least six or more, at least seven or more, at least eight or more, at least nine or more, at least 10 or more, at least 11 or more, at least 12 or more, at least 13 or more, at least 14 or more, at least 15 or more, at least 16 or more, at least 17 or more, at least 18 or more, at least 19 or more, at least 20 or more, at least 21 or more, at least 22, at least 24 or more, at least 30 or more, at least 40 or more, at least 50 or more, at least 80 or more, at least 100 or more, at least 120 or more, or at least 140 or more) SNP alleles depicted in Table 3B.
Grouping of multiple SNPs (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 70, 100, 120, or 140 or more SNPs depicted in Table 3B) into sets or clusters can improve the sensitivity or specificity of the method. A group of SNPs comprising individual SNPs selected from each of the clusters can then be tested for predictive accuracy and the classifiers can be recalculated based on the group of SNPs.
After profiling and characterizing the drug sensitivity of a tumor, a medical practitioner (e.g., a physician) can select an appropriate therapeutic modality for the subject (e.g., chemotherapeutic drugs selected from the group consisting of erlotinib, gefitinib, cetuximab, panitumumab, cisplatin, carboplatin, procarbazine, mechlorethamine, cyclophosphamide, camptothecin, adriamycin, ifosfamide, melphalan, chlorambucil, bisulfan, nitrosurea, dactinomycin, daunorubicin, doxorubicin, bleomycin, plicomycin, mitomycin, etoposide, verampil, podophyllotoxin, tamoxifen, taxol, transplatinum, 5-flurouracil, vincristin, vinblastin, methotrexate, and an analog of any of the aforementioned. Selecting a therapy for a subject can be, e.g.: (i) writing a prescription for a medicament; (ii) giving (but not necessarily administering) a medicament to a subject (e.g., handing a sample of a prescription medication to a patient while the patient is at the physician's office); (iii) communication (verbal, written (other than a prescription), or electronic (email, post to a secure site)) to the patient of the suggested or recommended therapeutic modality (e.g., non-immunosuppresive therapy or immunosuppresive therapy); or (iv) identifying a suitable therapeutic modality for a subject and disseminating the information to other medical personnel, e.g., by way of patient record. The latter (iv) can be useful in a case where, e.g., more than one therapeutic agent are to be administered to a patient by different medical practitioners.
It is understood that genetic profile of a tumor can be in electronic form (e.g., an electronic patient record stored on a computer or other electronic (computer-readable) media such as a DVD, CD, or floppy disk) or written form.
In one embodiment, the genotyping platform consists of nine multiplexed reactions that query 73 commonly mutated loci (Table 3A) within 16 key cancer genes (FIGS. 14A to 14AG). Since multiple nucleotide variants have been described at most of these sites, the test can detect over 120 previously described mutations (Table 3B).
In implementing this assay in a clinical setting, approximately two to three weeks are required from the time of test requisition until genotyping report finalization. This is referred to as a “real-time” assay, as oncologists ordering the test will have access to their patients' tumor mutational profiling data in time to influence clinical decision making. In these initial analyses, SNAPSHOT® results have substantially impacted therapeutic decisions. For lung cancer patients, detection of activating mutations in EGFR will identify patients most appropriate for first-line treatment with EGFR TKI therapy (Kobayashi et al. (2005) N Engl J Med 352, 786-792; Lynch et al. (2004) N Engl J Med 350, 2129-2139; Paez et al. (2004) Science 304, 1497-1500; Pao et al. (2004) Proc Natl Acad Sci USA 101, 13306-13311; Zhu et al. (2008) Cancer Lett 265, 307-317). Conversely, tumors harboring KRAS mutations are associated with lack of responsiveness to EGFR TKI treatment, and such patients are advised to pursue other therapeutic options (Pao et al. (2005b) PLoS Med 2, e17).
Also described herein are kits for use in the present methods. For example, the kit can include a set of primers for detecting mutations in a biological sample; and a standard. The primers can be packaged in a suitable container, and can be in suitable combinations, e.g., Tables 8A and 8B. The kit can further comprise instructions for using the kit in the present methods.
The kit can also include a buffering agent, a preservative, or a protein stabilizing agent. The kit can also include components necessary for detecting the detectable agent (e.g., an enzyme or a substrate). The kit can also contain a control sample or a series of control samples which can be assayed and compared to the test sample contained. Each component of the kit can be enclosed within an individual container and all of the various containers can be within a single package, along with instructions for interpreting the results of the assays performed using the kit.
The invention is further described in the following examples, which do not limit the scope of the invention described in the claims.
A total of 250 primary cancer samples spanning 26 human malignancies were tested, which included: lung cancer (n=87), breast cancer (n=33), colorectal cancer (n=30), pancreatic cancer (n=23), prostate cancer (n=20), melanoma (n=11), chronic myeloproliferative disease (n=10), cholangiocarcinoma (n=6), gastric cancer (n=4), ovarian cancer (n=3), salivary gland cancer (n=3), and thyroid cancer (n=3) among others. Sixty-two of these primary tumor samples were evaluated for official clinical testing, and included 52 lung adenocarcinomas, most of them small core biopsies with very limited tissue. For hematopoietic malignancies, spare DNA that had been previously extracted from patient blood for clinical testing was obtained from the Massachusetts General Hospital (MGH) Molecular Diagnostics Laboratory. For solid tumors, formalin-fixed paraffin-embedded (FFPE) tumor blocks were obtained from MGH archives. Histological examination of hematoxylin and eosin-stained slides derived from FFPE samples was performed by a pathologist and assessed for the presence of a tumor. Available tumor tissue was manually macro-dissected from serial 5 μm unstained sections, or cored from the paraffin block using a 1.5 mm dermal punch. Total nucleic acid was extracted from FFPE material using a modified FormaPure System (Agencourt Bioscience Corporation, Beverly, Mass.) on a custom Beckman Coulter Biomek NXP workstation. Blood-derived DNA was extracted using the QIAamp Blood kit (QIAGEN Inc., Valencia, Calif.).
Assay Design and Validation
The COSMIC (Bamford et al. (2004) Br J Cancer 91, 355-358) database and PubMed was evaluated to select a panel of genes and loci previously reported to be frequently affected by somatic mutation in human cancer. Thirteen cancer genes were selected and 58 assays were designed to test for individual mutational events, which included: one insertion, three deletions and 52 substitutions (Tables 3A and 3B). Genomic position and sequencing information for all mutation sites were collected using the RefSeq gene sequences obtained using the human genome browser from the University of California Santa Cruz (UCSC), NCBI build 36.1. Primers for multiplexed PCR amplification were designed using Primer 3 software. Since FFPE tissue can be highly fragmented and of poor quality, design parameters restricted amplicon length to a maximum of 200 nt. All amplification primers (Table 7A) include a 10 nt long 5′ anchor tail (5′-ACGTTGGATG-3′ (SEQ ID NO: 236)) and the final PCR products range in length between 75 and 187 nt. The extension primer probes (Table 7B) were designed manually, according to the ABI PRISM SNAPSHOT® Multiplex Kit protocol recommendations (Life Technologies/Applied Biosystems, Foster City, Calif.) and using primer analysis tools available through the Primer 3 and Integrated DNA Technologies (IDT) web interfaces. Optimal conditions for multiplexed assays were determined empirically and are summarized in Table 8.
As part of the design rationale, assays covering four adjacent loci that are commonly mutated in the therapeutically relevant KRAS and NRAS oncogenes were included (nucleotide positions 34G, 35G, 37G and 38G were targeted for both genes). Due to the close proximity of these sites and to avoid compromising assay sensitivity due to primer competition, each nucleotide position was assayed in an independent panel. In addition, due to the extreme sequence similarity between KRAS and NRAS, to avoid non-specific results, the assays for these two genes were segregated into individual multiplexed reactions. Eight panels were populated with the 58 assays outlined in Table 3. Many of these genes and assays are clinically relevant. In addition, since the costs of running the assay (regarding tumor material and the actual price per assay) are mainly dictated by the number of panels, a set of common mutations affecting critical cancer genes for which a therapeutic agent is still currently unavailable was also included. The addition of these mutations is useful in a clinical setting, as they may correlate with a better or worse prognosis or to influence response to specific therapies, and thus contribute to better cancer care in the future.
In order to develop a robust assay for clinical tumor genotyping, several high-throughput platforms were evaluated for the ability to detect low-level mutations in DNA extracted from FFPE tissues. The SNAPSHOT® assay from Applied Biosystems consisting of a multiplexed PCR step followed by a single-base extension reaction that generates allele-specific fluorescently labeled probes (
Assays were designed to detect recurrent mutations in some of the most important cancer genes, many of which activate cancer signaling pathways that are currently targeted by either FDA-approved therapies or by agents in advanced stages of clinical development (Table 1). The genotyping platform consists of eight multiplexed reactions that query 58 commonly mutated loci within 13 key cancer genes. Since multiple nucleotide variants have been described at most of these sites, the test can detect 120 previously described mutations (Table 3). The assay is focused predominantly on oncogenes because aberrantly activated oncogenes are preferential targets for pharmacologic inhibition, and gain-of-function mutations in oncogenes are usually limited to a small set of codons. Accordingly, the assay captures 94% to 99% of the mutation frequency described for the BRAF, KRAS, and JAK2 oncogenes, which are frequently mutated in a very few hotspots. Representative spectra of all eight SNAPSHOT® genotyping panels are depicted in
Assay validation was carried out with control DNA harboring the mutations of interest, which included: primary tumor DNA, cancer cell line DNA, and custom-designed synthetic oligonucleotides (Table 3). All SNAPSHOT® assays identified the expected mutations. In addition, allele-specific assays that could be validated using genomic DNA were assessed for sensitivity, which ranged from 11.4% to 1.4% and was on average approximately 5% (
As an example of validation and sensitivity testing,
The Applied Biosystems (ABI) PRISM® SNAPSHOT® Multiplex system was originally developed to detect single nucleotide polymorphisms (SNPs) (Lindblad-Toh et al. (2000) Nat Genet 24, 381-386) (
Two hundred fifty primary cancer samples representative of major human malignancies were profiled, and a total of 100 mutations were detected in 86 (34%) of the cases (Table 4). Of note, the majority of these tumor samples (96%) were derived from FFPE tissue. The most frequently mutated gene was KRAS, across multiple tumor types, followed by EGFR, which was detected in lung adenocarcinomas (Table 2 and
The specificity of SNAPSHOT® genotyping was evaluated by analysis of primary tumor samples and matching normal tissue from the same individual.
In general, the genotyping results were consistent with the documented mutational prevalence for oncogenes, but lower than expected mutational frequencies were observed for tumor suppressors (Table 5). Slight discrepancies between these observations and the reported mutation frequencies for oncogenes included lower than expected mutation prevalences for beta-catenin (CTNNB1) and BRAF in pancreatic and colorectal tumors, respectively; and higher than the reported frequencies for NRAS in colorectal cancer. Surprisingly, the incidence of NRAS mutations in the colorectal cancer population tested was three-fold higher than previously described. Interestingly, a number of mutations and combination of mutations (marked by the asterisks in Table 2) were identified that are rare or not previously described in the respective tumor types. Some of these less common events are illustrated in
Within the subset of events captured by the panel, the observations were consistent with previous findings from genome-wide studies (
Traditional Sanger sequencing was performed in a volume of 20 μl, containing 1 unit of Taq polymerase (Invitrogen, Carlsbad, Calif.), 4 nmol of dNTPs (Invitrogen, Carlsbad, Calif.), 10 pmol of forward (a1) and reverse (a2) primers, 40 nmol of MgCl2 (or the amount indicated in Table 10), and either 40 ng of genomic DNA or 120 ng of total nucleic acid. Initially, sequencing was attempted with the same amplification primers and cycling parameters used for SNAPSHOT® multiplexed PCR. For those cases where this strategy was not successful, new primers were designed (Table 10) and the cycling conditions were: 94° C. for 5 min, followed by 38 cycles of 94° C. for 30 s, a specific annealing temperature for 30 s and 72° C. for 45 sec, and one last cycle of 72° C. for 10 min. The annealing temperature and amount of MgCl2 used for each PCR are detailed in Table 10. The resulting PCR products were treated using 1 unit of shrimp alkaline phosphatase (USB, Cleveland, Ohio) and 5 units of exonuclease I (USB, Cleveland, Ohio) at 37° C. for 20 minutes followed by 80° C. for 15 minutes, and tested for the presence of mutations by bi-directional Sanger sequencing using the BigDye Terminator V1.1 Cycle Sequencing Kit (Applied Biosystems), according to the manufacturer's recommendations. The sequencing reaction step was performed with the original PCR primers or with the incorporated M13 tags. Tumor and control human genomic DNA (Promega, Madison, Wis.) sequences were compared using the AB Sequencing Analysis Software v5.2 (Applied Biosystems).
A PCR-based strategy was developed to identify insertions or deletion mutations in exon 19 of the EGFR gene, which is a hotspot region for deletions. Amplification primer sequences were as follows, with the forward primer being 5′-labeled with the NED fluorophore: NED-EGFR_Ex19_F [0.1 μM]: 5′-NED-GCACCATCTCACAATTGCCAGTTA-3′ (SEQ ID NO:234); EGFR-Ex19-REV1 [0.1 μM]: 5′-AAAAGGTGGGCCTGAGGTTCA-3′ (SEQ ID NO:235). 20 ng of DNA template was amplified using Platinum Taq polymerase in the presence of 2 mM MgCl2 (Invitrogen, Carlsbad, Calif.). The 20 μl reaction was subjected to 5 minutes of denaturation at 94° C. and 40 cycles of denaturation at 94° C. for 30 seconds, annealing at 60° C. for 30 seconds, and elongation at 72° C. for 60 seconds. Following PCR amplification, products were diluted 1:30 in water and a 1 μl aliquot was added to 9.9 μl of Hi-Di Formamide and 0.1 μl of GeneScan 500 LIZ Size Standard (Applied Biosystems Inc, Foster City, Calif.). Heat-denatured samples were analyzed through capillary electrophoresis using the automated ABI 3730 DNA Analyzer with GeneMapper software (Applied Biosystems Inc). Insertions or deletions were visualized by shifts in molecular weight of the fluorescently-identifiable PCR amplicon relative to wild-type.
Panels and bin set parameters for automatic data analysis were created using GeneMapper Software version 4.0, according to the manufacturer's instructions and are provided herein. Briefly, for each genetic locus tested by a SNAPSHOT® mutation assay, there are four possible alleles (for deletion and insertion assays only two alleles were considered: the wild-type allele and the expected nucleotide change resulting from the specified deletion or insertion). The position of each of these alleles can be automatically captured by the analysis software upon the creation of specific bins (allele definitions). Bin parameters for each assay were initially established using Primer Focus Kit data (Life Technologies/Applied Biosystems) according to the manufacturer's recommendations and were subsequently adjusted using reference data from wild-type tumor samples and from the mutant controls used for assay validation. The panel and bin set parameters used in this study are provided herein. Automatic mutation calling was set at a 5% sensitivity threshold. Interpretation of SNAPSHOT® genotyping results was accomplished by automatic analysis of the raw data using the established panels and bin settings, followed by visual inspection of the spectra for all loci by at least two users. In addition, if a mutation was detected, a third user reviewed the panel containing the mutation. Since spectral analysis follows a very strict set of scoring guidelines (described below), the concordance in calling between different users was extremely high.
Data analysis was performed using the following scoring criteria.
Pass. For each sample, an individual SNAPSHOT® assay passed if: (1) the peak fluorescent height for the wild type allele was ≧1,000 f.u. (this value was selected for being approximately 50-100 times higher than the overall background noise, however, since signal intensities may vary for different genetic analyzer instruments, this value should be adjusted by different users); and (2) the peak fluorescent height for the wild type allele in the negative control (water sample) was <10% of the height of the wild type allele in the clinical sample.
Mutant. A mutation was called for a specific assay when: (1) the % of mutant allele for one of the 3 possible nucleotide variants, falling within its corresponding bin, was ≧10% (fluorescent peak height ratio of [mutant/(mutant+wild type)] alleles>0.10), and (2) the peak fluorescence of the mutant allele was >3 times above the background in the wild type control sample (
Repeat. A specific panel was repeated if it contained an assay with a suspected mutation, or if it contained an assay that failed (either because: (1) the peak fluorescent height for the wild type allele was <1,000 f.u. or (2) the negative control produced a peak fluorescent height for the wild type allele that was ≧10% of the height of that same peak in the test sample).
The tumor genotyping assay described in this example consists of 8 SNAPSHOT® multiplex panels that test for 58 commonly mutated loci in 13 cancer genes. Since multiple nucleotide variants have been described at most of these loci, the assay can detect 120 previously described mutations (Table 3). The frequency of occurrence of each allele variant was calculated using data compiled by the Wellcome Trust Sanger Institute and reported for each cancer gene in the COSMIC database (Bamford et al. (2004) Br J Cancer 91, 355-358) (v42 release). To calculate the frequencies of gene mutation depicted in Tables 1 and 3, all mutations described in the COSMIC database with available positional information at the amino acid level were included.
Eighty-one out of the 120 allele variants covered by our panel were validated, using three types of control samples (Table 3): (1) whenever possible, primary tumor samples that had been previously tested at the MGH Molecular Diagnostics Pathology Laboratory were used and shown to carry the mutations of interest; (2) for the majority of the assays, validation was performed using cancer cell lines harboring known mutations, which were identified using the Wellcome Trust Sanger Institute Cancer Cell Line Project database; and (3) synthetic oligonucleotides harboring the mutation of interest were designed to validate those allele variants for which an appropriate tumor sample or cancer cell line control were not identified (Table 9).
Genomic DNA was extracted from blood using the QIAamp Blood kit (QIAGEN Inc., Valencia, Calif.), or from FFPE primary tumor tissue and frozen cancer cell line pellets using the RecoverALL™ Total Nucleic Acid Isolation Kit (Applied Biosystems, Foster City, Calif.), according to the manufacturer's recommendations. To prepare the synthetic control samples, 1 to 40 pmol of custom-made oligonucleotides designed to include the mutation of interest, were added to 3 μl of PCR product obtained from amplification of 20 ng of male genomic DNA (Promega, Madison, Wis.) as indicated in Table 9, followed by Exo/SAP treatment and by the extension reaction. Each mutant sample was tested using the SNAPSHOT® genotyping panel containing the assay to be validated, and male genomic DNA (Promega, Madison, Wis.) was used as a wild-type control for each run.
For those allele-specific assays that could be validated using genomic DNA derived from primary tumor tissue or from cancer cell lines, a sensitivity assessment was also performed (
It is well established that cancer cells are prone to genetic instability, which can result in the gain or loss of genetic material. In addition, primary tumor specimens may contain normal (non-cancerous) cells. Due to this heterogeneity, the calculated amount of input mutant DNA material does not accurately reflect the relative amount of mutant vs. wt allele in each tested sample. Thus, the percentage of mutant allele in each sample was calculated by comparing the fluorescent peak heights of the mutant and wild-type alleles, according to the following: % mutation=[mutant allele peak height/(wild-type allele peak height+mutant allele peak height)]*100.
The sensitivity of each assay was established as the lowest % mutation for which the fluorescent peak height of the mutant allele is >3× background (the background for a specific mutant allele is defined as the height of the fluorescent peak corresponding to that allele, within its assigned bin in the wild type control genomic DNA sample). For a detailed explanation of the process involved in sensitivity assessment, please refer to
All of the mutations detected in a primary tumor sample were initially verified by an independent SNAPSHOT® reaction using the genotyping panel containing the assay in question. The cases of chronic myeloproliferative disease and a small number of colorectal adenocarcinomas had been previously sequenced for JAK2 exon 12 and for KRAS exon 2, respectively, as part of standard clinical testing. Once genotyping analysis was completed, the SNAPSHOT® results were confirmed to match the previous clinical findings. The additional mutations were evaluated using standard Sanger sequencing. In total, 90% of the mutations identified by SNAPSHOT® genotyping were independently confirmed (inability to independently verify the presence of mutation in 10% of the cases was due to unsuccessful Sanger sequencing data, as a result of limiting amounts of nucleic acid).
Mutational profiling of 250 primary tumor samples identified a total of 100 mutations that could be classified into 33 distinct mutation groups. Attempts to identify cases with normal matching tissue for each of these 33 independent mutation types, and perform a side-by-side comparison between tumor and normal tissue from the same individual, to test the specificity of the SNAPSHOT® assay were conducted for 25 out of the 33 mutation types (76%). In all cases, the somatic mutant allele was only detected in the tumor specimen and not in the matching normal tissue, which confirmed the specificity of the corresponding SNAPSHOT® assays.
Out of all primary tumors examined, 62 cases were genotyped as part of what has now become routine clinical testing (Table 4). Exon 19 of the EGFR gene is a hotspot for in-frame deletions, often found in lung cancer and that have been associated with response to EGFR TKI therapy (Lynch et al. (2004) N Engl J Med 350, 2129-2139; Mok et al. (2009) N Engl J Med 361, 947-957; Paez et al. (2004) Science 304, 1497-1500; Pao et al. (2004) Proc Natl Acad Sci USA 101, 13306-13311). Although the assay described herein tests for the two most common deletions in the EGFR intracellular domain, due to the therapeutic implications of this region, mutational profiling of clinical cases was complemented by a PCR-based sizing assay designed to capture all deletions (or insertions) in EGFR exon 19. For most cases (98%) there was concordance between the SNAPSHOT® results and the exon 19 sizing data, however, the second approach identified one additional deletion in EGFR which was not captured by SNAPSHOT® genotyping (Table 4).
While mutational analysis of EGFR and KRAS is already widely viewed as the modern standard of care, the present assays uncovered additional events that also influenced clinical decisions.
To further investigate sample heterogeneity within the primary tumors evaluated for clinical testing, all mutant cases were re-examined and the levels of mutant alleles identified by SNAPSHOT® genotyping were compared with the extent of stromal contamination in each original tumor specimen. As shown in Table 6, the extent of stromal contamination (column 2), and the levels of mutant alleles (column 3) are distinct for different tumor specimens, which is most likely reflective of an inability to accurately predict stromal contamination in a tridimensional tumor specimen, based on the histological evaluation of a single tumor section. In addition, some of these discrepancies may be due to tumor heterogeneity and the presence of activating mutations within variable subsets of tumor cell populations. Concerns with tumor heterogeneity underscore the importance of using highly sensitive mutation detection methods. This matter has been widely appreciated, particularly for mutations that confer resistance to targeted therapeutics where the detection of minor resistant clones, either in the primary tumor or during the course of treatment, is critical to predict response (Maheswaran et al. (2008) N Engl J Med 359, 366-377; Marchetti et al. (2009) Neoplasia 11, 1084-1092; Yung et al. (2009) Clin Cancer Res 15, 2076-2084). By contrast, the clinical implications of identifying low levels of drug-sensitizing mutations are currently unknown. To address this issue, the response of patients with low abundance EGFR sensitizing mutations to EGFR TKIs was examined. Within this small cohort, two patients (NA09-129 and NA09-184) were identified with low levels (<20%) of EGFR exon 19 deletions, both of whom achieved a clinical response to EGFR TKI therapy (Table 6). These results demonstrate that the use of targeted agents may be helpful even in cases where the sensitizing mutations are restricted to smaller clones of the tumor cell population. Importantly, these findings indicate that highly sensitive detection methods will be fundamental in identifying these patients.
1S.ctrl primers were designed as the coding strand (sense) for validation of reverse orientation assays.
2Amount of mutation control oligonucleotide used for SNaPshot assay validation.
It is to be understood that while the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.
This application is a continuation of U.S. application Ser. No. 12/799,415, filed on Apr. 23, 2010, which claims priority from U.S. Provisional Application Ser. No. 61/172,342, filed on Apr. 24, 2009, which are incorporated herein by reference in their entirety.
| Number | Date | Country | |
|---|---|---|---|
| 61172342 | Apr 2009 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 12799415 | Apr 2010 | US |
| Child | 14475155 | US |
