DNA MUTATION DETECTION EMPLOYING ENRICHMENT OF MUTANT POLYNUCLEOTIDE SEQUENCES AND MINIMALLY INVASIVE SAMPLING

Abstract
The invention relates to a method for enriching a target polynucleotide sequence containing a genetic variation said method comprising: (a) providing two primers targeted to said target polynucleotide sequence; (b) providing a target specific xenonucleic acid clamp oligomer specific for a wildtype polynucleotide sequence; (c) generating multiple amplicons using PCR under specific temperature cycling conditions; and (d) detecting said amplicons. We introduce a novel molecule, Xenonucleic Acid (XNA) for the NGS library preparation. XNA is able to selectively suppress amplification of DNA with wild type alleles and amplify DNA containing mutant alleles. Mutants with low allelic frequency will be easily detectable without deep sequencing after enrichment by adding XNA in multiplex PCR. The 17 actionable mutants related to lung or colorectal cancer diseases at different variant allelic frequency (VAF)% were investigated. Clinical sensitivity is significantly improved with XNA in various types of samples.
Description
FIELD OF THE INVENTION

The present invention relates to DNA mutation detection. The invention further relates to enrichment of mutant polynucleotide sequences. The present invention further relates to minimally invasive sampling and analysis of mutations in clinical samples.


The instant invention also relates to a method for determining whether a target polynucleotide sequence contained in a nucleic acid sample has nucleotide variation(s) in a selected region thereof, the steps of which involve the use of a pair of primers that allows the formation of a PCR product having a sequence covering that of the selected region of the target polynucleotide sequence via a PCR process, and a xenonucleic acid (XNA) that acts as a PCR clamp as well as a sensor probe. This invention also relates to a kit for use in determining the presence of nucleotide variation(s) in the target polynucleotide sequence, which comprises the pair of primers and the XNA.


The present embodiments relate to precision molecular diagnostics, and in particular, to compositions in detecting sequence variants, such as SNPs, insertions deletions, and altered methylation patterns, from samples. The embodiments disclosed herein can be used to detect (and quantify) sequence variants present in samples that include an excess of wild-type sequences.


BACKGROUND OF THE INVENTION

Polymerase chain reaction (PCR) is a widely used technique for the detection of pathogens. The technique uses a DNA polymerase used to amplify a piece of DNA by in vitro enzymatic replication. The PCR process generates DNA that is used as a template for replication. This results in a chain reaction that exponentially amplifies the DNA template.


Technologies for genomic detection most commonly use DNA probes to hybridize to target sequences. To achieve required sensitivity, the use of PCR to amplify target sequences has remained standard practice in many labs. While PCR has been the principle method to identify genes associated with disease states, the method has remained confined to use within a laboratory environment. Most current diagnostic applications that can be used outside of the laboratory are based on antibody recognition of protein targets and use ELISA-based technologies to signal the presence of a disease. These methods are fast and fairly robust, but they can lack the specificity associated with nucleic acid detection.


With the advent of molecular diagnostics and the discovery of numerous nucleic acid biomarkers useful in the diagnosis and treatment of conditions and diseases, detection of nucleic acid sequences, and sequence variants, mutations and polymorphisms has become increasingly important. In many instances, it is desirable to detect sequence variants or mutations (which may in some instances, differ by one a single nucleotide) present in low copy numbers against a high background of wild-type sequences. For example, as more and more somatic mutations are shown to be biomarkers for cancer prognosis and prediction of therapeutic efficacy, the need for efficient and effective methods to detect rare mutations in a sample is becoming more and more critical. In the case in which one or more allelic variants is/are present in low copy number compared to wild-type sequences, the presence of excess wild-type target sequence creates challenges to the detection of the less abundant variant target sequence. Nucleic acid amplification/detection reactions almost always are performed using limiting amounts of reagents. A large excess of wild-type target sequences, thus competes for and consumes limiting reagents. As a result amplification and/or detection of rare mutant or variant alleles under these conditions is substantially suppressed, and the methods may not be sensitive enough to detect the rare variants or mutants. Various methods to overcome this problem have been attempted. These methods are not ideal, however, because they either require the use of a unique primer for each allele, or the performance of an intricate melt-curve analysis. Both of these shortcomings limit the ability and feasibility of multiplex detection of multiple variant alleles from a single sample.





BRIEF DESCRIPTION OF THE FIGURES


FIG. 1 illustrates the mechanism of the XNA clamping process.



FIG. 2 shows the differential melting temperature (Tm) between the XNA clamp bound to mutant templates vs wild type templates.



FIG. 3 show specific hydrolysis probe having a different fluorophore (and quencher) selected from the available fluorophores for multiplex applications.



FIG. 4 is a representative fluorophore spectral data and quencher selection guide.



FIG. 5 shows a specific locus specific hydrolysis probe assay.



FIG. 6 is a schematic illustrating how circulating tumor cells (CTC's) and cell-free DNA (cfDNA) derived from tumor cells are present in the peripheral blood of cancer patients.



FIG. 7A. illustrates a Xenonucleic Acid (XNA) structure.



FIG. 7B shows preferred Xenonucleic acids having oxy-aza, aza-aza and sulfa-aza (thio-aza) bonding for use in the present invention.



FIG. 7C illustrates the following: (i) the mechanism of XNA Molecular Clamp Technology, (ii) how XNA makes Low Frequency variant detection easy, and (iii) target enrichment for NGS analysis.



FIG. 8 describes the effects of XNA mix on Variant Allelic Frequency (VAF) using OPTISEQ™ Dual Cancer Panel.



FIG. 9 illustrates the effects of XNA mix on total coverage using OPTISEQ™ Dual Cancer Panel.



FIG. 10 shows the effects of XNA mix on variant number using OPTISEQ™ Dual Cancer Panel.



FIG. 11 features the effects of XNA mix on VAF enrichment and variant number using OPTISEQ™ Dual Cancer Panel.



FIGS. 12A to 12P describes the correlation of Enriched VAF and original VAF 2.00%) with corresponding reggression equations.



FIG. 13 shows experimental and data analysis workflows for study of XNA effects on enrichment of variant alleles.



FIGS. 14A to 14Q shows the correlation of enriched variants allelic frequency (Enriched VAF) and original variant allelic frequency (more than 2.00%) (Original VAF) with corresponding regression equations.





SUMMARY OF THE INVENTION

Detection of rare sequence variants in biological samples presents numerous challenges. The methods and kits disclosed herein provide for improved, efficient means to detect rare mutations within a high background of wild-type allelic sequences using real-time amplification methods.


The instant invention provides a method for enriching a target polynucleotide sequence containing a genetic variation said method comprising: (a) providing two primers targeted to said target polynucleotide sequence; (b) providing a target specific xenonucleic acid clamp oligomer specific for a wildtype polynucleotide sequence; (c) generating multiple amplicons using PCR under specific temperature cycling conditions; and (d) detecting said amplicons.


The invention further provides a method for enriching a target polynucleotide sequence containing a genetic variation, said method comprising: (a) providing a biological sample; (b) isolating DNA from said biological sample; said DNA including said target polynucleotide sequence containing a genetic variation; (c) providing two primer probes targeted to said target polynucleotide sequence said primer probes allowing formation of a PCR process product; (d) providing a target specific xenonucleic acid clamp oligomer probe specific for a wildtype polynucleotide sequence; wherein said target specific xenonucleic acid clamp has oxy-aza and aza-aza moieties so that during the qPCR process only mutant templates are amplified; (e) admixing the primer probes and the xenonucleic clamping probe with the target nucleic acid sample; (f) performing a PCR amplification process in a reaction solution under hybridization conditions thereby generating multiple amplicons; and (g) detecting said amplicons.


The invention also relates to a method for enriching multiple target polynucleotide sequences containing a genetic variation said method comprising: (a) providing a library of amplifying primers targeted to said multiple target polynucleotide sequence; (b) providing a library of target specific xenonucleic acid clamp oligomer specific for multiple wildtype polynucleotide sequences; (c) generating multiple amplicons using PCR under specific temperature cycling conditions; and (d) detecting said amplicons.


The invention further relates to a method for conducting a minimally invasive biopsy in a mammalian subject suspected of a having a neoplastic disease, said method comprising: (a) sampling of target polynucleotides derived from said mammalian subject; (b) providing a library of amplifying primers targeted to said multiple target poly-nucleotide sequence; (c) providing a library of target specific xenonucleic acid clamp oligomer specific for multiple wildtype polynucleotide sequences; (d) generating multiple amplicons using PCR under specific temperature cycling conditions; and (e) detecting said amplicons.


The invention is also directed to means and methodology for the rapid isolation of genetic material from biological fluids and the sensitive detection of somatic and germ-line mutations present in circulating cells and cell-free genetic material obtained from said biological fluids using gene amplification and xeno-nucleic acid (XNA) clamping.


This invention provides a method for determining whether a target polynucleotide sequence contained in a nucleic acid sample has nucleotide variation(s) in a selected region thereof, comprising the steps of: providing a pair of a first primer and a second primer which allows the formation of a PCR product having a sequence covering that of the selected region of the target polynucleotide sequence via a PCR process, the first primer having a sequence identical to that of a first region located upstream of the selected region of the target polynucleotide sequence, the second primer having a sequence based on that of a second region located downstream of the selected region of the target polynucleotide sequence, wherein the 5′-end of the sequence of the first region is spaced apart from the 5′-end of the sequence of the selected region by 30 nucleotides or more;


providing a detectable xenonucleic acid probe having a sequence that complements fully the sequence of the selected region of the target polynucleotide sequence having no nucleotide variation(s) therein, such that hybridization of the detectable xenonucleic acid probe to the selected region of the target polynucleotide sequence having no nucleotide variation(s) results in the formation of a duplex having a melting temperature;


determining the melting temperature of the duplex;


admixing the detectable xenonucleic acid probe and the pair of the first primer and the second primer with the nucleic acid sample to form a mixture;


subjecting the mixture to a PCR process including an extension reaction set to run at a temperature lower than the melting temperature of the duplex by 5 to 20° C., such that a mixture of PCR products is obtained; and subjecting the mixture of PCR products thus-obtained to a melting analysis to determine melting temperatures of the PCR products, wherein the presence of at least one melting temperature lower than the melting temperature of the duplex is indicative of the nucleotide variation(s) in the selected region of the target polynucleotide sequence contained in the nucleic acid sample.


The invention also provides a kit for determining whether a target polynucleotide sequence contained in a nucleic acid sample has nucleotide variation(s) in a selected region thereof, comprising: a detectable xenonucleic acid probe having a sequence that complements fully the sequence of the selected region of the target polynucleotide sequence having no nucleotide variation(s) therein, such that hybridization of the detectable xenonucleic acid probe to the selected region of the target polynucleotide sequence having no nucleotide variation(s) results in the formation of a duplex having a melting temperature;


a pair of a first primer and a second primer which allows the formation of a PCR product having a sequence covering that of the selected region of the target polynucleotide sequence via a PCR process, the first primer having a sequence identical to that of a first region located upstream of the selected region of the target polynucleotide sequence, the second primer having a sequence based on that of a second region located downstream of the selected region of the target polynucleotide sequence, wherein the 5′-end of the sequence of the first region is spaced apart from the 5′-end of the sequence of the selected region by 30 nucleotides or more; and an instruction sheet providing guidance for a user to use the detectable xenonucleic acid probe and the pair of the first primer and the second primer in a method as described above.


The identification of genetic variants with low variant frequency using next-generation sequencing method is confounded by the complexity of human genome sequence and by bias that arise during library preparation, sequencing and analysis. The present invention also provides a novel molecule, Xenonucleic Acids (XNA) for the NGS library preparation. XNA is able to selectively suppress amplification of DNA with wild type alleles and amplify DNA containing mutant alleles. Mutants with low allelic frequency will be easily detectable without deep sequencing after enrichment by adding XNA in multiplex PCR. The 17 actionable mutants related to lung or colorectal cancer diseases at different VAF % have been studied in great detail in the present invention. Upon XNA blocking of wild type alleles, detectable enriched variant allelic frequency (VAF) can be increased by ˜32 fold from 10 ng of gDNA samples containing mutants as low as 0.10%. Analytical sensitivity of Limit of Detection (LoD) is about 0.10% VAF. These 17 actionable mutants were tested and verified by using FFPE and cfDNA of lung or colon cancer patient samples. Clinical sensitivity for FFPE sample is about 100% for lung cancer and colorectal cancer samples respectively, comparing to without XNA NGS about 85.7% for lung cancer and 70% for colon cancer. For cfDNA sample its clinical sensitivity is about 100% for lung and early colon cancer, but without XNA NGS is about 70% for lung cancer and undetectable for early colon cancer. This invention provides a simple, accurate, higher sensitive and lower cost alternative compared with conventional NGS with deep sequencing.


DETAILED DESCRIPTION OF THE INVENTION

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not intended to limit the scope of the current teachings. In this application, the use of the singular includes the plural unless specifically stated otherwise. Also, the use of “comprise”, “contain”, and “include”, or modifications of those root words, for example but not limited to, “comprises”, “contained”, and “including”, are not intended to be limiting. Use of “or” means “and/or” unless stated otherwise. The term “and/or” means that the terms before and after can be taken together or separately. For illustration purposes, but not as a limitation, “X and/or Y” can mean “X” or “Y” or “X and Y”. Whenever a range of values is provided herein, the range is meant to include the starting value and the ending value and any value or value range there between unless otherwise specifically stated. For example, “from 0.2 to 0.5” means 0.2, 0.3, 0.4, 0.5; ranges there between such as 0.2-0.3, 0.3-0.4, 0.2-0.4; increments there between such as 0.25, 0.35, 0.225, 0.335, 0.49; increment ranges there between such as 0.26-0.39; and the like.


In a first embodiment, the present invention relates to compositions and methods for the selective enrichment of low-abundance polynucleotides in a sample. These methods use xeno-nucleic acid (XNA) nucleobase oligomers to selectively block DNA polymerase activity on high abundance wild-type DNA templates, thereby resulting in enrichment of less abundant mutated DNA templates present in a biological sample during a polymerase chain reaction (PCR). The methodology of the present invention can be used to improve DNA sequencing (Sanger sequencing and Pyrosequencing) and also enhance cDNA library preparation for next generation DNA sequencing (NGS).


Utilizing xeno-nucleic acid (XNA) clamping probes in the PCR mediated amplification of DNA templates, only target genetic material that has a variation, e.g. single nucleotide polymorphism (SNP), gene deletion or insertion and/or translocation or truncation is amplified in the oligonucleotide primer directed polymerase chain reaction (qPCR).


The XNA probe clamping sequences are designed to bind specifically by Watson-Crick base pairing to abundant wild-type sequences in the DNA templates derived from the biological sample of interest. The presence of the XNA probes in the PCR primer mix employed for the target amplification reaction causes inhibition of the polymerase mediated amplification of wild-type templates but does not impede the amplification of mutant template sequences.


The mechanism of the XNA clamping process is depicted in FIG. 1. As shown in FIG. 1, the modified DNA oligo probe binds or clamps to wild type DNA and blocks further wild type amplification. This probe or XNA “clamp” does not bind to mutated DNA, allowing it to be amplified and detected.


The suppression of wild-type (wt) template amplification and amplification of only mutant templates is achieved because there is a differential melting temperature (Tm) between the XNA clamp bound to mutant templates vs wild type templates:






Tm(XNA mutant template)<<Tm(XNA wt template)


The Tm differential is as much as 15-20° C. for the XNA clamp probes. So that during the PCR process only mutant templates are amplified.


The methods disclosed herein can be used to analyze nucleic acids of samples. The term “sample” as described herein can include bodily fluids (including, but not limited to, blood, urine, feces, serum, lymph, saliva, anal and vaginal secretions, perspiration, peritoneal fluid, pleural fluid, effusions, ascites, and purulent secretions, lavage fluids, drained fluids, brush cytology specimens, biopsy tissue (e.g., tumor samples), explanted medical devices, infected catheters, pus, biofilms and semen) of virtually any organism, with mammalian samples, particularly human samples.


Amplification primers useful in the embodiments disclosed herein are preferably between 10 and 45 nucleotides in length. For example, the primers can be at least 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, or more nucleotides in length. Primers can be provided in any suitable form, included bound to a solid support, liquid, and lyophilized, for example. In some embodiments, the primers and/or probes include oligonucleotides that hybridize to a reference nucleic acid sequence over the entire length of the oligonucleotide sequence. Such sequences can be referred to as “fully complementary” with respect to each other. Where an oligonucleotide is referred to as “substantially complementary” with respect to a nucleic acid sequence herein, the two sequences can be fully complementary, or they may form mismatches upon hybridization, but retain the ability to hybridize under stringent conditions or standard PCR conditions as discussed below. As used herein, the term “standard PCR conditions” include, for example, any of the PCR conditions disclosed herein, or known in the art, as described in, for example, PCR 1: A Practical Approach, M. J. McPherson, P. Quirke, and G. R. Taylor, Ed., (c) 2001, Oxford University Press, Oxford, England, and PCR Protocols: Current Methods and Applications, B. White, Ed., (c) 1993, Humana Press, Totowa, N.J. The amplification primers can be substantially complementary to their annealing region, comprising the specific variant target sequence(s) or the wild type target sequence(s). Accordingly, substantially complementary sequences can refer to sequences ranging in percent identity from 100, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89, 85, 80, 75 or less, or any number in between, compared to the reference sequence. Conditions for enhancing the stringency of amplification reactions and suitable in the embodiments disclosed herein, are well-known to those in the art. A discussion of PCR conditions, and stringency of PCR, can be found, for example in Roux, K. “Optimization and Troubleshooting in PCR,” in Pcr Primer: A Laboratory Manual, Diffenbach, Ed. © 1995, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.; and Datta, et al. (2003) Nucl. Acids Res. 31(19):5590-5597.


Provided herein are methods useful in the detection of sequence variants, i.e., insertions, deletions, nonsense mutations, missense mutations, and the like. In the methods for detecting allelic variants or variant target sequences disclosed herein, the sample, which comprises the nucleic acids to be analyzed, are contacted with an amplification primer pair, i.e., comprising a forward primer and a reverse primer that flank the target sequence or target region containing a sequence of interest {e.g., a wild-type, mutant, or variant allele sequence) to be analyzed. By “flanking” the target sequence, it is understood that the variant or wild-type allelic sequence is located between the forward and reverse primers, and that the binding site of neither the forward nor reverse primer comprises the variant or wild-type allelic sequence to be assessed. For example, in some embodiments, the variant or wild-type allelic sequence to be assessed is removed from or positioned away from the 3′ end of either oligonucleotide by 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, or more, e.g., 100 or more, 200 or more, 300 or more, 400 or more, 500 or more, etc., nucleotides. Amplification primers that flank, but that do not overlap with, the variant target sequence or the wild-type target sequence are thus not “allele-specific” amplification primers, and are capable of amplification of various different alleles or variants of a sequence of interest. Thus, in some embodiments, the amplification primers are configured to amplify various mutant or variant alleles and wild type alleles non-preferentially. As discussed in further detail below, the addition of XNA to an amplification reaction suppresses the amplification of wild-type target sequences and enables preferential amplification of non-wild-type, e.g., variant, mutant or rare variant alleles. FIG. 1 is a depictions of exemplary method according to the embodiments disclosed herein for the detection of sequence variants. As shown in FIG. 1, amplification primers (i.e., forward primer 1 and reverse primer 2) flank the wild type and mutant allele sequences of interest, and comprise sequences common to both wild-type and mutant or variant allele sequences. Accordingly, as shown in FIG. 1, in contrast to methods that utilize allele-specific amplification primers to achieve preferential amplification of rare sequences, the present methods advantageously enable the simultaneous amplification of multiple variant sequences, using a single amplification primer pair.


In a second embodiment, the invention relates to compositions and methods for the detection of genetic variations (mutations) in DNA templates derived from biological samples with xeno-nucleic acid clamping probes. The first method employs multi-color fluorescence detection using locus specific fluorescent hybridization probes (Hyb Probes), hydrolysis (TaqMan or ZEN) probes or molecular beacons. The second method employs mutant specific amplicon capture probes immobilized on multiple bar-coded capture beads.


Current XNA clamping qPCR methodologies utilize a single tube-single mutation detection format it is preferable to detect multiple genetic variations in a single tube thus reducing the complexity of the assay and the amount of template DNA required for analysis.


This second embodiment of the invention is directed to the use of locus specific fluorescent probes designed to detect the genetic variant (mutant) amplicons generated during the XNA clamping PCR reaction. This second embodiment discloses locus specific probes that bind to mutant specific amplicons at a region upstream or downstream from the site of the mutation to be detected. Furthermore, the second embodiment discloses the use of multiplexed XNA clamping qPCR reactions that are able to detect multiple mutations (up to a maximum of 6) in one PCR reaction tube using fluorescence detection methodology.


In a third embodiment of the invention, there is provided a method the rapid isolation of genetic material present in circulating cells and also cell-free genetic material from biological fluids and the determination of genetic variations in those cells and biological fluids. Such biological fluids include: blood, serum, plasma, saliva, mucus, urine, sputum, semen or other biological secretions. In this embodiment, the invention also provides the detection of somatic and germ-line mutations in the genetic material derived from these biological fluids utilizing gene amplification and xeno-nucleic acid clamping.


Circulating tumor cells (CTC's) and cell-free DNA (cfDNA) derived from tumor cells are present in the peripheral blood of cancer patients (See FIG. 6). Tumor derived DNA can also be found in the urine and even the saliva of cancer patients.


In general circulating free DNA is smaller in size than DNA derived directly from a surgical biopsy or FFPE sample. This embodiment also describes a novel sample treatment procedure that utilizes a novel lysis reagent called QZol™. QZol™ sample lysis is a direct one tube procedure and an aliquot of the lysate is used directly in molecular genetic and cytogenetic analysis procedures such as PCR, RTPCR, FISH, Next Generation Sequencing (NGS) and branched DNA (bDNA) assays. The QZol™ procedure eliminates the tedious multistep preanalytical processing that is currently used in Molecular Pathology and Cytogenetic analysis.


The lysis reagent is a 50% solution (A) containing chaotropic salts and detergent (nonionic, anionic, cationic or zwitterionic) and a 50% solution (B) containing neutralizing reagents and stabilizers.


This invention also concerns to the specific amplification of genetic variant templates from the isolated genetic material described above. Only target genetic material that has a variation, e.g. single nucleotide polymorphism (SNP), gene deletion or insertion and/or translocation or truncation is amplified in a quantitative primer directed polymerase chain reaction (qPCR). This is achieved utilising xenonucleic acid (XNA) probe clamping sequences that have been designed to bind specifically by Watson-Crick base pairing to wild-type sequences in the sample. The presence of the XNA probes in the qPCR primer mix employed for the target amplification reaction causes inhibition of the polymerase mediated amplification of wild-type templates but does not impede the amplification of mutant template sequences.


The mechanism of the XNA clamping process is depicted in FIG. 1.


The suppression of wild-type (wt) template amplification and amplification of only mutant templates is achieved because there is a differential melting temperature (Tm) between the XNA clamp bound to mutant templates vs wt templates:






Tm(XNA mutant template)<<Tm(XNA wt template)


The Tm differential is as much as 15-20° C. for the XNA clamp probes. So that during the qPCR process only mutant templates are amplified.


The methods disclosed herein can be used in the detection of numerous allelic variants, including nonsense mutations, missense mutations, insertions, deletions, and the like. Owing to the advantageous sensitivity and specificity of detection afforded by the methods disclosed herein, the methods can detect the presence of a rare allelic variant within a sample, amongst a high wild-type background. Accordingly, although the skilled artisan will appreciate that the methods disclosed herein can be used in a variety of settings to detect, e.g., germline mutations, the methods are particularly well-suited for use in the detection of somatic mutations, such as mutations present in tumors. Non-limiting examples of rare, somatic mutations useful in the diagnosis, prognosis, and treatment of various tumors include, for example, mutations in ABL, AKT1, AKT2, ALK, APC, ATM, BRAF, CBL, CDH1, CDK 2A, CEBPA, CRLF2, CSF1R, CTNNB1, EGFR, ERBB2, EZH2, FBXW7, FGFR, FGFR2, FGFR3, FLT3, FOXL2, GATA1, GATA2, GNAQ, GNAS, HNF1A, HRAS, IDH1, IDH3, JAK2, KIT, KRAS, MEK1, MET, MPL, NF2, NOTCH 1, NOTCH2, NPM, NRAS, PC A3, PDGFRA, PIK3CA, PIK3R1, PIK3R5, PTCH1, PTEN, PTPN1 1, RBI, RET, RUNX1, SMAD4, SMARCB, SMO, STK11, TET2, P53, TSHR, VHL, WT1, and others. Exemplary mutant alleles associated with cancer useful in the embodiments disclosed herein include, but are not limited to those described in publications listed on the world wide web site for COSMIC (Catalogue Of Somatic Mutations In Cancer).


Next-generation sequencing (NGS) is widely used to detect sequence variations and an array of genetic markers for oncological diagnostic research and, in combination with bioinformatics, is increasingly used to analyze multiple biomarkers in a low-cost, time-effective manner1. However, one of the challenges in detecting cancer variants with standard NGS analysis is the low frequency of mutant alleles in cancer cells amongst a background of wild type alleles in healthy cells. The adequate resolution of low-frequency SNVs is essential both to improve treatment of cancer and to monitor minimal residue disease status during follow-up. However, typically NGS sensitivity is limited to variants at 0.1-1.0% mainly due to sequencing related background errors. In order to meet clinical standards and to distinguish true variants from sequencing errors, NGS has to be accurate and robust, several solutions have been described. For example, the application of proofreading enzymes (proofreading DNA-polymerase containing 3′-5′ exonuclease activity) significantly increased NGS sensitivity by reducing false-positive variant calls at respective genomic positions. And the use of complex barcoding strategies, which enable the separation of true single nucleotide variants (SNVs) from errors. Deep sequencing is another solution to achieve the detection of variant with low frequency, however, deep sequencing increases the systematic error rate arise from sequencing machine and leads to unreliable result2,3. In some cases, deep sequencing is still not able to achieve the detection of hotspots covered by low performance primer set amongst large primers pool, which makes deep sequencing a pricy and inefficient method. Detecting the variant with low frequency is still challenging for most of the researcher in this area. In order to reliably distinguish true variants from sequencing-related errors at mutant allele frequencies of <0.1% and to identify suitable markers for cancer disease prognostic detection, A new technology that it enables to detect the “needle” from the “haystack” is needed to face the challenge.


Xenonucleic Acid (XNA) molecular clamp is an innovative nucleic acid molecular oligomers (FIG. 1a) that hybridize by Watson-Crick base pairing to target DNA sequences, which are used during polymerase chain reaction (PCR) to selectively suppress amplification of DNA with wild type alleles and amplify DNA containing mutant alleles (FIG. 1b). Mutants with low allelic frequency will be easily detectable without deep sequencing after enrichment by adding XNA in PCR4,5,6 (FIG. 1b).


Herein, we introduce a highly sensitive OptiSeq™ Lung and Colorectal Cancer Dual Cancers Panel powered by the proprietary XNA technology to detect low frequency variants in human standard reference samples and lung or colorectal cancer patients' samples. This NGS diagnostic platform with XNA significantly improves the detection sensitivity of variants for diagnosis of cancer mutants even at ultra-low allele frequency.


Here we present results of XNAs mix enrichment effects on cell line genomic DNA samples with low variant allelic frequency, and lung and colorectal cancer patient samples, a benchmarking efforts aimed at enriching variant allelic frequency of samples with low frequency, and made low VAF samples detected by next generation sequencing method reliably and cost-efficiently, thus drawing conclusion confidently without sacrificing the quality of results. Meanwhile, regression models for 17 hotspots were constructed to get the relationship between enriched VAF and original VAF. In this way, original VAF value can be derived from enriched VAF by the corresponding equation, which provides an insight for clinical professionals to draw conclusion based on original VAF, particularly for variants with super low variant frequency, since typically NGS sensitivity is limited to variants at 0.1-1.0% mainly due to sequencing related background errors. Any variant allelic frequency below 1.0% will not be sufficient to draw reliable conclusion about the authenticity of mutations.


From the results of enrichment effects of XNAs mix on cell line genomic DNA samples, the mutant detection powered by the XNAs mix was dramatically boosted. 14 out of 17 hotspots were able to go down to the detection limit 0.10% with detected variant number more than 2. On samples originally with estimated 1.25% of mutants, in 14 of 17 hotspots, observed VAFs were more than 10% after XNA enrichment. This result suggested that XNA is able to enrich mutant alleles and make high confidence calls. The enrichment effects of 13 different XNAs varied based on the characteristics of each XNA. For XNA named EGFR G719, it shows a strong binding affinity towards the wild type and is able to enrich detected VAF up to 94.43% from 1.01%, which is 93.5 times more than the original VAF in the sample. However, for XNA like CTNNB1 S45, detected VAF after adding XNA was less than 1.0%, detected variant number was even less than 1 copy, which is not sufficient enough to draw the confident conclusion about the authenticity of mutant. It indicated that the binding affinity of XNA CTNNB1 S45 was weaker than that of EGFR 5719. It started to show detected variant on the condition of estimated original VAF 0.25% (Variant number was 2) with XNAs mix.


For some of the XNAs, they cover two loci at the same time. For example, NRAS A59 XNA covers two loci NRAS A59 and NRAS Q61, or NRAS G12 XNA covers two loci NRAS G12 and NRAS G13. Summary for covered hotspots by 13 XNAs was summarized in Table 11. Despite one XNA was used to block two loci, the blocking efficiency of XNA towards two loci was not directly related. For example, NRAS A59 XNA showed a good enrichment efficiency towards hotspot NRAS A59T, enriched VAF with XNA was 3.89 at original VAF 0.08, which is 48.6 times more than original VAF. While for hotspots NRAS Q61H, the enriched VAF was 0.16, which was only 3.2 folds than original VAF.


Enough sequencing coverage of each loci is necessary to achieve confident call of mutant, particularly for some mutants with super low frequency, in some rare cases, even pricy deep sequencing fails to detect them. From the results shown in Table 13-A and Table 13-B. The total sequencing coverage of samples with XNAs mix were less than those without XNAs mix. For example, average total coverage of estimated original VAF 0.10% with XNAs mix was 603, while that of same VAF without XNA WAS 2121. Despite the reduction of sequencing depth, enriched VAF for 14 out 17 hotspots were more than 1.00% to draw confident calls. While for same libraries without XNAs mix, only 1 out of 17 hotspots were more than 1.00%. Besides one important criterion “Enriched VAF”, actual detected variant number was of same importance as well. Enough variant number ensures the authenticity of mutant call. The average variant number with XNAs mix was 9.1 times of those without XNAs mix. All these results demonstrated XNAs effects on the enrichment of detected VAF, which is of great significance to get reliable call from sequencing machine, since typically NGS sensitivity is limited to variants at 0.1-1.0% mainly due to sequencing related background and PCR errors. Meanwhile, sufficient number of variants were got due to the blocking effects on wild type background noise.


From results of Table 14, we learnt that the higher the original VAF, the lower CV %. The reason that lower VAF leads to higher CV % might due to the sampling issue of the DNA input. Since the real copies of mutant with VAF 0.10% are only 3 copies, which made it hard for experimental operator to pick up exact 3 copies from the stock solution, this sampling issue made a butterfly effect and caused the big variance of variant numbers and VAF in library, thus leading to the high CV %. As the VAF increases up to 1.25%, copies number of mutant was 42 copies, this sampling issue got weakened and high CV % 17.7 was achieved. The trend found in Table 14 was similar to that in Table 14 and it can be explained by sampling issue as well. Since as the original VAF increased, the positive predictive values (PPV) increased and reached 100% when estimated original VAF was 1.25%.


Although regression equations deduced by modeling can help to get the original VAF from enriched VAF with XNAs mix, it only applies when deduced original VAF value falls within confidence interval range (up to VAF 15%). It might applies when out of confidence interval, however, additional data are required to verify this assumption. For example, Lung cancer FFPE sample ID 16A140, original VAF of mutation EGFR L858R was 34.31%, detected enriched VAF for this mutation was 83.76%. If we applied regression equation, calculated VAF was 134.05%, which is beyond 100% and greatly off the true value 83.76%. While for FFPE sample ID 16A011, original VAF of mutation EGFR L858R was 20.37%, despite off of confidence interval limit 12.4%, calculated enriched VAF was 97.81% which is approximately close to detected enriched 91.91%. we acknowledged that It would be better and more comprehensive of this study to get the full regression model from original VAF 0.00% to 100.00% for each hotspots, however, in this study, we only focus on the XNAs enrichment effects on mutations with super low or low variant frequency help detect existed low variant frequency mutations with more cost-efficient method. For original VAF more than 15.0%, it can be detected confidently with normal NGS method.


In summary, XNA molecular clamp technology in combination with NGS have a great potential for cancer molecular diagnosis of cancer mutations in ultra-low allele frequency. OptiSeq™ Lung and Colorectal Cancer Mini Panel powered by XNAs is able to report mutants from 10 ng of input gDNA with allele frequency as low as 0.10% with confident calls for 14 out of 17 hotspots. The relationship between enriched VAF and original VAF were derived using regression model for 17 hotspots. Some of regression equations were verified using clinical patient samples and proved reliable to deduce original VAF from enriched VAF. Significant progress has been made in characterizing and optimizing the use of XNA in conjunction with OptiSeq™ oncology NGS panel, which provides a promising solution to detect mutants with low frequency with improvement sensitivity and confidence. Clinical sensitivity for FFPE is about 100% for lung cancer (14/14 samples) and colorectal cancer samples (10/10 samples), comparing to normal NGS about 85.7% (12/14 lung sample) and 70% (7/10) for colon cancer. For cfDNA its clinical sensitivity is about 100% for lung (10/10) and colon cancer (2/2), but normal NGS is about 70% for lung (3/10) and 0% for colon cancer (0/2 sample)


EXAMPLES
Example 1

The kit described in great detail in this Example is a KRAS mutation detection kit. However, the same type of kit may be assembled to detect mutations in NRAS, EGFR, BRAF, PIK3CA, JAK2, as well as other genes of importance in precision molecular diagnostics.


QCLAMP™ Technology for Mutation Detection

The QCLAMP™ KRAS Mutation Detection Kit is based on xenonucleic acid (XNA) mediated PCR clamping technology. XNA is a synthetic DNA analog in which the phosphodiester backbone has been replaced by a repeat formed by units of (2-aminoethyl)-glycine. XNAs hybridize tightly to complementary DNA target sequences only if the sequence is a complete match. Binding of XNA to its target sequence blocks strand elongation by DNA polymerase. When there is a mutation in the target site, and therefore a mismatch, the XNA:DNA duplex is unstable, allowing strand elongation by DNA polymerase. Addition of an XNA, whose sequence with a complete match to wild-type DNA, to a PCR reaction, blocks amplification of wild-type DNA allowing selective amplification of mutant DNA. XNA oligomers are not recognized by DNA polymerases and cannot be utilized as primers in subsequent real-time PCR reactions.


DNA Isolation

Human genomic DNA must be extracted from tissue or blood, or fixed paraffin-embedded tissue prior to use. Several methods exist for DNA isolation. For consistency, we recommend using a commercial kit, such as Qiagen DNA extraction kit (QIAamp DNA FFPE Tissue Kit, cat No. 56404, for paraffin embedded specimens; DNeasy Blood & Tissue kit, cat. No. 69504 or 69506, for tissue and blood specimens). Follow the genomic DNA isolation procedure according to manufacturer's protocol. Sufficient amounts of DNA can be isolated from FFPE blocks or fresh frozen sections (approx. 2-10 μg).


This QCLAMP™ assay requires a total of 30-60 ng of DNA per sample (5-10 ng/reaction). After DNA isolation, measure the concentration using spectrophotometric analysis (i.e. Nanodrop or UV spectrophotometer) and dilute to it to 1.25-2.5 ng/μ1. Make sure A260/A230 value is greater than 2.0 and A260/A280 value between 1.8 and 2.0.


Preparation of Reagents

Each kit contains enough material to run 3 sets (10-sample test kit) or 6 sets (30-sample test kit) of Clamping Controls, Positive Controls and Non-Template Controls. Thaw all Primers, XNAs, Positive Control, WT Clamping Control, water and 2×PCR Mastermix provided. Thaw all reaction mixes at room temperature for a minimum of 1 hour. Vortex all components except the PCR Master Mix the reaction mixes for 5 sec and perform a quick spin. The PCR Master Mix should be mixed gently by inverting the tube a few times. Do not leave kit components at room temperature for more than 4 hours. After thawing, keep materials on ice at all times. The PCR reactions are set up in a total volume of 20 μl/reaction.


Table 1 shows the component volumes for each 20ul reaction.









TABLE 1







QCLAMP ™ Assay Components and Reaction Volume










Components
Volume/Reaction







2X PCR Master mix
10 μl 



Primer Mix
4 μl



XNA
2 μl



DNA sample or Controls
4 μl



Total volume
20 μl 










For accuracy, 2×PCR Master mix, primers and XNA should be pre-mixed into assay mixes as described in Table 2 below.


Preparation of Assay Mixes

IMPORTANT: Assay mixes should be prepared just prior to use. Do not store assay mixes. Prepare and keep assay mixes on ice, until ready for per. Label 7 micro centrifuge tubes (not provided) according to each corresponding reaction mix shown in Table 2.









TABLE 2







Preparation of Assay Mixes











Volume of
Volume of
Volume of XNA



2X PCR
Primer
(†use water for



Master Mix
Mix
ext control)














Ext Control Mix
10 μl × (*n + 1)
4 μl × (*n + 1)
2 μl × (*n + 1)


G12 Mix
10 μl × (*n + 1)
4 μl × (*n + 1)
2 μl × (*n + 1)


G13 Mix
10 μl × (*n + 1)
4 μl × (*n + 1)
2 μl × (*n + 1)


A59 Mix
10 μl × (*n + 1)
4 μl × (*n + 1)
2 μl × (*n + 1)


Q61 Mix
10 μl × (*n + 1)
4 μl × (*n + 1)
2 μl × (*n + 1)


K117 Mix
10 μl × (*n + 1)
4 μl × (*n + 1)
2 μl × (*n + 1)


A146 Mix
10 μl × (*n + 1)
4 μl × (*n + 1)
2 μl × (*n + 1)





*n = number of reactions (DNA samples plus 3 controls). Prepare enough for 1 extra sample (n + 1) to allow for sufficient overage for the PCR set.


†Use 2 ul of water provided in the kit as the Ext Control Mix does not require XNA. For accuracy, do not pipette less than 10 ul of the XNA.






Prepare sufficient working assay mixes for the DNA samples, one KRAS Mixed Positive Control, one Nuclease-Free Water for no template control, and one WT Clamping Control, according to the volumes in Table 2. Include reagents for 1 extra sample to allow sufficient overage for the PCR set up. The master mixes contain all of the components needed for PCR except the sample.


Each sample requires one reaction for each mutation site detected by the kit and an external control. The External Control uses Exon 5 primers to determine if an appropriate level of amplifiable DNA is present in the sample, and ensures that that the supplied primers and polymerase are working properly on the sample. The KRAS Codon-Specific kit requires a total of 7 reactions for each sample.


A set of clamping controls must be run with each of the 7 reaction mixes, every time the assay is run. Clamping Controls use wild-type DNA as the template. Wild-type DNA should have no mutations, therefore the XNA probes will bind strongly, blocking the polymerase from making amplicons. However, the External Control Mix with the Clamping Control should make amplicons efficiently, providing another way to monitor performance of the primers, polymerase, and sample.


A set of positive controls must also be run with each of the 7 reaction mixes, every time the assay is run. The Positive Control contains one mutant template for each reaction mix. Positive controls contain mutations; therefore XNA probes will not bind, allowing amplification of the mutant template. Positive controls must show the appropriate values for the reaction to be valid.


A set of no template control (tube NTC) is run with each of the 7 reaction mixes every time the assay is run. Nuclease-Free Water is used in the place of template. The NTC serves as a negative control and assesses potential contamination during assay set-up.


Further quantities of KRAS Wild-Type Genomic Reference DNA Control, and Positive Control mixes can be purchased as a separate item, if desired.


Suggested Run Layout (96-Well Plate, Tube Strips, or Tubes)

Gently vortex the assay mixes for 5 sec and do a quick spin. Add 16 μl of the appropriate assay mix to the plate or tubes. Add 4 μl of template. Prepare and keep on ice until ready for PCR.


In the case of 96-well plates, the exact plate layout can be set to the user's preference. However, take care to remember which wells are for which reaction mixes, to ensure that all potential detected mutations and controls are processed properly. Table 3 is a suggested plate set-up for a single experiment analyzing 3 unknown samples.









TABLE 3







Suggested Plate Layout














1
2
3
4
5
6

















A
NTC
PC
CC
S1
S2
S3



Ext Ctrl Mix
Ext Ctrl Mix
Ext Ctrl Mix
Ext Ctrl Mix
Ext Ctrl Mix
Ext Ctrl Mix


B
NTC
PC
CC
S1
S2
S3



G12 Mix
G12 Mix
G12 Mix
G12 Mix
G12 Mix
G12 Mix


C
NTC
PC
CC
S1
S2
S3



G13 Mix
G13 Mix
G13 Mix
G13 Mix
G13 Mix
G13 Mix


D
NTC
PC
CC
S1
S2
S3



A59 Mix
A59 Mix
A59 Mix
A59 Mix
A59 Mix
A59 Mix


E
NTC
PC
CC
S1
S2
S3



Q61 Mix
Q61 Mix
Q61 Mix
Q61 Mix
Q61 Mix
Q61 Mix


F
NTC
PC
CC
S1
S2
S3



K117 Mix
K117 Mix
K117 Mix
K117 Mix
K117 Mix
K117 Mix


G
NTC
PC
CC
S1
S2
S3



A146 Mix
A146 Mix
A146 Mix
A146 Mix
A146 Mix
A146 Mix





PC: Positive Control,


NTC: No Template Control (water),


CC: Clamping Control (Wild-type DNA),


S1-3: Samples 1-3.


NOTE:


For setup on the Rotor-Gene Q Platforms, the layout must be changed such that the first well contains Positive Control.






When all reagents have been loaded, tightly close the PCR tubes or seal the 96-well plate to prevent evaporation. Spin at 2000 rpm for 1 minute to collect all the reagents. Place in the real-time PCR instrument immediately or store on ice until the instrument is ready.


Instrument Set-Up
Roche LightCycler 96 or RocheLightCycler 480

1. Select New empty experiment >create


2. In the Run Editor>Measurement, choose SYBR Green 1 (470/514) channel on (LC96), SYBR Green 1/HRM Dye on (LC480)


3. Set up run profile using parameters in Table 7. Ramp rates for the LC 96 and LC480 should match settings below.


4. During the analysis set threshold to Auto.









TABLE 4







Roche Light Cycler, LC96 and LC480 Parameters














Temperature
Time

Ramp

Acquisition


Step
(° C.)
(Seconds)
Cycles
Rate
Mode
Mode
















PreIncubation
95
300
1
4.4

None


Denaturation
95
20
X40
2.2
Standard
None


XNA
70
40

2.2

None


Annealing


Primer
64
30

2.2

None


Annealing


Extension
72
30

1.0

Single


Melting
95
10
1
4.4

None



65
60

2.2

None



97
1

0.20

Continuous








(5 readings/° C.)


Cooling
37
30
1
2.2

None





*An HRM curve or melt analysis should be run at the end of the PCR reaction. This helps to verify the PCR amplification results and with troubleshooting.






Applied Biosystems Platforms
1. Select File>New Experiment

2. Enter an experiment name and select 7500 (96 wells) or as appropriate


3. Select Quantitation—Standard Curve
4. Select SYBR Green Reagents

5. Select Standard Ramp Rate if available


6. Click on Plate Setup in the left navigation panel 7. Select the Assign Targets and Samples tab and assign samples to the wells


8. Select NONE for the Passive Reference Dye

9. Click on Run Method on the left panel, set reaction volume to 20ul


10. Setup the cycling parameters as shown in the table below


11. Add Melt Curve at the end of the Cycling Stage. Use continuous and leave default setting for data collection


12. During the analysis set threshold to 0.5 (ABI 7900) and 5000 (ABI 7500).









TABLE 5







Applied Biosystems Platforms Cycling Parameters












Temperature
Time




Step
(° C.)
(Seconds)
Cycles
Data Collection














PreIncubation
95
300
1
OFF


Denaturation
95
20
X40
OFF


XNA Annealing
70
40

OFF


Primer Annealing
66
30

OFF


Extension
72
30

ON


Melt Curve
Default


Continuous









Rotor-Gene Q Platforms

In the instrument software version 2.1 and above


1. Select File>New, Select Three Step with Melt and click New


2. Select 72-Well Rotor, check the Locking Ring Attached box, click Next


3. Set Reaction volume to 20ul, click next


4. Set Temperature profile as shown in Table 6.


5. Channel Setup: Select Green Source 470 nm, Detector 510 nm, Gain 7

a. Click Gain Optimization


b. Set Temperature to 70 C


c. Perform Optimization before 1st acquisition


d. Click optimize acquiring


e. In the pop-up box enter


i. Target Sample Range 5FL up to 10FL


ii. Acceptable Gain Range −10 to 10


f. Click OK, Click Close, Click Next


6. Start-run

7. During the analysis set threshold to Auto.









TABLE 6





Rotor-Gene Q Platforms Cycling Parameters




















Hold

95° C.
5 minutes
X1 
Not Acquiring


Cycling
Timed Step
95° C.
20 seconds
X40
Not Acquiring



Timed Step
70° C.
40 seconds

Not Acquiring



Timed Step
64° C.
30 seconds

Not Acquiring



Timed Step
72° C.
40 seconds

Acquiring to Cycling A







on Green









Melt
Ramp from 65 to 95, rising by 1degree each
Acquire to melt A on



step
green



Wait for 90 sec of pre-melt conditioning on first



step



Wait for 5 seconds for each step afterwards



Gain Optimization



Check optimize gain before melt on all tubes



The gain giving the highest fluorescence less



than 95 will be selected.









Assessment of Real-Time PCR Results

For the analysis use Absolute Quantitation, automatic baseline. The threshold to be used with each instrument is listed above. Check threshold to ensure that the Threshold is within the exponential growth phase of the amplification plot. If not, the threshold maybe adjusted depending on the run.


The real-time PCR instrument generates a Cq value. Cq is the cycle threshold, the cycle number at which a signal is detected above background fluorescence. The lower the cycle number at which signal rises above background, the stronger the PCR reaction it represents


No Template Controls

Verify that there is no amplification in no-template controls for each of the reaction mixes. Cq should be undetermined. For some mixes a Cq of 36 or higher may be observed in the NTC. In such cases, check the melting curves obtained. If the melting curve indicates the presence of primer dimers, the reaction may be acceptable. SYBR green binds to primer dimers, resulting in a peak with a lower melting temperature, than the desired amplicon. In many cases formation of primer dimers can be avoided by setting up the PCR reactions on ice, until ready to load into the PCR instrument.


Analysis of Clamping and Positive Controls

The Cq values of the Positive Control (mixed mutant templates) should amplify in the presence of XNAs and yield Cq values given in Table 7.









TABLE 7







Acceptable Cq Ranges for Positive Controls









Positive Control



Acceptable Cq Range














Ext Control
20 ≤ Cq ≤ 26



G12 Mix
≤32



G13 Mix
≤32



A59 Mix
≤32



Q61 Mix
≤30



K117 Mix
≤34



A146 Mix
≤30







The Cq value of the Clamping Control (WT DNA) with the Ext Control Mix should be within 20 and 26.



In addition, the Cq of the Clamping Control with each of the mutation reaction mixes should be at least 3 Cq greater than the Cq of Positive Control with the same reaction mix. If these criteria are not met, the reaction has failed and the results are not valid.







PASS: Cq of Clamping Control with mutation reaction mix−Cq of Positive Control with same mutation reaction mix ≥3


FAIL: Cq of Clamping Control with mutation reaction mix−Cq of Positive Control with same mutation reaction mix ≤3


Judging Validity of Sample Data Based on External Control Mix Results

The Cq value of the Ext Control Mix can serve as an indication of the purity and the concentration of DNA. Thus, the validity of the test can be decided by the Cq value of the Ext Control Mix. Cq values of any sample with Ext Control Mix should be in the range of 20-27. If the Cq values fall outside the range given in Table 8, the test results should be considered invalid. The experiment should be repeated.









TABLE 8







Acceptable Cq Ranges for Samples with External Control Mix










Cq Value of Ext



Validity
Control Mix
Descriptions and Recommendations





Optimal
20 < Cq < 27
The amplification and amount of DNA




sample were optimal.


Invalid
Cq ≤20
Possibility of a false positive is high. Repeat




the PCR reaction with less DNA.


Invalid
Cq ≥27
Not enough DNA or DNA not pure. The




amplification is not optimal. Check DNA




amount and purity. Repeat the experiment









Scoring Mutational Status

IMPORTANT: Refer to the Macro Sheet for QCLAMP™ Cq Mutation Analysis for scoring mutational status. Macro maybe requested by contacting information@diacarta.com


If a Cq value is undetermined, assign a Cq of 40 and proceed to analysis.


The table below should be used to determine mutational status









TABLE 9







Scoring Mutational Status













Mutation
G12
G13
A59
Q61
K117
A146

















Strong Positive:
Cq
≤32
≤32
≤32
≤30
≤33
≤30


Mutation Content >5%


Weak Positive:
Cq
32-35*
32-35*
30-35*
30-35*
33-35*
30-35*


Mutation Content 1-5%
ΔCq
≤10
≤9
≤8
≤8
≤10
≤8


Negative
Cq
≥35
≥35
≤30
≥35
≥35
≥35





*If reaction has been set-up with 5 ng of DNA, it is recommended that the experiment be repeated with 10 ng of template DNA to confirm the results.


*Refer to Table 9 for interpretation of A59/Q61 Mutational Status







If the Cq value suggests mutation content between 1%-5%, a further calculation of ΔCq should be performed to determine mutational status.


ΔCq=[Cq value of sample with mutant reaction mix]−[Cq value of sample with Ext Control Mix]


For ex: ΔCq=[Cq of sample with G12 mutant reaction mix]−[Cq of sample with Ext Control Mix]


Refer to the table above to confirm mutational status of weak positives.


Differentiating A59/Q61 Mutational Status

The Q61 reaction mix detects both A59 and Q61 mutations, whereas the A59 reaction mix detects only A59 mutations. Therefore, in order to differentiate between A59 and Q61 Mutations a combination of results from the 2 mixes should be used, as described in Table 10 below.









TABLE 10







Interpretation of A59/Q61 Mutational Status









Reaction Mix
Result Based on Table 12
Mutational Status





A59 Reaction Mix
Positive
A59 Mutation


Q61 Reaction Mix
Positive


A59 Reaction Mix
Negative
Q61 Mutation


Q61 Reaction Mix
Positive


A59 Reaction Mix
Negative
Q61 Mutation


Q61 Reaction Mix
Positive









HRM Curves as a Tool to Confirm Analyses

In High Resolution Melting Analysis (HRM), the region of interest amplified by PCR is gradually melted. SYBR green is a dsDNA binding dye that is released as the dsDNA amplicon is melted. Emitted fluorescence is measured to generate a characteristic curve. The Tm (Melting Temperature) is characteristic of the GC content, length and sequence of a DNA product and is a useful tool in product identification. The resulting melt profile reflects the mix of amplicons present.


Wild-type DNA (clamping control) is provided. Some amplification may occur in these reactions. Melt profiles of unknown samples should be compared to wild-type and positive controls. Enrichment of one or more peaks, resulting in a melt profile distinct from wild-type DNA profile, can serve as an indication of specific amplification of a mutation target. If the melt profile of an unknown sample is similar to wild-type DNA, and has been scored as a mutation due to Cq, the analysis should be repeated. The resulting PCR product can be sent for Sanger sequencing for further clarification.


HRM curves obtained from unknown samples can be compared to HRM curves obtained from positive controls. Amplicons of similar length and sequence will exhibit the same melt profile.


Example 2

PCR based enrichment of mutant DNA template sequences from template DNA derived from a lung cancer tumor biopsy sample is shown below using a xeno-nucleic acid clamping probe specific for KRAS Exon 2 codon 12. Only codon 12 mutant sequences are amplified as shown by the melting profile of the PCR amplicons generated before enrichment and after XNA clamped PCR enrichment:


The PCR product from the XNA clamped mutant enriched PCR reaction can be isolated and used directly in a Sanger sequencing or Pyrosequencing reaction or else it can be processed for next generation sequencing (NGS) by ligation of adapters and after removal of excess a dapters can be used directly for NGS without the need for another PCR amplification step.


Example 3
Multiplex Detection of KRAS Mutations.

In this example of this invention, locus specific hydrolysis probes are designed to detect mutant amplicons in the KRAS proto-oncogene. Locus specific probes are designed for the following mutant amplicons in KRAS:


Probe 1 KRAS Exon 2 codon 12,


Probe 2 KRAS Exon 2 codon 13,


Probe 3 KRAS Exon 3 codon 59


Probe 4 KRAS Exon3 codon 61,


Probe 5 KRAS Exon 4 codon 117,


Probe 6 KRAS Exon 4 codon 146


and a control probe for a coding sequence in KRAS that has no mutations—Probe 7 KRAS Control probe


Each locus specific hydrolysis probe has a different fluorophore (and quencher) selected from the available fluorophores for multiplex applications (see FIGS. 3 and 4).


For the KRAS multiplex assay, KRAS c12, c59, c117 and c146 and KRAS control are detected in a one tube and KRAS c13 and c61 and KRAS control in a separate tube. So that all mutations in the KRAS proto-oncogene can be detected using only 2 PCR reaction tubes. FIG. 5 is an Example of the Exon 4 locus specific probes assay.


Example 4

This example of the invention describes the use of mutation specific capture probes covalently attached to optically bar-coded beads via an amino-linker spacer. Mutant specific probes and control probes for the detection of mutations in KRAS Exon 2 codons 12 and 13 are shown below:












 1.
G12A
SEQ ID NO: 1
AGCTGCTGGCGTA





 2.
G12R
SEQ ID NO: 2
AGCTCGTGGCGTA





 3.
G12D
SEQ ID NO: 3
AGCTGATGGCGTA





 4.
G12C
SEQ ID NO: 4
AGCTTGTGGCGTA





 5.
G12I
SEQ ID NO: 5
GAGCTATTGGCGT





 6.
G12L
SEQ ID NO: 6
GAGCTCTTGGCGT





 7.
G12S
SEQ ID NO: 7
AGCTAGTGGCGTA





 8.
G12V
SEQ ID NO: 8
AGCTGTTGGCGTA





 9.
G13C
SEQ ID NO: 9
TGGTTGCGTAGGC





10.
G13D
SEQ ID NO: 10
TGGTGACGTAGGC





11.
G13A
SEQ ID NO: 11
TGGTGCCGTAGGC





12.
G13V
SEQ ID NO: 12
TGGTGTCGTAGGC





13.
G13S
SEQ ID NO: 13
TGGTAGCGTAGGC





14.
G13R
SEQ ID NO: 14
TGGTCGCGTAGGC







The control Capture Probes are:












15.
(HLA-)DRA Match
SEQ ID NO: 15
GGAGACGGTCTGG





16.
(HLA-)DRA Mismatch
SEQ ID NO: 16
GGAGACGCTCTGG





17.
KRAS Wild type:
SEQ ID NO: 17
CTGGTGGCGTAGG





18.
KRAS PCR control
SEQ ID NO: 18
AAGGCCTGCTGAA






All probes contain a 5′-amino-linker for bar-coded bead conjugation. After, performing XNA clamping PCR reaction is done to eliminate wild-type KRAS using the following primers: KRAS Exon 2 Forward: SEQ ID NO: 19 5′-GTACTGGTGGAGTATTTGATAGTG-3′ KRAS Exon 2 Reverse: SEQ ID NO: 20 5′-ATCGTCAAGGCACTCTTGCCTAC-3′ and XNA Clamp Probe Blocker specific for KRAS Exon 2 12/13 optically bar-coded mutation specific capture beads are added and incubated for hybridization capture. After washing detection is performed with Streptavidin Phycoerythrin (SAPE) and measured on DigiPlex analyzer.


Example 5

QCLAMP™ Sample DNA Preparation Protocol


Genomic DNA should be obtained either from whole blood, cells, purified peripheral blood lymphocytes of whole blood, polynuclear cells, or granulocytes, tissue biopsies or FFPE sections. For comparable results it is recommended that the same cellular fraction and DNA extraction method are used. DNA extraction can be performed using a homebrew method or a commercially available kit.


Carefully transfer FFPE section(s) or equivalent amount of fresh tissue, cells (100 to 100,000 cells) or 200 μl whole blood to a clean 1.7 ml polypropylene micro-centrifuge tube and add the required volume of lysis solution. For FFPE sections add 50 μL of lysis Solution. For liquid or moist cells or tissues add 2× volume of the sample volume.


For FFPE samples warm each sample in heating block at 95° C. until paraffin melts and then vortex each warm sample for 10 seconds. Return the sealed sample preparation tubes to the heating block and heat at 95° C. for 20 minutes make sure to carefully remove the tubes every 5 min and vortex each tube for 10 s and return to heating block.


Remove sample preparation tube from heating block and immediately add an equivalent volume of lysis solution as the volume added of lysis solution from step 1 above. For example, if 50 μL of lysis solution was added, add 50 μL of lysis solution.


Vortex each sample for 10 seconds. Spin down the sample preparation tubes in a microcentrifuge and allow to cool. Use the resultant lysis solution lysate supernatant directly in the PCR reaction.


The extracted DNA needs to be diluted to a concentration of 5 ng/μl in 1× TE buffer at pH 8.0 and then stored at +4 to +8° C. for 1 week or at −20° C. if longer term storage is required. The QCLAMP™ qPCR reaction is optimized for DNA samples containing 5-20 ng of purified genomic DNA.


The sequences in the Table below show exemplary primers and xenonucleic acids (XNA's).














Sequence Name









1047SSF001NEW
SEQ ID NO: 21
CGAAAGACCCTAGCCTTAGATAAAACT





1047SSR0012NEW
SEQ ID NO: 22
ATTGTGTGGAAGATCCAATCCATTT





146R002f
SEQ ID NO: 23
ACGTTGGATGTGTACCATACCTGTCTGGTCTT





21FW1S
SEQ ID NO: 24
GTTTTCCCAGTCACGACACGTTGGATGCAGCCAGGAACG




TACTGGTGA





BIOBRAFCONTRLFP
SEQ ID NO: 25
/5Biosg/CTCCAGATCTCAGTAAGGTACGG





BIOKRASCONTRLFP
SEQ ID NO: 26
/5Biosg/TGAGGGAGATCCGACAATACAG





BRAFAZFPNEW02
SEQ ID NO: 27
ACAGTAAAAATAGGTGATTTTGGTCTAGCTA





BRAFAZFPNew02s
SEQ ID NO: 28
GTTTTCCCAGTCACGACACGTTGGATGACAGTAAAAATA




GGTGATTTTGGTCTAGCTA





BRAFAZRP001
SEQ ID NO: 29
CATCCACAAAATGGATCCAGACAA





BRAFAZRP001s
SEQ ID NO: 30
CAGGAAACAGCTATGACACGTTGGATGCATCCACAAAAT




GGATCCAGACAA





BRAFCONTRLFP
SEQ ID NO: 31
CTCCAGATCTCAGTAAGGTACGG





BRAFCONTRLRP
SEQ ID NO: 32
GGGAAAGAGTGGTCTCTCATC





C790F002f
SEQ ID NO: 33
ACGTTGGATGTCCACCGTGCAGCTCATC





C790F002fS
SEQ ID NO: 34
GTTTTCCCAGTCACGACACGTTGGATGTCCACCGTGCAG




CT





C790R001Bf
SEQ ID NO: 35
ACGTTGGATGGTCTTTGTGTTCCCGGACAT





C790R001BfS
SEQ ID NO: 36
CAGGAAACAGCTATGACACGTTGGATGGTCTTTGTGTTC




CC





Ex19NewFS
SEQ ID NO: 37
GTTTTCCCAGTCACGACACGTTGGATGCTCTCTGTCATA




GGGACTCTGGATCC





Ex19NewFwd
SEQ ID NO: 38
CTCTCTGTCATAGGGACTCTGGATCC





Ex19NewRev
SEQ ID NO: 39
AGCAAAGCAGAAACTCACATCGAG





Ex19NewRS
SEQ ID NO: 40
CAGGAAACAGCTATGACACGTTGGATGAGCAAAGCAGAA




ACTCACATCGAG





Exon18NewFS
SEQ ID NO: 41
GTTTTCCCAGTCACGACACGTTGGATGGCTCCCAACCAA




GCTCTCTTGA





Exon18NewFwd
SEQ ID NO: 42
GCTCCCAACCAAGCTCTCTTGA





Exon18NewRev
SEQ ID NO: 43
CTGTGCCAGGGACCTTACCTTATAC





Exon18NewRS
SEQ ID NO: 44
CAGGAAACAGCTATGACACGTTGGATGCTGTGCCAGGGA




CCTTACCTTATAC





Exon2FowardNew
SEQ ID NO: 45
TTTGCCAAGGCACGAGTAACAAG





Exon2ReverseNew
SEQ ID NO: 46
CCCAAGGACCACCTCACAGTTAT





JAK2XN9F001
SEQ ID NO: 47
TTAACTGCAGATGCACATCATTACCT





KRAS117F002
SEQ ID NO: 48
GGACTCTGAAGATGTACCTATGG





KRAS117F002s
SEQ ID NO: 49
GTTTTCCCAGTCACGACACGTTGGATGGGACTCTGAAGA




TGTACCTATGG





KRAS117R002
SEQ ID NO: 50
GCTAAGTCCTGAGCCTGTTT





KRAS117R002s
SEQ ID NO: 51
CAGGAAACAGCTATGACACGTTGGATGGCTAAGTCCTGA




GCCTGTTT





KRAS146F003
SEQ ID NO: 52
ACACAAAACAGGCTCAGGAC





KRAS146F003s
SEQ ID NO: 53
GTTTTCCCAGTCACGACACGTTGGATGACACAAAACAGG




CTCAGGAC





KRAS146R002
SEQ ID NO: 54
CAGTGTTACTTACCTGTCTTGTCTT





KRAS146R002s
SEQ ID NO: 55
CAGGAAACAGCTATGACACGTTGGATGCAGTGTTACTTA




CCTGTCTTGTCTT





KRASBIOFP002
SEQ ID NO: 56
AAGGCCTGCTGAAAATGACTG





KRASBioFP002s
SEQ ID NO: 57
GTTTTCCCAGTCACGACACGTTGGATGAAGGCCTGCTGA




AAATGACTG





KRASC12RP002s
SEQ ID NO: 58
CAGGAAACAGCTATGACACGTTGGATGTCAAGGCACTCT




TGCCTACGC





KRASc13F001
SEQ ID NO: 59
ACTTGTGGTAGTTGGAGCTGGT





KRASC13F001s
SEQ ID NO: 60
GTTTTCCCAGTCACGACACGTTGGATGACTTGTGGTAGT




TGGAGCTGGT





KRASC13NEWR001
SEQ ID NO: 61
TCATGAAAATGGTCAGAGAAACCTT





KRASC13NewR001s
SEQ ID NO: 62
CAGGAAACAGCTATGACACGTTGGATGACTTGTGGTAGT




TGGAGCTGGT





KRASC59R001
SEQ ID NO: 63
ATTGCACTGTACTCCTCTTGACC





KRASC59R001s
SEQ ID NO: 64
CAGGAAACAGCTATGACACGTTGGATGATTGCACTGTAC




TCCTCTTGACC





KRASc61F001
SEQ ID NO: 65
CTCTTGGATATTCTCGACACAGCAGGT





KRASC61F001s
SEQ ID NO: 66
GTTTTCCCAGTCACGACACGTTGGATGCTCTTGGATATT




CTCGACACAGCAGGT





KRASc61F003
SEQ ID NO: 67
CCAGACTGTGTTTCTCCCTT





KRASC61F003s
SEQ ID NO: 68
GTTTTCCCAGTCACGACACGTTGGATGCCAGACTGTGTT




TCTCCCTT





KRASCONTRLFP
SEQ ID NO: 69
TGAGGGAGATCCGACAATACAG





KRASCONTRLRP
SEQ ID NO: 70
TCTGCCAAAATTAATGTGCTGAACT





L858RBR001
SEQ ID NO: 71
TTCTCTTCCGCACCCAGC





L858RBR001S
SEQ ID NO: 72
CAGGAAACAGCTATGACACGTTGGATGTTCTCTTCCGCA




CCCAGC





L858RNewFS
SEQ ID NO: 73
GTTTTCCCAGTCACGACACGTTGGATGTGAAAACACCGC




AGCATGTCAAGA





L858RNewFwd
SEQ ID NO: 74
TGAAAACACCGCAGCATGTCAAGA





L858RNewRev
SEQ ID NO: 75
CCTTACTTTGCCTCCTTCTGCATG





L858RNewRS
SEQ ID NO: 76
CAGGAAACAGCTATGACACGTTGGATGCCTTACTTTGCC




TCCTTCTGCATG





NC12FP004
SEQ ID NO: 77
TGGTGGGATCATATTCATCTACAAAG





NC12FP004_G13_Rev
SEQ ID NO: 78
TGGTGGGATCATATTCATCTACAAAG





NC12FP004s
SEQ ID NO: 79
CAGGAAACAGCTATGACACGTTGGATGTGGTGGGATCAT




ATTCATCTACAAAG





NRAS117F001
SEQ ID NO: 80
AGTAAAAGACTCGGATGATGTACCTAT





NRAS117F002f
SEQ ID NO: 81
ACGTTGGATGACCTATGGTGCTAGTGGGAAAC





NRAS117F003
SEQ ID NO: 82
ACGTTGGATGTCCCGTTTTTAGGGAGCAGA





NRAS117F004
SEQ ID NO: 83
CCCGTTTTTAGGGAGCAGAT





NRAS117R002
SEQ ID NO: 84
CAGTTCGTGGGCTTGTTTTG





NRAS117R004
SEQ ID NO: 85
CTTGCACAAATGCTGAAAGC





NRASc12F001
SEQ ID NO: 86
AAACTGGTGGTGGTTGGAGCA





NRASC12F001s
SEQ ID NO: 87
GTTTTCCCAGTCACGACACGTTGGATGAAACTGGTGGTG




GTTGGAGCA





NRASC13F001
SEQ ID NO: 88
GGTGGTGGTTGGAGCAGGT





NRASC13F001s
SEQ ID NO: 89
GTTTTCCCAGTCACGACACGTTGGATGGGTGGTGGTTGG




AGCAGGT





NRASC59F001
SEQ ID NO: 90
ACACCCCCAGGATTCTTACAGA





NRASC59F001s
SEQ ID NO: 91
GTTTTCCCAGTCACGACACGTTGGATGACACCCCCAGGA




TTCTTACAGA





NRASC59R001
SEQ ID NO: 92
ATGGCACTGTACTCTTCTTGTCC





NRASC59R001s
SEQ ID NO: 93
CAGGAAACAGCTATGACACGTTGGATGATGGCACTGTAC




TCTTCTTGTCC





NRASc61F001
SEQ ID NO: 94
GTTGGACATACTGGATACAGCTGGA





NRASC61F001s
SEQ ID NO: 95
GTTTTCCCAGTCACGACACGTTGGATGGTTGGACATACT




GGATACAGCTGGA





NRASXN3REVSet4
SEQ ID NO: 96
CCGCAAATGACTTGCTATTA





NRASXN3RevSet4s
SEQ ID NO: 97
CAGGAAACAGCTATGACACGTTGGATGCCGCAAATGACT




TGCTATTA





NRASXN5FwSet1
SEQ ID NO: 98
ACACACTGGTAAGAGAAATAC





NRASXN5REVSet1
SEQ ID NO: 99
CTGAGTCCCATCATCACT





BR001
SEQ ID NO: 100
ATCGAGATTTCACTGTAGCTAGAC





DPCA001
SEQ ID NO: 101
ACTTCAGGCAGCGTCTTCA





DPCA002
SEQ ID NO: 102
TGTTCAGAGCACACTTCAG





DPCA003
SEQ ID NO: 103
CTGGTGGTTGAATTTGCTG





DPCA004
SEQ ID NO: 104
CATGAGCTCCAGCAGGATGAAC





DPCA005
SEQ ID NO: 105
CCGAAGTCTCCAATCTTGG





DPCA006
SEQ ID NO: 106
TAGATGTCTCGGGCCATCC





DPCBRC001
SEQ ID NO: 107
GGGACACTCTAAGAT





DPCBRC002
SEQ ID NO: 108
TTCTGTCCTGGGATTCTC





DPCBRC003
SEQ ID NO: 109
AGATTTTCCACTTGCTGT





DPCBRCA001-2
SEQ ID NO: 110
CCAGATGGGACACTCTAAGATTTTC





DPCBRCA002-2
SEQ ID NO: 111
CCTTTCTGTCCTGGGATTCTCTT





DPCBRCA003-2
SEQ ID NO: 112
GACAGATTTTCCACTTGCTGTGCTAA





DPCBRCA004
SEQ ID NO: 113
CATAAAGGACACTGTGAAGGCC





DPCBRCA004B
SEQ ID NO: 114
D-LYS-O-GGCCTTCACAGTGTCCTTTATG





DPCCKT002
SEQ ID NO: 115
D-LYS-O-CATTCTTGATGTCTCTGGCTAG





DPCE001
SEQ ID NO: 116
GAGCCCAGCACTTT





DPCE001B
SEQ ID NO: 117
D-LYS-O-CGGAGCCCAGCACTTTGAT





DPCE001B1
SEQ ID NO: 118
D-LYS-O-CGGAGCCCAGCACTTTGAT





DPCE002
SEQ ID NO: 119
NH(2)-AGATGTTGCTTCTCTTAA-CONH(2)





DPCE002B
SEQ ID NO: 120
D-LYS-O-AGATGTTGCTTCTCTTAA





DPCE002C
SEQ ID NO: 121
D-LYS-O-CGGAGATGTTGCTTCTCTTAATTCC





DPCE004
SEQ ID NO: 122
CAGTTTGGCCAGCCCA





DPCE004B
SEQ ID NO: 123
CAGTTTGGCCAGCCCA-O-D-LYS





DPCE004C
SEQ ID NO: 124
D-LYS-O-TTTGGCCAGCCCAAAATCTGT





DPCE004D
SEQ ID NO: 125
D-LYS-O-GGCCAGCCCAAAATCTGT





DPCE005
SEQ ID NO: 126
ACCCAGCAGTTTGGC





DPCE005B
SEQ ID NO: 127
D-LYS-O-ACCCAGCAGTTTGGC





DPCE006
SEQ ID NO: 128
GCTGCGTGATGAG





DPCE007
SEQ ID NO: 129
GCTGCGTGATGA





DPCE008
SEQ ID NO: 130
AGCTCATCACGCAGCTCATG





DPCE008B
SEQ ID NO: 131
D-LYS-O-CAGCTCATCACGCAGCTCATGC





DPCE008C
SEQ ID NO: 132
D-LYS-O-TCATCACGCAGCTCATGCCCTT





DPCE008D
SEQ ID NO: 133
D-LYS-O-CTCATCACGCAGCTCATG





DPCE008E
SEQ ID NO: 134
D-LYS-O-TGAGCTGCGTGATG





DPCE009B
SEQ ID NO: 135
D-LYS-O-TCCACGCTGGCCATCACGTA





DPCE009B-1
SEQ ID NO: 136
TCCACGCTGGCCATCACGTA-O-D-LYS





DPCE010B
SEQ ID NO: 137
TGGGGGTTGTCCAC-O-D-LYS





DPCE011
SEQ ID NO: 138
GCACACGTGGGGGTT-O-D-LYS





DPCE012
SEQ ID NO: 139
D-LYS-O-ACAACCCCCACGTGTGC





DPCH001
SEQ ID NO: 140
CTGAGCCAGGAGAAAC





DPCH002
SEQ ID NO: 141
GTAAACTGAGCCAGGAG





DPCH003
SEQ ID NO: 142
ATGGCACTAGTAAACTGAGC





DPCH004
SEQ ID NO: 143
ATCCATATAACTGAAAGCCAA





DPCH005
SEQ ID NO: 144
ACCACATCATCCATATAACTGAA





DPCHRAS001B
SEQ ID NO: 145
D-LYS-O-O-TTGCCCACACCGCCGGC





DPCHRAS002
SEQ ID NO: 146
D-LYS-O-O-TCTTGCCCACACCGCC





DPCHRAS003
SEQ ID NO: 147
D-LYS-O-O-TACTCCTCCTGGCCGGC





DPCJ001
SEQ ID NO: 148
CGTCTCCACAGACACATACTCCA





DPCJ002B
SEQ ID NO: 149
CGTCTCCACAGACACATACTCCA-O-D-LYS





DPCK001B
SEQ ID NO: 150
GCCTACGCCACCAGCTCCAAC-O-D-LYS





DPCK001B2
SEQ ID NO: 151
GCCTACGCCACCAGCTCCAAC-O-O-D-LYS





DPCK001C
SEQ ID NO: 152
CTACGCCACCAGCTCCAACTACCA





DPCK001C2
SEQ ID NO: 153
CTACGCCACCAGCTCCAACTACCA-O-D-LYS





DPCK002
SEQ ID NO: 154
TCTTGCCTACGCCACCAGCTCCA





DPCK003
SEQ ID NO: 155
TGTACTCCTCTTGACCTGCTGTG





DPCK003B
SEQ ID NO: 156
D-LYS-O-TGTACTCCTCTTGACCTGCTGTG





DPCK004
SEQ ID NO: 157
NH(2)-GGCAAATCACATTTATTTCCTAC-CONH(2)





DPCK004B
SEQ ID NO: 158
D-LYS-O-GGCAAATCACATTTATTTCCTAC





DPCK005B
SEQ ID NO: 159
D-LYS-O-TGTCTTGTCTTTGCTGATGTTTC





DPCK005
SEQ ID NO: 160
TGTCTTGTCTTTGCTGATGTTTC





DPCK005C
SEQ ID NO: 161
D-LYS-O-TGTCTTGTCTTTGCTGATGTTTC





DPCK006
SEQ ID NO: 162
NH(2)-CTCTTGACCTGCTGTGTCGAG-CONH(2)





DPCN001
SEQ ID NO: 163
TCCCAACACCACCTGCTCCAA





DPCN001B
SEQ ID NO: 164
D-LYS-O-CAACACCACCTGCTCCAACCACCAC





DPCN002
SEQ ID NO: 165
CTTTTCCCAACACCACCTGCTCC





DPCN002B
SEQ ID NO: 166
D-LYS-O-TGCGCTTTTCCCAACACCACCTGCT





DPCN003B
SEQ ID NO: 167
GGCACTGTACTCTTCTTGTCCAG





DPCN004B
SEQ ID NO: 168
D-LYS-O-TCTGGTCTTGGCTGAGGTTTC





DPCN006
SEQ ID NO: 169
NH(2)-GGCAAATCACACTTGTTTCCCAC-CONH(2)





DPCN006B
SEQ ID NO: 170
D-LYS-O-GGCAAATCACACTTGTTTCCCAC





DPCN007
SEQ ID NO: 171
NH(2)-TTCTTGTCCAGCTGTATCCAGTATG-CONH(2)





DPCPKA003B
SEQ ID NO: 172
D-LYS-O-AGATCCTCTCTCTGAAATCAC





DPCPKA004
SEQ ID NO: 173
D-LYS-O-TCTTTCTCCTGCTCAGTGATTTCA





DPCPKA005
SEQ ID NO: 174
D-LYS-O-AATGATGCACATCATGGTGGCTG





NRASN003C
SEQ ID NO: 175
D-LYS-O-GGCACTGTACTCTTCTTGTCCAG





QMDXNA001
SEQ ID NO: 176
NH(2)-O-TTCATCAACCGCACTCTGTTTATCTC





QMDXNA002
SEQ ID NO: 177
NH(2)-O-TGGCGACGACAATGGACCCAATTAT





QMDXNA003
SEQ ID NO: 178
NH(2)-O-AGATGTAGTTAGCAATCGGTCCTTGTTGTA





QMDXNA004
SEQ ID NO: 179
NH(2)-O-GGGTAATTGAGGTAACGTAGGTATCAAGAT





QMDXNA005
SEQ ID NO: 180
NH(2)-O-TACTATCGACTGACATGAGGCTTGTGT





XNADE001
SEQ ID NO: 181
D-LYS-O-AGTCCGACGATCTGGAATTC





XNADE002
SEQ ID NO: 182
D-LYS-O-ACTGGAGTTCAGACGTGTG





XNADE003
SEQ ID NO: 183
D-LYS-O-CTCTTCCGATCAGATCGGAA





XNADE003b
SEQ ID NO: 184
D-LYS-O-CTCTTCCGATCAGATCGGAAG





XNAFGFR001
SEQ ID NO: 185
D-LYS-O-O-AGCGCTCCCCGCACC





XNAFGFR001
SEQ ID NO: 186
D-LYS-O-O-AGCGCTCCCCGCACC





XNAFGFR002
SEQ ID NO: 187
D-LYS-O-GGGGAGCGCTCTGT-O-TTTTT





XNAFGFR003
SEQ ID NO: 188
D-LYS-O-O-AGCGCTCCCCGCACC-O-TTTTTT





XNAFGFR004
SEQ ID NO: 189
D-LYS-O-TGCATACACACTGCCCGCCT









Other sequences of interest in connection with the invention include the following exons:










BRAF Ex 15 NCBI NG_007873.3;DNA;Wildtype



SEQ ID NO: 190



TAGAAATTAG ATCTCTTACC TAAACTCTTC ATAATGCTTG CTCTGATAGG AAAATGAGAT






CTACTGTTTT CCTTTACTTA CTACACCTCA GATATATTTC TTCATGAAGA CCTCACAGTA





AAAATAGGTG ATTTTGGTCT AGCTACAGTG AAATCTCGAT GGAGTGGGTC CCATCAGTTT





GAACAGTTGT CTGGATCCAT TTTGTGGATG GTAAGAATTG AGGCTATTTT TCCACTGATT





AAATTTTTGG CCCTGAGATG CTGCTGAGTT ACTAGAAAGT CATTGAAGGT CTCAACTATA





GTATTTTCAT AGTTCCCAGT ATTCACAAAA ATCAGTGTTC TTATTTTTTA TGTAAATAGA





EGFR Ex18 GeneGenBank: AF288738.1 NCBI NM_005228.3; DNA;Wildtype


SEQ ID NO: 191



TAGAGAAGGC GTACATTTGT CCTTCCAAAT GAGCTGGCAA GTGCCGTGTC CTGGCACCCA






AGCCCATGCC GTGGCTGCTG GTCCCCCTGC TGGGCCATGT CTGGCACTGC TTTCCAGCAT





GGTGAGGGCT GAGGTGACCC TTGTCTCTGT GTTCTTGTCC CCCCCAGCTT GTGGAGCCTC





TTACACCCAG TGGAGAAGCT CCCAACCAAG CTCTCTTGAG GATCTTGAAG GAAACTGAAT





TCAAAAAGAT CAAAGTGCTG GGCTCCGGTG CGTTCGGCAC GGTGTATAAG GTAAGGTCCC





TGGCACAGGC CTCTGGGCTG GGCCGCAGGG CCTCTCATGG TCTGGTGGGG AGCCCAGAGT





CCTTGCAAGC TGTATATTTC CATCATCTAC TTTACTCTTT GTTTCACTGA GTGTTTGGGA





AACTCCAGTG TTTTTCCCAA GTTATTGAGA GGAAATCTTT TATAACCACA GTAATCAGTG





EGFR Ex19 GeneGenBank: AF288738.1 NCBI NM_005228.3; DNA;Wildtype


SEQ ID NO: 192



AGCCCAACAG CTGCAGGGCT GCGGGGGCGT CACAGCCCCC AGCAATATCA GCCTTAGGTG






CGGCTCCACA GCCCCAGTGT CCCTCACCTT CGGGGTGCAT CGCTGGTAAC ATCCACCCAG





ATCACTGGGC AGCATGTGGC ACCATCTCAC AATTGCCAGT TAACGTCTTC CTTCTCTCTC





TGTCATAGGG ACTCTGGATC CCAGAAGGTG AGAAAGTTAA AATTCCCGTC GCTATCAAGG





AATTAAGAGA AGCAACATCT CCGAAAGCCA ACAAGGAAAT CCTCGATGTG AGTTTCTGCT





TTGCTGTGTG GGGGTCCATG GCTCTGAACC TCAGGCCCAC CTTTTCTCAT GTCTGGCAGC





TGCTCTGCTC TAGACCCTGC TCATCTCCAC ATCCTAAATG TTCACTTTCT ATGTCTTTCC





EGFR Ex20 GeneGenBank: AF288738.1 NCBI NM_005228.3; DNA;Wildtype


SEQ ID NO: 193



AAAATTCCCG TCGCTATCAA GGAATTAAGA GAAGCAACAT CTCCGAAAGC CAACAAGGAA






ATCCTCGATG AAGCCTACGT GATGGCCAGC GTGGACAACC CCCACGTGTG CCGCCTGCTG





GGCATCTGCC TCACCTCCAC CGTGCAGCTCATCACGCAGC TCATGCCCTT CGGCTGCCTC





CTGGACTATG TCCGGGAACA CAAAGACAAT ATTGGCTCCC AGTACCTGCT CAACTGGTGT





GTGCAGATCG CAAAGGGCAT GAACTACTTG GAGGACCGTC GCTTGGTGCA CCGCGACCTG





GCAGCCAGGA ACGTACTGGT GAAAACACCG CAGCATGTCA AGATCACAGA TTTTGGGCTG





GCCAAACTGC TGGGTGCGGA AGAGAAAGAA TACCATGCAG AAGGAGGCAA AGTGCCTATC





AAGTGGATGG CATTGGAATC AATTTTACAC AGAATCTATA CCCACCAGAG TGATGTCTGG





EGFR Ex21 GeneGenBank: AF288738.1 NCBI NM_005228.3; DNA;Wildtyp


SEQ ID NO: 194



GGCATCTGCC TCACCTCCAC CGTGCAGCTC ATCACGCAGC TCATGCCCTT CGGCTGCCTC






CTGGACTATG TCCGGGAACA CAAAGACAAT ATTGGCTCCC AGTACCTGCT CAACTGGTGT





GTGCAGATCG CAAAGGGCAT GAACTACTTG GAGGACCGTC GCTTGGTGCA CCGCGACCTG





GCAGCCAGGA ACGTACTGGT GAAAACACCG CAGCATGTCA AGATCACAGA TTTTGGGCTG





GCCAAACTGC TGGGTGCGGA AGAGAAAGAA TACCATGCAG AAGGAGGCAA AGTGCCTATC





AAGTGGATGG CATTGGAATC AATTTTACAC AGAATCTATA CCCACCAGAG TGATGTCTGG





AGCTACGGGG TGACCGTTTG GGAGTTGATG ACCTTTGGAT CCAAGCCATA TGACGGAATC





HRAS Ex3 NCBI Reference Sequence: NG_007666.1; DNA;Wildtype


SEQ ID NO: 195



CTGCAGGATT CCTACCGGAA GCAGGTGGTC ATTGATGGGG AGACGTGCCT GTTGGACATC






CTGGATACCG CCGGCCAGGA GGAGTACAGC GCCATGCGGG ACCAGTACAT GCGCACCGGG





GAGGGCTTCC TGTGTGTGTT TGCCATCAAC AACACCAAGT CTTTTGAGGA CATCCACCAG





TACAGGTGAA CCCCGTGAGG CTGGCCCGGG AGCCCACGCC GCACAGGTGG GGCCAGGCC





JAK2 NCBI Reference Sequence: NG_009904.1; DNA; wildtype


SEQ ID NO: 196



CTGACATCTACCTCTAGTTGTACTTCTGTCCTCTATTTCAGGTGTTATGGGTCAAGCCTGTTTGA






CTGGCATTATTCATGATTCCTGTACCACTCTTGCTCTCTCTCACTTTGATCTCCATATTCCAGGC





TTACACAGGGGTTTCCTCAGAACGTTGATGGCAGTTGCAGGTCCATATAAAGGGACCAAAGCACA





TTGTATCCTCATCTAGTCATGCTGAAAGTAGGAGAAAGTGCATCTTTATTATGGCAGAGAGAATT





TTCTGAACTATTTATGGACAACAGTCAAACAACAATTCTTTGTACTTTTTTTTTTCCTTAGTCTT





TCTTTGAAGCAGCAAGTATGATGAGCAAGCTTTCTCACAAGCATTTGGTTTTAAATTATGGAGTA





TGTGTCTGTGGAGACGAGAGTAAGTAAAACTACAGGCTTTCTAATGCCTTTCTCAGAGCATCTGT





TTTTGTTTATATAGAAAATTCAGTTTCAGGATCACAGCTAGGTGTCAGTGTAAACTATAATTTAA





CAGGAGTTAAGTATTTTTGAAACTGAAAACACTGTAGGACTATTCAGTTATATCTTGTGAAAAAG





GAAAGCAATGAAGTTAAAAGTAGAAGGTTACAATGCCCAAACAATAGAGTATTATAGTAAACAAA





TGTCTATAAAACATTTTGTGTTCATGATAGCAAAAGAGATTATGGCAGGTTCAACATAACATTGG





AATAACTGGCCTTTTCAGTACAAACTTATCTGGAATTATGAAGACAAAGCATA





KRAS Ex2 NCBI Reference Sequence: NG_007524.1; DNA; wildtype


SEQ ID NO: 197



GGTACTGGTG GAGTATTTGA TAGTGTATTA ACCTTATGTG TGACATGTTC TAATATAGTC






ACATTTTCAT TATTTTTATT ATAAGGCCTG CTGAAAATGA CTGAATATAA ACTTGTGGTA





GTTGGAGCTG GTGGCGTAGG CAAGAGTGCC TTGACGATAC AGCTAATTCA GAATCATTTT





GTGGACGAAT ATGATCCAAC AATAGAGGTA AATCTTGTTT TAATATGCAT ATTACTGGTG





KRAS Ex3 NCBI Reference Sequence: NG_007524.1; DNA; wildtype


SEQ ID NO: 198



CTTCTCAGGA TTCCTACAGG AAGCAAGTAG TAATTGATGG AGAAACCTGT CTCTTGGATA






TTCTCGACAC AGCAGGTCAA GAGGAGTACA GTGCAATGAG GGACCAGTAC ATGAGGACTG





GGGAGGGCTT TCTTTGTGTA TTTGCCATAA ATAATACTAA ATCATTTGAA GATATTCACC





ATTATAGGTG GGTTTAAATT GAATATAATA AGCTGACATT AAGGAGTAAT TATAGTTTTT





KRAS Ex4 NCBI Reference Sequence: NG_007524.1; DNA; wildtype


SEQ ID NO: 199



GTGCTATAAC TTTTTTTTCT TTCCCAGAGA ACAAATTAAA AGAGTTAAGG ACTCTGAAGA






TGTACCTATG GTCCTAGTAG GAAATAAATG TGATTTGCCT TCTAGAACAG TAGACACAAA





ACAGGCTCAG GACTTAGCAA GAAGTTATGG AATTCCTTTT ATTGAAACAT CAGCAAAGAC





AAGACAGGTA AGTAACACTG AAATAAATAC AGATCTGTTT TCTGCAAAAT CATAACTGTT





ATGTCATTTA ATATATCAGT TTTTCTCTCA ATTATGCTAT ACTAGGAAAT AAAACAATAT





KRAS Ex5 NCBI Reference Sequence: NG_007524.1; DNA; wildtype


SEQ ID NO: 200



AATGCAACAG ACTTTAAAGA AGTTGTGTTT TACAATGCAG AGAGTGGAGG ATGCTTTTTA






TACATTGGTG AGGGAGATCC GACAATACAG ATTGAAAAAA ATCAGCAAAG AAGAAAAGAC





TCCTGGCTGT GTGAAAATTA AAAAATGCAT TATAATGTAA TCTGGTAAGT TTAAGTTCAG





NRAS Exon 2 NCBI Reference Sequence: NG_007572.1; DNA; wildtype


SEQ ID NO: 201



GTGTTTTTGC GTTCTCTAGT CACTTTAAGA ACCAAATGGA AGGTCACACT AGGGTTTTCA






TTTCCATTGA TTATAGAAAG CTTTAAAGTA CTGTAGATGT GGCTCGCCAA TTAACCCTGA





TTACTGGTTT CCAACAGGTT CTTGCTGGTG TGAAATGACT GAGTACAAAC TGGTGGTGGT





TGGAGCAGGT GGTGTTGGGA AAAGCGCACT GACAATCCAG CTAATCCAGA ACCACTTTGT





AGATGAATAT GATCCCACCA TAGAGGTGAG GCCCAGTGGT AGCCCGCTGA CCTGATCCTG





TCTCTCACTT GTCGGATCAT CTTTACCCAT ATTCTGTATT AAAGGAATAA GAGGAGAGAA





AGTAAAAAGT TATTTTGGGT ATACATTCAG TTATGCAATA AGCTTAACGT GTTTATAGAG





AACAGTTCAT TTTTATTAGC TGCTGAAGTT TCTAAAACCT GTCCAGTTTT TAACAGTTCT





NRAS Exon 3 NCBI Reference Sequence: NG_007572.1; DNA; wildtype


SEQ ID NO: 202



TGGGCTTGAA TAGTTAGATG CTTATTTAAC CTTGGCAATA GCATTGCATT CCCTGTGGTT






TTTAATAAAA ATTGAACTTC CCTCCCTCCC TGCCCCCTTA CCCTCCACAC CCCCAGGATT





CTTACAGAAA ACAAGTGGTT ATAGATGGTG AAACCTGTTT GTTGGACATA CTGGATACAG





CTGGACAAGA AGAGTACAGT GCCATGAGAG ACCAATACAT GAGGACAGGC GAAGGCTTCC





TCTGTGTATT TGCCATCAAT AATAGCAAGT CATTTGCGGA TATTAACCTC TACAGGTACT





AGGAGCATTA TTTTCTCTGA AAGGATGATC TTTGTGTTCT GAATCTTTAT GGGGAAATGA





GGTTACCACA CTAGGGAAGA TAGAGCTTTT TAATTATGGG AAGAGTTGGT TTTAGGTTGT





TTGACATTGA GAATCTAGGG TAATTACTGA AAGTTAATAC TGGAATTTAT TTTACATAAT





NRAS Exon 4 NCBI Reference Sequence: NG_007572.1; DNA; wildtype


SEQ ID NO: 203



TGGATACAGC TGGACAAGAA GAGTACAGTG CCATGAGAGA CCAATACATG AGGACAGGCG






AAGGCTTCCT CTGTGTATTT GCCATCAATA ATAGCAAGTC ATTTGCGGAT ATTAACCTCT





ACAGGGAGCA GATTAAGCGA GTAAAAGACT CGGATGATGT ACCTATGGTG CTAGTGGGAA





ACAAGTGTGA TTTGCCAACA AGGACAGTTG ATACAAAACA AGCCCACGAA CTGGCCAAGA





GTTACGGGAT TCCATTCATT GAAACCTCAG CCAAGACCAG ACAGGGTGTT GAAGATGCTT





TTTACACACT GGTAAGAGAA ATACGCCAGT ACCGAATGAA AAAACTCAAC AGCAGTGATG





ATGGGACTCA GGGTTGTATG GGATTGCCAT GTGTGGTGAT GTAACAAGAT ACTTTTAAAG





204 PIK3CA Ex9 NCBI Reference Sequence: NG_012113.2; DNA; wildtype


SEQ ID NO: 204



TGTAAAATTT ATTGAAAATG TATTTGCTTT TTCTGTAAAT CATCTGTGAA TCCAGAGGGG






AAAAATATGA CAAAGAAAGC TATATAAGAT ATTATTTTAT TTTACAGAGT AACAGACTAG





CTAGAGACAA TGAATTAAGG GAAAATGACA AAGAACAGCT CAAAGCAATT TCTACACGAG





ATCCTCTCTC TGAAATCACT GAGCAGGAGA AAGATTTTCT ATGGAGTCAC AGGTAAGTGC





TAAAATGGAG ATTCTCTGTT TCTTTTTCTT TATTACAGAA AAAATAACTG AATTTGGCTG





ATCTCAGCAT GTTTTTACCA TACCTATTGG AATAAATAAA GCAGAATTTA CATGATTTTT





PIK3CA Ex20NCBI Reference Sequence: NG_012113.2; DNA; wildtype


SEQ ID NO: 205



TAGCTATTCG ACAGCATGCC AATCTCTTCA TAAATCTTTT CTCAATGATG CTTGGCTCTG






GAATGCCAGA ACTACAATCT TTTGATGACA TTGCATACAT TCGAAAGACC CTAGCCTTAG





ATAAAACTGA GCAAGAGGCT TTGGAGTATT TCATGAAACA AATGAATGAT GCACATCATG





GTGGCTGGAC AACAAAAATG GATTGGATCT TCCACACAAT TAAACAGCAT GCATTGAACT





GAAAAGATAA CTGAGAAAAT GAAAGCTCAC TCTGGATTCC ACACTGCACT GTTAATAACT





PIK3CA Ex16 NCBI Reference Sequence: NG_012113.2; DNA; wildtype


SEQ ID NO: 206



GTTGTAAATCTTTGTAACACTTCAAAAAGCTATATTGTATTTATATTTTAAAATAAATTTCAGGG






TAAAATAATAATAAAGCAAAGGTACCTAGTAAAGTTTTTAACTATTTTAAAGGCTTGAAGAGTGT





CGAATTATGTCCTCTGCAAAAAGGCCACTGTGGTTGAATTGGGAGAACCCAGACATCATGTCAGA





GTTACTGTTTCAGAACAATGAGATCATCTTTAAAAATGGGGATGGTAAGGAAGAGTATTAATGAG





CTTATGATGCATGAATTTAGCTATCTTTTTATACACAGGATATTTATGAACCATGAAAACTACTG





AAAGCCATTTAAGGAATATACACATGTGATAAAATATGTAATATTTATCAGATGTCTTGACCTTT





GAAATATGCATGTATAATCAATGAAAAGAAAAGAAGTACTAGGTTTAGATCAGAAGTCCTGAAAT





CAGTTTTTTGTTTTTTCTTTTTCCTGTTCCCTGCC







Other XNA sequences used in the invention and more in particular with respect to Example 6 of the invention includes:











EGFR G719



SEQ ID NO: 207



D-Lys-O-CGOAGAAAGCCCOAAGCACTTTGAT







EGFR Ex19Del



SEQ ID NO: 208



D-Lys-O-COAGOAGOAAOAGOAATGTTGCTOATOACTCTTAATTCC







EGFR T790



SEQ ID NO: 209



D-Lys-O-TAACAAAAATCACOAGCOAAGCTC







EGFR L858



SEQ ID NO: 210



D-Lys-O-GGCCAGCOACOACAAAATAACTGT







NRAS G12



SEQ ID NO: 211



D-Lys-O-COAAAOACACAACAAACOACTGCTCCAACCACCAC







NRAS A59



SEQ ID NO: 212



D-Lys-O-TTCOATTGTCOACAOAGCTAAGTATAACCAGTATG







KRAS G12



SEQ ID NO: 213



D-Lys-O-CAATACGCCACCOAAGCTCOACAACTACCA







KRAS A59



SEQ ID NO: 214



D-Lys-O-COATCTTGACCTOAGCTOAGTGTAACGAG







KRAS A146



SEQ ID NO: 215



D-Lys-O-TOAGTCTTTAAGCTGOAATGT







APC E1309



SEQ ID NO: 216



D-Lys-O-CAATGACOACTAGTOATCCAATAACTTTTCTT







PIK3CA H1047



SEQ ID NO: 217



D-Lys-O-AOAATGATAAGCACATCATOAGGTGGCTG







CTNNB1 S45



SEQ ID NO: 218



D-Lys-O-CAATCCTTOACTCTAAGAGOATG







BRAF V600



SEQ ID NO: 219



D-Lys-O-AOATCOAGAGATAATTOACACTAAGTAGCTAGAC







In sequences 207 through 219 the subscripts designations OA and AA stand for oxy-aza and aza-aza moieties in the Xenonucleic acid.


Example 6

The Following is exemplary of XNA Oligomer Synthesis:


Part I. Synthetic Procedure of the Fmoc Oxy-Aza-T XNA Monomer.



embedded image


embedded image


The other oxy-aza nucleotide Monomers A, C and G are prepared similarly with suitable protecting groups on the nucleoside bases.


Step 1:


To a solution of O-benzylhydroxylamine (2.00 g, 15.9 mmol) and diisopropylethylamine (3.08 mL, 17.51 mmol) in THF (25 mL) was added dropwise tert-butyl 2-bromoacetate (2.5 mL, 16.71 mmol) in THF (10 mL). The reaction mixture was stirred at 50° C. for 4 hours then at room temperature overnight. Solvent was removed under vacuum to obtain crude which was purified by Biotage Isolera flash column to obtain title compound A (1.17 g, 29.4%) as a colorless oil.


Step 2:


Thymine (3.00 g, 23.0 mmol) and potassium carbonate (3.30 g, 24.0 mmol) were dissolved in dry N,N-dimethylformamide (˜70 mL). Benzyl bromoacetate (3.50 mL, 22.0 mmol) was added dropwise and the reaction mixture was stirred at room temperature overnight. The suspension was filtered and solvent was removed to obtain a residue which was purified by Biotage flash column to obtain compound B (4.09 g, 61.4%) as a white solid.


Step 3:


Benzyl 2-(5-methyl-2,4-dioxo-3,4-dihydropyrimidin-1(2H)-yl)acetate (3.00 g, 10.0 mmol), di-tert-butyl decarbonate (4.92 mL, 22.0 mmol), and 4-dimethylaminopyridine (2.56 g, 22 mmol) were added to THF (˜30 mL) at 0° C. The reaction mixture was stirred at 0° C. for 30 minutes and then at room temperature overnight. The solvent was removed. The residue was dissolved in dichloromethane (100 mL) and washed with water, brine, and dried over anhydrous MgSO4, filtered and concentrated. The crude was purified by Biotage flash column to obtain compound C (2.91 g, 71.1%) as a white solid.


Step 4:


To a solution of tert-butyl 3-(2-(benzyloxy)-2-oxoethyl)-5-methyl-2,6-dioxo-2,3-dihydropyrimidine-1(6H)-carboxylate (2.91 g, 7.38 mmol) in methanol (30 mL) and acetone (30 mL), 5% Pd/C (582 mg) was added. The reaction mixture was degassed with hydrogen 3 times and stirred at room temperature under hydrogen for 3 hours. The mixture was filtered with celite and washed with methanol and acetone. The filtrate was concentrated to obtain crude compound D (1.84 g, 83.3%).


Step 5:


(9H-fluoren-9-yl)methyl carbamate (3.00 g, 12.0 mmol) and paraformaldehyde (0.43 g, 14.0 mmol), were suspended in a mixture of acetic acid (22.5 mL) and acetic anhydride (70 mL). The reaction mixture was stirred at room temperature for 3 days and then filtered. The solvent was removed by distillation in vacuum and the crude was purified by flash column to get compound E (3.46 g, 85.9%) as a white solid.


Step 6:


((((9H-fluoren-9-yl)methoxy)carbonyl)amino)methyl acetate (3.40 g, 10.0 mmol) was dissolved in THF (˜10 mL) and loaded on a 68-gram neutral alumina column. The loaded cartridge was allowed to stand for 5 hours then eluted by THF, and thereafter concentrated to obtain compound F (1.28 g, 43.5%) as a white solid.


Step 7:


N,N-diisopropylethylamine (1.15 mL, 6.49 mmol) was added to a solution of 2-(3-(tert-butoxycarbonyl)-5-methyl-2,4-dioxo-3,4-dihydropyrimidin-1(2H)-yl)acetic acid (1.03 g, 3.245 mmol), tert-butyl 2-((benzyloxy)amino)acetate (0.89 g, 3.57 mmol), 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide-HCl (3.38 g, 17.13 mmol) and hydroxybenzotriazole hydrate (2.68 g, 17.13 mmol) in N,N-dimethylformamide (˜40 mL). The reaction mixture was stirred at room temperature overnight and diluted with dichloromethane (˜50 mL). The solution was washed with water, brine, dried over anhydrous MgSO4, filtered and concentrated. The crude was purified by flash column to obtain compound G (1.08 g, 59.5%) as a white solid.


Step 8:


To a solution of tert-butyl 3-(2-((benzyloxy)(2-(tert-butoxy)-2-oxoethyl)amino)-2-oxoethyl)-5-methyl-2,6-dioxo-2,3-dihydropyrimidine-1(6H)-carboxylate (Compound G; 1.08 g, 2.04 mmol) in methanol (10 mL), 5% Pd/C (216 mg) was added. The reaction mixture was degassed with hydrogen for 3 times and stirred at room temperature under hydrogen for 3 hours. The mixture was filtered by celite and washed with methanol. The filtrate was concentrated to obtain a crude compound H (865 mg, 97.6%) as white foam.


Steps 9 and 10:


To a solution of (9H-fluoren-9-yl)methyl (hydroxymethyl)carbamate (Compound F; 1.03 g, 3.63 mmol) in chloroform (40 mL), trimethylsilyl chloride (0.93 mL, 7.267 mmol) was added dropwise and stirred at room temperature for 1 hour. After 1 hour, tert-butyl 3-(2-((2-(tert-butoxy)-2-oxoethyl)(hydroxy)amino)-2-oxoethyl)-5-methyl-2,6-dioxo-2,3-dihydropyrimidine-1(6H)-carboxylate (1.74 g, 4.00 mmol) and N,N-diisopropylethylamine (2.58 mL, 14.53 mmol) were added to the above solution. The reaction mixture was stirred at room temperature for 1 hour. The reaction mixture was washed with water, brine, dried over anhydrous Na2SO4, filtered, and concentrated to get the residue which was purified by flash column to get compound J (762 mg, 30.0%) as a white solid.


Step 11:


To a solution of tert-butyl 3-(7-(2-(tert-butoxy)-2-oxoethyl)-1-(9H-fluoren-9-yl)-3,8-dioxo-2,6-dioxa-4,7-diazanonan-9-yl)-5-methyl-2,6-dioxo-2,3-dihydropyrimidine-1(6H)-carboxylate (0.60 g, 0.857 mmol) in dichloromethane (˜12 mL), trifluoroacetic acid was added (˜5 mL, 85.8 mmol) at 0˜5° C. The reaction mixture was stirred at room temperature for 1 hour. The mixture was concentrated to obtain a residue which was purified by Biotage Isolera flash column to obtain the title compound (220 mg, 48.0%) as an off-white solid.



1H NMR (300 MHz, CDCl3): 10.3 (s, 1H), 8.75 (s, 1H), 7.88 (d, J=7.5 Hz, 2H), 7.69 (d, J=7.3 Hz, 2H), 7.44-7.29 (m, 5H), 4.92 (d, J=6.1 Hz, 2H), 4.66 (s, 2H), 4.40-4.37 (m, 2H), 4.25 (t, J=6.4 Hz, 1H), 4.08-3.97 (m, 2H), 1.73 (s, 3H) ppm. LC-MS [M+Na]+: 508.97, [M+Na]+: 531.23. HPLC purity: 95.7% at 254 nm.


Part II. Synthesis of Chemically-Modified EGFR c797S XNA, Using Fmoc Oxy-Aza-T XNA Monomer (Bold Red) to Replace the Regular Fmoc-T Monomer (Bold Black) as Specified Below:











EGFR c797S



Regular-T original sequence:



SEQ ID NO: 246



5′-D-LYS-O-TTCGGCTGCCTCCTGG-3′







Partial Oxy-Aza-T Replacement Sequence:



SEQ ID NO: 247



5′-D-LYS-O-TTCGGCTOAGCCTOACCTGG-3′







where OA is oxy-aza.






a) Solid-Phase Synthesis Step

This step has been conducted on an INTAVIS MultiPep automatic synthesizer (INTAVIS Bioanalytical Instruments AG, Cologne, Germany), coupled with a compact Welch vacuum pump (4 m3 per hour ventilation rate), a 20-liter stainless steel waste container, and a long ventilation hose to discharge the solvent vapor and smell from the system into a nearby chemical fume hood.


In a typical 24-port (4×6) array plate, a micro column (0.5-ml capacity) with PTFE filters was inserted tightly into a chosen port. A certain weight of TentaGel resin (1 micromole, namely 10.0 mg resin at 0.10 mmol/gram loading capacity) was loaded to this column.


Four regular monomers (Fmoc-T/A/C/G) and O-linker monomer (Fmoc-AEEA-OH) were purchased commercially (98+% purity) and prepared freshly as 0.3 M solutions in N-methyl 2-pyrrolidone (NMP); Fmoc-D-Lysine(t-Boc) monomer as a 0.5 M solution in NMP. This unconventional Fmoc Oxy-Aza-T monomer was also made as a 0.3 M solution in a smaller 15-ml polypropylene vial (100 mg about 0.2 mmol dissolved in 600 uL of NMP solvent), and was accordingly given a new code of monomer in the program (perhaps like “oaT”?). All other reagents (from Sigma-Aldrich if not specified otherwise, with purity of 98% or higher) include 0.5 M DMF solution of HATU (from P3 BioSyetems Inc, 1-[Bis(dimethylamino)-methylene]-1H-1,2,3-triazolo[4,5-b]pyridinium 3-oxid hexafluorophosphate, Hexafluoro-phosphate Azabenzotriazole Tetramethyl Uronium) for carboxy activation, a base solution containing 1.2 M DIPEA and 1.8 M 2,6-lutidine(1:1, v/v) in DMF for acid scavenger, a 20% piperidine solution in DMF (v %) for Fmoc group deprotection, 5% (v %) acetic anhydride in DMF for amino capping procedure, NMP and methylene chloride and ethanol for column wash use.


After the preparative procedures above are completed, the XNA sequence was input to the operating PC's INTAVIS program with double check. The automatic synthesis on the TentaGel resin was started from the 3′ terminal of XNA sequence (namely from C-terminal) following this program, using a pre-set 1-micromole-scale double-coupling synthesis method. Briefly, in a typical cycle, a double deprotection, a double coupling and a single capping procedure was included to assure the sufficiently high-yielding and clean synthesis; a molar ratio of HATU/Base/monomer/amino=5:25:5:1 was chosen in general. The synthesizer was programmed to automatically repeat the cycles from 3′ end to 5′ end, till the 5′ end of the sequence that is the D-lysine terminus here. At this last cycle, the resin was thoroughly washed and then dried. Resin weight was found to increase obviously.


b) Resin Cleavage and Side-Chain Deprotection

The dried resin was transferred to a 50-ml polypropylene centrifuge vial, using methylene chloride as the suspension medium for an easy and complete transfer, then dried in vacuum. A cocktail of TFA/m-cresol/TIPS/water (90:5:2.5:2.5, v %) was added (1000 uL for 1 umol resin), the cleavage/deprotection procedure was carried out at room temperature on an orbital shaker for 3 hrs at 160 cpm. The resin was then filtered out, the filtrate (˜1 mL) was mixed with 40-mL of cold anhydrous ether (0-5 Celsius degree), a significant amount of off-white loose precipitate appeared. The precipitate was collected and vacuum-dried after high-speed centrifuge (4500 cpm, 20 minutes) on a WAVERLY fixed-angle centrifuge. The crude solid was redissolved in about 300 ul of water for HPLC purification.


c) HPLC Purification of Fmoc-ON XNA

Our Agilent HPLC 1100 system consists of a G1322A degasser, G1311A Quaternary Pump, G1313A automatic sampler, G1316A column compartment with temperature control and G1315B diode array detector.


A typical HPLC purification run is conducted as below on a Aeris peptide XB-C18 RP-HPLC column (100×4.5 mm, 3.6 um particle size): 5%-29% gradient of mobile phase B in 0-28 minutes (mobile phase A: 0.1% TFA in water; mobile phase B: 0.1% TFA in acetonitrile) for elation of the XNA product and byproduct peaks, followed by 29%-60% wash for 4 minutes (28-32 min), and then 60%-5% wash back to equilibrate the column for the next run (32-36 min). Other parameters: 1.0 ml/min flow rate, column temperature 50.0+/−0.5 Celsius degree, UV detection at 260 nm and 205 nm simultaneously (detecting DNA base and TFA impurity respectively), a single sample injection as 100 ul each run.


The XNA product peak fractions (a main and sharp peak usually in the range of 17-23 min) were collected and combined, as the eluted solution of purified XNA (Fmoc-ON version).


d) Lyophilization of Fmoc-ON XNA

The purified Fmoc-ON XNA solution (in mixed solvent of water and acetonitrile, with 0.1% TFA) was transferred to a 50-ml centrifuge vial (polypropylene) and frozen either in cold bath of dry-ice/acetone or −80 Celsius degree freezer, then subjected to lyophilization.


A 1200-ml LABCONCO flask including the frozen sample vial(s) was attached to a port of multifold of a LABCONCO desktop lyophilizer (Freezone 4.5 model) which was already stabilized at −40 Celsius degree and approximately 100 microbar (0.1 mmHg). The process continued usually for 8-48 hours depending on total sample volume. Upon completion of this process, a loose and white solid was obtained as the dried XNA product (Fmoc-ON version).


This version of purified XNA can be used directly after being re-dissolved in water or TE buffer. The product quantity can be calculated by the base concentration measured at 260 nm and the XNA solution total volume, then the synthetic yield (%) can be calculated. MALDI-TOF mass spectrum of the synthesized XNA (Fmoc-ON version) was measured on Shimadzu Axima MALDI-TOF mass spectrometer and data was recorded, using sinapinic acid as the matrix and the bovine cytochrome C protein as the molecular weight reference standard. If even higher water solubility is mandatory, then the deprotection of the terminal Fmoc group of the purified XNA above can be further processed, see Step (e) and Step (f) below.


e) Additional D-Lysine Fmoc Deprotection and Further HPLC Purification

The purified XNA above is redissolved in small amount of DMF (e.g. 300 ul for each micromole), then a calculated amount of piperidine was added in at room temperature so as to make it a 10% piperidine/DMF solution, the deprotection only took a few minutes to complete. Following the deprotection, 40-ml of cold anhydrous ether is added to precipitate the crude product.


Another round of HPLC was repeated with the conditions listed above, the Fmoc-OFF XNA peak comes out earlier, usually in the range of 10-15 min window due to its increased hydrophilicity and thus less stronger adsorption on the RP-HPLC column. All product fractions were collected and combined.


f) Further Lyophilization and Formulation

Lyophilization procedure is similar to the procedure (d) described above, during which the acetonitrile and TFA can be completely removed, leaving a final powder product of XNA (Fmoc-OFF version).


The product quantity can be calculated by the base concentration measured at 260 nm and the XNA solution total volume, and then the synthetic yield (%) can be calculated.


MALDI-TOF mass spectrum of the synthesized XNA (Fmoc-OFF version) was measured on Shimadzu Axima MALDI-TOF mass spectrometer and data was recorded, using sinapinic acid as the matrix and the bovine cytochrome C protein as the molecular weight reference standard.


The powder XNA is then redissolved in either pure water or TE buffer, as an aqueous solution of typically 200 micromolar concentration. The resulting solution can be either directly used for the subsequent XNA clamping-based qPCR or aliquoted (e.g. 50 ul=10 nmol) for lyophilization again to store for long term.


Other XNA oligomers can be synthesized in a similar fashion composed partially or entirely of oxy-aza, aza-aza and/or sulfa-aza (thio-aza) XNA monomers.


Example 7
XNA-Based OPTISEQ™ Lung and Colorectal Cancer Dual Cancer Panel, a High Sensitivity Method for Cancer Diagnostic
Patient Eligibility

Patient eligibility criteria included, histological or cytological diagnosis of advanced solid cancer, potential candidates for phase I/II clinical trials, at least one biopsiable lesion, laboratory parameters safe for tumor biopsy and written voluntary informed consent.


DNA Extraction

The DNA of lung/Colorectal Cancer patients' samples were manually extracted using QIAamp DNA FFPE Tissue Kit (Qiagen, Venlo, Limburg, Netherlands) following the manufacturer's protocol. Eluted DNA was measured using Qubit™ dsDNA HS Assay kit (ThermoFisher Scientific Corp., Waltham, Mass., USA), according to the manufacturer's recommendations. At least 10 ng DNA was obtained for each sample for following amplicon sequencing.


Preparation of Genomic DNA Reference Standard Mix

17 Cell line genomic DNA containing specific human cancer mutation were obtained from Horizon Discovery (Horizon Discovery Group plc, Waterbeach, UK) and other commercial vendors. Wild type human gDNA controls were obtained from Bioline (London, UK). Human gDNA containing cancer mutants were pooled in equal amount, and then mixed with wild type controls to reconstitute human tumor samples containing 0.00%, 0.10% 0.25%, 0.50% and 1.25% of mutant alleles in 17 hotspots mutants covered by OptiSeq™ lung and colorectal cancer mini panel. 10 ng of tumor samples/reference genomic DNA standard mix were used for library preparation.


Primers and XNA Mix

The experiment was conducted using OptiSeq™ lung and colorectal cancer mini panel in the presence and absence of XNA oligomers pool (a mixture of 13 XNAs). OptiSeq™ lung and colorectal cancer mini panel contains PCR primers for amplification of 13 amplicons, which cover 17 hotspots in 7 frequently mutated oncogenes. 17 mutations and corresponding drug therapy and related diseases were summarized in Table 18 (Supplementary to Table 11). Primer sequences and corresponding hotspot covered information were listed in Table 19 (Supplementary to Table 12). It also contains 13 XNAs individually designed and optimized for enrichment of mutant alleles targeted by 13 amplicons. These genes, hotspots and XNAs covered by OptiSeq™ Nano panel V2 are illustrated in Table 11. PCR primer concentration of OptiSeq™ lung and colorectal cancer dual cancer panel in reaction was 100 nM.


For some of XNAs, they are able to target for more than one mutant hotspot present in same amplicon, due to close approximate locations. For example, XNA “NRAS A59” are able to target for hotspots “NRAS A59” and “NRAS Q61”. In this case, only a single XNA “NRAS A59” is applied to enrich these two hotspots. The classifications of mutation type of each hotspot are included in Table 11, as well.


Library Preparation

Libraries were prepared by using in-house developed protocol. The protocol is for targeted enrichment sequencing. The details of protocol was attached as supplementary file at the end of this article. There are six steps in total and required reagents and vendors' information were listed in Table 12. Amongst 6 steps, two PCR reaction steps are included 1st Target PCR Amplification and 2nd Indexing PCR Amplification. 1st Target PCR Amplification: 95° C. for 10 mins; 18 cycles for 98° C. for 15 sec; 60° C. for 5 mins; then 10° C. until being used for next 1st Beads Clean-up Step. While for PCR protocol of 2nd Indexing PCR Amplification: 98° C. for 30 sec; 12 cycles at 98° C. for 10 sec; 60° C. for 20 sec; 72° C. for 10 sec; Keep samples at 10° C. until being used for next 3rd Beads Clean-up Step. At 3rd Beads Clean-up, 10 μL elution nuclease-free water is used to elute and dissolve the library. Qubit 4 Fluorometer instrument (Thermo Fisher Scientific, MA, USA) was applied to quantify library. All libraries for one sequencing run were pooled together with equimolar amount. Pooled library was quantified by Qubit as well. Agilent 2100 BioAnalyzer (Agilent Technologies, CA, USA) was applied to make sure the targeted amplicons of pooled library fall within the expected range.









TABLE 11







Gene and Hotspots covered OptiSeq ™ Nano Panel V2 as well as corresponding


XNA information















Hotspots



XNA



Gene
Covered by
Mutation


Concentration,


Hotspots #
Name
XNA
Type
XNA #
XNA Name
nM
















1
NRAS
A59
SNV
1
NRAS A59
200


2
NRAS
Q61
SNV


3
NRAS
G12
SNV
2
NRAS G12
8


4
NRAS
G13
SNV


5
CTNNB1
S45
Deletion
3
CTNNB1 S45
100


6
PIK3CA
H1047
SNV
4
PIK3CA H1047
15


7
APC
E1309
Deletion
5
APC E1309
200


8
EGFR
G719
SNV
6
EGFR G719
300


9
EGFR
E746-A750
Deletion
7
EGFR E746-
300







A750


10
EGFR
T790
SNV
8
EGFR T790
30


11
EGFR
L858
SNV
9
EGFR L858
100


12
BRAF
V600
SNV
10
BRAF V600
70


13
KRAS
A146
SNV
11
KRAS A146
250


14
KRAS
A59
SNV
12
KRAS A59
550


15
KRAS
Q61
SNV


16
KRAS
G12
SNV
13
KRAS G12
30


17
KRAS
G13
SNV









Sample Sequencing and Data Analysis

MiSeq Sequencing System (Illumina Inc., US) was applied to sequence the libraries. Sample sheet was generated by using Illumina Experiment Manager version 1.11.0. “Fastq Only” was chosen as the application of this sequencing run. TruSeq HT was chosen as the selected barcodes. Cluster density of sequenced pooled libraries should fall within the range from


800-1200 K/mm2, otherwise being deemed as failing QC criteria. Besides cluster density, clusters passing filter (>90%) and Q30 score (>90%) are included in quality control criteria to evaluate the sequencing quality. After sequencing is done, resulting fastq data of each sample was analyzed using Biomedical Genomics Workbench (Qiagen, Hilden, Germany) to generate calls and allele frequency reports. The experiment and data analysis workflows are shown in FIG. 14.









TABLE 12







Brief summary of library preparation protocols and


required reagents/volume information









Step Name
Reagents (Volume, μL)
Vendor





1st Target PCR
2X mPCR Premix (5)
DiaCarta, Inc


Amplification
OptiSeqTM Lung and Colorectal
DiaCarta, Inc



Cancer Mini Panel (1)
DiaCarta, Inc



OptiSeq ™ XNA Mix (1)
Horizon Discovery Group plc



DNA Template (1~3)
GE Healthcare Life Science



Nuclease-free Water (0~2)
N/A



Total (10)


1st Bead Cleanup
PlexPure Magnetic Beads (13)
DiaCarta, Inc



70% Ethanol (Details in
DiaCarta, Inc



Supplementary)
GE Healthcare Life Science



Nuclease-free Water


Non-Specific Amplicon
20X mPCR Cleanup Mix (1)
DiaCarta, Inc


Digestion
10× mPCR Cleanup Buffer (2)
DiaCarta, Inc



10× Cleanup Stop Buffer (2)
DiaCarta, Inc



Nuclease-free Water (7)
GE Healthcare Life Science


2nd Bead Cleanup
PlexPure Magnetic Beads (29)
DiaCarta, Inc



70% Ethanol
DiaCarta, Inc



Nuclease-free Water
GE Healthcare Life Science


2nd Indexing PCR
2X Indexing PCR Premix (10)
DiaCarta, Inc


Amplification
Index Primer (10 μM) (2)
DiaCarta, Inc


3rd Bead Cleanup
PlexPure Magnetic Beads (18)
DiaCarta, Inc



70% Ethanol
DiaCarta, Inc



Nuclease-free Water
GE Healthcare Life Science









Investigate the XNA Enrichment Effects on Variant Allelic Frequency

Effects of 13 XNAs mix on blocking wild type alleles and enrichment of mutant alleles were investigated by performing multiplexing PCR on control cell line human tumor gDNA samples containing low percentage of cancer mutant variant alleles frequency (VAF, 0.00%, 0.10%, 0.25%, 0.50%, and 1.25%) in wild type background, in the presence and absence of XNA oligomers. Results from six experimental replicates were obtained for each type of human standard reference sample mix to evaluate assay reproducibility. After indexing PCR, libraries were pooled and sequenced using Illumina MiSeq and resulting fastq data of each sample was analyzed using Biomedical Genomics Workbench to generate calls and allele frequency reports. The experiment and data analysis workflows are shown in FIG. 14.


Determine the Correlation of Enriched Variant Frequency and Original Variant Frequency

To determine the relationship between enriched variant allelic frequency (Enriched VAF) and original allelic frequency (Original VAF), cell line human tumor gDNA samples containing same frequency cancer mutant alleles (0.00%, 0.50%, 1.00%, 2.50%, 5.00%, 10.00% and 15.00% VAF) were prepared in wild type background, in the presence and absence of XNA oligomers. Six experimental replicates were obtained for each condition. After indexing PCR, libraries were pooled and sequenced using Illumina MiSeq and resulting fastq data of each sample was analyzed using Qiagen Biomedical Genomics Workbench to generate calls and allele frequency reports. The experiment and data analysis workflows are shown in supplementary FIG. 13.


Verification Study of XNA Enrichment Effects on Patients' Samples

Effects of 13 XNAs mix on detecting the VAF % of lung and colorectal cancer patients' samples were also investigated. Total 36 patient samples were investigated in this study (14 lung cancer and 10 colorectal Formalin-Fixed, Paraffin-Embedded (FFPE) patients, 10 lung Cancer and 2 colorectal cell-free DNA patients' samples were investigated in this validation experiment. 2 replicates of each patient samples were included. 10 ng DNA (Maximum DNA amount of cfDNA samples input were used due to the limited amount of the DNA, Maximum amount DNA is 10 ng) for each library construction procedure. The experiment and data analysis workflows are the same as the above protocols.


Xenonucleic Acids Structure and its Function

Xenonucleic acids (XNA), are innovative new nucleic acid molecular oligomers that hybridize by Watson-Crick base pairing to target DNA sequences yet have a modified chemical backbone. XNA oligomers are highly effective at hybridizing to targeted normal DNA sequences and can be employed as molecular clamps in quantitative real-time polymerase chain reactions (PCR) or as highly specific molecular probes for detection of nucleic acid target sequences. The XNA tightly binds to the wild-type sequence that is 100% complementary in sequence and blocks DNA polymerase from DNA elongation; only the mutant target sequence gets amplified because the XNA:mutant DNA duplex is not stable due to mismatch and fall off from the template in PCR reactions.


Effects of XNAs Mix on Enrichment of Mutants in Human Reference Standard gDNA Mix Samples


XNAs mix was spiked into the PCR reaction containing OptiSeq™ Dual Cancer Panel primer mix and human reference standard gDNA control samples containing mutants at different abundance levels. The estimated VAFs of 17 hotspots in human tumor samples were at 0.00%, 0.10%, 0.25%, 0.50% and 1.25%, respectively, of which mutant copy number at 5 different frequency were 0, 3, 8, 17 and 42, respectively.


The detected VAFs by Next Generation Sequencing are shown in FIG. 8. The mutant detection powered by the XNAs mix was dramatically boosted. There were, on average, 32.0, 23.7, 25.0 and 18.4 folds of increase in VAF for synthetic tumor samples with 0.10%, 0.25%, 0.50% and 1.25% mutants, respectively.


On samples originally with 1.25% of mutants, in 14 of 17 hotspots, observed VAFs were more than 10% after XNA enrichment. This result suggested that XNA is able to enrich mutant alleles and make high confidence calls. It is also noticeable that some hotspots were enriched less efficiently than others. For example, “CTNNB1 S45del” was enriched from 0.96% to 7.82%. In addition, “KRAS Q61L” was merely enriched from 1.16% to 2.80%. Furthermore, “NRAS Q61H” was enriched from 0% to 1.15%, after adding XNA. These results suggested that the design of XNA and/or experimental condition should be further improved.


In samples containing 0.00% mutants or negative controls, the VAFs were either small or undetectable. The reason for detection of mutants in negative control in the presence of XNA is likely due to low level of DNA contamination from environment or some unknown mutations present in cell line DNA controls from commercial vendors.


XNA-NGS Reduce the Sequencing Coverage to Achieve Required Sensitivity

Sufficient sequencing coverage is necessary to get reliable results for mutant detection. One of the concerns of using XNA for blocking wild type DNA amplification is that it may also eliminate amplicons for mutant detection. The total coverage of each locus after XNA enrichment PCR is displayed in FIG. 9 and Table 13, and Table 20 (Supplementary to Table 13). Average coverage per hotspot in reference standard gDNA mix samples containing 0.10%, 0.25%, 0.50% and 1.25% of mutants upon XNA enrichment were, 603x, 434x, 556x, and 1156x, respectively. Although the average total coverage of sample was relatively low compared to those without XNA, average variant number per hotspot gets boosted by 9.1×, 5.3×, 8.4×, and 10.9×, respectively after XNA enrichment in gDNA samples with original VAF % 0.10%, 0.25%, 0.50% and 1.25%. Hence, there is enough confidence to identify mutants 0.1% VAF even at relative lower coverage 500×. comparing to classic NGS (without XNA) needs 2000× coverage to achieve 1% sensitivity.


Effects of XNAs Mix Enhance NGS Mutation Reading Number

XNA is designed for blocking amplification of wild type DNA, which leads to increase of the percentage mutant DNA in amplified product. This mutant enrichment mechanism is illustrated in FIG. 7c. As a result, it is expected that more variants will be detected in library prepared after XNA enrichment than library prepared without XNA enrichment, on the same sample and in same number of reads.


From FIG. 10, Table 13 and Table 20 (Supplementary to Table 13), on average, the NGS read number of mutants at each hotspot in samples with mutant VAF of 0.10% were 7 and 41, without or with XNA enrichment, respectively. Similarly, for samples with mutant VAF at 0.25%, 0.50%, and 1.25%, average number of NGS reads containing mutant alleles at each hotspot were 17 and 49, 33 (without XNA) and 125, and 83 and 443 with XNA enrichment, respectively, which results in 9.1, 5.3, 8.4, and 10.9 folds enrichment. This result demonstrated that XNA can selectively block amplification of wild type DNA, which leads to increase of VAF of mutants in amplified library.


Detected VAF of 14 hotspots in gDNA reference standard samples with original VAF at 1.25% without or with XNA enrichment are shown in FIG. 11. There are 14 panels, each containing summary of analysis results of one mutant targeted by XNA. For instance, panel in column 1 (from left) and row 2 (from top) is a summary for “EGFR G719S” mutation. The table displayed on left side of the panel contains detected VAF %, total coverage, and variant number of EGFR G719S mutation. The IGV allele coverage plots (noise allele frequency cut off at 4%) on the right side of the panel contains 8 tracks, each from a single sample. The top six tracks are from 6 replicates in XNA enrichment experiment. The bottom two tracks are from two control experiments without XNA enrichment. The wild type reference and mutant alleles for “EGFR G719S” are G (Brown Color) and A (Green Color), respectively. They are shown as G>A in the inset of the plot. It is clear to see that XNA enrichment is specific to the targeted alleles in each amplicon and the effect of enrichment is very robust in all hotspots shown in the figure.


The Correlation of Enriched Variant Frequency (Enriched VAF) and Original Variant Frequency (Original VAF)

XNAs mix was spiked into the PCR reaction containing OptiSeq™ Dual Cancer Panel primer mix and human reference standard gDNA control samples containing mutants at different abundance levels. The estimated VAFs of 17 hotspots in human tumor samples were at 0.00%, 0.50%, 1.00%, 2.50%, 5.00%, 10.00% and 15.00% respectively, of which mutant copy number at 7 different frequency were 0, 17, 83, 167, 333, and 500 copies, respectively.


The average (Mean) variant allelic frequency (VAFs) with by Next Generation Sequencing, in present and absent of XNAs mix are summarized in Table 21 (Supplementary to Table 14)-A and Table 14-B. As expected, mutant detection powered by XNAs mix was dramatically boosted. To get the relationship between enriched VAF and original VAF of the sample, 17 graphs for 17 hotspots (Enriched VAF against Original VAF) were drafted in the FIG. 12 and S. FIG. 8. From the experiment results, we found out relationship between enriched VAF and original VAF tends to be linear when original VAF is less than 2.00%, while it tends to be polynomial with order 2 when original VAF is more than 2.00%. To get the regression model for each hotspot at different original VAF, we chose original VAF 2.00% as the cut-off value to fit the data less than 2.00% to the linear model, for data points with original VAF more than 2.00%, they were fitted to the polynomial with order 2 model. For example, KRAS A146T from FIG. 12, data on horizontal axis reflects original VAF (less than 2.00%), while those on vertical axis are enriched VAF. These data points fit in the regression equation y=36x with confidence R2=0.9517. For the original VAF of KRAS A146T more than 2.00%, data points fit polynomial with order 2 equation y=−2.3889x2+27.709x well with confidence R2=0.9865. Regression equations of 17 hotspots were summarized in Table 22-A (Supplementary to Table 15) (Original VAF less than 2.00%) and Table 22-B (Original VAF more than 2.00%). 14 out of 17 hotspots (82.35%) achieved a high confidence level with R2 more than 0.9 (Table 22-A), while 11 out of 17 hotspots (64.17%) with original VAF more than 2.00% achieved a high confidence level with R2 more than 0.9 (Table 22-B), which gave us confidence to draw the conclusion that relationship between enriched VAF and original VAF less than 2.00% is linear, while those fit in polynomial with order 2 when original VAF is more than 2.00%.


On average, enriched VAF, original VAF, the number of mutants at each hotspot with original VAF at 6 variant allelic frequency at 0.50%, 1.00%, 2.50%, 5.00%, 10.00%, and 15.00% were summarized in Table 14-A (0.50%, 1.00%, and 2.50%) and Table 14-B (5.00%, 10.00%, and 15.00%). As expected, mutant detection powered by XNAs mix was dramatically boosted. Average enriched VAF for 17 hotspots were enriched by 48.8, 33.4, 12.5, 9.4, 6.8, and 5.0 folds compared to samples with estimated original VAF 0.50%, 1.00%, 2.50%, 5.00%, 10.00%, and 15.00%. Meanwhile, the average total coverage in presence or absence of XNAs mix were comparable. Enriched VAF in presence of XNAs mix ensures higher amount of detectable mutants in the sample. The results showed that average boost folds of mutant number in samples with original VAF 0.50%, 1.00%, 2.50%, 5.00%, 10.00%, and 15.00% are 9.8, 10.2, 5.5, 3.8, 3.8, and 4.8, respectively compared to samples without XNAs mix. This result further demonstrates that XNA can selectively block amplification of wild type DNA, which leads to increase of VAF of mutants in amplified library.


In samples containing 0.00% mutants or negative controls, the VAFs were either small or undetectable. The reason for detection of mutants in negative control in the presence of XNA is likely due to low level of DNA contamination from environment or some unknown mutations present in cell line DNA controls from commercial vendors.


Verification of XNA-Based Assay by FFPE Patient Samples

14 lung cancer FFPE samples and 10 colorectal cancer FFPE samples were applied to investigate the enriched effects of XNAs mix on real patient samples. Average detected VAF in presence and absence of XNAs mix were summarized in Table 15a (14 lung cancer FFPE samples and triplicate tests for each sample) and Table 15b (10 colorectal cancer FFPE samples, one replicate test for each sample). Detected mutations in patients' samples were compared against wild type healthy patient, the mutations detected in healthy people as well in presence of XNAs mix were filtered out in the patients' samples. For patient with ID 16A130, two mutations were detected by sequencing without XNAs mix, they are BRAF V600E (VAF=20.4%) and EGFR L858R (VAF=2.08%). After adding XNAs mix into the patient samples, 6 more mutations were detected (Table 15a). These 6 new mutations were not be able to be detected by normal sequencing method due to the super lower frequency of the samples. Meanwhile, the detected VAF of BRAF V600E increased to 77.17% from original VAF 20.4% and EGFR L858R of which increased from VAF 2.08% to 43.42% after adding XNAs mix. Due to the enriched VAF, mutant number of EGFR L858R increased to 116 from 79, while for the BRAF V600E, despite the enriched VAF, total coverage of loci BRAF V600 was only 242X with XNAs mix compared to that of patient without XNAs mix, that is 4807X, which resulted in decreased number of mutants after adding XNAs mix. Similar phenomena happened to the rest of 13 samples. Despite slight inconsistency with previous results of cell line genomic DNA samples, the overall boost folds of mutant number with XNAs mix is 1.33 times of those without XNAs mix, while the overall boost folds of VAF is 5.21 times of those without XNAs mix. For wild type control, we did not see any such mutants detectable. without XNA, the clinical assay sensitivity for lung cancer is about 86% (12/14 patients). With XNA, its clinical assay sensitivity for lung cancer is 100% (14/14 patients).


Similarly result was saw for colorectal cancer FFPE samples. From results in Table 15b, overall boost folds of mutant number with XNAs mix is 3.32 times of those without XNAs mix, while the overall boost folds of VAF is 4.40 times of those without XNAs mix. Clinical sensitivity for normal NGS is about 70% (7/10 patients). However, with XNA technology, clinical sensitivity is about 100% (10/10 patients). Wild type sample did not have any mutations detectable.


Verification of XNA-Based Assay with Cell Free DNA (cfDNA) Patient Samples


10 lung cancer cfDNA samples and 2 colorectal cancer cfDNA samples were applied to investigate the enriched effects of XNAs mix on real patient samples. Average detected VAF in presence and absence of XNAs mix were summarized in Table 16. The analysis criteria is the same with that of 6.1. One replicate was conducted for each experiment due to the limited amount of cfDNA. For most of the libraries, DNA inputs varied and were less than 10 ng, information of DNA input amount was included in the Table 10. The maximum DNA input for each library was 10 ng. The experiment results for both Lung cancer patient and colorectal cancer patient were included in single table (Table 10). Similar to results of FFPE samples, XNAs mix made mutation with low frequency detectable, at the same time, it enriched the VAF and increased mutant readable number in the sequencing pool. For example, patient ID D1729-B, the original VAF of EGFR L858R without XNA was 2.00%, while the enriched VAF was 40.37% after adding XNAs mix. Despite decreased total coverage from 3549 (without XNAs mix) to 379 (with XNAs mix), the mutant readable number increased to 153 from 71 after XNAs mix enrichment. Similar to Lung cancer cfDNA sample, colorectal cfDNA patients samples showed a similar results compared to those of lung cancer cfDNA. The overall boost folds of mutant number with XNAs mix is 1.10 times of those without XNAs mix, while the overall boost folds of VAF is 8.16 times of those without XNAs mix.









TABLE 13







Summary Table for the Effects of XNA mix on Detected Variant Allelic Frequency (VAF) and Coverage of sample


using OptiSeq ™ Lung and Colorectal Cancer Mini Panel, 0.10% and 0.25%










Variant Allelic Frequency, 0.10%
Variant Allelic Frequency, 0.25%




















Frequency





Frequency








without
# of
Frequency
# of
Mutant

without
# of
Frequency
# of
Mutant



XNA,
Mutants
with XNA,
Mutants
#
VAF
XNA,
Mutants
with XNA,
Mutants
#
VAF



% (Total
without
% (Total
with
Boost
Boost
% (Total
without
% (Total
with
Boost
Boost


Hotspot Name
Coverage)
XNA
Coverage)
XNA
Folds
Folds
Coverage)
XNA
Coverage)
XNA
Folds
Folds






















KRAS A146T
0.25 (3324)
8
12.68 (477) 
60
7
50.7
0.62 (3324)
21
26.05 (377) 
98
5
42.0


KRAS G13D
0.16 (1098)
2
2.59 (204)
5
3
16.2
0.41 (1098)
5
5.82 (136)
8
2
14.2


NRAS A59T
0.08 (2288)
2
 3.89 (1176)
46
25
48.6
0.21 (2288)
5
11.94 (485) 
58
12
56.9


EGFR T790M
0.09 (3396)
3
 2.88 (1353)
39
13
32.0
0.23 (3396)
8
5.97 (849)
51
6
26.0


EGFR G719S
1.01 (5624)
57
94.43 (313) 
296
5
93.5
2.52 (5624)
142
94.22 (386) 
364
3
37.4


NRAS Q61H
0.05 (1436)
1
0.16 (87) 
0
0
3.2
0.14 (1436)
2
0.68 (289)
2
1
4.9


NRAS G12V
0.08 (1495)
1
3.03 (119)
4
3
37.9
0.21 (1495)
3
5.6 (91)
5
2
26.7


PIK3CA
0.71 (1879)
13
10.98 (499) 
55
4
15.5
1.77 (1879)
33
17.22 (312) 
54
2
9.7


H1047R


EGFR E746-
0.06 (3424)
2
3.36 (845)
28
14
56.0
0.14 (3424)
5
7.03 (527)
37
8
50.2


A750


EGFR L858R
0.08 (2651)
2
 3.33 (1590)
53
25
41.6
 0.2 (2651)
5
3.58 (966)
35
7
17.9


BRAF V600E
0.68 (2356)
16
12.04 (505) 
61
4
17.7
 1.7 (2356)
40
19.28 (278) 
54
1
11.3


KRAS G12D
0.17 (1099)
2
6.98 (180)
13
7
41.1
0.42 (1099)
5
14.28 (136) 
19
4
34.0


NRAS G13D
0.08 (1012)
1
3.35 (105)
4
4
41.9
 0.2 (1012)
2
4.6 (54)
2
1
23.0


APC E1309fs*
0.08 (1771)
1
1.68 (845)
14
10
21.0
0.21 (1771)
4
2.09 (367)
8
2
10.0


KRAS A59T
0.05 (1633)
1
 1.14 (1896)
22
26
22.8
0.12 (1633)
2
 3.23 (1247)
40
21
26.9


CTNNB1
0.102 (65)  
0
0.45 (62) 
0
4
4.4
0.255 (65)  
0
1.85 (110)
2
12
7.3


S45del


KRAS Q61L
0.05 (1564)
1
 0 (0)
0
0
0.0
0.12 (1564)
2
0.53 (772)
4
2
4.4















Average Total
2121
603
9.1
32.0
2121
434
5.3
23.7


Coverage
















TABLE 14-A







Summary for the Effects of XNA mix on Detected Variant Allelic Frequency (VAF) and Coverage of sample using


OptiSeq ™ Lung and Colorectal Cancer Mini Panel, 0.50%, 1.00%, and 2.50%











Variant Allelic Frequency, 0.50%
Variant Allelic Frequency, 1.00%
Variant Allelic Frequency, 2.50%


























Frequency

Frequency



Frequency





Frequency








without
# of
with
# of
Mutant

without
# of
Frequency
# of


without
# of
Frequency
# of
Mutant



XNA, %
Mutants
XNA, %
Mutants
#
VAF
XNA, %
Mutants
with XNA,
Mutants
Mutant #
VAF
XNA, %
Mutants
with XNA,
Mutants
#
VAF


Hotspot
(Total
without
(Total
with
Boost
Boost
(Total
without
% (Total
with
Boost
Boost
(Total
without
% (Total
with
Boost
Boost


Name
Coverage)
XNA
Coverage)
XNA
Folds
Folds
Coverage)
XNA
Coverage)
XNA
Folds
Folds
Coverage)
XNA
Coverage)
XNA
Folds
Folds




























KRAS
 1.04 (2267)
29
41.52 (336)
139
5
39.9
2.05 (2239)
45
52.26 (377)
198
4
25.5
5.99 (1845)
111
81.22 (751)
610
5
13.6


A146T


KRAS
 0.6 (616)
7
 9.59 (198)
19
3
16.0
1.47 (1089)
16
15.72 (301)
46
3
10.7
4.49 (930) 
41
22.33 (478)
106
3
5.0


G13D


NRAS
0.17 (457) 
5
20.72 (625)
131
26
121.9
0.77 (1520)
14
25.89 (965)
254
18
33.6
2.89 (1624)
48
 57.69 (1019)
581
12
20.0


A59T


EGFR
0.14 (603) 
5
15.04 (816)
125
25
107.4
0.73 (1791)
19
 19.08 (1121)
215
11
26.1
2.15 (2636)
57
 43.53 (1093)
471
8
20.2


T790M


EGFR
 4.14 (3929)
162
98.19 (574)
563
3
23.7
9.54 (3373)
328
 98.93 (1274)
1261
4
10.4
22.51 (3517) 
792
 99.53 (2733)
2720
3
4.4


G719S


NRAS
0 (0)
0
 1.16 (577)
8
N/A
N/A
0.45 (1063)
10
 2.8 (966)
27
3
6.2
2.31 (1624)
38
 5.69 (1022)
61
2
2.5


Q61H


NRAS
0 (0)
0
 4.48 (153)
6
N/A
N/A
0.3 (316)
3
20.02 (187)
39
13
66.7
2.58 (1099)
29
24.93 (192)
48
2
9.7


G12V


PIK3CA
 2.82 (1849)
53
 5.29 (7052)
376
7
1.9
6.11 (1404)
86
 13.9 (5804)
723
8
2.3
17.49 (1214) 
212
 30.01 (5776)
1717
8
1.7


H1047R


EGFR
0 (0)
0
35.58 (178)
65
N/A
N/A
0.29 (1327)
12
47.85 (253)
121
10
165.0
1.44 (3708)
54
 69.8 (352)
246
5
48.5


E746-


A750


EGFR
0 (0)
0
11.76 (891)
101
N/A
N/A
0.55 (963) 
11
 17.85 (1130)
202
18
32.5
1.96 (1867)
36
 36.74 (1144)
422
12
18.7


L858R


BRAF
 3.31 (2085)
69
38.32 (345)
132
2
11.6
6.44 (1815)
118
52.92 (584)
310
3
8.2
16.07 (2030) 
328
75.23 (814)
613
2
4.7


V600E


KRAS
0.31 (447) 
4
25.25 (197)
51
13
81.5
1.28 (957) 
15
37.87 (299)
114
8
29.6
4.02 (930) 
37
59.79 (477)
288
8
14.9


G12D


NRAS
0.15 (265) 
2
 5.27 (129)
9
5
35.1
0.52 (637) 
7
13.63 (187)
25
4
26.2
2.61 (1098)
28
25.09 (192)
49
2
9.6


G13D


APC
0 (0)
0
 6.95 (397)
31
N/A
N/A
0.23 (301) 
4
11.21 (609)
67
17
48.7
1.71 (1452)
25
26.03 (422)
116
5
15.2


E1309fs*


KRAS
0 (0)
0
 6.09 (1695)
101
N/A
N/A
0.27 (618) 
5
 8.06 (1988)
159
32
29.9
1.92 (1621)
31
 22.34 (1597)
352
11
11.6


A59T


CTNNB1
0 (0)
0
3.26 (89)
4
N/A
N/A
0.51 (66) 
1
 6.79 (114)
8
8
13.3
1.86 (220) 
4
15.09 (90) 
14
4
8.1


S45del


KRAS
0 (0)
0
 1.28 (1696)
22
N/A
N/A
0 (0) 
0
 3.08 (1991)
62
N/A
N/A
2.08 (1622)
33
 7.56 (1600)
119
4
3.6


Q61L



















Average
736
938
9.8
48.8
1146
1068
10.2
33.4
1708
1162
5.5
12.5


Total


Coverage
















TABLE 14-B







Summary for the Effects of XNA mix on Detected Variant Allelic Frequency (VAF) and Coverage of sample using


OptiSeq ™ Lung and Colorectal Cancer Mini Panel, 5.00%, 10.00%, and 15.00%











Variant Allelic Frequency, 0.50%
Variant Allelic Frequency, 1.00%
Variant Allelic Frequency, 2.50%


























Frequency





Frequency





Frequency








without
# of
Frequency
# of
Mutant

without
# of
Frequency
# of


without
# of
Frequency
# of
Mutant



XNA, %
Mutants
with XNA,
Mutants
#
VAF
XNA, %
Mutants
with XNA,
Mutants
Mutant #
VAF
XNA, %
Mutants
with XNA,
Mutants
#
VAF


Hotspot
(Total
without
% (Total
with
Boost
Boost
(Total
without
% (Total
with
Boost
Boost
(Total
without
% (Total
with
Boost
Boost


Name
Coverage)
XNA
Coverage)
XNA
Folds
Folds
Coverage)
XNA
Coverage)
XNA
Folds
Folds
Coverage)
XNA
Coverage)
XNA
Folds
Folds




























KRAS
3.19 (1226)
39
64.13 (292)
187
5
20.1
    6.53
83
 80.6 (445)
358
4
12.3
 6.53 (1539)
100
 76.8 (871)
669
7
11.8


A146T






(1253)


KRAS
5.73 (777) 
44
10.17 (799)
70
2
1.8
    6.71
69
17.76 (380)
67
1
2.6
12.72 (907) 
117
26.15 (685)
179
2
2.1


G13D






(1015)


NRAS
7.87 (2333)
182
 84.13 (1549)
1306
7
10.7
   12.06
190
 89.93 (1694)
1523
8
7.5
20.29 (980) 
197
94.07 (2442)
2296
12
4.6


A59T






(1568)


EGFR
3.06 (3836)
122
59.22 (914)
542
4
19.4
    7.43
198
 76.21 (1355)
1026
5
10.3
15.31 (2535)
388
83.45 (3538)
2952
8
5.5


T790M






(2680)


EGFR
22.68 (4879) 
1108
 99.51 (2181)
2170
2
4.4
   19.38
578
 98.85 (1310)
1304
2
5.1
11.28 (4571)
517
90.81 (905)
895
2
8.1


G719S






(2983)


NRAS
2.89 (2333)
65
 2.69 (1551)
40
1
0.9
    7.06
110
 3.39 (1698)
59
1
0.5
10.85 (980) 
106
 2.83 (2446)
69
1
0.3


Q61H






(1568)


NRAS
3.93 (1756)
68
40.57 (191)
76
1
10.3
    5.03
46
30.19 (166)
50
1
6.0
9.47 (743)
71
66.06 (130)
86
1
7.0


G12V






 (921)


PIK3CA
23.77 (1746) 
418
 48.54 (4095)
1702
4
2.0
   39.28
621
 53.11 (5120)
2756
4
1.4
27.83 (1334)
373
79.36 (1309)
1023
3
2.9


H1047R






(1588)


EGFR
5.41 (4783)
256
92.11 (850)
786
3
17.0
    6.76
214
91.07 (671)
613
3
13.5
15.07 (4083)
608
93.28 (1677)
1583
3
6.2


E746-






(3185)


A750


EGFR
1.53 (1480)
22
28.31 (698)
195
9
18.5
   4.8
82
 57.35 (1054)
604
7
11.9
12.37 (1773)
219
77.01 (2442)
1884
9
6.2


L858R






(1708)


BRAF
6.06 (1584)
96
45.17 (290)
127
1
7.5
   14.01
263
71.38 (442)
316
1
5.1
55.13 (1683)
928
  95 (1596)
1516
2
1.7


V600E






(1851)


KRAS
14.32 (776) 
112
83.72 (794)
679
6
5.8
    6.78
70
68.99 (378)
263
4
10.2
10.21 (907) 
93
66.39 (683)
454
5
6.5


G12D






(1013)


NRAS
4.02 (1757)
70
23.46 (191)
46
1
5.8
    8.76
81
40.83 (166)
68
1
4.7
14.56 (825) 
122
79.98 (280)
225
2
5.5


G13D






 (920)


APC
5.07 (2120)
107
55.23 (418)
234
2
10.9
    9.89
174
68.65 (492)
329
2
6.9
11.77 (1363)
160
55.75 (956)
633
4
4.7


E1309fs*






(1752)


KRAS
2.54 (1376)
35
 27.14 (1360)
353
10
10.7
   7.1
102
 47.98 (1983)
941
9
6.8
 6.7 (1500)
101
39.64 (3756)
1484
15
5.9


A59T






(1454)


CTNNB1
4.09 (339) 
13
41.72 (95) 
41
3
10.2
    5.85
5
54.71 (74) 
41
8
9.4
12.49 (90) 
11
 55.2 (139)
77
7
4.4


S45del






 (92)


KRAS
2.56 (1376)
36
 7.97 (1360)
108
3
3.1
   18.63
271
 25.96 (1987)
521
2
1.4
29.76 (1500)
450
38.61 (3760)
1456
3
1.3


Q61L






(1453)



















Average
2028
1037
3.8
9.4
1588
1142
3.8
6.8
1607
1624
4.8
5.0


Total


Coverage
















TABLE 15a







Summary of 14 lung cancer FFPE patient detected VAF % and mutant number


changes before and after adding XNA mix
















Frequency









without
# of
Frequency
# of




XNA, %
Mutants
with XNA,
Mutants
VAF
Mutant


Patient

(Total
without
% (Total
with
Boost
# Boost


ID
Hotspots
Coverage)
XNA
Coverage)
XNA
Folds
Folds

















16A129
EGFR A750T
0 (0)
0
2.37 (440)
10
N/A
N/A



EGFR P753L
0 (0)
0
3.53 (441)
16
N/A
N/A



EGFR T790M
0 (0)
0
 5.82 (1695)
97
N/A
N/A



EGFR L858R
 86.9 (9432)
8196
 98.93 (28526)
28219
1.14
3.44


16A130
EGFR T790M
0 (0)
0
6.76 (297)
21
N/A
N/A



EGFR L858R
 2.08 (3817)
79
43.42 (267) 
116
20.88 
1.47



KRAS S145*
0 (0)
0
 4.5 (150)
7
N/A
N/A



EGFR I744-
0 (0)
0
1.73 (130)
5
N/A
N/A



L747del



EGFR A859S
0 (0)
0
1.53 (131)
4
N/A
N/A



BRAF R603Q
0 (0)
0
1.55 (113)
4
N/A
N/A



BRAF V600E
 20.4 (4807)
980
77.17 (242) 
187
3.78
0.19



BRAF R603*
0 (0)
0
3.86 (130)
10
N/A
N/A


16A131
EGFR T790M
0 (0)
0
5.36 (372)
20
N/A
N/A



EGFR L858R
0 (0)
0
1.41 (125)
4
N/A
N/A



EGFR G719S
0 (0)
0
49.18 (27) 
13
N/A
N/A



KRAS A146T
0 (0)
0
1.03 (98) 
2
N/A
N/A



BRAF V600E
13.29 (3011) 
408
68.05 (279) 
189
5.12
0.46



NRAS G12D
0 (0)
0
8.62 (15) 
3
N/A
N/A



EGFR G857R
0 (0)
0
4.77 (225)
11
N/A
N/A



EGFR L858M
0 (0)
0
1.02 (98) 
2
N/A
N/A



NRAS G13S
0 (0)
0
7.89 (19) 
3
N/A
N/A



APC E1309K
0 (0)
0
2.48 (71) 
4
N/A
N/A



APC I1311N
0 (0)
0
1.77 (71) 
3
N/A
N/A



BRAF T599K
0 (0)
0
1.25 (180)
5
N/A
N/A


16A132
EGFR T790M
0 (0)
0
  9 (219)
20
N/A
N/A



EGFR L858R
0 (0)
0
3.62 (69) 
5
N/A
N/A



NRAS L56Q
0 (0)
0
11.03 (34) 
4
N/A
N/A



EGFR G719S
0 (0)
0
35.71 (4)  
3
N/A
N/A



KRAS A146T
0 (0)
0
2.11 (71) 
3
N/A
N/A



KRAS T58L
0 (0)
0
2.05 (86) 
4
N/A
N/A



NRAS D57Y
0 (0)
0
13.1 (21) 
6
N/A
N/A



EGFR G746-
26.97 (2598) 
701
97.92 (2384)
2333
3.63
3.33



A750del



KRAS V14I
0 (0)
0
15.79 (10) 
3
N/A
N/A



KRAS G12S
0 (0)
0
15.79 (10) 
3
N/A
N/A



EGFR G746*
0 (0)
0
1.61 (125)
4
N/A
N/A



EGFR F856L
0 (0)
0
1.44 (70) 
2
N/A
N/A


16A133
EGFR T790M
0 (0)
0
1.26 (198)
5
N/A
N/A



BRAF
0 (0)
0
9.92 (91) 
9
N/A
N/A



c.1800G > T



KRAS A146T
0 (0)
0
5.92 (167)
9
N/A
N/A



APC G1312fs
0 (0)
0
1.74 (86) 
3
N/A
N/A



EGFR A859S
0 (0)
0
5.93 (68) 
8
N/A
N/A



KRAS G60D
0 (0)
0
2.28 (220)
10
N/A
N/A



PIK3CA
0 (0)
0
1.54 (818)
12
N/A
N/A



H1047Y



BRAF L601fs
0 (0)
0
1.67 (60) 
2
N/A
N/A



KRAS S145fs
0 (0)
0
1.55 (113)
4
N/A
N/A


16A134
EGFR L858R
51.02 (19)  
10
75 (3) 
2
1.47
0.20


16A135
EGFR L858R
20.53 (135)  
34
68.76 (27) 
19
3.35
0.56



EGFR K852R
0 (0)
0
20.24 (21) 
9
N/A
N/A


16A136
EGFR G719A
55.27 (160)  
89
100 (5)  
5
1.81
0.06



EGFR L858R
0 (0)
0
 85 (11)
9
N/A
N/A


16A137
EGFR A750T
0 (0)
0
8.7 (23)
4
N/A
N/A



EGFR A750E
0 (0)
0
5.43 (23) 
3
N/A
N/A



EGFR T790M
 0.49 (1186)
12
6.17 (77) 
10
12.59 
0.83



EGFR L858R
 1.03 (1557)
16
6.16 (65) 
4
5.98
0.25



PIK3CA
0 (0)
0
2.5 (40)
2
N/A
N/A



G1049D



PIK3CA
0 (0)
0
4.38 (40) 
4
N/A
N/A



D1045G



EGFR G746-
0 (0)
0
4.35 (23) 
2
N/A
N/A



T751del


16A139
EGFR A750T
0 (0)
0
1.75 (72) 
3
N/A
N/A



EGFR S752F
0 (0)
0
1.75 (72) 
3
N/A
N/A



EGFR P753L
0 (0)
0
3.42 (147)
5
N/A
N/A



EGFR T790M
0 (0)
0
3.79 (192)
15
N/A
N/A



EGFR L858R
0 (0)
0
1.11 (113)
3
N/A
N/A



KRAS G60D
0 (0)
0
1.35 (259)
7
N/A
N/A



NRAS D57Y
0 (0)
0
5.26 (38) 
4
N/A
N/A


16A140
EGFR L858R
34.31 (560)  
191
83.76 (198) 
169
2.44
0.88



KRAS S145*
0 (0)
0
15.38 (7)  
2
N/A
N/A



EGFR
0 (0)
0
6.86 (203)
13
N/A
N/A



c.2592G > A



EGFR G857R
0 (0)
0
4.83 (88) 
9
N/A
N/A



EGFR L858W
0 (0)
0
5.4 (88)
10
N/A
N/A



EGFR A864V
0 (0)
0
2.29 (88) 
4
N/A
N/A


16A141
EGFR T790M
0 (0)
0
7.03 (139)
11
N/A
N/A



EGFR G719S
0 (0)
0
18.18 (6)  
2
N/A
N/A



BRAF
0 (0)
0
4.17 (48) 
4
N/A
N/A



c.1800G > T



KRAS S145*
0 (0)
0
6.05 (123)
6
N/A
N/A



KRAS A146G
0 (0)
0
2.12 (95) 
4
N/A
N/A



PIK3CA
0 (0)
0
1.09 (92) 
2
N/A
N/A



H1047Y



KRAS G13C
14.41 (2267) 
327
43.08 (81) 
48
2.99
0.15


16A010
EGFR G719D
0 (0)
0
7.41 (14) 
2
N/A
N/A



EGFR T790M
0 (0)
0
3.69 (741)
27
N/A
N/A



EGFR
0 (0)
0
15.1 (20) 
3
N/A
N/A



c.2157C > T



BRAF
0 (0)
0
3.53 (281)
10
N/A
N/A



c.1800G > T



KRAS A146T
0 (0)
0
2.53 (301)
8
N/A
N/A



KRAS S145*
0 (0)
0
2.79 (301)
9
N/A
N/A



EGFR G857R
0 (0)
0
1.12 (444)
5
N/A
N/A



KRAS S145fs
0 (0)
0
1.05 (143)
3
N/A
N/A



NRAS G60V
0 (0)
0
 3.2 (155)
5
N/A
N/A



APC S1315A
0 (0)
0
1.56 (129)
4
N/A
N/A



BRAF V600L
0 (0)
0
1.11 (157)
4
N/A
N/A



KRAS G13C
0 (0)
0
4.31 (29) 
3
N/A
N/A



NRAS G60Q
0 (0)
0
1.49 (67) 
2
N/A
N/A



APC T1313I
0 (0)
0
 1.3 (115)
3
N/A
N/A



EGFR
 30.5 (3995)
1226
96.97 (6739)
6543
3.18
5.34



G746_A750del



BRAF S602C
0 (0)
0
2.15 (281)
7
N/A
N/A



BRAF A598D
0 (0)
0
1.27 (157)
4
N/A
N/A


16A011
EGFR L858R
20.37 (1753) 
374
91.91 (592) 
542
4.51
1.45



EGFR P753T
0 (0)
0
3.17 (32) 
2
N/A
N/A



NRAS A59G
0 (0)
0
10.75 (47) 
10
N/A
N/A



NRAS A59S
0 (0)
0
9.78 (46) 
9
N/A
N/A



KRAS G12D
0 (0)
0
22.73 (6)  
3
N/A
N/A


Wild
All mutations
0 (0)
0
 0 (0)
0
N/A
N/A


Type









Average VAF Boost Folds
5.21
1.33
















TABLE 15b







Summary of 10 Colon cancer FFPE patient detected VAF % and mutant number


changes before and after adding XNA mix
















Frequency









without
# of
Frequency
# of




XNA, %
Mutants
with XNA,
Mutants
VAF
Mutant


Patient

(Total
without
% (Total
with
Boost
# Boost


ID
Hotspots
Coverage)
XNA
Coverage)
XNA
Folds
Folds

















 #7
NRAS V14I
0 (0)
0
2.03 (493)
10
N/A
N/A



PIK3CA
0 (0)
0
3.88 (103)
4
N/A
N/A



A1046V



PIK3CA
0 (0)
0
11.76 (102) 
12
N/A
N/A



H1047Y



PIK3CA
0 (0)
0
9.18 (98) 
9
N/A
N/A



H1048Y



APC G1312R
0 (0)
0
3.02 (398)
12
N/A
N/A



EGFR T790M
0 (0)
0
 2.79 (1004)
28
N/A
N/A



EGFR G812R
0 (0)
0
4.58 (262)
12
N/A
N/A



EGFR A859T
0 (0)
0
5.28 (265)
14
N/A
N/A



BRAF K599E
0 (0)
0
2.56 (156)
4
N/A
N/A



KRAS A59V
0 (0)
0
 1.29 (1005)
13
N/A
N/A



KRAS T58I
0 (0)
0
 1.17 (1029)
12
N/A
N/A



KRAS G13S
0 (0)
0
2.04 (442)
9
N/A
N/A



KRAS G12S
0 (0)
0
1.36 (442)
6
N/A
N/A



KRAS A11V
0 (0)
0
2.08 (432)
9
N/A
N/A


 #41
NRAS V14I
0 (0)
0
2.04 (392)
8
N/A
N/A



PIK3CA
0 (0)
0
2.58 (892)
23
N/A
N/A



A1046V



APC G1312R
0 (0)
0
2.55 (314)
8
N/A
N/A



EGFR T790M
0 (0)
0
4.23 (449)
19
N/A
N/A



EGFR Q791*
0 (0)
0
3.52 (454)
16
N/A
N/A



KRAS D57N
0 (0)
0
2.55 (706)
18
N/A
N/A



KRAS G12S
0 (0)
0
6.35 (252)
16
N/A
N/A



KRAS A11V
0 (0)
0
3.59 (251)
9
N/A
N/A



NRAS G13D
0 (0)
0
2.95 (407)
12
N/A
N/A



NRAS G13S
0 (0)
0
2.12 (378)
8
N/A
N/A



APC R1314K
0 (0)
0
7.39 (284)
21
N/A
N/A



EGFR A859D
0 (0)
0
1.96 (153)
3
N/A
N/A



BRAF
0 (0)
0
7.14 (140)
10
N/A
N/A



c.1800G > A



KRAS A146S
0 (0)
0
1.72 (232)
4
N/A
N/A



KRAS G60S
0 (0)
0
3.16 (697)
22
N/A
N/A



KRAS A59T
0 (0)
0
2.49 (723)
18
N/A
N/A



KRAS G13D
0 (0)
0
2.87 (244)
7
N/A
N/A


 #73
EGFR T790M
0 (0)
0
 3.71 (1160)
43
N/A
N/A



PIK3CA
0 (0)
0
 1.4 (429)
6
N/A
N/A



G1050D



EGFR T751K
0 (0)
0
3.07 (163)
5
N/A
N/A



KRAS G12V
 27 (963)
260
72.43 (1614)
1169
3
4


#81
EGFR T790M
0 (0)
0
2.02 (940)
19
N/A
N/A



KRAS D57N
0 (0)
0
3.36 (982)
33
N/A
N/A



APC R1314K
0 (0)
0
3.07 (261)
8
N/A
N/A



KRAS G12V
26.79 (922)  
247
91.44 (1880)
1719
3
7


 #99
EGFR P753T
0 (0)
0
1.73 (173)
3
N/A
N/A



EGFR T790M
0 (0)
0
 1.76 (1023)
18
N/A
N/A



BRAF
0 (0)
0
1.45 (275)
4
N/A
N/A



c.1800G > A



KRAS A146S
0 (0)
0
1.26 (397)
5
N/A
N/A



EGFR T751K
0 (0)
0
1.66 (181)
3
N/A
N/A



APC Q1311fs
29.66 (2788) 
827
73.66 (911) 
671
2
1



BRAF S602C
0 (0)
0
1.44 (277)
4
N/A
N/A



KRAS A146G
0 (0)
0
1.28 (390)
5
N/A
N/A


#104
EGFR Q791*
0 (0)
0
3.89 (180)
7
N/A
N/A



KRAS T58I
0 (0)
0
2.55 (275)
7
N/A
N/A



KRAS D57N
0 (0)
0
2.24 (268)
6
N/A
N/A



PIK3CA
15.99 (2357) 
377
39.38 (480) 
189
2
1



H1047R



BRAF V600E
11.05 (1900) 
210
61.45 (83) 
51
6
0


#116
EGFR G857E
0 (0)
0
6.74 (89) 
6
N/A
N/A



KRAS D57N
0 (0)
0
2.48 (323)
8
N/A
N/A



KRAS G13D
12.85 (996)  
128
80.51 (508) 
409
6
3


#138
PIK3CA
 1.28 (2424)
31
11.58 (1304)
151
9
5



H1047Y



KRAS D57N
0 (0)
0
3.53 (935)
33
N/A
N/A



KRAS G12S
27.28 (1338) 
365
89.68 (2239)
2008
3
6



EGFR A750T
0 (0)
0
5.97 (134)
8
N/A
N/A


#150
EGFR T790M
0 (0)
0
 2.05 (1124)
23
N/A
N/A



BRAF R603Q
0 (0)
0
 1.4 (214)
3
N/A
N/A


#152
EGFR T790M
0 (0)
0
2.42 (496)
12
N/A
N/A



EGFR Q791*
0 (0)
0
1.79 (502)
9
N/A
N/A



EGFR G857R
0 (0)
0
 3.2 (125)
4
N/A
N/A



KRAS D57N
0 (0)
0
1.12 (538)
6
N/A
N/A



KRAS G13D
0 (0)
0
  10 (140)
14
N/A
N/A


Wild
All Mutations
0 (0)
0
 0 (0)
0
N/A
N/A


Type


Average
4.4
3.32


VAF


Boost


Folds
















TABLE 16







Summary of Lung and Colon cancer cfDNA patient detected VAF % and mutant


number changes before and after adding XNA mix




















Frequency

Frequency









without
# of
with
# of




DNA

XNA,
Mutants
XNA, %
Mutants
VAF
Mutant #


Cancer
Patient
Input,

%(Total
without
(Total
with
Boost
Boost


Type
ID
ng
Hotspots
Coverage)
XNA
Coverage)
XNA
Folds
Folds



















Lung
D1811-B
3.9
NRAS T58S
0 (0)
0
2.15 (419)
9
N/A
N/A


Cancer





NRAS
0 (0)
0
 3.2 (281)
9
N/A
N/A





c.36T > C





CTNNB1
0 (0)
0
1.32 (227)
3
N/A
N/A





c.132T > A





EGFR
0 (0)
0
3.87 (155)
6
N/A
N/A





L718Q





EGFR
0 (0)
0
 1.3 (154)
2
N/A
N/A





G719D





EGFR
0 (0)
0
1.71 (175)
3
N/A
N/A





P753Q





EGFR
0 (0)
0
1.13 (796)
9
N/A
N/A





F856L





KRAS
0 (0)
0
1.12 (534)
6
N/A
N/A





Q61fs





KRAS
5.16 (310) 
16
60.38 (106) 
64
11.70
4.00





G12V


Lung
D1779-B
10.0
EGFR
0 (0)
0
 4.2 (119)
5
N/A
N/A


Cancer


G719D





KRAS
0 (0)
0
3.52 (199)
7
N/A
N/A





G12V





EGFR
0 (0)
0
2.52 (119)
3
N/A
N/A





G719D





EGFR
0 (0)
0
5.93 (118)
7
N/A
N/A





c.2157C > T





EGFR
0 (0)
0
1.62 (431)
7
N/A
N/A





A750T





EGFR
0 (0)
0
1.86 (430)
8
N/A
N/A





S752P


Lung
D1738-B
3.9
EGFR
  10.4 (11946)
1242
98.19 (2381)
2338
9.44
1.88


Cancer


G719D





NRAS
0 (0)
0
2.37 (253)
6
N/A
N/A





G13S





PIK3CA
0 (0)
0
2.55 (274)
7
N/A
N/A





c.3135T > C





PIK3CA
0 (0)
0
2.93 (273)
8
N/A
N/A





c.3138A > T





EGFR
0 (0)
0
 1.01 (1778)
18
N/A
N/A





T790A





BRAF
0 (0)
0
1.27 (473)
6
N/A
N/A





K601E





KRAS
0 (0)
0
4.33 (231)
10
N/A
N/A





A146T





KRAS
0 (0)
0
 1.32 (2343)
31
N/A
N/A





D57N


Lung
D1729-B
6.0
NRAS
0 (0)
0
9.09 (55) 
5
N/A
N/A


Cancer


G60E





NRAS
0 (0)
0
12.73 (55) 
7
N/A
N/A





G60R





APC I1311T
0 (0)
0
3.32 (211)
7
N/A
N/A





APC
0 (0)
0
5.19 (212)
11
N/A
N/A





T1313A





APC
0 (0)
0
2.84 (211)
6
N/A
N/A





S1315P





EGFR
  2 (3549)
71
40.37 (379) 
153
20.19
2.15





L858R


Lung
D1689-B
4.1
NRAS
0 (0)
0
 4.7 (447)
21
N/A
N/A


Cancer


G60E





NRAS
0 (0)
0
2.46 (447)
11
N/A
N/A





G60R





APC
0 (0)
0
 2.01 (1197)
24
N/A
N/A





K1310R





EGFR
0 (0)
0
2.75 (218)
6
N/A
N/A





EGFR
0 (0)
0
2.44 (614)
15
N/A
N/A





c.2231T > C


Lung
D1685-B
8.2
NRAS T58S
0 (0)
0
1.43 (838)
12
N/A
N/A


Cancer





KRAS
0 (0)
0
4.07 (270)
11
N/A
N/A





G12V





EGFR
0 (0)
0
1.94 (515)
10
N/A
N/A





A750T





EGFR
0 (0)
0
2.53 (514)
13
N/A
N/A





P753T





EGFR
14.29 (4067) 
581
86.83 (4511)
3917
6.08
6.74





L858R





EGFR
0 (0)
0
1.17 (515)
6
N/A
N/A





c.2256T > A





NRAS I55M
0 (0)
0
1.31 (838)
11
N/A
N/A





EGFR
0 (0)
0
1.17 (515)
6
N/A
N/A





E749K





BRAF
0 (0)
0
1.42 (564)
8
N/A
N/A





S602F


Lung
D1768-D
3.5
EGFR
28.07 (3666) 
1029
89.78 (2134)
1916
3.20
1.86


Cancer


L858R





BRAF
0 (0)
0
16.08 (199) 
32
N/A
N/A





c.1800G > A





PIK3CA
0 (0)
0
2.66 (864)
23
N/A
N/A





H1047R





PIK3CA
0 (0)
0
1.62 (863)
14
N/A
N/A





D1047G





APC
0 (0)
0
1.19 (336)
4
N/A
N/A





K1308E





APC
0 (0)
0
1.17 (341)
4
N/A
N/A





R1314T


Lung
D1743-B
3.4
EGFR
0 (0)
0
 1.5 (133)
2
N/A
N/A


Cancer


L718Q





APC
0 (0)
0
1.63 (551)
9
N/A
N/A





K1310E





EGFR
0 (0)
0
2.14 (887)
19
N/A
N/A





T751A





BRAF
0 (0)
0
7.98 (163)
13
N/A
N/A





V600E





EGFR
0 (0)
0
11.94 (134) 
16
N/A
N/A





c.2148A > G





EGFR
72.98 (9948) 
7260
86.4 (890)
769
1.18
0.11





L747P





KRAS
0 (0)
0
1.92 (834)
16
N/A
N/A





c.177A > G





KRAS
0 (0)
0
10.81 (74) 
8
N/A
N/A





G13D


Lung
D1734-B
3.3
NRAS T58S
0 (0)
0
1.92 (156)
3
N/A
N/A


Cancer





EGFR
0 (0)
0
5.18 (193)
10
N/A
N/A





P753T





EGFR
16.81 (5837) 
981
89.34 (2290)
2046
5.31
2.09





L858R





NRAS
0 (0)
0
4.49 (156)
7
N/A
N/A





Q61R





NRAS
0 (0)
0
7.69 (156)
12
N/A
N/A





A59V


Lung
D1732-B
3.592
APC
0 (0)
0
2.05 (830)
17
N/A
N/A


Cancer


C.3936A > G





BRAF
0 (0)
0
1.57 (191)
3
N/A
N/A





S602F





EGFR
0 (0)
0
 2.5 (160)
4
N/A
N/A





T751A





KRAS
0 (0)
0
5.08 (118)
6
N/A
N/A





c.438A > G





NRAS
0 (0)
0
8.65 (185)
16
N/A
N/A





c.168G > A





PIK3CA
0 (0)
0
 1.41 (1559)
22
N/A
N/A





c.3144 T > C





APC
0 (0)
0
1.57 (828)
13
N/A
N/A





S1315L





EGFR
0 (0)
0
 1.09 (3022)
33
N/A
N/A





c.2235G > A





EGFR
0 (0)
0
1.16 (344)
4
N/A
N/A





c.2571G > A





BRAF
0 (0)
0
9.95 (191)
19
N/A
N/A





S602P


Colon
D1175-B
7.8
NRAS T58S
0 (0)
0
2.45 (408)
10
N/A
N/A


Cancer





BRAF
0 (0)
0
1.91 (314)
6
N/A
N/A





K601E





KRAS
0 (0)
0
 1.11 (1986)
22
N/A
N/A





D57N





NRAS T58I
0 (0)
0
1.71 (409)
7
N/A
N/A





EGFR
0 (0)
0
6.38 (47) 
3
N/A
N/A





S720P





EGFR
0 (0)
0
1.61 (372)
6
N/A
N/A





L858fs





KRAS
0 (0)
0
6.12 (147)
9
N/A
N/A





G12S


Colon
D1022-B
3.6
EGFR
0 (0)
0
 5.1 (471)
24
N/A
N/A


Cancer


G857R





EGFR
0 (0)
0
2.94 (102)
3
N/A
N/A





c.2152C > T





EGFR
0 (0)
0
4.22 (166)
7
N/A
N/A





A750V





BRAF
0 (0)
0
1.01 (298)
3
N/A
N/A





c.1791A > T





KRAS Q61*
0 (0)
0
 1.56 (1922)
30
N/A
N/A


Wild
Healthy
5
All
0 (0)
0
 0 (0)
0
N/A
N/A


Type
People

mutations









Average VAF Boost Folds
8.16
1.10
















TABLE 17







Comparison between calculated enriched VAF and detected enriched VAF by using regression equations





















Calculated










Original
enriched
Enriched






VAF %
VAF %
VAF %


Sample
Cancer
Patient

(No
(With
(With


Type
Type
ID
Hotpots
XNA)
XNA)
XNA)
Error, %
Equation
R2



















FFPE
Lung
16A130
EGFR
2.1
50.3
43.3
16.0
y = 2.5996x +
1



Cancer

L858R




44.863





BRAF
20.4
85.0
77.2
10.1
y = −0.0464x2 +
0.9901





V600E




3.7915x +










26.927


FFPE
Lung
16A131
BRAF
13.3
69.1
68.1
1.6
y = −0.0464x2 +
0.9901



Cancer

V600E




3.7915x +










26.927


FFPE
Lung
16A137
EGFR
0.5
12.2
6.2
98.2
y = 24.962x
0.9052



Cancer

T790M





EGFR
1.0
19.8
6.2
221.9
y = 19.254x
0.9733





L858R


FFPE
Colorectal
#104
PIK3CA
16.0
40.1
39.4
1.7
y = −0.0641x2 +
0.8138



Cancer

H1047R




4.3557x −










13.199





BRAF
11.1
63.2
61.5
2.8
y = −0.0464x2 +
0.9901





V600E




3.7915x +










26.927


FFPE
Colorectal
#138
PIK3CA
1.28
13.7
11.58
17.9
y = 10.655x
0.905



Cancer

H1047Y


cfDNA
Lung
D1811-B
KRAS
5.16
62.5
60.38
3.4
y = 0.1551x2
0.8543



Cancer

G12V




0.817x + 62.541


cfDNA
Lung
D1738-B
EGFR
10.4
95.4
98.19
2.8
y = 0.0222x2
0.3157



Cancer

G719D




0.3879x + 97.06


cfDNA
Lung
D1729-B
EGFR
2
38.5
40.37
4.6
y = 19.254x
0.9733



Cancer

L858R









Average standard error rate, %
34.7



Average standard error rate, % exclude sample 16A137
6.8









For the mutations detected and listed in Table 15a, Table 15b and Table 16, they are more than 17 hotspots as we discussed before. Since XNA only show a higher blocking effects towards wild type sequence. Any mutant happened in this range will lead to loose affinity of the template, thus facilitating the amplification of the mutants. Hence, all loci covered by 13 XNAs were included in these two Tables. The information of covered range of 13 XNAs were summarized in Table 20 (Supplementary to Table 13).


Although we use some FFPE and cfDNA patients' samples to verify the enrichment effects of XNAs mix on samples with low variant frequency, it is critical to get the real/original VAF in patient, that can be utilized by clinical professional as the criterion to make insight judgement of the patient disease. Particularly for patients with super low VAF that can't be detected by normal NGS method. Meanwhile, this variant is critically related to specific cancer disease. To verify these regression equations, VAF from patient sample with/without XNAs mix were evaluated by NGS method. We applied regression equations to get calculated enriched VAF and compared them with enriched VAF from NGS method. The resulted were summarized in Table 17. Original VAF of all mutations listed in Table 16 fell into confidence interval range (x). For those falling out of this range, they were excluded from this table. For example, patient ID 16A130 on the first raw of Table 17, there are two mutations detected by NGS for both with XNAs mix and without XNAs mix conditions. VAF of EGFR L858R was 2.1% without XNA enrichment, 43.3% after XNA enrichment. Since the original VAF was more than 2.0% cut-off value, regression equation y=2.5996x+44.863 was applied to get the calculated enriched VAF, the result was 50.3%. Standard error was 16.0% compared to detected enriched VAF. The average standard error of 11 mutations were 34.7%. There was one sample with two mutations that had a comparable higher standard error rate, they are EGFR T790M and EGFR L858R from sample 16A137. If excluding this sample, average standard error for 9 mutations will be decreased to 6.8%. This result demonstrated that regression equations got from cell-line genomic DNA are reliable and can be utilized to deduced original VAF of patient samples.









TABLE 18







Mutations summary and corresponding drug therapy and related diseases













Mutation
Nucleotide
Amino Acid
FDA Approved



Gene
Type
Change
Change
Therapies for Indication
Related Diseases





APC
Deletion
c.3921_3925
p.Glu1309fs
N/A
Rectal cancers, Colon




delAAAAG


cancers, Melanomas,







Colorectal adenomas


BRAF
SNV
c.1799T > A
p.Val600Glu
5-fluorouracil,
Metastatic colorectal






Bevacizumab,
cancer, Non-squamous






Aflibercept, 5-
non-small cell lung






fluoropyrimidine,
cancer, Metastatic renal






Regorafenib, Tipiracil,
cell carcinoma, Cervical






Trifluridine, 5-
cancer, Peritoneal Cancer,






fluorouracil,
Metastatic melanoma






Bevacizumab,






Trametinib, Cobimetinib,






BRAF inhibitor, MEK,






Ipilimumab, BRAF






inhibitor, Sorafenib,






Cobimetinib, Dabrafenib,






Nivolumab, Dabrafenib,






Vemurafenib


CTNNB1
Deletion
c.131_133del
p.Ser45del
Crizotinib
Metastatic nonsmall cell




CTT


lung cancer, Liver







Cancers, Endometrial







Cancers, Renal Cancers


EGFR
Deletion
c.2235_2249
p.Glu746_Ala
Tyrosine kinase,
Metastatic colorectal




del
750del
Bevacizumab,
cancer, Non-squamous




GGAATTA

Carboplatin, Erlotinib,
non-small cell lung




AGAGAAGC

Carboplatin, Cetuximab,
cancer, Metastatic renal






Panitumumab,
cell carcinoma, Cervical






Vandetanib, Bosutinib,
cancer, Peritoneal cancer,






Lapatinib, Brigatinib,
Endometrial, Ovarian,






Necitumumab,
Head,






Pembrolizumab, Afatinib,
neck cancers,






Cetuximab, EGFR TKIs,
Symptomatic or






Cetuximab, Cisplatin,
progressive medullary






Erlotinib, Osimertinib,
thyroid cancer, Advanced






Gefitinib, Afatinib
or metastatic breast







cancer


EGFR
SNV
c.2155G > A
p.Gly719Ser
Bevacizumab,
Metastatic colorectal






Carboplatin, Erlotinib,
cancer, Non-squamous






Carboplatin,
non-small cell lung






Panitumumab,
cancer, Metastatic renal






Vandetanib, Bosutinib,
cell carcinoma, Cervical






Lapatinib, Brigatinib,
cancer, Peritoneal cancer,






Necitumumab, Tyrosine
Endometrial, Ovarian,






kinase, Pembrolizumab,
Head, neck cancers,






Afatinib, Cetuximab,
Symptomatic or






EGFR TKIs, Cetuximab,
progressive medullary






Cisplatin, Erlotinib,
thyroid cancer, Advanced






Osimertinib, Gefitinib,
or metastatic breast






Afatinib
cancer


EGFR
SNV
c.2573T > G
p.Leu858Arg
Bevacizumab,
Metastatic colorectal






Carboplatin, Erlotinib,
cancer, Non-squamous






Carboplatin, Cetuximab,
non-small cell lung






Panitumumab,
cancer, Metastatic renal






Vandetanib, Bosutinib,
cell carcinoma, Cervical






Lapatinib, Brigatinib,
cancer, Peritoneal cancer,






Necitumumab, Tyrosine
Endometrial, Ovarian,






kinase, Pembrolizumab,
and Head and neck






Afatinib, Cetuximab,
cancers, Symptomatic or






EGFR TKIs, Cetuximab,
progressive medullary






Cisplatin, Erlotinib,
thyroid cancer, Advanced






Osimertinib, Gefitinib,
or metastatic breast






Afatinib
cancer


EGFR
SNV
c.2369C > T
p.Thr790Met
Bevacizumab,
Metastatic colorectal






Carboplatin, Erlotinib,
cancer, Non-squamous






Carboplatin, Cetuximab,
non-small cell lung






Brigatinib, Tyrosine
cancer, Metastatic renal






kinase, Pembrolizumab,
cell carcinoma, Cervical






Afatinib, Cetuximab,
cancer, Peritoneal cancer,






EGFR TKIs, Cetuximab,
Endometrial, Ovarian,






Cisplatin, Erlotinib,
and head and neck






Osimertinib, Gefitinib,
cancers






Afatinib


KRAS
SNV
c.436G > A
p.Ala146Thr
Carboplatin, Erlotinib,
Metastatic colorectal






Paclitaxel, Bevacizumab,
cancer, Endometrial,






Fluoropyrimidine, 5-
Ovarian, and head and






fluorouracil, Irinotecan,
neck cancers, Metastatic






Leucovorin,
renal cell carcinoma,






Ramucirumab,
Cervical cancer






Bevacizumab, 5-






fluorouracil, Irinotecan,






Leucovorin, Oxaliplatin


KRAS
SNV
c.175G > A
p.Ala59Thr
Panitumumab, Cetuximab
Metastatic colorectal







cancer


KRAS
SNV
c.35G > A
p.Gly12Asp
5-fluorouracil,
Metastatic colorectal






Bevacizumab,
cancer, Non-squamous






Aflibercept, 5-
non-small cell lung






fluoropyrimidine,
cancer, Metastatic renal






Regorafenib, Tipiracil,
cell carcinoma, Cervical






Trifluridine, 5-
cancer, Peritoneal cancer,






fluorouracil,
Endometrial, ovarian, and






Bevacizumab,
head and neck cancers






Carboplatin, Erlotinib,






Carboplatin, Cetuximab,






Panitumumab


KRAS
SNV
c.38G > A
p.Gly13Asp
Regorafenib, 5-
Metastatic colorectal






fluorouracil, Carboplatin,
cancer, Endometrial,






Erlotinib, Bevacizumab,
Ovarian, and head and






Fluoropyrimidine,
neck cancers, Non-small






Tipiracil, Trifluridine,
cell lung cancer,






Aflibercept, 5-
Metastatic testicular






fluorouracil, Carboplatin,
tumor, Metastatic ovarian






Bevacizumab,
tumor






Panitumumab,






Cetuximab, Irinotecan,






Cetuximab, Erlotinib,






Vinorelbine, Cisplatin,






Platinum, Cetuximab,






Chemother, EGFR






tyrosine kinase,






Carboplatin, Erlotinib,






Irinotecan, Panitumu,






Carboplatin, Paclitaxel,






Panitumumab, Cetuximab


KRAS
SNV
c.182A > T
p.Gln61Leu
Gefitinib, Erlotinib,
Intestine cancer, Lung






Ektorinib, Cetuximad,
cancer, Pancreas cancer,






Panitumumad,
Haematopoietic,






Nimotuzumab
lymphoid cancer and skin







cancer


NRAS
SNV
c.175G > A
p.Ala59Thr
5-fluorouracil,
Metastatic colorectal






Bevacizumab,
cancer, Non-squamous






Aflibercept, 5-
non-small cell lung






fluoropyrimidine,
cancer, Metastatic renal






Regorafenib, Tipiracil,
cell carcinoma, Cervical






Trifluridine, 5-
cancer, Peritoneal cancer






fluorouracil,






Bevacizumab


NRAS
SNV
c.35G > T
p.Gly12Val
Cetuximad, Panitumumad
Colorectal Cancer


NRAS
SNV
c.38G > A
p.Gly13Asp
Cetuximad, Panitumumad
Colorectal Cancer


NRAS
SNV
c.183A > T
p.Gln61His
5-fluorouracil,
Metastatic colorectal






Bevacizumab,
cancer, Non-squamous






Aflibercept, 5-
non-small cell lung






fluoropyrimidine,
cancer, Metastatic renal






Regorafenib, Tipiracil,
cell carcinoma, Cervical






Trifluridine, 5-
cancer, Peritoneal cancer






fluorouracil,






Bevacizumab


PIK3CA
SNV
c.3140A > G
p.His1047Arg
N/A
Unresectable or







metastatic melanoma,







Nonsmall cell lung







cancer, Unresectable or







metastatic pancreatic







cancer
















TABLE 19







Primer sequences and corresponding hotspots covered information










Primer


Covered


Pair Name
Fwd primer
Rev primer
Hotspots





DCNP001
SEQ ID NO: 220
SEQ ID NO: 221
CTNNB1



CCTACACGACGCTCTTCCGATCTAGCAAC
TTCAGACGTGTGCTCTTCCGATCTGGGA
S45



AGTCTTACCTGGACT
GGTATCCACATCCTCTTC






DCNP002
SEQ ID NO: 222
SEQ ID NO: 223
KRAS A146



CCTACACGACGCTCTTCCGATCTGTATTT
TTCAGACGTGTGCTCTTCCGATCTAAGA




ATTTCAGTGTTACTTACCTGTCTTGT
TGTACCTATGGTCCTAGTAGGA






DCNP003
SEQ ID NO: 224
SEQ ID NO: 225
NRAS A59,



CCTACACGACGCTCTTCCGATCTCCTGTA
TTCAGACGTGTGCTCTTCCGATCTGTTA
NRAS Q61



GAGGTTAATATCCGCAAATG
TAGATGGTGAAACCTGTTTGTTG






DCNP004
SEQ ID NO: 226
SEQ ID NO: 227
NRAS G12,



CCTACACGACGCTCTTCCGATCTTGGGAT
TTCAGACGTGTGCTCTTCCGATCTTTAC
NRAS G13



CATATTCATCTACAAAGTGGTT
TGGTTTCCAACAGGTTCTTG






DCNP005
SEQ ID NO: 228
SEQ ID NO: 229
PIK3CA



CCTACACGACGCTCTTCCGATCTCTCTGG
TTCAGACGTGTGCTCTTCCGATCTGTGG
H1047



AATGCCAGAACTACAAT
AAGATCCAATCCATTTTTGTTG






DCNP006
SEQ ID NO: 230
SEQ ID NO: 231
APC E1309



CCTACACGACGCTCTTCCGATCTCAGGAA
TTCAGACGTGTGCTCTTCCGATCTAAGA




GCAGATTCTGCTAATACC
TAAACTAGAACCCTGCAGTCT






DCNP007
SEQ ID NO: 232
SEQ ID NO: 233
EGFR G719



CCTACACGACGCTCTTCCGATCTCCTTGT
TTCAGACGTGTGCTCTTCCGATCTTATA




CTCTGTGTTCTTGTCC
CACCGTGCCGAACGC






DCNP008
SEQ ID NO: 234
SEQ ID NO: 235
EGFR



CCTACACGACGCTCTTCCGATCTCAGTTA
TTCAGACGTGTGCTCTTCCGATCTGCAA
del19



ACGTCTTCCTTCTCTCTCT
AGCAGAAACTCACATCGA






DCNP009
SEQ ID NO: 236
SEQ ID NO: 237
EGFR



CCTACACGACGCTCTTCCGATCTCACACT
TTCAGACGTGTGCTCTTCCGATCTTCTT
T790M



GACGTGCCTCTC
TGTGTTCCCGGACATAGT






DCNP010
SEQ ID NO: 238
SEQ ID NO: 239
EGFR L858



CCTACACGACGCTCTTCCGATCTTCTGTT
TTCAGACGTGTGCTCTTCCGATCTTCCT




TCAGGGCATGAACTACT
TCTGCATGGTATTCTTTCTCT






DCNP011
SEQ ID NO: 240
SEQ ID NO: 241
BRAF V600



CCTACACGACGCTCTTCCGATCTGTGGAA
TTCAGACGTGTGCTCTTCCGATCTACCT




AAATAGCCTCAATTCTTACCAT
CAGATATATTTCTTCATGAAGACCTC






DCNP012
SEQ ID NO: 242
SEQ ID NO: 243
KRAS A59,



CCTACACGACGCTCTTCCGATCTACCCAC
TTCAGACGTGTGCTCTTCCGATCTGAGA
KRAS Q61



CTATAATGGTGAATATCTTCAA
AACCTGTCTCTTGGATATTCTC






DCNP013
SEQ ID NO: 244
SEQ ID NO: 245
KRAS G12,



CCTACACGACGCTCTTCCGATCTGTCCTG
TTCAGACGTGTGCTCTTCCGATCTCTGC
KRAS G13



CACCAGTAATATGCATATTAAA
TGAAAATGACTGAATATAAACTTGTG
















TABLE 20







Summary Table for the Effects of XNA mix on (VAF) and Coverage of sample


using OptiSeq ™ Lung and Colorectal Cancer Mini Panel, 0.50% and 1.25%










Variant Allelic Frequency, 0.50%
Variant Allelic Frequency, 1.25%




















Frequency

Frequency



Frequency

Frequency






without
# of
with
# of


without
# of
with
# of



XNA, %
Mutants
XNA, %
Mutants
Mutant #
VAF
XNA, %
Mutants
XNA, %
Mutants
Mutant #
VAF


Hotspot
(Total
without
(Total
with
Boost
Boost
(Total
without
(Total
with
Boost
Boost


Name
Coverage)
XNA
Coverage)
XNA
Folds
Folds
Coverage)
XNA
Coverage)
XNA
Folds
Folds






















KRAS
1.23 (3324)
41
39.23 (581) 
228
6
31.9
3.08 (3324)
102
64.95 (970) 
630
6
21.1


A146T


KRAS
0.82 (1098)
9
9.89 (130)
13
1
12.1
2.04 (1098)
22
16.81 (442) 
74
3
8.2


G13D


NRAS
0.42 (2288)
10
31.52 (499) 
157
16
75.0
1.05 (2288)
24
41.29 (1277)
527
22
39.3


A59T


EGFR
0.46 (3396)
16
12.36 (979) 
121
8
26.9
1.15 (3396)
39
25.59 (1680)
430
11
22.3


T790M


EGFR
5.04 (5624)
283
98.52 (873) 
860
3
19.5
12.6 (5624)
709
  994 (3062)
3044
4
7.9


G719S


NRAS
0.27 (1436)
4
1.36 (319)
4
1
5.0
0.68 (1436)
10
 3.66 (1275)
47
5
5.4


Q61H


NRAS
0.42 (1495)
6
 8.4 (115)
10
2
20.0
1.05 (1495)
16
22.13 (244) 
54
3
21.1


G12V


PIK3CA
3.55 (1879)
67
31.99 (413) 
132
2
9.0
8.87 (1879)
167
64.97 (776) 
504
3
7.3


H1047R


EGFR
0.28 (3424)
10
18.21 (659) 
120
13
65.0
0.69 (3424)
24
34.88 (1004)
350
15
50.6


E746-


A750


EGFR
 0.4 (2651)
11
10.81 (1290)
139
13
27.0
  1 (2651)
27
24.81 (1724)
428
16
24.8


L858R


BRAF
3.41 (2356)
80
37.51 (341) 
128
2
11.0
8.52 (2356)
201
61.43 (921) 
566
3
7.2


V600E


KRAS
0.83 (1099)
9
29.6 (129)
38
4
35.7
2.09 (1099)
23
51.09 (443) 
226
10
24.4


G12D


NRAS
 0.4 (1012)
4
6.92 (93) 
6
2
17.3
1.01 (1012)
10
17.65 (243) 
43
4
17.5


G13D


APC
0.42 (1771)
7
8.51 (384)
33
4
20.3
1.05 (1771)
19
14.73 (799) 
118
6
14.0


E1309fs*


KRAS
0.25 (1633)
4
 8.13 (1328)
108
26
32.5
0.61 (1633)
10
16.94 (2276)
386
39
27.8


A59T


CTNNB1
0.51 (65) 
0
5.46 (215)
12
35
10.7
1.275 (65)  
1
8.92 (238)
21
26
7.0


S45del


KRAS
0.23 (1564)
4
 1.38 (1106)
15
4
6.0
0.58 (1564)
9
 3.77 (2276)
86
9
6.5


Q61L















Average
2121
556
8.4
25.0
2121
1156
10.9
18.4


Total


Coverage
















TABLE 21-A







Average enriched variant allelic frequency (VAF) with XNAs mix

















Original
Original
Original
Original
Original
Original
Original
Original
Original



VAF
VAF
VAF
VAF
VAF
VAF
VAF
VAF
VAF



0.00%
0.10%
0.25%
0.50%
1.00%
2.50%
5.00%
10.00%
15.00%



With
With
With
With
With
With
With
With
With


Hotspots
XNA
XNA
XNA
XNA
XNA
XNA
XNA
XNA
XNA



















KRAS
2.13
12.68
26.05
41.52
52.26
81.22
64.13
80.60
76.80


A146T


KRAS
0.00
2.59
5.82
9.59
15.72
22.33
10.17
17.76
26.15


G13D


NRAS
0.34
3.89
11.94
20.72
25.89
57.69
84.13
89.93
94.07


A59T


EGFR
0.00
2.88
5.97
15.04
19.08
43.53
59.22
76.21
83.45


T790M


EGFR
16.92
94.43
94.22
98.19
98.93
99.53
99.51
98.85
90.81


G719S


NRAS
0.00
0.16
0.68
1.16
2.80
5.69
2.69
3.39
2.83


Q61H


NRAS
0.00
3.03
5.60
4.48
20.02
24.93
40.57
30.19
66.06


G12V


PIK3CA
0.00
10.98
17.22
5.29
13.90
30.01
48.54
53.11
79.36


H1047R


EGFR
0.00
3.36
7.03
35.58
47.85
69.80
92.11
91.07
93.28


E746-


A750


EGFR
0.00
3.33
3.58
11.76
17.85
36.74
28.31
57.35
77.01


L858R


BRAF
0.00
12.04
19.28
38.32
52.92
75.23
45.17
71.38
95.00


V600E


KRAS
0.59
6.98
14.28
25.25
37.87
59.79
83.72
68.99
66.39


G12D


NRAS
0.00
3.35
4.60
5.27
13.63
25.09
23.46
40.83
79.98


G13D


APC
0.00
1.68
2.09
6.95
11.21
26.03
55.23
68.65
55.75


E1309fs*


KRAS
0.00
1.14
3.23
6.09
8.06
22.34
27.14
47.98
39.64


A59T


CTNNB1
0.00
0.45
1.85
3.26
6.79
15.09
41.72
54.71
55.20


S45del


KRAS
0.00
0.00
0.53
1.28
3.08
7.56
7.97
25.96
38.61


Q61L
















TABLE 21-B







Average original variant allelic frequency (VAF) without XNAs mix

















Original
Original
Original
Original
Original
Original
Original
Original
Original



VAF
VAF
VAF
VAF
VAF
VAF
VAF
VAF
VAF



0.00%
0.10%
0.25%
0.50%
1.00%
2.50%
5.00%
10.00%
15.00%



No
No
No
No
No
No
No
No
No


Hotspots
XNA
XNA
XNA
XNA
XNA
XNA
XNA
XNA
XNA



















KRAS
0.00
0.24
0.60
1.20
2.39
5.99
3.19
6.53
6.53


A146T


KRAS
0.00
0.18
0.45
0.90
1.80
4.49
5.73
6.71
12.72


G13D


NRAS
0.00
0.12
0.29
0.58
1.15
2.89
7.87
12.06
20.29


A59T


EGFR
0.00
0.09
0.21
0.43
0.86
2.15
3.06
7.43
15.31


T790M


EGFR
0.00
0.90
2.25
4.50
9.00
22.51
22.68
19.38
11.28


G719S


NRAS
0.00
0.09
0.23
0.46
0.92
2.31
2.89
7.06
10.85


Q61H


NRAS
0.00
0.10
0.26
0.52
1.03
2.58
3.93
5.03
9.47


G12V


PIK3CA
0.00
0.70
1.75
3.50
6.99
17.49
23.77
39.28
27.83


H1047R


EGFR
0.00
0.06
0.14
0.29
0.58
1.44
5.41
6.76
15.07


E746-


A750


EGFR
0.00
0.08
0.20
0.39
0.79
1.96
1.53
4.80
12.37


L858R


BRAF
0.00
0.64
1.61
3.21
6.43
16.07
6.06
14.01
55.13


V600E


KRAS
0.00
0.16
0.40
0.80
1.61
4.02
14.32
6.78
10.21


G12D


NRAS
0.00
0.10
0.26
0.52
1.05
2.61
4.02
8.76
14.56


G13D


APC
0.00
0.07
0.17
0.34
0.68
1.71
5.07
9.89
11.77


E1309fs*


KRAS
0.00
0.08
0.19
0.38
0.77
1.92
2.54
7.10
6.70


A59T


CTNNB1
0.00
0.07
0.19
0.37
0.75
1.86
4.09
5.85
12.49


S45del


KRAS
0.00
0.08
0.21
0.42
0.83
2.08
2.56
18.63
29.76


Q61L









Cut-Off—2% for Original Variant Allelic Frequency









TABLE 22-A







Regression equations for hotspots with original allelic frequency


(Original VAF) less than 2.00%














Confidence
Confidence


Hotspots
Equation
R2
interval (x)
interval (y)














KRAS A146T
y = 36.96x
0.9517
[0, 2]
[0, 73.9]





KRAS G13D
y = 9.3533x
0.9602
[0, 2]
[0, 18.7]





NRAS A59T
y = 25.954x
0.8504
[0, 2]
[0, 51.9]





EGFR T790M
y = 24.962x
0.9052
[0, 2]
[0, 49.9]





EGFR G719S
y = 104.89x
0.9047
[0, 2]
[0, 100]





NRAS Q61H
y = 2.9212x
0.9887
[0, 2]
[0, 5.8]





NRAS G12V
y = 17.558x
0.8874
[0, 2]
[0, 35.1]





PIK3CA H1047R
y = 10.655x
0.905
[0, 2]
[0, 21.3]





EGFR E746-A750
y = 55.532x
0.8163
[0, 2]
[0, 100]





EGFR L858R
y = 19.254x
0.9733
[0, 2]
[0, 38.5]





BRAF V600E
y = 12.929x
0.9149
[0, 2]
[0, 25.9]





KRAS G12D
y = 25.768x
0.9353
[0, 2]
[0, 51.5]





NRAS G13D
y = 12.837x
0.9244
[0, 2]
[0, 25.7]





APC E1309fs*
y = 15.525x
0.9915
[0, 2]
[0, 31.1]





KRAS A59T
y = 11.693x
0.9868
[0, 2]
[0, 23.4]





CTNNB1 S45del
y = 8.2626x
0.996
[0, 2]
[0, 16.5]





KRAS Q61L
y = 3.5017x
0.9722
[0, 2]
[0, 7]













Number with R2 > 0.9
14







Percentage with R2 > 0.9
82.35%
















TABLE 22-B







Regression equations for hotspots with original allelic


frequency (Original VAF) more than 2.00%














Confidence
Confidence


Hotspots
Equation
R2
interval (x)
interval (y)














KRAS A146T
y = −2.3889x2 + 27.709x
0.9865
[2, 6.5]
[45.9, 79.2]





KRAS G13D
y = 0.5868x2 − 9.3552x + 50.331
0.6263
[2, 12.7]
[34, 26.2]





NRAS A59T
y = −0.202x2 + 6.6933x + 41.012
0.9806
[2, 20.3]
[53.6, 93.6]





EGFR T790M
y = −0.37892x2 + 9.3359x + 29.137
0.955
[2, 15.3]
[46.3, 83.3]





EGFR G719S
y = 0.0222x2 − 0.3879x + 97.06
0.3157
[2, 22.7]
[96.4, 99.7]





NRAS Q61H
y = 0.0337x2 − 0.6216x + 5.7134
0.3222
[2, 10.9]
[4.6, 2.9]





NRAS G12V
y = 0.4788x2 − 0.3143x + 25.679
0.8782
[2, 9.6]
[27, 65.9]





PIK3CA
y = −0.0641x2 + 4.3557x − 13.199
0.8138
[2, 39.3]
[0, 59]


H1047R









EGFR
y = 0.107x2 − 2.0697x + 100.18
1
[2, 15.1]
[96.5, 93.3]


E746-A750









EGFR L858R
y = 2.5996x + 44.863
1
[2, 12.4]
[50.1, 77.1]





BRAF V600E
y = −0.0464x2 + 3.7915x + 26.927
0.9901
[2, 55.1]
[34.3, 95]





KRAS G12D
y = 0.1551x2 − 0.817x + 62.541
0.8543
[2, 14.3]
[61.5, 82.6]





NRAS G13D
y = 0.3565x2 − 1.4161x + 25.151
0.9975
[2, 14.6]
[23.7, 80.5]





APC
y = −1.44x2 + 24.328x − 31.099
1
[2, 11.8]
[11.8, 55.5]


E1309fs*









KRAS A59T
y = 3.8664x2 − 32.697x + 85.225
1
[2, 7.1]
[35.3, 48]





CTNNB1
y = −0.8701x2 + 16.029x − 9.2552
1
[2, 12.5]
[19.3, 55.2]


S45del









KRAS Q61L
y = 0.0008x2 + 1.0992x + 5.212
1
[2, 29.8]
[7.4, 38.7]













Number with R2 > 0.9
11







Percentage with R2 > 0.9












All literature and similar materials cited in this application including, but not limited to, patents, patent applications, articles, books, treatises, and internet web pages, regardless of the format of such literature and similar materials, are expressly incorporated by reference in their entirety for any purpose as if they were entirely denoted. In the event that one or more of the incorporated literature and similar materials defines or uses a term in such a way that it contradicts that term's definition in this application, this application controls.


Although the foregoing description contains many specifics, these should not be construed as limiting the scope of the present invention, but merely as providing illustrations of some of the presently preferred embodiments. Similarly, other embodiments may be devised without departing from the spirit or scope of the present invention. Features from different embodiments may be employed in combination. The scope of the invention is, therefore, indicated and limited only by the appended claims and their legal equivalents rather than by the foregoing description. All additions, deletions and modifications to the invention as disclosed herein which fall within the meaning and scope of the claims are to be embraced thereby.


REFERENCES



  • 1. Muzzey, D., Evans, E. A. & Lieber, C. Understanding the Basics of NGS: From Mechanism to Variant. Calling. Curr. Genet. Med. Rep. 3, 158-165 (2015).

  • 2. Meldrum, C., Doyle, M. A. & Tothill, R. W. Next-Generation Sequencing for Cancer Diagnostics: a Practical Perspective. Clin. Biochem. Rev. 32, 177-195 (2011).

  • 3. Kou, R. et al. Benefits and challenges with applying unique molecular identifiersin next generation sequencing to detect low frequency mutations. PLoS ONE. 11, e0146638 (2016).

  • 4. Kinde, I., Wu, J., Papadopoulos, N., Kinzler, K. W. & Vogelstein, B. Detection and quantification of rare mutations with massively parallel sequencing. Proc. Natl. Acad. Sci. U.S.A. 108, 9530-9535 (2011).

  • 5. Clement, K., Farouni, R., Bauer, D. E. & Pinello, L. AmpUMI: design and analysis of unique molecular identifiers for deep amplicon sequencing. Bioinformatics. 34, i202-i210 (2018).

  • 6. Powell, J. P. & Zhang, A. DNA Mutation Detection Employing Enrichment of Mutant Polynucleotide Sequences and Minimally Invasive Sampling. U.S. Pat. No. 20160194691. United States Patent and Trademark Office (2016).

  • 7. Powell, J. P. & Zhang, A. Detection of PNA clamping. U.S. Pat. No. 9,745,633. United States Patent and Trademark Office (2017).

  • 8. Powell, J. P. Specific Synthetic Chimeric Xenonucleic Acid Guide RNA; s(XNA-gRNA) for Enhancing CRISPER Mediated Genome Editing Efficiency. U.S. Pat. No. 20180066258. United States Patent and Trademark Office (2018).


Claims
  • 1. A method for enriching a target polynucleotide sequence containing a genetic variation said method comprising: (a) providing two primers targeted to said target polynucleotide sequence;(b) providing a target specific xenonucleic acid clamp oligomer specific for a wildtype polynucleotide sequence, wherein said xenonucleic acid includes moieties selected from the group consisting of oxy-aza, aza-aza, thio-aza and mixtures thereof;(c) generating multiple amplicons using PCR under specific temperature cycling conditions; and(d) detecting said amplicons.
  • 2. The method of claim 1, wherein said detection employs oligonucleotide probes specific for hybridization of variant polynucleotide amplicon sequences.
  • 3. The method of claim 1, wherein the variant target sequence is in a gene selected from the group consisting of: KRAS, BRAF, EGFR, TP53, JAK2, NPM1, and PCA3.
  • 4. A method for enriching multiple target polynucleotide sequences containing a genetic variation said method comprising: (a) providing a library of amplifying primers targeted to said multiple target polynucleotide sequence;(b) providing a library of target specific xenonucleic acid clamp oligomer specific for multiple wildtype polynucleotide sequences, wherein said xenonucleic acid includes moieties selected from the group consisting of oxy-aza, aza-aza, thio-aza and mixtures thereof;(c) generating multiple amplicons using PCR under specific temperature cycling conditions; and(d) detecting said amplicons.
  • 5. The method of claim 3, wherein said detection employs oligonucleotide probes specific for hybridization of variant polynucleotide amplicon sequences.
  • 6. A method for conducting a minimally invasive biopsy in a mammalian subject suspected of a having a neoplastic disease, said method comprising: (a) sampling of target polynucleotides derived from said mammalian subject;(b) providing a library of amplifying primers targeted to said multiple target poly-nucleotide sequence;(c) providing a library of target specific xenonucleic acid clamp oligomer specific for multiple wildtype polynucleotide sequences, wherein said xenonucleic acid includes moieties selected from the group consisting of oxy-aza, aza-aza, thi-aza and mixtures thereof;(d) generating multiple amplicons using PCR under specific temperature cycling conditions; and(e) detecting said amplicons.
  • 7. The method of claim 6, wherein said sampled target polynucleotides are sampled from cells derived from said mammalian subject.
  • 8. The method of claim 6, wherein said sampled target polynucleotides are sampled from free circulating cell free polynucleotides derived from said mammalian subject.
  • 9. The method of claim 4, which includes using multiple XNA clamp probes and amplifying primers targeted to multiple polynucleotide sequences.
  • 10. The method of claim 6, wherein said neoplastic disease is lung cancer.
  • 11. The method of claim 6, wherein said neoplastic disease is colorectal cancer.
  • 12. The method of claim 6, wherein said neoplastic disease is breast cancer.
Parent Case Info

This application is a continuation-in-part of pending U.S. Ser. No. 14/822,874 filed Aug. 10, 2015; U.S. Ser. No. 15/786,591 filed Oct. 17, 2017; and U.S. Ser. No. 15/862,581 filed Jan. 4, 2018; the entire contents of which are incorporated herein in their entirety. This application also claims the priority benefit under 35 U.S.C. section 119 of U.S. Provisional Patent Application No. 62/010,339 entitled “Method For Enrichment Of Target Mutant Polynucleotide Sequences” filed on Jun. 10, 2014; U.S. Provisional Patent Application No. 62/010,357 entitled “Detection Of Multiple Mutations In A Single Tube Using QCLAMP™ Assay QCLAMP™ Mplex” filed on Jun. 10, 2014; and U.S. Provisional Patent Application No. 62/010,359 entitled “Liquid Biopsy” filed on Jun. 10, 2014; which are in their entirety herein incorporated by reference. This application further claims the priority benefit under 35 U.S.C. section 119 of U.S. Provisional Patent Application No. 62/376,206 entitled “Specific Synthetic Chimeric Xenonucleic Acid Guide RNA; s(XNA-gRNA) For Enhancing CRISPR Mediated Genome Editing Efficiency” filed on Aug. 17, 2016; and Provisional Patent Application No. 62/376,287 filed Aug. 17, 2016 entitled “Synthetic Routes To Xenonucleic Acid (Xna) Monomers” which are in their entirety herein incorporated by reference. This application claims the priority benefit under 35 U.S.C. section 119 of U.S. Provisional Patent Application No. 62/442,898 entitled “Method For Conducting Early Detection Of Colon Cancer And/Or Of Colon Cancer Precursor Cells And For Monitoring Colon Cancer Recurrence” filed Jan. 5, 2017, which is in its entirety herein incorporated by reference.

Provisional Applications (6)
Number Date Country
62010339 Jun 2014 US
62010357 Jun 2014 US
62010359 Jun 2014 US
62376206 Aug 2016 US
62376287 Aug 2016 US
62442898 Jan 2017 US
Continuation in Parts (3)
Number Date Country
Parent 14822874 Aug 2015 US
Child 16510722 US
Parent 15786591 Oct 2017 US
Child 14822874 US
Parent 15862581 Jan 2018 US
Child 15786591 US