Next-generation sequencing-based method for detection of microsatellites stability and genomic changes in plasma samples

Abstract

To provide a method for determining a stability status of microsatellite loci using a plasma sample from a cancer patient based on next-generation high-throughput sequencing.SOLUTION: A method comprises the following steps: 1) determining length characteristics of repetitive sequences of multiple microsatellite loci in a plasma sample and a MSS plasma sample as a reference sample on the basis of next-generation sequencing method; 2) calculating its corresponding enrichment index Z score for any one of microsatellite loci; 3) summing the enrichment index Z score of all microsatellite loci to calculate the index MS score for determining the status of microsatellites of the sample; 4) calculating a mean and a standard deviation SD of the MS score of the MSS plasma sample as the reference sample, with mean+3SD as the threshold cutoff; and 5) performing determination using the MS score and cutoff.SELECTED DRAWING: None

Description

[Technical field]

[0001] <CROSS REFERENCE TO RELATED APPLICATIONS> This application claims priority to the following patent application, filed on September 29, 2018, application number CN201811149011.0, entitled "Next-generation sequencing-based method for detecting microsatellite stability and genomic alterations from plasma," and the following patent application, filed on September 29, 2018, application number CN201811149015.9, entitled "Microsatellite biomarker panel, detection kit and use thereof."

[0002] <Technical field> The present invention relates to a biomarker panel, a kit for detecting same, a method for detecting microsatellite stability in plasma samples using same, and its use in the non-invasive diagnosis, prognosis assessment, treatment selection, or genetic screening of cancer, preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer. [Background technology]

[0003] Microsatellites are short repeated DNA sequences or single nucleotide regions in the genome. In tumor cells, the failure of mismatch repair genes due to DNA methylation or genetic mutations leads to microsatellite repeat mismatches (microsatellite mutations), shortening or lengthening the sequence, which results in microsatellite instability (MSI). Depending on the degree of instability, MSI can be classified into microsatellite instability-high (MSI-H), microsatellite instability-low (MSI-L) and microsatellite stable (MSS) types.

[0004] Numerous studies have shown that MSI is involved in the development of malignant tumors and is closely associated with colorectal cancer (e.g., intestinal cancer), gastric cancer, and endometrial cancer. For example, about 15% of colorectal cancer patients show MSI-H phenomenon, among which more than 90% of typical hereditary nonpolyposis colorectal cancer (HNPCC) patients show MSI-H, which indicates that MSI-H can be used as an important marker in detecting HNPCC patients. Compared with MSS (i.e., microsatellite stable) colorectal cancer, colorectal cancer patients with MSI-H have a better prognosis, and the drug response of both is also different, which suggests that MSI-H can be used as an independent predictor of colorectal cancer prognosis. Therefore, MSI testing is very important for colorectal cancer patients.

[0005] The National Comprehensive Cancer Network (NCCN, 2016 Version 2) colorectal cancer treatment guidelines, updated in 2016, clearly state for the first time that "all patients with a history of colorectal cancer should be tested for MMR (mismatch repair) or MSI." This is because MSI-H (i.e., high microsatellite instability) stage II colorectal cancer has a good prognosis (simple surgery 5y-OS rate is 80%) and cannot benefit from 5FU adjuvant chemotherapy (it is harmful). The guidelines also recommend for the first time the application of PD-1 monoclonal antibodies Pembrolizumab and Nivolumab to the treatment of advanced mCRC with dMMR / MSI-H molecular phenotype, fully demonstrating the importance of detecting MMR and MSI in advanced colorectal cancer. At the same time, because of the large number of genes associated with hereditary colorectal cancer, the 2016 updated NCCN Guidelines for Colorectal Cancer Genetic Risk Assessment recommends that patients and their family members with a clear family history undergo initial detection using multigene panel sequencing.

[0006] In 2017, Merck's PD-1 monoclonal antibody Keytruda was approved by the US FDA for the treatment of patients with solid tumors with MSI-H or deficient mismatch repair (dMMR). This again demonstrated that MSI-H can be used as a pan-cancer tumor marker independent of tumor site. Therefore, the detection of cancer by MSI is of great importance.

[0007] Currently, the detection method of MSI is limited to tissue detection. For example, MMR gene tests performed in hospitals in China usually include only MLH1 and MSH2, and some of them also include MSH6 and PMS2 at the same time, but the concordance rate between the positive results and the MSI test results is low. Only a few hospitals perform MSI status detection by PCR combined with capillary electrophoresis, and most of them are outsourced detection. In this method, 5 to 11 single nucleotide repeat sites, usually about 25 bp in length, are selected, and after PCR amplification, their length distribution intervals are measured by capillary electrophoresis to determine the microsatellite instability of the sample. This method is the current gold standard detection method. Recently, the detection method of MSI in tissue based on next-generation sequencing has been proven to show a very high concordance rate with PCR-MSI, which can create a genome map while determining the MSI status, providing more information for cancer diagnosis. However, all of these methods require a sufficient proportion of tumor cells. Because the amount of circulating tumor DNA (ctDNA) in the blood is extremely low, tissue-based methods cannot be achieved in plasma.

[0008] Tumor blood tests have characteristics not found in tissue tests, such as non-invasiveness, real-timeness, and non-tissue specificity, and are of great clinical significance. Therefore, there is a strong need in the art for a plasma-based MSI detection method, particularly a method for detecting MSI in a tumor blood test in the non-invasive diagnosis, prognosis evaluation, treatment selection, or genetic screening of cancer, preferably colorectal cancer (e.g., intestinal cancer), gastric cancer, or endometrial cancer. Summary of the Invention

[0009] The present invention is the first to present a method for detecting plasma MSI. Compared with the detection of tissue MSI, the detection of plasma MSI of the present invention has the characteristics of non-invasiveness, real-timeness, non-tissue specificity, and the ability to detect multiple lesions early. At the same time, the method of the present invention can realize the detection of microsatellite status in plasma samples with very low ctDNA content, filling the gap in the detection of microsatellite status by plasma samples. In addition, the method of the present invention has a fast detection speed, does not depend on the matching of white blood cell samples, is low in price, is convenient to detect, and can determine the microsatellite stability (MS) status of a sample with high accuracy, high sensitivity, and high specificity.

[0010] Furthermore, the detection method of the present invention can be used for non-invasive diagnosis, prognosis assessment, or treatment selection in patients with cancer, preferably colorectal cancer (eg, intestinal cancer), gastric cancer or endometrial cancer.

[0011] Specifically, the present invention relates to the following aspects:

[0012] In one aspect, the invention provides a biomarker panel comprising one or more of the eight microsatellite loci shown in Table 1.

[0013] In another aspect, the invention provides a biomarker panel comprising a combination of microsatellite loci and one or more genes, wherein the microsatellite loci include the eight microsatellite loci set forth in claim 1, or any combination thereof, and the one or more genes are any one or more of the following 41 genes: AKT1, APC, ATM, BLM, BMPR1A, BRAF, BRCA1, BRCA2, CDH1, CHEK2, CYP2D6, DPYD, EGFR, EPCAM, ERBB2, GALNT12, GREM1, HRAS, KIT, KRAS, MET, MLH1, MSH2, MSH6, MUTYH, NRAS, PDGFRA, PIK3CA, PMS1, PMS2, POLD1, POLE, PTCH1, PTEN, SDHB, SDHC, SDHD, SMAD4, STK11, TP53, UGT1A1.

[0014] In another aspect, the invention provides a kit for detecting microsatellite stability in a plasma sample, comprising a detection reagent for use in a biomarker panel of the invention.

[0015] In another aspect, the invention provides a kit for use in the non-invasive diagnosis, prognosis assessment, treatment selection or genetic screening of cancer, preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer, comprising a detection reagent for use in the biomarker panel of the invention.

[0016] Preferably, in the kit provided by the present invention, the plasma sample is a cancer plasma sample, preferably a colorectal cancer plasma sample, such as a colon cancer plasma sample, a gastric cancer plasma sample, an endometrial cancer plasma sample. More preferably, the microsatellite stability includes types of microsatellite instability-high (MSI-H), microsatellite instability-low (MSI-L), and microsatellite stable (MSS).

[0017] In one embodiment, in the kit provided by the present invention, the detection reagent is a reagent for performing high-throughput next-generation sequencing (NGS).

[0018] Furthermore, the present invention relates to the use of the biomarker panel in detecting the stability of microsatellites in plasma samples.Preferably, said plasma samples are cancer plasma samples, preferably colorectal cancer plasma samples, such as intestinal cancer plasma samples, gastric cancer plasma samples, endometrial cancer plasma samples.More preferably, said microsatellite stability comprises the types of microsatellite instability-high (MSI-H), microsatellite instability-low (MSI-L) and microsatellite stable (MSS).

[0019] The present invention also relates to the use of the biomarker panel in the non-invasive diagnosis, prognosis assessment, treatment selection or genetic screening of cancer, preferably colorectal (eg intestinal), gastric or endometrial cancer.

[0020] In one aspect, the invention provides a method for determining microsatellite marker loci that can be used to detect the stability status of microsatellites in a plasma sample, comprising the steps of: 1) detecting microsatellite loci of a sequencing region in a sample; 2) counting the number of reads of different repeat length types counted by the NGS data statistics for any one of the microsatellite loci i (a read is an estimated sequence of base pairs (or base pair probabilities) corresponding to all or part of a single DNA fragment); and 3) determining, for any one of the microsatellite loci, a length characteristic of the repeat sequence of the locus in a microsatellite stability type (MSS) and a length characteristic of the repeat sequence of the locus in a high microsatellite instability type (MSI-H); wherein the MSS length characteristic is a minimum contiguous length range such that the number of corresponding reads in the MSS sample exceeds 75% of the total number of reads supported at the locus; and wherein the MSI-H length characteristic is a contiguous length range that is highly differentiated in the MSS sample and the MSI-H sample, wherein a) the total number of reads supported in this range is less than 0.2% of the total number of reads at the locus in the MSS sample, and b) accounts for more than 50% of the total number of reads at the locus in the MSI-H sample, and the microsatellite locus having the above characteristics is a detection marker for the microsatellite locus.

[0021] In one embodiment, in the method for determining microsatellite marker loci, the samples include normal white blood cells and samples derived from tissues of cancer patients, where the cancer is preferably colorectal cancer (e.g., intestinal cancer), gastric cancer or endometrial cancer.Preferably, the microsatellite loci determined by the method for determining microsatellite marker loci of the present invention include one or more of the eight microsatellite loci shown in Table 1.

[0022] More preferably, in the method for determining a microsatellite marker locus, the detection of said microsatellite stability status is used for the non-invasive diagnosis, prognosis assessment, treatment selection or genetic screening of cancer, preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer.

[0023] In one aspect, the present invention provides a method for determining the stability of microsatellite loci from plasma samples of cancer patients based on next-generation high-throughput sequencing methods, comprising the steps of: 1) measuring the length characteristics of repeat sequences of a plurality of microsatellite loci in a plasma sample and an MSS plasma sample as a reference sample based on a next-generation sequencing method, wherein the plurality of microsatellite loci include one or more microsatellite loci selected from the eight microsatellite loci shown in Table 1; 2) calculating the corresponding enrichment index Zscore for any one of the microsatellite loci described in 1); 3) summing the enrichment indices Zscore of all microsatellite loci to calculate an index MSscore that determines the microsatellite status of the sample; 4) calculating the mean and standard deviation (SD) of the MSscore of the MSS plasma sample as the reference sample, and setting the mean+3SD as a threshold cutoff; 5) A step of determining a plasma sample derived from a cancer patient as MSI-H if its MSscore>cutoff, and as MSS if its MSscore≦cutoff.

[0024] In one embodiment, in a method for determining the stability status of microsatellite loci from plasma samples of cancer patients based on next-generation high-throughput sequencing, the Zscore is S It is evaluated by.

number

number

[0025] In one embodiment, in the method of determining the stability status of microsatellite loci from plasma samples of cancer patients based on next generation high throughput sequencing, the MSscore is calculated based on the following formula:

number

[0026] Preferably, said cancer is colorectal cancer (eg intestinal cancer), gastric cancer or endometrial cancer.

[0027] Furthermore, in another aspect, the present invention provides a method for detecting microsatellite stability status and disease-associated genetic mutations in a patient based on next-generation high-throughput sequencing methods, thereby providing clinical guidance regarding risk management, treatment and / or prognosis of the patient or his / her family, comprising the steps of: (1) simultaneously detecting multiple microsatellite loci according to claim 15; (2) determining the stability status of the microsatellite loci in said sample according to the method of any one of claims 15 to 18; (3) obtaining detection results of one or more of the disease-related genes according to the sequencing results; (4) Providing clinical guidance regarding risk management, treatment and / or prognosis for the patient or his / her family by combining the results of steps (2) and (3) above.

[0028] Preferably, in the method provided by the present invention for detecting microsatellite stability status and disease-associated genetic mutations in a patient based on next generation high throughput sequencing to provide clinical guidance regarding risk management, treatment and / or prognosis of said patient or his / her family, said disease is cancer, preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer.

[0029] Furthermore, in another aspect, the present invention relates to a kit for use in one of the various methods of the present invention, comprising reagents for detecting a plurality of microsatellite loci as described above.

[0030] Furthermore, in another aspect, the present invention provides an apparatus for determining microsatellite marker loci used for detecting the stability status of microsatellites in a plasma sample, comprising the following modules: a sequencing data reading module for reading the sequencing data of the sample acquired and stored by the sequencing device; a microsatellite marker locus detection module for analyzing and detecting all microsatellite loci in the sequencing region in the sample from the sequencing data of the sample; a repeat sequence length type determination module for counting the number of reads of each length type of different repeat sequences by the sample sequence data read by the sequencing data reading module for any one of the microsatellite loci i; and a determination module for determining whether any one of the microsatellite loci i is a microsatellite marker locus, the determination module including a first analysis module, a second analysis module, and a third analysis module; The first analysis module is used to determine a length characteristic of a repeat sequence at a locus at microsatellite stability (MSS) and to determine whether the number of corresponding reads in the MSS sample is greater than 75% of the total number of reads supported at the locus, where the MSS length characteristic is a minimum range of contiguous lengths, where a positive result is recorded as "+" and a negative result is recorded as "-", The second analysis module is used to determine a length characteristic of a locus repeat sequence at high microsatellite instability (MSI-H) and to determine a) and b) below, wherein the MSI-H length characteristic is a contiguous length range that is highly distinct in MSS samples and MSI-H samples, a) determining whether the total number of reads supported within the contiguous length range is less than 0.2% of the total number of reads at the locus in the MSS samples, recording a positive result as "+" and a negative result as "-", b) determining whether the reads account for 50% or more of the total number of reads at the locus in the MSI-H sample, recording a "+" if a positive result is obtained and a "-" if a negative result is obtained; The third analysis module is used to analyze the results of the first analysis module and the second analysis module, and if three positive results, i.e., three "+", are obtained, the microsatellite locus i is determined as a microsatellite marker locus.

[0031] Preferably, in the device for determining microsatellite marker loci used for detecting the stability status of microsatellites in plasma samples provided by the present invention, said samples include normal white blood cells and samples derived from tissues of cancer patients, and said cancer diseases are preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer. More preferably, the microsatellite loci determined by the device include one or more of the eight microsatellite loci shown in Table 1.

[0032] In one embodiment, the present invention provides a device for determining microsatellite marker loci for use in detecting the stability status of a microsatellite in a plasma sample, wherein said detection of the stability status of a microsatellite is used for non-invasive diagnosis, prognosis assessment, treatment selection or genetic screening of cancer, preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer.

[0033] Further, in another aspect, the present invention provides an apparatus for determining the stability status of microsatellite loci from plasma samples of cancer patients based on next generation high throughput sequencing methods, comprising the following modules: a sequencing data reading module for reading the sequencing data of the sample acquired and stored by the sequencing device; a repeat sequence length signature determination module for analyzing the repeat sequence length signatures of multiple microsatellite loci in the plasma sample and the MSS plasma sample as a reference sample from the sequencing data of the samples; wherein the plurality of microsatellite loci comprises one or more microsatellite loci selected from the eight microsatellite loci set forth in Table 1; an enrichment index calculation module for calculating the enrichment index Zscore of microsatellite loci; a microsatellite status index calculation module for calculating an index MSscore that can determine the microsatellite status of a sample by summing the enrichment index Zscore of all microsatellite loci; A threshold calculation module that calculates the mean value and standard deviation (SD) of the MSscore of the MSS plasma sample as the reference sample and sets the mean value + 3SD as the threshold cutoff; and A microsatellite locus stability status determination module for comparing the index MSscore with a threshold cutoff for a plasma sample derived from a cancer patient, such that if MSscore>cutoff, the sample is determined to be MSI-H, and if MSscore≦cutoff, the sample is determined to be MSS.

[0034] In one embodiment, in a device for determining the stability status of microsatellite loci by plasma samples of cancer patients based on next generation high throughput sequencing, the Zscore is S It is evaluated by.

number

number

[0035] Preferably, in the above-mentioned device for determining the stability state of a microsatellite locus, the MSscore is calculated based on the following formula:

number

[0036] More preferably, in the device for determining the stability status of microsatellite loci as described above, said disease is cancer, preferably colorectal cancer (eg intestinal cancer), gastric cancer or endometrial cancer. [Brief description of the drawings]

[0037] [Figure 1]FIG. 1(A) shows the distribution of the number of reads of each repeat sequence length of the microsatellite marker locus bMS-BR1 in complete MSI-H cancer cells and white blood cell samples. The blue frame (lower) indicates that the MSS characteristic range of the locus is 22-25 bp, and the red frame (upper) indicates that the MSI-H characteristic range of the locus is <16 bp. FIG. 1(B) shows the distribution of fragments of each repeat sequence length of non-marker loci in complete MSI-H cancer cells and white blood cell samples. The length of the repeat sequence of the locus was shortened by about 2 bp, but this difference is not enough to distinguish from the variation in the capture of white blood cells themselves under conditions where the ctDNA content of the tumor is very low, and there is no repeat sequence length type that appears frequently only in MSI-H samples. [Diagram 2] Figure 2 shows the detection effect of bMSISEA. Figure 2(A) shows the distribution of MSscore of 127 intestinal cancer plasma samples, where the MS status was determined by matched tissue, including a total of 44 MSI-H samples and 83 MSS samples. If the MSscore was higher than cutoff=15, the plasma sample was determined as MSI-H, and if the MSscore was 15 or less, it was determined as MSS. Figure 2(B) shows the correlation between maxAF and MSscore of 44 MSI-H samples. Red dots (below the horizontal line) indicate that MSscore>15, and the sample was determined as MSI-H, and blue dots (above the horizontal line) indicate that MSscore did not meet the threshold, and the sample was determined as MSS. Figure 2(C) shows the correlation between detection sensitivity and maxAF by simulation samples. The results are based on 350 simulation samples with different ctDNA content gradients. The horizontal axis indicates that only samples with maxAF greater than the corresponding value are counted, and the vertical axis indicates the sensitivity of MSI-H detection. When maxAF>0.2%, the sensitivity of MSI-H detection is greater than 93%, and when maxAF>0.5%, the sensitivity is greater than 98%. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0038] The present invention provides for the first time a method for detecting microsatellite stability and disease-related genes by plasma based on next generation sequencing, and based on this detection method, MSI loci for detecting cancer, preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer, with high sensitivity and specificity.

[0039] Furthermore, the present invention establishes a method for determining microsatellite marker loci that can be used to detect microsatellite status based on plasma samples. Moreover, the present invention realizes the simultaneous detection of multiple microsatellite loci and multiple disease-related genes in a sample, which can provide more comprehensive conclusions and suggestions regarding prognosis, treatment, investigation, etc. for the detected samples.

[0040] Thus, the present invention provides a method for detecting plasma MSI for the first time, and compared with the detection of tissue MSI, the detection of plasma MSI of the present invention has the characteristics of non-invasiveness, real-timeness, non-tissue specificity, etc. At the same time, the method of the present invention can realize the detection of microsatellite status in plasma samples with very low ctDNA content, filling the gap in the detection of microsatellite status by plasma samples. In addition, the method of the present invention can achieve a very high accuracy rate for samples with ctDNA content above 0.4%, has a fast detection speed, does not depend on the matching of white blood cell samples, is low in price, is convenient in detection, and can determine the microsatellite stability (MS) status of a sample with high sensitivity and high specificity.

[0041] Furthermore, the detection method of the present invention can be used for non-invasive diagnosis, prognosis assessment, or treatment selection in patients with cancer, preferably colorectal cancer (eg, intestinal cancer), gastric cancer or endometrial cancer.

[0042] The present invention also provides an apparatus for determining microsatellite marker loci used to detect the stability status of microsatellites in plasma samples, and an apparatus for determining the stability status of microsatellite loci using plasma samples from cancer patients based on next generation high throughput sequencing methods.

[0043] The present inventors found that for samples with high microsatellite instability, the microsatellite loci have numerous repeat expansions or contractions due to erroneous DNA duplications. In this regard, by comparing the length types of repeat sequences in the reads of MSI-H tissue samples and normal white blood cell samples, the inventors found that the length types of repeat sequences that appear frequently in MSI-H tissue samples and rarely appear in normal white blood cell samples are used as the length characteristics of the repeat sequences of the loci in the MSI-H state.

[0044] The specific criteria for selecting the marker locus are as follows: a) the number of reads within the length range of the repeat sequence in the MSS sample is less than 0.2% of the total number of reads at the locus; b) the number of reads within the range in the MSI-H sample accounts for more than 50% of the total number of reads supported at the locus, where the length range is defined as the length characteristic of the repeat sequence of the locus in the MSI-H state. The above two conditions ensure that the reads covering the length characteristic of MSI-H are almost entirely derived from tumor DNA, even when the content of ctDNA is extremely low.

[0045] Based on this selection, we screened eight microsatellite marker loci (see Table 1 for details). Table 1. Information on microsatellite detection marker loci [Table 1]

[0046] The present invention is based on a method for determining the stability status of microsatellite loci in plasma samples derived from cancer patients based on next-generation high-throughput sequencing; that is, the main strategy of the applicant's microsatellite instability plasma detection technology named bMSISEA is to first find marker loci with completely different read coverage in MSI-H and MSS states based on tissue samples, describe the main length types of reads supported by the loci in both states, and evaluate the instability status by enrichment analysis of the read characteristics in the MSI-H state for each marker locus, thereby determining the microsatellite status of the sample.

[0047] The method of determining the stability status of microsatellite loci in plasma samples derived from cancer patients of the present invention includes the following steps: 1) preparing samples, detecting microsatellite loci in sequencing regions, and preparing data including statistics on the length type of repeat sequences of the loci; 2) screening marker loci and describing locus characteristics; 3) enrichment analysis of microsatellite instability characteristics; 4) evaluating the average variation level of enrichment index of each locus; 5) constructing an MSscore based on the relative levels of enrichment index of the measured plasma samples and determining the MS status of the samples.

[0048] Further, the specification provides the following examples to aid in the understanding of the present invention, the scope of which is set forth in the appended claims. It should be understood that certain procedures can be modified without departing from the spirit of the invention.

[0049] Working Example 1. Data preparation: Gene panel detection was performed based on next-generation sequencing as follows: The tissue sample collection procedure was as follows: DNA was extracted from tumor tissues and paracancerous normal tissues using the QIAamp DNA FFPE tissue kit (QIAGEN: 56404). Accurate quantification was performed using a Qubit3.0 fluorometer and a dsDNA HS Assay Kit (ThermoFisher: Q32854). DNA was physically fragmented into 180-250 bp fragments using a Covaris M220 sonicator (Covaris: PN500295), end-repaired, phosphorylated, and deoxyadenine was added to the 3' end, and ligated with a linker. The ligated DNA was then purified with Agencourt AMPure XP paramagnetic beads, pre-amplified with PCR polymerase, and the purified amplified products were hybridized with a multiplex biotin-labeled probe set customized by Agilent (the gene panel design included sequences from exons and some intron regions of 41 genes). Successfully hybridized fragments were specifically eluted and amplified with PCR polymerase, followed by quantification and fragment length distribution measurement, and next-generation sequencing was performed with an Illumina Novaseq 6000 sequencer (catalog number: 20012850) at a sequencing depth of 1000X.

[0050] The blood sample collection procedure is as follows. First, free DNA in plasma and genomic DNA of matched peripheral blood leukocytes were extracted with a nucleic acid extraction reagent, and the genomic DNA of the leukocytes was fragmented. Then, a whole genome prelibrary was created through procedures such as linker addition and PCR amplification. A biotin-labeled RNA probe of a specific sequence was hybridized with this prelibrary to specifically capture a portion of the exon and intron regions (the entire coding region, exon-intron junction region, UTR region, and promoter region) of 41 genes in the human genome. The DNA fragments captured by the probe were enriched with streptavidin magnetic beads, and the enriched DNA fragments were used as templates for amplification to create the final library. After quantification and quality control of the final library, high-throughput sequencing was performed on the final library at a sequencing depth of 15000X using an IlluminaNovaSeq gene sequencer.

[0051] Finally, the measured sequences were aligned to the human genome sequence (version hg19) using BWA version 0.7.10, GATK 3.2 for local optimization of the alignment, VarScan 2.4.3 for variant calling, and ANNOVAR and SnpEff 4.3 for variant annotation. For variant calling, loci with low coverage were removed by VarScan fpfilter (tissue: less than 50X, plasma: less than 500X, leukocyte: less than 20X); for indels and single point mutations, at least five and eight mutated reads were required, respectively.

[0052] 2. Statistics of repeat length types of microsatellite loci based on next-generation high-throughput sequencing (NGS) data The detection of the microsatellite instability detection algorithm bMSISEA requires only binary sequence alignment (BAM) files of cancer plasma samples. For baseline construction, BAM files of sufficient samples of matched MSI-H cancer tissues and normal tissues (number >50), sufficient white blood cell samples (number >100), and sufficient MSS plasma samples (number >100) are additionally required.

[0053] In this method, we first used MSIsensor (v0.5) software to obtain all microsatellite loci with a length of more than 10 and one repeat sequence in the sequencing coverage region, and then calculated the number of reads covered by the repeat sequences of each length type at the microsatellite loci.

[0054] The method for counting the number of reads covered by each length type of locus by MSIsensor is as follows. For each microsatellite locus, first, its position information and both end sequences are searched in the human genome, and then all sequences with intermediate repeat sequences of 1 to L-10 bp length connected by both end sequences are constructed as a search dictionary, where L is the length of the read. For example, in the case of a single base microsatellite locus on chromosome 1 (14T, T is the repeat base, 14 is the number of repeats), the sequences at both ends are ATTCC and GCTTT, respectively, and the constructed search dictionary includes ATTCCTGCTTT (repeat length is 1), ATTCCTTGCTTT (repeat length is 2), ATTCCTTTGCTTT (repeat length is 3), etc. Next, paired reads with at least one end located within 2 kb of the locus were extracted from the sample BAM file and aligned to the sequences in the search dictionary for the locus. The number of reads covering different lengths in the search dictionary was counted and a histogram of the number of reads covering all length types of loci was created.

[0055] 3. Screening for marker loci for microsatellite instability 3.1 Repeat length characteristics of loci in the MSS state For the microsatellite loci of normal samples, the reads have a high probability of being covered by one or two types of repeat sequence length corresponding to the genotype of the sample. In this step, based on the white blood cell samples, the repeat sequence length types that are highly likely to appear in the reads of each locus in the normal state were described as the repeat sequence length characteristic of the locus in the MSS state. For each white blood cell sample of each locus, a minimum continuous length range was searched for such that the number of corresponding reads exceeds 75% of the total number of reads supported by the locus, and this continuous length range was called the peak region at the locus of the sample. For each locus, the repeat sequence length range selected as the peak region in at least 25% of the white blood cell samples was taken as the repeat sequence length characteristic of the locus in the MSS state.

[0056] 3.2 Repeat length characteristics of MSI-H status loci and selection of marker loci For samples with high microsatellite instability, the microsatellite loci cause the expansion or contraction of many repeat sequences due to erroneous DNA duplication. Here, we focus on the phenomenon of sequence contraction of long repeat sequences. In this step, based on the matched MSI-H cancer tissue and side cancerous normal tissue samples, the type of repeat sequence length that occurs in large quantities in reads in the MSI-H state, which is different from the normal state, is described as the length characteristic of the repeat sequence of the locus in the MSI-H state. Since the cancer tissue sample is a mixture of cancer cells and normal cells, the first step of this method is to estimate the proportion of tumor cells in the sample. Specifically, in the cancer tissue and side cancerous normal tissue, the number of reads of the repeat sequence length type of the locus corresponding to the MSS state of each locus was counted, and a linear model was established to estimate the proportion of tumor cells u, assuming that the MSS state reads in the cancer tissue sample are completely derived from normal cells. In the next step, after normalizing the total number of reads in the cancer tissues and matched normal tissues, the statistics of the repeat length in the complete MSI-H cancer cells were estimated by correspondingly subtracting the number of reads of each repeat length at each locus in the cancer tissues by u times the corresponding data in the matched normal tissues.

[0057] For all microsatellite loci, based on the statistical data of the length of the repeat sequence of complete MSI-H cancer cells, loci with the following characteristics were selected as marker loci for bMSISEA, and the length range of the repeat sequence was taken as the length characteristic of the repeat sequence at the locus in MSI-H state. The characteristic is that the total number of reads supported by the length range of the repeat sequence is less than 0.2% of the total number of reads at the locus in MSS samples, and accounts for more than 50% of the total number of reads at the locus in MSI-H samples. Due to the above two conditions, even when the content of ctDNA is extremely low, the reads covering the length characteristic of MSI-H are almost entirely derived from cancer DNA.

[0058] Table 1 shows eight microsatellite detection marker loci for microsatellite status detection screened according to the above method. Figure 1(A) shows the marker locus bMS-BR1. Here, the characteristic length range of the repeat sequence of the locus in the MSS state is 22-25 bp, and the characteristic length range of MSI-H is 1-16 bp. Also, Figure 1(B) shows the coverage feature map of the non-marker locus in two types of samples. Compared with the MSS sample, the length of the repeat sequence of the locus in the MSI-H state is shortened by about 2 bp, but this variation cannot be distinguished from the variation of the capture of the leukocyte itself under the condition of very low ctDNA content, and does not meet the screening conditions of the marker locus, so it cannot be used to determine the microsatellite status of the sample.

[0059] 4. MSI signature enrichment analysis For each marker locus, the plasma samples were subjected to MSI-H feature enrichment analysis against the background of the number of reads corresponding to the set of length features in the MSS and MSI-H states in normal leukocyte samples. In this step, the total number of reads corresponding to the length set of repeat sequences in the MSS and MSI-H states was calculated based on a large number of normal leukocyte samples, denoted as K and NK, respectively. Similarly, the number of reads k and nk corresponding to the length set of repeat sequences in the MSS and MSI-H states were calculated for the plasma samples. If the sample state is MSS, the read features are consistent with the state of the leukocyte sample and fit a hypergeometric distribution.

number

number

[0060] In addition, we calculated the range of enrichment index variation for each locus based on a large number of MSS plasma samples. For each plasma sample, we calculated the enrichment index Zscore for each locus based on this range of variation, and then summed all Zscores to obtain the index MSscore that determines the microsatellite status of the sample.

number

[0061] Taking the bMS-BR1 locus as an example, based on 100 WBC samples, the total number K of reads with a length range of 1-16 bp for the repetitive sequence is 504, and the total number N of reads with a length range of 1-16 bp or 22-25 bp is 190588. In addition, for the measurement sample, the total number k of reads of the repetitive sequence at the locus in the length range of 1-16 bp is 65, and the total number n of reads in the length range of 1-16 bp or 22-25 bp is 1308. This allows H S =-log(P S (X>k S )=-log(P S (X>65)=140.6. Furthermore, based on the MSS plasma samples, H S The fluctuation level of the stimuli was evaluated, and the results are shown in Table 1. The Zscore value of the locus is 108.6 according to TIFF2024174926000011.tif17160. The calculation method of other loci is as above. Finally, by summing all Zscores, the final MSscore of the locus is 355.3. In this sample, the frameshift mutation p.D214fs of the suspected pathogenic system of MLH1, pathogenic / suspected pathogenic mutations including PIK3CA, KRAS, PTEN, mutations with unknown pathogenic information including BRCA2, STK11, PMS1, and benign mutations of other genes included in the kit were simultaneously detected.

[0062] 5. Determining microsatellite status in cancer samples For plasma samples, the mean and standard deviation (SD) are calculated based on the MSscore value of the MSS plasma sample, and the mean + 3SD is set as the cutoff threshold. If MSscore > cutoff, the sample is determined to be MSI-H, and if MSscore ≦ cutoff, the sample is determined to be MSS.

[0063] 6. Detection of bMSISEA microsatellite instability in plasma Using the bMSISEA microsatellite detection technology, NGS detection, including mutation and microsatellite detection, was performed on 127 actual clinical intestinal cancer plasma samples based on the eight microsatellite marker loci and detection kits shown in Table 1. The microsatellite status of the samples was double-confirmed by IHC and NGS-MSI technology based on the matched tissue samples of the corresponding patients, and finally consisted of 44 MSI-H samples and 83 MSS samples. Here, the tissue detection method is as follows: Based on the difference in the length of the repeat sequence, the microsatellite status of the samples was determined by 22 marker loci with the NGS detection method. In this method, for each marker locus, the length range of the repeat sequence of the reads that collectively appeared in the MSS state was evaluated, and the change rate of the reads within this range to the total number of reads at the locus was evaluated. The mean-3sd was used as a threshold, and if the above ratio at the locus in the measurement sample is smaller than the threshold, the locus was determined to be an unstable locus. If the total number of unstable loci is less than 15% of the total number of loci, the sample is determined as MSS, if it is more than 40%, the sample is determined as MSI-H, and if it is intermediate between the two, it is determined as MSI-L. This detection method can be referred to Chinese Patent Application No. 201710061152.6. In addition, IHC evaluation was performed through histopathological sections. The expression status of MMR proteins, including MLH1, PMS2, MSH2, and MSH6 proteins, was detected by IHC using immunohistochemistry. If one of the proteins is deleted, it is determined as dMMR, and if no protein is deleted, it is determined as pMMR. Patients with dMMR are usually MSI-H due to abnormalities in the mismatch repair mechanism.

[0064] The sensitivity and specificity of the bMSISEA assay were obtained by comparing the detection results of the bMSISEA assay in the plasma samples of the 127 patients and those of the matched tissues, as shown in Table 2.

[0065] Table 2. Plasma-based bMSISEA detection results for 127 cases of intestinal cancer (based on tissue detection results). [Table 2]

[0066] In the case of ctDNA (maxAF>0.2%), the accuracy of plasma MSI detection reached 98.5%. [Table 3]

[0067] *The results of tissue detection of microsatellite status were double-confirmed by NGS and IHC methods. The detection indices are sensitivity, specificity, PPV, positive predictive value, NPV, negative predictive value, and accuracy. Their calculation methods are as follows:

number

[0068] Here, TP, TN, FP, and FN represent the number of samples that were true positive (both tissue and plasma detection results were MSI-H), true negative (both tissue and plasma detection results were MSS), false positive (tissue detection result was MSS and plasma detection result was MSI-H), and false negative (tissue detection result was MSI-H and plasma detection result was MSS), respectively.

[0069] From Table 2, we can see that the specificity of MSI-H detection by plasma samples is 100%. When all samples are included without screening, the overall detection sensitivity is only 52.3% and the accuracy is 83.5% because the ctDNA content in most samples is extremely low. In contrast, when only plasma samples that meet maxAF>0.2% (ctDNA>0.4%) are screened, the detection sensitivity is 93.8% and the accuracy is 98.5%. In fact, when only samples with maxAF>0.5% are screened among this sample group, the detection accuracy is 100%. Thus, it can be seen that bMSISEA has a sufficiently high detection sensitivity when plasma contains a sufficient amount of ctDNA, assuming that the specificity of detection is ensured.

[0070] Further, more detailed detection results are shown in Figure 2. Figure 2(A) shows the MSscore distribution by MSI detection of 127 intestinal cancer plasma samples. According to the bMSISEA method, the MSscore of 83 MSS samples is less than 15, and the specificity is 100%. The MSscore of 23 / 44 MSI-H samples is greater than 15, and the sensitivity is 52.3%. Considering the difference in ctDNA content between samples, Figure 2(B) shows the correlation between maxAF and the MSscore of MSI-H samples. Considering only samples with maxAF>0.2%, the MSscore of 15 / 16 MSI-H samples is greater than 15, and the accuracy is 93.8%.

[0071] 7. Confirmation of the effect of ctDNA content in plasma on detection sensitivity in a simulation experiment Generally, the content of ctDNA in plasma is extremely low, so the detection sensitivity is affected by the content of ctDNA. Therefore, in this experiment, based on actual clinical plasma and white blood cell samples, a group of 350 simulated samples with different ctDNA content gradients was constructed to evaluate the sensitivity of the present method to detect microsatellite instability by plasma samples under conditions of different ctDNA content. Here, the ctDNA content of a cancer sample can be evaluated by the maximum somatic gene mutation frequency (maxAF) of the sample.

[0072] We selected 18 pairs of matched plasma and leukocyte samples, mixed the bam files of plasma and leukocyte samples in proportions according to the maxAF of the plasma samples, and resampled them into the original plasma samples to simulate 350 samples with different ctDNA content gradients and evaluate the sensitivity level of plasma samples with different contents of ctDNA. In the simulated samples, the same mutation detection process as in the real clinical samples was adopted to detect mutations and determine the maxAF level. As shown in Figure 2(C), the horizontal axis is the counting of only samples with maxAF greater than the threshold, and the vertical axis is the detection sensitivity of MSI-H. When maxAF>0.2%, the detection sensitivity of MSI-H is higher than 93%, and when maxAF>0.5%, the sensitivity is higher than 98%. When the ctDNA content is too low, there is a limit to the detection of MSI-H. However, when the ctDNA content reaches a stable detection range (maxAF>0.2%), the bMSISEA method can determine the microsatellite stability (MS) status of the sample with high accuracy and sensitivity, providing the possibility of non-invasively detecting the MS status in plasma.

[0073] Therefore, for plasma samples with maxAF>0.2% (approximately corresponding to a ctDNA content of more than 0.4%), the bMSISEA method can provide sensitivity comparable to tissue detection and extremely high specificity. Compared with tissue MSI detection, the plasma MSI detection of the present invention has the unique advantages of liquid biopsy, such as non-invasive diagnosis, non-tissue specificity, and detection of multiple lesions. The bMSISEA method does not rely on matched white blood cell samples to detect mutations while determining the microsatellite status of the sample, and therefore can be processed quickly and at a low cost.

Claims

1. A biomarker panel comprising one or more of the eight microsatellite loci shown in Table 1.

2. 1. A biomarker panel comprising a combination of microsatellite loci and one or more genes, comprising: Here, the microsatellite loci include the eight microsatellite loci described in claim 1, or any one or more combinations thereof, and the one or more genes include the following 41 genes: AKT1, APC, ATM, BLM, BMPR1A, BRAF, BRCA1, BRCA2, CDH1, CHEK2, CYP2D6, DPYD, EGFR, EPCAM, Any one or more of ERBB2, GALNT12, GREM1, HRAS, KIT, KRAS, MET, MLH1, MSH2, MSH6, MUTYH, NRAS, PDGFRA, PIK3CA, PMS1, PMS2, POLD1, POLE, PTCH1, PTEN, SDHB, SDHC, SDHD, SMAD4, STK11, TP53, and UGT1A1.

3. A kit for detecting microsatellite stability in a plasma sample, comprising: A detection reagent for use in the biomarker panel of claim 1 or 2, kit.

4. A kit for use in the non-invasive diagnosis, prognosis assessment, treatment selection or genetic screening of cancer, preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer, comprising: A detection reagent for use in the biomarker panel of claim 1 or 2, kit.

5. The plasma sample is a cancer plasma sample, preferably a colorectal cancer plasma sample, such as a bowel cancer plasma sample, a gastric cancer plasma sample, an endometrial cancer plasma sample; The kit according to claim 3 or 4.

6. The microsatellite stability includes types of high frequency microsatellite instability (microsatellite instability-high, MSI-H), low frequency microsatellite instability (microsatellite instability-low, MSI-L), and microsatellite stable (microsatellite stable, MSS); The kit of claim 3.

7. The detection reagent is a reagent for performing next-generation high-throughput sequencing (NGS); The kit according to any one of claims 3 to 6.

8. 3. Use of the biomarker panel of claim 1 or 2 in detecting microsatellite stability in a plasma sample.

9. The plasma sample is a cancer plasma sample, preferably a colorectal cancer plasma sample, such as a bowel cancer plasma sample, a gastric cancer plasma sample, an endometrial cancer plasma sample; 9. The use according to claim 8.

10. The microsatellite stability includes types of high frequency microsatellite instability (microsatellite instability-high, MSI-H), low frequency microsatellite instability (microsatellite instability-low, MSI-L), and microsatellite stable (microsatellite stable, MSS); 10. The use according to claim 9.

11. 3. Use of a biomarker panel according to claim 1 or 2 in the non-invasive diagnosis, prognosis assessment, treatment selection or genetic screening of cancer, preferably colorectal (e.g. intestinal), gastric or endometrial cancer.

12. 1. A method for determining microsatellite marker loci that can be used to detect microsatellite instability in a plasma sample, comprising: 1) detecting microsatellite loci of a sequencing region in a sample; 2) for any one of the microsatellite loci i, counting the number of reads of each length type of different repeat sequences counted by the NGS data; and 3) determining, for any one of the microsatellite loci, a length characteristic of the repeat sequence of the locus in a microsatellite stable type (MSS) and a length characteristic of the repeat sequence of the locus in a high microsatellite instability type (MSI-H); wherein the MSS length characteristic is a minimum contiguous length range such that the number of corresponding reads in the MSS sample is greater than 75% of the total number of reads supported at the locus; and the MSI-H length characteristic is a contiguous length range that is highly differentiated in the MSS sample and the MSI-H sample, wherein a) the total number of reads supported in this range is less than 0.2% of the total number of reads at the locus in the MSS sample, and b) the total number of reads at the locus accounts for 50% or more of the total number of reads at the locus in the MSI-H sample, and the microsatellite locus having the above characteristics is a detection marker for the microsatellite locus; method.

13. The samples include normal white blood cells and samples derived from tissues of cancer patients, wherein the cancer is preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer. The method of claim 12.

14. The microsatellite loci determined according to the method of claim 12 include one or more of the eight microsatellite loci shown in Table 1. The method of claim 12.

15. The detection of said microsatellite instability is used for non-invasive diagnosis, prognosis assessment, treatment selection or genetic screening of cancer, preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer. The method according to any one of claims 12 to 14.

16. 1. A method for determining the stability status of microsatellite loci in plasma samples from cancer patients based on next generation high throughput sequencing, comprising: 1) measuring the length characteristics of the repeat sequences of a plurality of microsatellite loci in a plasma sample and an MSS plasma sample as a reference sample based on a next-generation sequencing method, wherein the plurality of microsatellite loci includes one or more microsatellite loci selected from the eight microsatellite loci shown in Table 1; 2) calculating the corresponding enrichment index Zscore for any one of the microsatellite loci described in 1); 3) summing the enrichment indices Zscore of all microsatellite loci to calculate an index MSscore that determines the microsatellite status of the sample; 4) calculating the mean value (mean) and standard deviation (SD) of the MSscore of the MSS plasma sample as the reference sample, and setting the mean+3SD as a threshold cutoff; 5) for a plasma sample derived from a cancer patient, if its MScore>cutoff, the sample is judged as MSI-H, and if MSscore≦cutoff, the sample is judged as MSS; method.

17. The Zscore is H Ｓ Evaluated by [0010] [0025] where N is the total number of reads of the set of repeat sequence lengths in the MSI-H and MSS states, K is the total number of reads of the set of repeat sequence lengths in the MSI-H state, and N-K is the total number of reads of the set of repeat sequence lengths in the MSS state, and correspondingly, n and k are the numbers of corresponding reads in the measurement sample, respectively.

17. The method of claim 16.

18. The MScore is calculated based on the following formula: [0030] 17. The method of claim 16.

19. The cancer is colorectal cancer (e.g., intestinal cancer), gastric cancer or endometrial cancer, 17. The method of claim 16.

20. 1. A method for detecting microsatellite instability and disease-associated genetic mutations in a patient based on next-generation high-throughput sequencing methods to provide clinical guidance regarding risk management, treatment and / or prognosis of said patient or family, comprising: (1) simultaneously detecting multiple microsatellite loci according to claim 16; (2) determining the stability status of the microsatellite loci in said sample according to the method of any one of claims 5 to 8; (3) obtaining detection results of one or more of the disease-related genes according to the sequencing results; (4) providing clinical guidance regarding risk management, treatment and / or prognosis of the patient or family by combining the results of the above steps (2) and (3); method.

21. The disease is cancer, preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer, 21. The method of claim 20.

22. Reagents for detecting the plurality of microsatellite loci, A kit for use in the method according to any one of claims 12 to 20.

23. 1. A device for determining microsatellite marker loci for use in detecting microsatellite instability in a plasma sample, comprising: a sequencing data reading module for reading the sequencing data of the sample acquired and stored by the sequencing device; a microsatellite marker locus detection module for analyzing and detecting all microsatellite loci in the sequencing region in the sample from the sequencing data of the sample; A repeat sequence length type determination module for counting the number of reads of each length type of different repeat sequences according to the sample sequence data read by the sequencing data reading module for any one of the microsatellite loci i; and a determination module for determining whether any one of the microsatellite loci i is a microsatellite marker locus, the determination module including a first analysis module, a second analysis module, and a third analysis module, The first analysis module is used to determine a length characteristic of a repeat sequence at a locus at microsatellite stability (MSS) and determine whether the number of corresponding reads in the MSS sample is greater than 75% of the total number of reads supported at the locus, where the length characteristic of the MSS is a minimum range of contiguous lengths, where a positive result is recorded as "+" and a negative result is recorded as "-", The second analysis module is used to determine a length characteristic of a locus repeat sequence at high microsatellite instability (MSI-H) and to determine a) and b) below, wherein the MSI-H length characteristic is a contiguous length range that is highly distinct in MSS samples and MSI-H samples, a) determining whether the total number of reads supported within the contiguous length range is less than 0.2% of the total number of reads at the locus in the MSS samples, recording a positive result as "+" and a negative result as "-", b) determining whether the reads account for 50% or more of the total number of reads for the locus in the MSI-H sample, recording a "+" if a positive result is obtained and a "-" if a negative result is obtained; The third analysis module is used to analyze the results of the first analysis module and the second analysis module, and if three positive results, i.e., three "+", are obtained, the microsatellite locus i is determined as a microsatellite marker locus; Device.

24. The samples include samples from normal white blood cells and tissues of cancer patients, and the cancer is preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer.

24. The apparatus of claim 23.

25. The microsatellite loci determined according to the device of claim 23 include one or more of the eight microsatellite loci shown in Table 1.

24. The apparatus of claim 23.

26. The detection of said microsatellite instability is used for non-invasive diagnosis, prognosis assessment, treatment selection or genetic screening of cancer, preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer.

24. The apparatus of claim 23.

27. 1. An apparatus for determining microsatellite instability in plasma samples from cancer patients based on next-generation high-throughput sequencing, comprising: a sequencing data reading module for reading the sequencing data of the sample acquired and stored by the sequencing device; a repeat sequence length signature determination module for analyzing the length signature of repeat sequences of a plurality of microsatellite loci in the plasma sample and the MSS plasma sample as a reference sample from the sequencing data of the samples; wherein the plurality of microsatellite loci comprises one or more microsatellite loci selected from the eight microsatellite loci set forth in Table 1; an enrichment index calculation module for calculating an enrichment index Zscore of a microsatellite locus; a microsatellite status index calculation module for calculating an index MSscore that can judge the stability status of the microsatellite of the sample by summing the enrichment indexes Zscore of all microsatellite loci; A threshold calculation module that calculates the mean value (mean) and standard deviation (SD) of the MSscore of the MSS plasma sample as a reference sample and sets the mean+3SD as a threshold cutoff; and A microsatellite locus stability status determination module for comparing the index MSscore with a threshold cutoff, such that for a plasma sample derived from a cancer patient, if MSscore>cutoff, the sample is determined to be MSI-H, and if MSscore≦cutoff, the sample is determined to be MSS; Device.

28. The Zscore is H Ｓ Evaluated by [0045] [0050] where N is the total number of reads of the set of repeat sequence lengths in the MSI-H and MSS states, K is the total number of reads of the set of repeat sequence lengths in the MSI-H state, and N-K is the total number of reads of the set of repeat sequence lengths in the MSS state, and correspondingly, n and k are the numbers of corresponding reads in the measurement sample, respectively.

28. The apparatus of claim 27.

29. The MScore is calculated based on the following formula: [006] 28. The apparatus of claim 27.

30. the disease is cancer, preferably colorectal cancer (e.g. intestinal cancer), gastric cancer or endometrial cancer, 28. The apparatus of claim 27.

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