Systems and methods for detecting tumor development

Abstract

This patent discloses a method for detecting a patient's tumor burden. DNA is extracted from a patient's tumor tissue sample, a predetermined number of biomarker genes are selected to form a biomarker gene cluster ("customized gene cluster"). A DNA sample of circulating free cells in the patient's body fluid is isolated. DNA sequences containing biomarker genes are enriched in the free DNA fragments. The enriched DNA is sequenced. The mutant and normal DNA sequences in the enriched DNA are counted. The patient's tumor burden is then determined. Preferably, mutations in therapeutically relevant genes ("drug-targeted genes") are detected simultaneously with the detection of the customized gene cluster.

Description

[0001] This application is a divisional application of the invention patent application with the application date of November 17, 2016, application number "201680003762.4", and invention name "System and method for detecting tumor development". Technical Field

[0002] The present invention relates generally to the field of precision medicine, and more particularly to systems and methods for monitoring a patient's tumor burden by testing customized circulating tumor DNA in a patient's blood sample, preferably in combination with the detection of treatment-related gene mutations. Background Art

[0003] According to Darwinian evolutionary theory, human cancers develop through genetic or epigenetic alterations that change the molecular phenotype of individual cells. As tumors grow, mutations occur, and numerous cell populations with distinct genetic characteristics emerge. Therefore, tumor diagnostics typically include multiple genotypically distinct cell populations or clones, which are phylogenetically related and serve as substrates for screening or therapeutic intervention within the tumor microenvironment. Tumor cells that adapt to new drugs become resistant to treatment, allowing them to survive and expand. This process is difficult to halt, as cancers continuously evolve within the body over time. This requires a comprehensive understanding of tumor-specific mutations and adaptive processes to assemble a more accurate picture of cancer evolution, uncover the sources of resistance, and identify solutions to address these issues.

[0004] Current technologies are unable to capture the precise evolution of tumor mutations during tumor development. For example, tissue biopsies are invasive and often subject to spatial and temporal constraints due to the limitations of tissue anatomy. Current non-invasive circulating tumor DNA sequencing methods cannot address the diverse range of tumor-specific mutations found in different patients, and the detection process is cumbersome. Therefore, new technologies are needed to monitor tumor cell mutations in a non-invasive, precise, and advanced manner. Summary of the Invention

[0005] A first aspect of the present invention provides a method for monitoring a patient's tumor burden. The method comprises the following steps: (a) selecting a predetermined number of biomarker genes from DNA extracted from a tumor tissue sample from the patient to form a biomarker gene cluster ("customized genes"); (b) isolating circulating cell-free DNA from a bodily fluid (also known as body fluid) sample from the patient; (c) enriching DNA sequences containing the biomarker genes from the cell-free DNA fragments; (d) sequencing the enriched DNA; (e) separately counting mutant DNA and normal DNA sequences read from the enriched DNA; and (f) obtaining the patient's tumor burden.

[0006] In some embodiments, the biomarker gene cluster comprises at least 5 biomarker genes. In other embodiments, the biomarker gene cluster comprises 5-10 biomarker genes. In other embodiments, the biomarker gene cluster comprises 11-20 biomarker genes. In preferred embodiments, the biomarker gene cluster comprises 21-30 biomarker genes. In other preferred embodiments, the biomarker gene cluster comprises 31-50 biomarker genes.

[0007] In some embodiments, the enrichment step comprises the following steps: performing multiplex PCR amplification using primers specific for the biomarker genes in the biomarker gene cluster; and adding adapters to the amplified DNA to obtain a DNA library.

[0008] In some embodiments, the sequencing step is performed on an Ion S5 NGS platform. In other embodiments, the method for detecting tumor burden further comprises the step of guiding the patient's treatment plan based on the obtained patient's cell-free tumor burden data.

[0009] In a preferred embodiment, steps bf of the method for detecting tumor burden can be repeated periodically. In some embodiments, steps bf are repeated every 1-3 months.

[0010] In some embodiments, the method further comprises selecting a predetermined number of biomarker gene clusters by the following steps: (a) determining somatic mutations in DNA extracted from a tumor tissue sample of the patient; (b) calculating a clonal ratio (CR) of somatic mutations for each somatic mutation; (c) ranking the clonal ratios of somatic mutations of all somatic mutations; and (d) selecting a predetermined number of somatic mutations from the highest-ranked somatic mutations as biomarker genes.

[0011] In some embodiments, the step of counting the clonal ratio of somatic mutations comprises: (a) determining the percentage of tumor cells (TP) in the tumor tissue; (b) determining the somatic mutation allele ratio (SA) for each somatic mutation; (c) determining, for each somatic mutation, the average score or mean (PLG) of a predetermined number of true germline hyterozygosis SNPs in normal tissue that are linked to the somatic mutation; (d) determining the copy number variation value (CNVR) for each somatic mutation; and (e) calculating the somatic mutation clonal ratio by the formula:

[0012]

[0013] In some embodiments, the step of obtaining the patient's tumor burden comprises: (a) obtaining, for each biomarker gene in each biomarker gene cluster, a somatic mutant allele ratio from a circulating tumor DNA test by the following steps, comprising the steps of: (i) counting the total number of circulating DNA; (ii) counting the circulating DNA with somatic mutant alleles; (iii) dividing the number of circulating DNA with somatic mutant alleles by the total number of circulating DNA to obtain a somatic mutant allele ratio; (b) obtaining, for each biomarker gene in each biomarker gene cluster, the somatic mutant clone ratio as described above (as claimed in claim 12); and (c) obtaining tumor burden data based on the average of the ratios of each somatic mutant allele ratio to the corresponding somatic mutant clone ratio.

[0014] In some embodiments, the step of determining the percentage of tumor cells in the tumor tissue (tumor purity) includes: (a) selecting germline heterozygous single nucleotide polymorphisms (SNPs) sites (THS) from common single nucleotide polymorphisms (SNPs) in normal tissues; (b) detecting THS in the tumor tissue; (c) plotting a density curve of THS alleles; and (d) calculating the percentage of tumor cells in the tumor tissue based on the THS detected in the tumor tissue.

[0015] In some embodiments, the step of detecting THS in tumor tissue includes: (a) calling each THS allele score in the tumor tissue; (b) using an algorithm to smooth the score group density curve; (c) determining the positions of two small peaks on the density and tumor tissue TH allele ratio map; (d) determining the percentage of tumor cells in the tumor tissue by the formula TP = ((100-(A+B)) / 2+A) / 100, wherein A is the position of the first identified small peak and B is the position of the second identified small peak.

[0016] In some embodiments, the method for detecting tumor burden further comprises detecting mutations in genes associated with therapy ("drug-targeted genes"). In some embodiments, the step of detecting mutations in genes associated with drug sensitivity comprises (a) enriching circulating cell-free DNA for DNA sequences containing drug-targeted genes; (b) sequencing the enriched DNA; and (c) separately counting the number of mutant DNA and all enriched DNA sequences.

[0017] In some embodiments, the enrichment, sequencing, and counting steps for detecting mutations in drug-targeted genes are performed simultaneously with the enrichment, sequencing, and counting steps for obtaining tumor burden based on a custom gene cluster. In some embodiments, drug-targeted gene mutations are ERBB2, MET, EGFR, KRAS, PIK3CA, BRAF, KIT, NRAS, ALK, ROS1, and RET. In one embodiment, drug-targeted gene mutations can include single nucleotide changes, copy number changes, insertions, deletions, fusions, and inversions. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flow chart representing the process of monitoring tumor evolution.

[0019] Figure 2 Figure 1 is a flow chart showing the simplified process of circulating tumor DNA analysis.

[0020] Figure 3 The image shows that the allele ratio of germline heterozygous SNPs is 50%.

[0021] Figure 4 The images show that the allele ratios of germline heterozygous SNPs are 72.5% and 23.75%.

[0022] Figure 5 Graph showing SNP allele ratios associated with mutation sites in single cells.

[0023] Figure 6A Figures 6B, 6C, 6D, and 6E illustrate the somatic mutation clone ratio (CR) in different situations. TP: tumor purity; SA: somatic mutation allele ratio; PLG: average number of four linked germline heterozygous SNPs; CNVR: copy number variation.

[0024] Figure 7 Figure 3 is a graph of tumor burden obtained from circulating tumor DNA of three samples from the same patient at three time points.

[0025] Figure 8A and 8BRepresents the number of CA199 tumor markers, and the treatment time of tumor patients was from February 3, 2015 to May 26, 2016. Previous treatment: Radical resection for colon cancer in February 2015; oxaliplatin 200 mg daily plus capecitabine 1500 mg bid daily for days 1-14 / q3W on March 18, 2015; oxaliplatin 200 mg daily plus capecitabine 1500 mg bid daily for days 1-14 and bevacizumab daily for days 1 / q3W on April 8, 2015; oxaliplatin 200 mg daily plus capecitabine 1500 mg bid daily for days 1-14 and bevacizumab daily for days 1 / q3W on April 29, 2015; capecitabine 1500 mg bid daily for days 1-14 and bevacizumab daily for days 1 / q3W on June 14, 2015; capecitabine 1500 mg bid daily for days 1-14 and bevacizumab daily for days 1 / q3W on July 8, 2015. Bid 1-14 + traditional Chinese medicine / q3W; Crizotinib capsules 250 mg twice / day from January 20 to February 20, 2016; TACE embolization on March 8, 2016 and April 19, 2016. DETAILED DESCRIPTION

[0026] The present invention relates to novel systems and methods for monitoring tumor cell evolution by detecting circulating tumor DNA. These systems and methods are based, in part, on our novel discovery that the clonality ratios of somatic mutations can be obtained from exome sequencing of tumor tissue. Tumor-specific mutations can be selected as customized gene clusters, ranked by tumor mutation clonality ratio, with higher clonality ratios representing more specific tumor mutations. When combined with the clonality ratios of somatic mutations, the allele ratios of each somatic mutation in circulating DNA can be used to assess a patient's tumor burden, thereby enabling a non-invasive, precise, and progressive approach to monitoring tumor mutations.

[0027] In a first aspect, the present invention discloses a method for detecting the patient's tumor burden by selecting a predetermined number of biomarker genes from DNA extracted from a patient's tumor tissue sample to form a biomarker gene cluster (a "customized gene cluster"); isolating circulating cell-free DNA from a patient's bodily fluid sample; enriching DNA sequences containing the biomarker genes from the cell-free DNA fragments; sequencing the enriched DNA; separately counting mutant DNA and normal DNA sequences in the enriched DNA; and obtaining the patient's tumor burden. In some embodiments, the bodily fluid is blood, serum, amniotic fluid, cerebrospinal fluid, conjunctival fluid, saliva, vaginal fluid, feces, semen, urine, or sweat.

[0028] In one embodiment, if Figure 1As shown in the flowchart in , based on the exome sequencing data of tissue samples, a custom gene or a biomarker gene cluster including 20 mutation biomarkers is selected; primers are designed for each biomarker; the biomarkers are enriched by multiplex PCR using primers; adapters are added to the amplified products to prepare sequencing libraries; and finally, the prepared libraries are sequenced on a second-generation sequencing platform.

[0029] In some embodiments, the tissue sample can be formalin-fixed, paraffin-embedded (FFPE) tissue, fresh-frozen (FF) tissue, or tissue in a solution that preserves nucleic acids or protein molecules. The sample is not limited and can be fresh, frozen, or fixed. The sample can be associated with relevant information such as the age, sex, and clinical symptoms of the individual; the source of the sample; the collection method; and the storage method of the sample. The sample is typically obtained from a single individual.

[0030] In other embodiments, the tissue sample is a sample from a biopsy. A biopsy can include the process of removing a tissue sample for diagnosis or prognostic assessment, as well as the tissue specimen itself. Biopsy techniques known in the art can be applied to the methods of the present invention. The biopsy technique can be applied based on factors such as the type of tissue being evaluated (e.g., colon, prostate, kidney, bladder, lymph node, liver, bone marrow, blood cells, lung, breast, etc.), the size and type of tumor (such as solid or suspended, blood or ascites). Representative biopsy techniques include, but are not limited to, excisional biopsy, incisional biopsy, puncture biopsy, surgical biopsy, and bone marrow biopsy. "Excisional biopsy" refers to the removal of the entire tumor with a small amount of surrounding normal tissue. "Incisional biopsy" refers to the removal of a wedge of tissue that includes the tumor tissue of the cross-sectional diameter. Molecular analysis can be performed using a "core needle biopsy" or "fine needle aspiration biopsy" of the tumor, which generally obtains suspended cells from the tumor tissue. Biopsy techniques are discussed, for example, in Harrison's Principles of Internal Medicine, ed. Kasper et al., 16th edition, 2005, Chapter 70, throughout Part V.

[0031] Standard molecular biology techniques for enrichment known in the art and methods not specifically described are generally in accordance with Sambrook et al., Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, New York (1989), and Ausubel et al., Principles of Molecular Biology, John Wiley & Sons, Baltimore, Maryland (1989), and perbal, Molecular Cloning: A Laboratory Manual, John Wiley and Sons, New York (1988), and Watson et al., Recombinant DNA, American Scientific Series, New York and Billen et al.; Genome Analysis: A Laboratory Manual Series, Volumes 1-4, Cold Spring Harbor Laboratory Press, New York (1998) and in U.S. Patent Nos. 4,666,828; 4,683,202; 4,801,531; 5,192,659 and 5,272,057 and references therein, which may be cited by reference. Polymerase chain reaction (PCR) was generally performed according to PCR: Methods and Applications Guide, Academic Press, San Diego, CA (1990).

[0032] In one embodiment, selecting a predetermined number of biomarker genes is selecting tumor-specific mutations. In some embodiments, tumor-specific mutations are selected based on the frequency of expression of mutations in tumor cells. The higher the percentage of tumor cells with a mutation, the more specific this mutation is for the tumor. The percentage of tumor cells with a mutation among all tumor cells is called the cloning ratio of the tumor mutation. The higher the cloning ratio, the higher the specificity of the tumor mutation for the tumor. For example, in one method, somatic mutations in DNA extracted from a patient's tumor tissue sample are first discovered; then the somatic mutation cloning ratio (CR) of each somatic mutation is calculated; the cloning ratios of all somatic mutations are ranked from high to low; among these somatic mutations, the somatic mutation with the highest ranking position is selected to form the somatic mutation group of the biomarker gene. This biomarker gene cluster is also referred to as a customized gene cluster in the present invention.

[0033] The percentage of tumor cells in tumor tissue (tumor purity, or TP) can be determined by analyzing germline heterozygous SNPs. In one embodiment, TP can be obtained by selecting germline heterozygous SNPs from conventional SNPs in normal tissues; detecting THS in tumor tissue; plotting THS allele density; and calculating the percentage of tumor cells in tumor tissue based on THS detected in tumor tissue. Figure 3 As shown, for germline heterozygous SNPs, the density peaks at around 50%.

[0034] In an embodiment, THS detection in tumor tissue includes the following steps: (i) scoring each THS allele of the tumor tissue; (ii) using an algorithm to smooth the density curve of the scoring group; (iii) determining the positions of two small peaks on the density of the tumor tissue and the TH allele ratio curve; (iv) determining the percentage of tumor cells in the tumor tissue by the formula TP = ((100-(A+B)) / 2+A) / 100, where A is the position of the first identified small peak and B is the position of the second identified small peak. Figure 4 In one example, the germline heterozygous allele density of the tumor ranged from 23.75% to 72.5%. Due to the diversification, the TP was calculated to be 25.652%.

[0035] In certain embodiments, the step of counting the clonality of somatic mutations comprises: (i) determining the percentage of tumor cells in the tumor tissue (tumor purity, or TP); (ii) determining the somatic mutation allele ratio (SA) for each somatic mutation; (iii) for each somatic mutation, determining a mean score or average (PLG) for a predetermined number of germline heterozygous SNPs in normal tissue that are linked to the somatic mutation; (iv) for each somatic mutation, determining a copy number variation value (CNVR); and (v) calculating the clonality of somatic mutations using the formula:

[0036]

[0037] In some embodiments, as Figure 5 As shown, the PLG is derived from the average score or mean of four germline heterozygous single nucleotide polymorphisms linked to the somatic mutation site in normal tissue (PLG = (80.3% + 82.3% + 81.2% + 78.5%) / 4 = 80.56%).

[0038] Figure 6A Figures 6B, 6C, 6D, and 6E illustrate some hypothetical typical scenarios to demonstrate how to obtain clonal ratios from exome sequencing data. Red bars indicate somatic mutant alleles (labeled SA). Blue bars (labeled NTHS) indicate linked heterozygous SNPs.

[0039] like Figure 6A As shown in Scenario 1, the tumor purity (TP) is 100%, meaning all cells in the tissue are tumor cells; the somatic allele ratio (SA) is 50%, meaning 50% of alleles in tumor cells are mutated; the PLG is 50%; and the CNVR is 1, meaning there is no change in copy number. In Scenario 1, according to the CR calculation formula, the somatic mutation clone ratio (CR) is 100%, indicating that all tumor cells have somatic mutations.

[0040] like Figure 6B In Scenario 2, TP is 2 / 3, meaning that 2 / 3 of the tumor tissue cells are actually tumor cells; SA is 1 / 3, meaning that 1 / 3 of the alleles in the tumor tissue cells are mutants; PLG is 50%; and CNVR is 1. In Scenario 2, CR would be 100%, meaning that all tumor cells have somatic mutations.

[0041] like Figure 6C In Scenario 3, the TP rate is 2 / 3, meaning that 2 / 3 of the tumor tissue cells are actually tumor cells; the SA rate is 4 / 8, meaning that 4 / 8 of the tumor tissue cells are mutant alleles; the PLG rate is 5 / 8; and the CNVR rate is 8 / 6, indicating that there are two chromosome duplications. In Scenario 3, the CR rate will be 100%, meaning that all tumor cells have somatic mutations.

[0042] like Figure 6D In Scenario 4, the TP rate is 2 / 3, meaning that 2 / 3 of the tumor cells are actually tumor cells; the SA rate is 2 / 8, meaning that 2 / 8 of the tumor cells are mutant alleles; the PLG rate is 5 / 8; and the CNVR rate is 8 / 6, indicating that there are two chromosome duplications. In Scenario 4, the CR rate will be 50%, meaning that half of the tumor cells have somatic mutations.

[0043] like Figure 6E In Scenario 5, the TP rate is 2 / 3, meaning that 2 / 3 of the tumor cells are actually tumor cells; the SA rate is 3 / 8, meaning that 3 / 8 of the tumor cells are mutant alleles; the PLG rate is 7 / 8; and the CNVR rate is 8 / 6, indicating that there are two chromosome duplications. In Scenario 5, the CR rate will be 50%, meaning that half of the tumor cells have somatic mutations.

[0044] Since the clone ratio is obtained by exome sequencing of tumor tissue samples, the patient's tumor burden is first obtained by obtaining the somatic mutation allele ratio of circulating tumor DNA for each biomarker gene. The specific steps are as follows: (i) count all circulating DNA; (ii) count the circulating DNA with somatic mutation alleles; and (iii) divide the number of circulating DNA with somatic mutation alleles by the number of all circulating DNA to obtain the somatic mutation allele ratio; then the tumor burden is obtained based on the average of the ratios of each somatic mutation allele ratio and the corresponding somatic mutation clone ratio.

[0045] The number of biomarker genes selected based on the cloning ratio can vary. In some embodiments, the custom gene cluster includes at least 5 biomarker genes. In other embodiments, the custom gene cluster includes 5-10 biomarker genes. In other embodiments, the custom gene cluster includes 11-20 biomarker genes. In a preferred embodiment, the custom gene cluster includes 21-30 biomarker genes. More preferably, the custom gene cluster includes more than 30 biomarker genes.

[0046] In some embodiments, samples are collected periodically from the patient as the tumor progresses. Circulating tumor DNA is measured to determine tumor burden according to the methods described above. In some embodiments, samples are collected every 1-3 months. In other embodiments, samples are collected every 1-3 weeks, as needed.

[0047] In some embodiments, the detection of tumor burden of tumor-specific mutations is performed simultaneously with the detection of treatment-related gene mutations. These genes are referred to herein as drug-targeted genes. The drug-targeted gene cluster may include any gene known or discovered in the future to be associated with the treatment of cancer or tumors.

[0048] In one embodiment, detecting drug-targeted genes includes the following steps: enriching free circulating DNA containing DNA sequences of drug-targeted genes; sequencing the enriched DNA; and separately counting mutant DNA and all enriched DNA sequences. In some embodiments, primers are designed for these drug-targeted genes and used to enrich the drug-targeted genes in an amplification reaction. The amplification reaction of the drug-targeted genes can be performed separately from the amplification reaction of the customized gene cluster. In some embodiments, the two amplification products can be combined in the sequencing and counting steps to simplify the detection procedures of the customized genes and the drug-targeted genes.

[0049] In some embodiments, the drug-targeted genes are ERBB2, MET, EGFR, KRAS, PIK3CA, BRAF, KIT, NRAS, ALK, ROS1, and RET, which are associated with treatment. For example, the presence of the KRAS gene mutation, G13D, indicates that the tumor is resistant to panitumumab. The presence of the PIK3CA gene mutation, E545K, indicates that the tumor is sensitive to everolimus. For more information, see Table 3 below.

[0050] In some embodiments, mutations in drug-targeted genes and custom genes include single nucleotide changes, copy number changes, insertions, deletions, fusions, and inversions.

[0051] In another aspect, the present invention relates to a simplified method for analyzing circulating tumor DNA. In one embodiment of the simplified method for analyzing circulating tumor DNA, Figure 2 As shown, plasma can be collected using strcl cell-free DNA tubes for efficient and cost-optimized nucleic acid extraction. The extracted nucleic acids are then used to generate a personalized library of 20 biomarker genes, which is then sequenced on the Ion S5 NGS platform (fubsequent sequencing).

[0052] In this application, including the appended claims, the term "about," particularly when referring to a particular quantity, is meant to include a range of plus or minus ten percent.

[0053] As used herein, the singular forms "a", "an" and "the" include plural referents unless the content clearly indicates otherwise and are used interchangeably with "at least one" and "one or more".

[0054] As used herein, the terms "comprises," "comprising," "includes," "containing," "includes," and any variations thereof, refer to non-exclusive inclusion, such as a process, method, product defined by a process, or composition includes, contains, or contains an ingredient or a series of ingredients, and includes not only those ingredients but also ingredients not expressly listed or other ingredients inherent to those processes, methods, products defined by the methods, or compositions.

[0055] Example

[0056] 1. Monitoring tumor burden using circulating tumor DNA

[0057] This example illustrates the use of circulating tumor DNA to monitor tumor burden in humans. Specifically, a 55-year-old female patient with metastatic colon cancer underwent three circulating tumor DNA (ctDNA) assays. She underwent colectomy in February 2015. Pathological examination confirmed stage IV metastatic adenocarcinoma (pT4N2M1), and WES revealed KRAS wild-type status and no BRAF V600E mutation. Postoperatively, the patient received chemotherapy starting in March 2015, with three cycles of treatment every three weeks, followed by postoperative capecitabine / oxaliplatin combined with bevacizumab. The capecitabine and bevacizumab combination therapy was continued for nine months before the development of liver metastases. Subsequently, transcatheter hepatic arterial chemoembolization with oxaliplatin was performed.

[0058] Exome sequencing was performed on formalin-fixed, paraffin-embedded (FFPE) tissue, tumor samples, and matched normal blood samples from patients. DNA was analyzed by Maxwell DNA was isolated from FFPE tissues and normal peripheral blood leukocytes using the Maxwell RSC DNA FFPE Kit and the Maxwell RSC Whole Blood DNA Kit (Promega), respectively. Pure high-molecular-weight genomic DNA samples were run on agarose gels and quantified using the Qubit 3.0 (Thermo Fisher Scientific).

[0059] DNA samples were sheared using a Covaris S220. Libraries were prepared using the Agilent SureSelect Human All Exon v5 Kit (Agilent Technologies) according to the manufacturer's instructions. 200-bp DNA fragments were sequenced using paired-end 150-bp HiSeqX (Illumina) reads, achieving an average depth of >=200× for tumor DNA and >=100× for normal DNA.

[0060] Each read was then aligned with hg19 (GRCh37 / hg19, February 2009) from the UCSC genome browser using the default parameters of the Burrows Wheeler Aligner. Germline and somatic mutations were called using the standard version of GATK (Genome Analysis Tools 1.6). The tumor purity of the tumor tissue can be easily estimated using conventional dbSNPs (dbSNP 142 database) in the LOH region. After obtaining the percentage of tumor cells in the tumor tissue, the mutation clone ratio of each somatic mutation site can be directly calculated (all tumor cells are divided by mutant tumor cells). Based on the clone ratio ranking from high to low, we selected the 30 most frequent somatic mutation sites, of which PCR primers were successfully designed for 23 somatic mutation sites.

[0061] As shown in Table 1, 23 somatic tumor mutational markers were selected. Primers were designed for each of the 23 mutational biomarker genes, but 17 of the mutational biomarkers were included in the final gene cluster, for a design rate of 74%. Primers were designed using the online tool IonAmpliSeq Designer (https: / / ampliseq.com). Following the website's instructions, a CSV file displaying the genomic coordinates of each mutation was uploaded. The application type was DNA hotspot design. The reference genome was the human genome (hg19). After several hours of running the program, the design results were ready, and the primer sequences are listed in Table 2.

[0062] Table 1. Somatic tumor mutations identified by exome sequencing

[0063]

[0064]

[0065] Multiplex PCR amplification of target biomarkers was performed according to the following steps. First, DNA was quantified using the Qubit dsDNA HS Assay Kit and a Qubit 3.0 Fluorometer. Amplification reactions were then performed as follows. (Y = 10 / C, where C is the concentration of each ctDNA sample (ng / μl)). In this example, the concentrations of the three ctDNA samples were 0.178 ng / μl, 0.283 ng / μl, and 0.334 ng / μl, respectively. Therefore, all three Y values ​​exceeded 50 μl, and the remaining reaction volume was occupied by ctDNA, i.e., Y = 13 and no nuclease-free water was added.

[0066]

[0067] Table 2 Customized primers for gene biomarkers

[0068]

[0069]

[0070] A separate amplification reaction was performed for the drug-related pool. In the drug-related pool, there are 11 therapeutically relevant gene mutations, as shown in Table 3 below. The primers used are listed in Table 4.

[0071] Table 3 Drug pool genes

[0072]

[0073]

[0074] Table 4 Primers for drug pool genes.

[0075]

[0076]

[0077]

[0078] The reaction mixture of the drug pool was prepared as follows.

[0079]

[0080] The two PCR reactions were performed according to the following steps.

[0081]

[0082]

[0083] The amplified target biomarker is then terminally repaired according to the following reaction steps.

[0084]

[0085] The end repair reaction mixture was incubated at room temperature for 20 minutes. The DNA product was then purified using magnetic beads. Specifically, 150 μL of the reagent (1.5 times the volume of the sample) is added to the sheared DNA sample and thoroughly mixed with the magnetic bead suspension, followed by incubation at room temperature for 5 minutes. The tube is then placed in a magnetic stand, such as Dynamag TM Incubate in a magnetic stand for 3 minutes or until the solution appears clear and brown when viewed from an angle. Remove the supernatant without disturbing the magnetic bead pellet. Without removing the tube from the magnet, wash the beads twice with 500 μL of freshly prepared 70% ethanol. After the beads have dried, elute the DNA with 42 μL of nuclease-free water. Adapter ligation is then performed by mixing 40 μL of the supernatant containing the eluted DNA with 5 μL of ligation buffer, 1 μL of Barcode X, 1 μL of P1 adapter, 1 μL of 10 mM dNTPs, 1 μL of T4 ligase, and 1 μL of Taq polymerase. Place the reaction mixture in a thermal cycler programmed at 22°C for 20 minutes, 72°C for 10 minutes, and then hold at 10°C until ready for use. The reaction product is then purified using magnetic beads. To amplify the library, add the PCR mixture (25 μl of 2× Phusion HF PCR Master Mix, 1 μl of library amplification primer, and 24 μl of nuclease-free water) to the air-dried magnetic beads containing the adapter-ligated DNA product. Incubate the mixture at room temperature for 2 minutes. Transfer the supernatant to a new tube and place it in a thermal cycler for the next step.

[0086]

[0087] The amplified library DNA was then purified using magnetic beads and quantified using a Qubit 3.0 fluorometer according to the manufacturer's manual. The library DNA was then diluted to 15 ng / ml to prepare the template. Following the manufacturer's standard instructions, the diluted library, Ion 520 chip, consumables, and reagents were loaded into the Ion Chef instrument for emulsion PCR and enrichment with Ion Sphere particles. The prepared chip was then placed in the Ion S5 sequencer and sequencing was initiated. The mutation rate test results for the three ctDNAs are listed in Table 5 below.

[0088] First, we applied the tumor purity estimation module tool CSMT-tools to calculate the percentage of tumor cells in the tumor tissue. As shown in the following figure, the result is 54.1%. Secondly, we calculated the mutation clone ratio of each somatic mutation in Table 5. Finally, based on the proportion of each free cell tumor somatic mutation DNA fragment in the total free cell DNA, the weighted average method (clone ratio and CR score weighted method) was applied to monitor the tumor burden of the patient at three different time points. The results are shown in Figure 5. Figure 7 shown.

[0089] Table 5 Mutation rates of three DNA samples

[0090] In this example, we obtained three blood samples from patient S1 and tested the customized gene pool and drug-targeted gene pool. The input DNA was 2.3ng, 3.68ng and 4.3ng respectively. Figure 7 As shown, the monitoring results show that peripheral

[0091]

[0092] The ratio of ctDNA in blood increased significantly from 0.1 in January 2016 to 11.0 in February 2016, and then decreased significantly from 11.0 in February 2016 to 0.4 in May 2016. Figure 8A and 8B As shown, this fluctuation is correlated with the changing trend of the patient's tumor marker CA199.

[0093] Sequencing results from the second drug pool revealed a panitumumab-resistant KRAS G13D mutation and an everolimus-sensitive PIK3CA E545K mutation. The detection of these drug-sensitizing mutations will guide the patient's future treatment plan. This patient will be treated with panitumumab and / or everolimus. See Table 6 for details of these mutations.

[0094] Table 6 Mutations in the drug pool

[0095]

Claims

1. Use of a biomarker gene cluster in preparing a system for detecting tumor burden, wherein the detecting of tumor burden comprises the steps of: a. selecting a predetermined number of biomarker genes from DNA extracted from a patient's tumor tissue sample to form a biomarker gene cluster; b. Isolation of circulating cell-free DNA from a patient's body fluid sample; c. Enriching DNA sequences containing biomarker genes from cell-free DNA fragments; d. Sequencing the enriched DNA; e. Counting mutant DNA and normal DNA sequences in the enriched DNA separately; and f. Obtain the patient's tumor burden; wherein the biomarker gene cluster comprises 5-10, 11-20, or 21-30 biomarker genes; and wherein selecting a predetermined number of biomarker genes comprises the following steps: a. Identify somatic mutations in DNA extracted from patient tumor tissue samples; b. Calculating the clonal ratio CR of somatic mutations for each somatic mutation includes determining the percentage of tumor cells TP in the tumor tissue, determining the somatic mutation allele ratio SA for each somatic mutation, determining the average heterozygosity PLG obtained by sequencing a predetermined number of germline heterozygous SNPs linked to the somatic mutation in normal tissues for each somatic mutation, determining the copy number change value CNVR for each somatic mutation, and calculating the clonal ratio of somatic mutations using the formula: ; c. rank the somatic mutation clone ratios of all somatic mutations; and d. selecting a predetermined number of somatic mutations from the top-ranked somatic mutations as biomarker genes; The step of determining the percentage of tumor cells in the tumor tissue comprises selecting a germline heterozygous SNP site THS from conventional SNPs in normal tissues, detecting THS in the tumor tissue, drawing a density curve of the THS allele ratio, and calculating the percentage of tumor cells in the tumor tissue based on the THS detected in the tumor tissue; The step of detecting THS in tumor tissue includes calling each THS allele ratio in the tumor tissue, using an algorithm to smooth the density curve of the THS allele ratio, identifying two small shoulder peak positions in the THS density curve of the tumor tissue, and calculating the percentage of tumor cells in the tumor tissue using the formula TP=((100-(A+B)) / 2+A) / 100, where A is the first identified small shoulder peak position and B is the second identified small shoulder peak position.

2. The use according to claim 1, characterized in that Described step c comprises the following steps: a. multiplex PCR amplification using primers specific for the biomarker gene cluster; and b. Add adapters to the amplified DNA to obtain the library.

3. The use according to claim 1, characterized in that The sequencing in step d is performed on an NGS platform.

4. The use according to claim 1, wherein The detection of tumor load further includes the step of guiding the patient's treatment plan based on the obtained free cell tumor load.

5. The use according to claim 1, characterized in that The detecting of tumor burden further comprises periodically repeating steps bf.

6. The use according to claim 1, wherein Steps b to f are repeated every 1-3 months.

7. The use according to claim 1, characterized in that The step of obtaining the patient's tumor burden comprises: a. For each biomarker gene in the biomarker gene cluster, obtain the somatic mutant allele ratio from the circulating tumor DNA test by the following steps: i. Count all circulating DNA; ii. Counting circulating DNA with somatic mutant alleles; and iii. Divide the amount of circulating DNA with somatic mutant alleles by the amount of all circulating DNA to obtain the somatic mutant allele ratio; b. obtaining the somatic mutation clone ratio of claim 1 for each biomarker gene in the biomarker gene cluster; and c. Tumor burden data were obtained based on the average of the ratios of each somatic mutant allele ratio to the corresponding somatic mutant clone ratio.

8. The use according to claim 1, characterized in that It also includes detecting genetic mutations in genes targeted by therapeutically relevant drugs.

9. The use according to claim 8, characterized in that The method for detecting a genetic mutation in a gene targeted by a therapeutically relevant drug comprises the following steps: a. Enrichment of DNA sequences containing drug-targeted genes in circulating cell-free DNA; b. sequencing the enriched DNA; and c. Count mutant DNA and all enriched DNA separately.

10. The use according to claim 9, characterized in that The enrichment, sequencing, and counting steps for detecting mutations in drug-targeted genes are performed simultaneously with the enrichment, sequencing, and counting steps for deriving tumor burden based on custom gene clusters.

11. The use according to claim 8, characterized in that The drug-targeted genes include one or more genes among ERBB2, MET, EGFR, KRAS, PIK3CA, BRAF, KIT, NRAS, ALK, ROS1 and RET genes.

12. The use according to claim 8, characterized in that The drug-targeted genes include ERBB2, MET, EGFR, KRAS, PIK3CA, BRAF, KIT, NRAS, ALK, ROS1 and RET genes.

13. The use according to claim 8, characterized in that The drug-targeted gene mutations include single nucleotide changes, copy number changes, insertions, deletions, fusions and inversions.

Images