A method for detecting malignant tumor-derived mutations in circulating cell-free DNA

Abstract

A method for detecting malignant tumor-derived variants in circulating cell-free DNA includes obtaining multiple first sequencing results from multiple reference individuals; identifying multiple reference gene variants in the first sequencing results; calculating a repetition rate for each reference gene variant; establishing a reference database based on the reference gene variants and the corresponding repetition rates; obtaining a second sequencing result of circulating cell-free DNA from an individual to be tested; identifying at least one gene variant to be tested in the second sequencing result; comparing the gene variant to be tested with the reference gene variants in the reference database; and determining, based on a comparison result, whether the gene variant to be tested is a malignant tumor-derived variant.

Description

[Technical Field]

[0001] This invention relates to a method for detecting gene mutations, and more particularly to a method for detecting whether gene mutations in circulating cell-free DNA are malignant tumor-derived mutations. [Previous Technology]

[0002] Cancer is caused by a variety of factors, including gene mutations, environmental factors, and lifestyle, and is one of the most common major diseases affecting humans and animals. Early detection of cancer is crucial for successful treatment. Many studies have shown that detecting and identifying gene mutations or other related signs in the early stages of cancer can not only help patients receive timely and effective treatment, preventing the disease from worsening, but also improve their survival rate.

[0003] Currently, cancer detection methods include tissue biopsy, tumor diagnosis, and liquid biopsy. Tissue biopsy requires invasive surgery or puncture to obtain tumor tissue samples, which not only increases the patient's physical burden and the risk of complications, but may also fail to provide a comprehensive understanding of the lesions throughout the body due to sampling limitations. Although tumor diagnosis is a non-invasive technique, it still carries certain radiation risks, and its sensitivity and specificity for early-stage small tumors are low, making it difficult to accurately distinguish between benign lesions and malignant tumors.

[0004] In contrast, liquid sectioning only requires a blood sample to analyze whether circulating cell-free DNA (cfDNA) in the patient's blood contains circulating tumor DNA (ctDNA) produced by tumor cell apoptosis, and further identify variant features to determine the possible type of tumor. Since ctDNA can include tumors from different parts of the body, liquid sectioning can not only comprehensively and sensitively detect early cancer, but also track tumor progression, treatment effects, and recurrence risk in real time. In addition, liquid sectioning is an ideal testing method for pets, as its low-invasiveness significantly reduces the discomfort and risk to pets during the testing process, especially for older, poorly healthy, or weak pets that are not suitable for highly invasive surgery.

[0005] The main process of liquid slicing includes extracting blood samples from the subject, isolating and extracting cfDNA from the blood, sequencing the cfDNA using high-throughput sequencing technology, analyzing possible ctDNA, and combining indicators such as variant allele frequency (VAF) to assess cancer risk and provide a test report. Currently, the main problem facing liquid slicing is the potential for false positive results due to interference from clonal hematopoietic mutations of indeterminate potential (CHIP). CHIP is a gene mutation that occurs with age and is unrelated to malignant tumors, but it can still appear in cfDNA and affect test results.

[0006] To eliminate the influence of CHIP on malignant tumor detection, several published patents, US20240321390A1, US12104212B2, US20230295738A1, and US20210043275A1, propose the need for dual sequencing of cfDNA in the subject's blood and DNA in peripheral blood mononuclear cells, using variations in the DNA of peripheral blood mononuclear cells as reference sites for CHIP mutations. This allows for the filtering of CHIP-related mutations by comparing the variation sites in cfDNA and peripheral blood mononuclear cell DNA.

[0007] However, the aforementioned techniques require separate extraction, purification, sequencing, and mutation site analysis of cfDNA and peripheral blood mononuclear cell DNA for each subject, resulting in a cumbersome overall testing process and significantly increased testing costs, thus hindering the widespread adoption of cancer testing in pets. Therefore, developing a detection method that can reduce the cost of liquid slicing while effectively eliminating interference from CHIP-related mutations has become an important goal for researchers in this field. [Summary of the Invention]

[0008] To solve the above problems, the present invention provides a method for detecting malignant tumor-derived mutations in circulating cell-free DNA. The method includes the following steps: obtaining multiple first sequencing results of peripheral blood mononuclear DNA from multiple reference individuals through a computer system, wherein the peripheral blood mononuclear DNA is extracted from the reference individuals; inputting the first sequencing results into one or more mutation analysis modules of the computer system, matching the first sequencing results with a reference genome through the one or more mutation analysis modules, and identifying multiple reference gene mutations in the first sequencing results; calculating a repetition rate of each reference gene mutation in the first sequencing results through one or more computing modules of the computer system; retrieving the reference gene mutations and the corresponding repetition rates through one or more database modules of the computer system to establish a reference database; obtaining and sequencing the circulating cell-free DNA of an individual to be tested through the computer system to generate a second sequencing result, wherein the circulating cell-free DNA is extracted from the individual to be tested, and the individual to be tested is different from the reference individuals. The second sequencing result is input into one or more variant analysis modules of the computer system. The second sequencing result is matched and identified with the reference genome through the one or more variant analysis modules to obtain at least one gene variant to be detected in the second sequencing result. The gene variant to be detected is compared with the reference gene variants in the reference database through one or more comparison modules of the computer system, and a comparison result is generated. When the comparison result meets any of the following conditions, a report is output through the computer system, which indicates that the gene variant to be detected is a malignant tumor-derived variant. The condition is: (1) the gene variant to be detected does not conform to the reference gene variants; or (2) the gene variant to be detected conforms to one of the reference gene variants, and the repetition rate of the reference gene variant is less than a preset value.

[0009] The present invention further provides a method for assessing whether an individual to be tested has cancer, the method comprising the following steps: providing multiple liquid slide samples obtained from multiple reference individuals; extracting multiple peripheral blood mononuclear DNAs corresponding to the reference individuals from the liquid slide samples; performing a polymerase chain reaction on the peripheral blood mononuclear DNAs; hybridizing the peripheral blood mononuclear DNAs with a nucleic acid probe to capture corresponding multiple gene fragments; sequencing the gene fragments and obtaining multiple first sequencing results through a computer system; inputting the first sequencing results into one or more variant analysis modules of the computer system, matching and identifying the first sequencing results with a reference genome through the one or more variant analysis modules to obtain multiple reference gene variants in the first sequencing results; calculating a repetition rate of each reference gene variant in the first sequencing results through one or more computing modules of the computer system; retrieving the reference gene variants and the corresponding repetition rates through one or more database modules of the computer system to establish a reference database; The system provides a liquid slide sample obtained from the individual to be tested, which is different from the reference individuals; extracts circulating cell-free DNA from the liquid slide sample; performs a polymerase chain reaction on the circulating cell-free DNA; hybridizes the circulating cell-free DNA with a nucleic acid probe to capture a corresponding gene fragment; sequences the gene fragment and obtains a second sequencing result through the computer system; analyzes the second sequencing result and inputs it into one or more variant analysis modules of the computer system, matching and identifying the second sequencing result with the reference genome through the one or more variant analysis modules to obtain at least one gene variant to be tested in the second sequencing result; compares the gene variant with reference gene variants in the reference database through one or more alignment modules of the computer system and generates an alignment result; and outputs a report through the computer system indicating that the gene variant to be tested is a malignant tumor-derived variant when the alignment result meets any of the following conditions: (1) The gene variant to be detected does not conform to the reference gene variants; or (2) The gene variant to be detected conforms to one of the reference gene variants, and the repetition rate of the reference gene variant is less than a preset value; and the individual is assessed by the computer system based on the report to have the cancer corresponding to the malignant tumor source variant.

Implementation Method

[0011] It should be understood that the terminology used in the description of various embodiments herein is for the purpose of describing particular examples only and is not intended to be limiting. Unless the context clearly indicates otherwise or intentionally limits the number of elements, the singular forms "a" and "the" as used herein also include the plural forms. It will be further understood that the term "comprising," as used herein, indicates the presence of the described features, elements, and / or components, but does not exclude the addition or presence of one or more other features, elements, components, and / or groups thereof. Indefinite and definite articles should include both plural and singular forms unless the opposite is clearly apparent from the context.

[0012] As used herein, the term “DNA” means a polymer composed of deoxyribonucleotides and may include natural, modified, or derived purine and pyrimidine bases. Nucleic acids may contain modified nucleotides, such as methylated nucleotides or analogs, which are derived from naturally occurring nucleosides and nucleotides by substituting or modifying bases, ribose, or phosphodiester portions.

[0013] As used herein, the term “malignant tumor” means any cell or tissue that may have been transformed at the genetic, cellular, or physiological level compared to normal cells or tissues. This term typically describes the malignant proliferation of a tumor, for example, a tumor that invades surrounding tissues and is usually capable of metastasis.

[0014] This invention provides a gene detection method based on liquid slicing for detecting whether circulating cell-free DNA contains tumor-derived mutations, as a basis for assessing whether an individual to be tested has cancer. Detectable gene mutations in circulating cell-free DNA include non-tumor-derived mutations that are unrelated to or have low association with tumorigenesis, as well as tumor-derived mutations caused by tumor-related mechanisms. This invention establishes a reference database of non-tumor-derived mutations in a population and compares the circulating cell-free DNA of the individual to be tested with the reference database to determine whether the gene mutations in the circulating cell-free DNA belong to tumor-derived mutations. This effectively distinguishes between non-tumor-derived and tumor-derived mutations without the need for additional sequencing of the peripheral blood mononuclear cell (PBMC) DNA of the individual to be tested.

[0015] Specifically, non-tumor-derived mutations arise from natural biological processes (such as cell division, DNA replication, and DNA repair) or are influenced by external environmental stresses (such as oxidative stress and radiation). These include clonal hematopoietic mutations of indeterminate potential (CHIP), telomere-related mutations, and mitochondrial DNA (mtDNA) mutations. Non-tumor-derived mutations typically accumulate gradually with increasing individual age and are normal changes during biological growth, unrelated to the development of tumors or cancer. Malignant tumor-derived mutations, on the other hand, usually lead to imbalances in cellular regulatory mechanisms, thereby promoting tumor formation. Examples include specific mutations in genes such as EGFR, KRAS, or BRAF.

[0016] Referring to Figure 1, the method for detecting tumor variants in circulating cell-free DNA according to the present invention includes the following steps: Step 10: establishing a reference database of non-malignant tumor variants in a population; Step 20: detecting at least one gene variant in the circulating cell-free DNA sequence of the individual to be tested; Step 30: comparing the gene variant with the reference database and generating a comparison result; Step 40: determining whether the comparison result meets a condition; if it does, proceeding to Step 50: determining that the gene variant is a malignant tumor variant; if the comparison result does not meet the condition, proceeding to Step 60: determining that the gene variant is a non-malignant tumor variant. Then, Step 70: outputting a report based on the comparison result.

[0017] In step 10, the reference database is established from the genomic DNA of multiple reference individuals within the population to which the individual to be tested belongs. These reference individuals may include, but are not limited to, healthy individuals, individuals with benign or malignant tumors, or individuals suffering from other diseases. In one example, the genomic DNA of these reference individuals is a DNA fragment extracted from peripheral blood mononuclear cells of these reference individuals. The reference database includes multiple reference gene variants of these reference individuals relative to a standard genome, and the frequency of occurrence of these reference gene variants in these reference individuals. In one example, the individual to be tested is a mammal, and the standard genome is a standard genome corresponding to the species of that mammal. In one example, the mammal is a human, a non-human primate, a canine, a cat, a sheep, a horse, a pig, a rodent, a rabbit, or a cattle. In one example, the individual to be tested is a dog, and the standard genome is the standard genome of a dog, such as the standard genome CanFam3.1 constructed by the National Center for Biotechnology Information (NCBI) for domestic dogs (Canis lupus familiaris), but is not limited to this.

[0018] Referring to Figure 2, which is a flowchart of establishing the reference database (step 10), the steps include: step 101: obtaining liquid slide samples of the reference individuals; step 102: extracting peripheral blood mononuclear cell DNA from the reference individuals; step 103: replicating and amplifying the peripheral blood mononuclear cell DNA; step 104: capturing multiple target gene fragments through a nucleic acid probe; step 105: sequencing the target gene fragments; step 106: detecting gene variations in the target gene fragments; step 107: calculating the repetition rate of the variant sites in the reference individuals; and step 108: establishing the reference database on non-malignant tumor-derived variants in the population.

[0019] In step 101, multiple liquid slide samples are obtained from the body fluids of the reference individuals. In one example, liquid slide samples can be collected from body fluids such as blood, urine, pleural fluid, ascites, or cerebrospinal fluid by means of venous blood collection, catheter aspiration, or puncture. The number of reference individuals can be adjusted according to actual needs. In some examples, the number of reference individuals can be at least 50, at least 100, at least 200, at least 300, or at least 400 individual individuals.

[0020] In step 102, peripheral blood mononuclear cells are first isolated from the liquid slice samples, and then the genomic DNA corresponding to each reference individual is extracted from the peripheral blood mononuclear cells. Peripheral blood mononuclear cells are blood cells with nuclei, including lymphocytes and monocytes. The nucleus of peripheral blood mononuclear cells contains genomic DNA carrying the complete genetic information of the reference individual. In one example, peripheral blood mononuclear cells can be obtained from the body fluid by low-speed centrifugation combined with density gradient centrifugation, erythrocyte lysis, magnetic bead separation technology, or flow cytometry. In another example, the genomic DNA of the peripheral blood mononuclear cells can be obtained by column extraction technology, magnetic bead separation technology, or organic solvent extraction technology.

[0021] In step 103, the extracted genomic DNA is amplified using polymerase chain reaction (PCR) technology. This polymerase chain reaction technology includes, but is not limited to, conventional PCR, quantitative PCR (qPCR), multiplex PCR, and digital PCR (dPCR). In one example, the polymerase chain reaction step includes adding an adapter and / or molecular barcoding for sequencing to the reaction process. The adapter is a specific sequence composed of multiple nucleotides complementary to a binding site in the gene sequencing platform; the molecular barcoding is a sequence of randomly composed multiple nucleotides used to label the amplified specific sequence fragment.

[0022] In step 104, a nucleic acid probe is used to hybridize the amplified genomic DNA to capture the target gene fragment. This nucleic acid probe is composed of multiple nucleic acid molecules and can form complementary base pairs with some nucleic acid molecules in the target gene fragment, thereby forming a nucleic acid probe-target gene fragment complex. The nucleic acid probe-target gene fragment complex and the non-target gene fragment without the nucleic acid probe are then separated using physical or chemical methods. In one example, the captured target gene fragment does not include genes highly associated with known non-malignant tumor-derived variants, such as genes associated with epigenetic regulatory factors; in another example, the captured target gene fragment includes tumor-related genes, such as signaling genes associated with cell proliferation and regulation; in yet another example, the captured target gene fragment includes, but is not limited to, genes associated with mammary gland tumor, lymphoma, hemangiosarcoma, mast cell tumor, liver cancer, transitional cell carcinoma, soft tissue sarcoma, lung cancer, testicular cancer, osteosarcoma, prostate cancer, spindle cell sarcoma, histocytic sarcoma, squamous cell carcinoma, histiocytic sarcoma, and renal cell carcinoma. Genes associated with carcinoma, melanoma, perianal gland carcinoma, transmissible venereal tumor, or canine adenocarcinoma; in one example, the captured target gene fragments include, but are not limited to, nucleic acid sequences associated with EGFR, KRAS, BRAF, CCNE1, CDKN2A, FANCC, GNAS, HRAS, MYD88, NRAS, PALB2, STK11, CDK2, ERRFI1, or TRAF3.

[0023] In step 105, the captured target gene fragment is sequenced to obtain its sequencing results. The sequencing technology includes, but is not limited to, traditional Sanger sequencing, next-generation sequencing (NGS), or nanopore sequencing. The sequencing results include multiple reads, each read representing the sequence of the target gene fragment composed of cytosine (C), guanine (G), adenine (A), and thymine (T). The sequencing results can be received and stored by a computer system.

[0024] In step 106, the computer system is used to process and analyze the data of each sequence read in the sequencing results, and to determine whether the target gene fragment has at least one gene variation. In one example, the data processing involves using one or more data processing modules of the computer system to remove artificially synthesized sequences (such as transducers and molecular barcodes), remove repetitive sequences, and perform mapping on the sequence read data, converting the sequence read data into a data format that can be aligned with the standard genome. In one example, the variation analysis involves using one or more variation analysis modules of the computer system to match the sequencing results with the standard genome and identify the gene variations in the sequencing results compared to the standard genome. The data processing module and the variation analysis module can be executed independently or synchronously, including but not limited to Genome Analysis Toolkit (GATK), Samtools, BCFtools, Illumina BaseSpace, or Qiagen CLC Genomics Workbench. Since these gene mutations originate in the peripheral blood mononuclear cells of these reference individuals, they can be defined as non-malignant tumor-derived mutations.

[0025] In one example, the data of the gene variation may be stored in text form in a suitable file format, such as a VCF file, and may be received by the computer system. In one example, each gene variation is defined by a characteristic information and a statistical information, the characteristic information being a constituent element of the gene variation, including at least a variation sequence, a variation type, and a variation location. In one example, the variation sequence is the nucleotide change of the gene variation relative to the standard genome, and may be any, a combination of, or a deletion of cytosine (C), guanine (G), adenine (A), or thymine (T). The variation type is the change state caused by the variation sequence, and may be a single nucleotide variation (SNV), a multi-nucleotide variation (MNV), a missense variation, a frameshift variation, a nonsense variation, a splice variation, a nucleotide insertion, deletion, or substitution, or any combination thereof. The mutation location is the specific location in the standard genome that the gene mutation corresponds to. The location may include, but is not limited to, chromosomal locations (such as chr1:123456) and complementary DNA (cDNA) coordinates (such as c.76A>T).

[0026] The statistical information consists of various parameters of the gene variant. In one example, the statistical information includes a sequence depth and an allele frequency. The sequence depth is the number of times the variant sequence is detected during the sequencing process, serving as an indicator of the reliability of detecting the gene variant. For example, if the variant sequence is detected 10 times, its sequence depth is 10x; if the variant sequence is detected 200 times, its sequence depth is 200x, and so on. The higher the value of the sequence depth, the higher the reliability of the variant sequence. The allele frequency is the proportion of the allele type of the gene variant in the standard genome, serving as an indicator for assessing gene diversity and the distribution of disease-related genes.

[0027] In step 107, a computing module of the computer system calculates the repetition rate of each gene variant in the sequencing results of all reference individuals, i.e., the frequency of occurrence of the gene variant in the reference database. For example, when the number of reference individuals is 200, and the same gene variant is identified up to 50 times in these sequencing results, the repetition rate of this gene variant is 0.25. In one example, the computing module includes, but is not limited to, GATK VariantAnnotator, PLINK, or BioConductor.

[0028] In step 108, the reference gene variants and their corresponding repetition rates are retrieved through one or more database modules of the computer system to establish the reference database. In one example, the reference database contains the characteristic information and statistical information of each gene variant. The gene variants in the reference database are non-malignant tumor-derived variants of a specific population and can be used as a basis for distinguishing whether they are directly or indirectly related to tumors.

[0029] Further referring to 'Figure 3', a flowchart of detecting at least one gene variation in the circulating cell-free DNA sequence of the individual to be tested after establishing the reference database (step 20) includes step 201: obtaining a liquid slice sample of the individual to be tested, step 202: extracting the circulating cell-free DNA of the individual to be tested, step 203: replicating and amplifying the circulating cell-free DNA, step 204: capturing multiple target gene fragments through the nucleic acid probe, step 205: sequencing the target gene fragments, step 206: detecting gene variations in the target gene fragments, and step 207: excluding gene variations that do not meet a comparison condition.

[0030] The individual to be tested is different from the reference individuals, that is, the individual to be tested and any of the reference individuals are two independent individuals. Therefore, the reference database established in step 10 does not contain the gene mutation of the peripheral blood mononuclear cell DNA of the individual to be tested.

[0031] In step 201, multiple liquid slide samples are obtained from the body fluids of the individual to be tested. In one example, liquid slide samples can be collected from body fluids such as blood, urine, pleural fluid, ascites, or cerebrospinal fluid by means of venous blood collection, catheter aspiration, or puncture.

[0032] In step 202, the plasma or liquid phase portion of the body fluid is first separated, and then the circulating cell-free DNA of the individual to be tested is extracted from the plasma or liquid phase portion. In one example, a supernatant containing the circulating cell-free DNA can be separated from the body fluid by low-speed centrifugation, high-speed centrifugation, filtration, or a combination thereof. In one example, the circulating cell-free DNA can be extracted from the supernatant by column extraction, magnetic bead separation, or organic solvent extraction. In one example, the circulating cell-free DNA may contain DNA fragments from normal cells, DNA fragments released due to apoptosis or necrosis, and / or malignant tumor-derived DNA from tumor cells.

[0033] In steps 203 to 206, the same process as steps 103 to 106 is performed, replacing the genomic DNA with the circulating cell-free DNA extracted in step 202, and sequentially amplifying the circulating cell-free DNA, capturing multiple target gene fragments, sequencing these target gene fragments, and determining whether the target gene fragments contain at least one gene variant. The sequencing results obtained in step 205 and the data on the at least one gene variant obtained in step 206 can be received and stored by the computer system. In one example, the data for each gene variant of the circulating cell-free DNA includes feature information and statistical information. In one example, the feature information includes at least a variant sequence, a variant type, and a variant location. In one example, the statistical information includes a sequence depth and an allele frequency.

[0034] In one example, after completing step 206, step 207 is further executed, screening the at least one gene variant in the circulating cell-free DNA through one or more filtering modules of the computer system, filtering out gene variants that do not meet at least one alignment condition. In one example, the alignment condition includes the allele frequency of the gene variant being a first value and the sequencing depth of the gene variant being a second value. In one example, the first value is between 0.05 and 0.3. In one example, the first value is between 0.1 and 0.2. In one example, the first value is 0.15. In one example, the second value is not less than 500X. In one example, the second value is not less than 1000X. In one example, the second value is not less than 2000X.

[0035] Next, the present invention utilizes the reference database established in step 10 to compare the gene variant of the individual to be tested obtained in step 20, and determines whether the gene variant of the individual to be tested matches any gene variant in the reference database. Referring to Figure 1, in step 30, the gene variant of the individual to be tested is compared with each gene variant in the reference database through one or more comparison modules of the computer system, and a comparison result is generated. When the comparison module compares the gene variant of the individual to be tested with all gene variants in the reference database, if the gene variant matches one of the gene variants in the database, a comparison result is generated that the gene variant of the individual to be tested matches the reference database; if the gene variant fails to match any gene variant in the database, a comparison result is generated that the gene variant of the individual to be tested does not match the reference database.

[0036] In one example, the comparison module compares based on the characteristic information of gene variation. That is, when the variation sequence, variation type and variation location of the gene variation of the individual to be tested are completely identical to one of the gene variations in the reference database, the two are judged to be consistent; otherwise, when any of the variation sequence, variation type and variation location is different from one of the gene variations in the reference database, the two are judged to be inconsistent.

[0037] Further, in step 40, the comparison module of the computer system determines whether the comparison result meets any of the following conditions: (1) the gene variation of the individual to be tested does not conform to all gene variations in the reference database; or (2) the gene variation of the individual to be tested conforms to one of the gene variations in the reference database, and the repetition rate of the gene variation in the reference database is less than a preset value. When condition (1) is met, it means that this gene variation does not exist in the population composed of these reference individuals and is not a normal variation due to natural growth; when condition (2) is met, it means that the frequency of this gene variation in the population composed of these reference individuals is lower than the frequency of normal variation in natural growth. In one example, the preset value is 10%.

[0038] As above, a gene mutation that meets one of the conditions is a gene mutation that has not appeared or has a very low frequency of appearance in the population composed of these reference individuals. Therefore, it can be determined to be a gene mutation caused by a tumor or related to tumor formation, that is, a malignant tumor-derived mutation.

[0039] When the comparison result meets one of the conditions, proceed to step 50, where the comparison module of the computer system determines that the gene mutation of the individual to be tested is a malignant tumor-derived mutation. When the comparison result does not meet any of the conditions, proceed to step 60, where the comparison module of the computer system determines that the gene mutation of the individual to be tested is a non-malignant tumor-derived mutation. Next, proceed to step 70, where the computer system outputs a report based on the comparison result, indicating whether the gene mutation of the individual to be tested is a malignant tumor-derived mutation. In one example, the computer system can evaluate whether the individual to be tested has cancer based on the report.

[0040] Referring to Figure 4, this is a schematic diagram of detecting malignant tumor-derived variants in circulating cell-free DNA using the method of the present invention. The reference database 80 established in step 10 contains the genomic DNA of multiple reference individuals (e.g., the first genomic DNA 81 of the first reference individual, the second genomic DNA 82 of the second reference individual, and the third genomic DNA 83 of the third reference individual). These genomic DNAs 81, 82, and 83 contain multiple reference gene variants relative to the standard genome. For example, as shown in Figure 4, these genomic DNAs 81, 82, and 83 are identical gene fragments in different reference individuals, which can be captured in step 104 using a corresponding nucleic acid probe. The first genomic DNA 81 includes a first gene variant 811 and a second gene variant 812; the second genomic DNA 82 includes a first gene variant 821, a second gene variant 822, and a third gene variant 823; the third genomic DNA 83 includes a first gene variant 831. These gene variants 811, 812, 821, 822, 823, and 831 can be obtained in step 106 by matching the sequencing results of these reference individuals with the standard genome through the variant analysis module and identifying the differences between the two.

[0041] In one example, the reference database 80 contains the variant sequences, variant types, and variant locations of the gene variants 811, 812, 821, 822, 823, and 831. Taking Figure 4 as an example, the first gene variants 811, 821, and 831 of the first gene DNA 81, the second gene DNA 82, and the third gene DNA 83 have the same variant sequences, variant types, and variant locations; that is, these first gene variants 811, 821, and 831 are the same gene variants. Similarly, the second gene variant 812 of the first gene DNA 81 and the third gene variant 823 of the second gene DNA 82 have the same variant sequences, variant types, and variant locations, and are therefore the same gene variants.

[0042] In one example, the reference database 80 includes the repetition rate corresponding to each gene variant. Referring to Figure 4, taking an example where the reference database 80 contains only three target gene fragments: the first genomic DNA 81, the second genomic DNA 82, and the third genomic DNA 83, there are three gene variants identical to the first gene variant 821 of the second genomic DNA 82, zero gene variants identical to the second gene variant 822, and two gene variants identical to the third gene variant 823. That is, in this example, the repetition rate of the first gene variant 821 is 100%, the repetition rate of the second gene variant 822 is 33.3%, and the repetition rate of the third gene variant 823 is 66.7%. In actual operation, the number of genomic DNA fragments contained in the reference database 80 will vary depending on the reference individual and the number of target gene fragments captured.

[0043] Next, the circulating cell-free DNA of the individuals to be tested obtained in step 20 (such as the first circulating cell-free DNA 91 and the second circulating cell-free DNA 92 of the first individual to be tested) each have multiple gene variants to be tested. Taking Figure 4 as an example, these circulating cell-free DNAs 91 and 82 are the same gene fragments in different individuals to be tested, and are the same as these gene DNAs 81, 82, and 83. This gene fragment can be captured by a corresponding nucleic acid probe in step 204. The first circulating cell-free DNA 91 includes a first gene variant 911 and a second gene variant 912; the second circulating cell-free DNA 92 includes a first gene variant 921, a second gene variant 922, and a third gene variant 923. These gene variants 911, 912, 921, 922, and 923 can be obtained in step 206 by matching the sequencing results of these individuals to be tested with the standard genome through the variant analysis module and identifying the differences between the two.

[0044] In step 30, the comparison module compares the gene variants 911, 912, 921, 922, and 923 with the gene variants 811, 812, 821, 822, 823, and 831 in the reference database 80. The second gene variant 912 of the first circulating cell-free DNA 91 has a variant sequence, variant type, and variant location that are different from all gene variants in the reference database 80. That is, the second gene variant 912 does not conform to the gene variants 811, 812, 821, 822, 823, and 831. Therefore, in step 40, the comparison module determines that the second gene variant 912 meets the criteria for being identified as a malignant tumor-derived variant. The other gene variants 911, 912, 921, 922, and 923 each match one of the gene variants 811, 812, 821, 822, 823, and 831 in the reference database 80. The comparison module then determines whether the repetition rate of these gene variants 811, 812, 821, 822, 823, and 831 is less than a preset value. Referring to Figure 4, assuming this preset value is 50% in this example, the comparison module determines that the second gene variant 922 of the second circulating cell-free DNA 92 meets the criteria for being identified as a malignant tumor-derived variant.

[0045] The present invention demonstrates through the following comparative experiments that the detection method disclosed in this invention can effectively detect malignant tumor-derived mutations in circulating cell-free DNA. The following comparative experiments are for illustrative purposes only, and the scope of the invention is not limited to the embodiments. Those skilled in the art can utilize the disclosure and teachings of this invention to generate other specific embodiments, forms, and variations without excessive experimentation.

[0046] In the comparative experiment, 140 dogs were selected as test subjects, and tests were performed on experimental and comparative examples respectively. In the experimental example, the detection method disclosed in this invention was used. First, step 10 was performed to establish a reference database of non-malignant tumor-derived mutations in a population. Then, steps 20 to 70 were performed on each test subject to compare the gene mutation in the circulating cell-free DNA of each test subject with the reference database, and the gene mutation was determined to be a malignant tumor-derived mutation based on the comparison result. In the comparative example, a conventional detection method was used, namely, extracting peripheral blood cell DNA (gDNA) and circulating cell-free DNA from each test subject, and sequencing the peripheral blood cell DNA and circulating cell-free DNA respectively. Then, the peripheral blood cell DNA and circulating cell-free DNA of each test subject were compared, and the gene mutation was determined to be a malignant tumor-derived mutation based on the comparison result.

[0047] Table 1 shows the detection performance of the experimental and comparative examples. The performance indicators include sensitivity, which is the proportion of individuals who correctly identify cancer; specificity, which is the proportion of individuals who correctly identify non-cancer; positive predictive value (PPV), which is the probability that an individual actually has cancer when the test result is positive; and negative predictive value (NPV), which is the probability that an individual actually does not have cancer when the test result is negative.

[0048] [Table 1] Experimental Example Comparative example Sensitivity 87.21% 88.37% Specificity 97.67% 95.35% Positive predictive value 98.68% 96.20% Negative predictive value 79.25% 80.39%

[0049] As shown in Table 1, the sensitivity, specificity, positive predictive value, and negative predictive value of the examples and comparative examples in detecting cancer are comparable, indicating that the detection method of the present invention can achieve the same detection effect as conventional detection methods. However, compared with conventional methods, the detection method of the present invention does not require extraction and sequencing of peripheral blood cell DNA for each individual to be tested, thus significantly shortening the detection time and reducing the detection cost, which helps to improve the efficiency of cancer screening and has higher clinical application value.

[0050] In summary, the present invention provides a gene detection method based on a reference database. This method, by pre-establishing a reference database containing non-malignant tumor-derived variants of multiple reference individuals, can directly compare gene variants in the circulating cell-free DNA of the individual to be tested and determine whether they are malignant tumor-derived variants. Unlike existing technologies, it is not necessary to additionally sequence and analyze the peripheral blood cell DNA of the individual to exclude non-malignant tumor-derived variants in the circulating cell-free DNA, thereby reducing detection costs and simplifying the analysis process. [Simplified Explanation of the Diagram]

[0010] Figure 1 is a flowchart of the method for detecting malignant tumor-derived mutations in circulating cell-free DNA according to the present invention; Figure 2 is a flowchart of the method for establishing a reference database of non-malignant tumor-derived mutations in a population according to the present invention; Figure 3 is a flowchart of the method for detecting gene mutations in circulating cell-free DNA of an individual to be tested according to the present invention; and Figure 4 is a schematic diagram of the method for comparing gene mutations in the circulating cell-free DNA with those in the reference database according to the present invention.

Claims

1. A method for detecting malignant tumor-derived variants in circulating cell-free DNA, the method comprising the following steps: obtaining multiple first sequencing results of peripheral blood mononuclear cell DNA from multiple reference individuals through a computer system, wherein the peripheral blood mononuclear cell DNA is extracted from the reference individuals; inputting the first sequencing results into one or more variant analysis modules of the computer system, and matching the first sequencing results with a reference genome through the one or more variant analysis modules to identify multiple reference gene variants in the first sequencing results; calculating a repetition rate of each reference gene variant in the first sequencing results through one or more computing modules of the computer system; retrieving the reference gene variants and the corresponding repetition rates through one or more database modules of the computer system to establish a reference database; obtaining and sequencing circulating cell-free DNA from an individual to be tested through the computer system to generate a second sequencing result, wherein the circulating cell-free DNA is extracted from the individual to be tested, and the individual to be tested is different from the reference individuals; The second sequencing result is input into one or more variant analysis modules of the computer system. The second sequencing result is matched and identified with the reference genome through the one or more variant analysis modules to obtain at least one gene variant to be detected in the second sequencing result. The gene variant to be detected is compared with the reference gene variants in the reference database through one or more comparison modules of the computer system, and a comparison result is generated. When the comparison result meets any of the following conditions, a report is output through the computer system, which indicates that the gene variant to be detected is a malignant tumor-derived variant. The condition is: (1) the gene variant to be detected does not conform to the reference gene variants; or (2) the gene variant to be detected conforms to one of the reference gene variants, and the repetition rate of the reference gene variant is less than a preset value.

2. The method as described in claim 1, wherein, The default value is 10%.

3. The method as described in claim 1, wherein, The reference gene variants and the gene variant to be detected are defined by a feature information and a statistical information, respectively. The feature information includes a variant sequence, a variant type, and a variant location. When the gene variant to be detected is completely identical to the variant sequence, variant type, and variant location of one of the reference gene variants, the gene variant to be detected is determined to conform to the reference gene variant. When the gene variant to be detected is not identical to any of the variant sequence, variant type, and variant location of one of the reference gene variants, the gene variant to be detected is determined to not conform to the reference gene variant.

4. The method as described in claim 3, wherein, The statistical information includes an allele mutation frequency and a certain sequence depth. In the step of obtaining the at least one gene variant to be detected in the second sequencing result, the method further includes filtering gene variants that do not meet at least one comparison condition through one or more filtering modules of the computer system. The comparison condition includes the allele mutation frequency of the gene variant to be detected being a first value and the sequence depth of the gene variant to be detected being a second value.

5. The method as described in claim 4, wherein, The first value is between 0.05 and 0.

3.

6. The method as described in claim 4, wherein, The second value is not less than 1000X.

7. The method as described in claim 1, wherein, These first and second sequencing results were obtained by hybridizing the circulating cell-free DNA of the reference individuals and the individuals to be tested with a nucleic acid probe to capture a target gene fragment corresponding to a tumor-related gene, and then sequencing the target gene fragment.

8. The method as described in claim 7, wherein, The target gene fragment includes nucleic acid sequences associated with breast cancer, lymphoma, angiosarcoma, mast cell tumor, liver cancer, transitional cell carcinoma, soft tissue sarcoma, lung cancer, testicular cancer, osteosarcoma, prostate cancer, spindle cell sarcoma, tissue sarcoma, squamous cell carcinoma, histiocytic sarcoma, renal cell carcinoma, melanoma, perianal adenocarcinoma, infectious venereal tumors, or canine anal cystadenocarcinoma.

9. The method as described in claim 7, wherein, The target gene fragment includes nucleic acid sequences associated with EGFR, KRAS, BRAF, CCNE1, CDKN2A, FANCC, GNAS, HRAS, MYD88, NRAS, PALB2, STK11, CDK2, ERRFI1, or TRAF3.

10. The method as described in claim 1, wherein, The individual to be tested is a mammal.

11. The method as described in claim 10, wherein, The mammal can be a human, a non-human primate, a dog, a cat, a sheep, a horse, a pig, a rodent, a rabbit, or a cow.

12. A method for assessing a candidate individual for cancer, the method comprising the following steps: providing multiple liquid slide samples obtained from multiple reference individuals; extracting multiple peripheral blood mononuclear cell DNA corresponding to the reference individuals from the liquid slide samples; performing a polymerase chain reaction on the peripheral blood mononuclear cell DNA; hybridizing the peripheral blood mononuclear cell DNA with a nucleic acid probe to capture corresponding multiple target gene fragments; sequencing the target gene fragments and obtaining multiple first sequencing results through a computer system; inputting the first sequencing results into one or more variant analysis modules of the computer system, and matching and identifying the first sequencing results with a reference genome through the one or more variant analysis modules to obtain multiple reference gene variants in the first sequencing results; calculating a repetition rate of each reference gene variant in the first sequencing results through one or more computing modules of the computer system; and retrieving the reference gene variants and the corresponding repetition rates through one or more database modules of the computer system to establish a reference database. The system provides a liquid slide sample to be tested, obtained from an individual to be tested, which is different from the reference individuals; extracts circulating cell-free DNA from the liquid slide sample; performs a polymerase chain reaction on the circulating cell-free DNA; hybridizes the circulating cell-free DNA with a nucleic acid probe to capture a corresponding target gene fragment; sequences the target gene fragment and obtains a second sequencing result through the computer system; inputs the second sequencing result into one or more variant analysis modules of the computer system, and matches and identifies the second sequencing result with the reference genome through the one or more variant analysis modules to obtain at least one gene variant to be tested in the second sequencing result; compares the gene variant to be tested with the reference gene variants in the reference database through one or more alignment modules of the computer system and generates an alignment result; and outputs a report through the computer system when the alignment result meets any of the following conditions, the report indicating that the gene variant to be tested is a malignant tumor-derived variant, the condition being: (1) The gene variant to be tested does not conform to the reference gene variants; or (2) The gene variant to be tested conforms to one of the reference gene variants, and the repetition rate of the reference gene variant is less than a preset value; and the computer system assesses that the individual to be tested has the cancer corresponding to the malignant tumor source variant based on the report.

13. The method as described in claim 12, wherein, The cancers include breast cancer, lymphoma, angiosarcoma, mast cell tumor, liver cancer, transitional cell carcinoma, soft tissue sarcoma, lung cancer, testicular cancer, osteosarcoma, prostate cancer, spindle cell sarcoma, tissue sarcoma, squamous cell carcinoma, histiocytic sarcoma, renal cell carcinoma, melanoma, perianal adenocarcinoma, infectious venereal tumors, or canine anal cystadenocarcinoma.

14. The method as described in claim 12, wherein, These target gene fragments include nucleic acid sequences associated with EGFR, KRAS, BRAF, CCNE1, CDKN2A, FANCC, GNAS, HRAS, MYD88, NRAS, PALB2, STK11, CDK2, ERRFI1, or TRAF3.

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