WO2018137678A1 - 一种基于二代测序的同时检测微卫星位点稳定性和基因组变化的方法 - Google Patents

一种基于二代测序的同时检测微卫星位点稳定性和基因组变化的方法 Download PDF

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WO2018137678A1
WO2018137678A1 PCT/CN2018/074092 CN2018074092W WO2018137678A1 WO 2018137678 A1 WO2018137678 A1 WO 2018137678A1 CN 2018074092 W CN2018074092 W CN 2018074092W WO 2018137678 A1 WO2018137678 A1 WO 2018137678A1
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microsatellite
colorectal cancer
loci
sample
microsatellite loci
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PCT/CN2018/074092
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French (fr)
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张之宏
汉雨生
揣少坤
刘成林
张周
邓望龙
李冰思
罗芳
刘静
张韩晗
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广州燃石医学检验所有限公司
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Priority to JP2019541262A priority Critical patent/JP7022758B2/ja
Priority to US16/480,628 priority patent/US20200032332A1/en
Priority to EP18744200.9A priority patent/EP3597769A4/en
Publication of WO2018137678A1 publication Critical patent/WO2018137678A1/zh

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Definitions

  • the present invention relates to a method for simultaneous detection of microsatellite stability and disease-related genes based on second-generation sequencing.
  • the invention also relates to the use of the detection method in the auxiliary diagnosis, prognosis evaluation, or selection treatment of colorectal cancer patients, and the application of the corresponding kit and detection reagent in the preparation kit.
  • CRC colorectal cancer
  • CRC CIN
  • FAP Familial adenomatous polyposis
  • APC APC germline mutation
  • sporadic CRC APC, P53, DCC, KRAS and other gene mutations
  • MSI Hereditary Nonpolyposis Colorectal Cancer
  • HNPCC Hereditary Nonpolyposis Colorectal Cancer
  • + CRC sporadic MSI
  • a microsatellite is a short sequence or single nucleotide region of a repeating DNA contained in a gene.
  • microsatellite mutation microsatellite repeat mismatch
  • MSI microsatellite instability
  • MSI-H high microsatellite instability
  • MSI-L low microsatellite instability
  • MSS microsatellite stability
  • MSI is involved in the development of malignant tumors and is closely related to colorectal cancer, gastric cancer and endometrial cancer.
  • About 15% of patients with colorectal cancer have MSI, and more than 90% of patients with hereditary nonpolyposis co-leukemia (HNPCC) have MSI, indicating that MSI can be used as an important factor in detecting patients with HNPCC.
  • Predictors therefore, MSI testing is significant for patients with colorectal cancer.
  • the MMR gene test carried out in domestic hospitals is a protein test based on immunohistochemical detection, usually containing only MLH1 and MSH2, and partially containing both MSH6 and PMS2, and the positive results are in agreement with the MSI test results;
  • the hospital carried out MSI state detection by PCR combined with capillary electrophoresis, and most of them were sent-out detection.
  • This method usually selects 5-11 single nucleotide repeat sites with a length of about 25 bp. After PCR amplification, the length distribution interval is measured by capillary electrophoresis to determine the microsatellite (not) steady state of the sample.
  • This method is the current gold standard detection method, but requires additional test samples to be performed, and the patient's normal tissue is required as a control for state determination, and thus is not convenient from an operational point of view.
  • the technical problem to be solved by the present invention is to overcome the deficiencies of the prior art, and provide an MSI detection method based on a second generation sequencing platform, and based on the detection method, a highly sensitive and specific method for detecting colorectal cancer is obtained.
  • Related MSI sites The method is named "Present MSI (Microsatellite Instability Detection based on Peak Ratio Estimation using Tumor Tissue only)", and its corresponding Chinese name is "method based on detecting microsatellite instability by utilizing only the target tissue height ratio of the tumor tissue in the second generation sequencing".
  • the present invention establishes a method for determining candidate microsatellite loci in a genetic assay that can be used for colorectal cancer prognosis assessment and/or treatment protocol selection.
  • the invention also realizes simultaneous detection of multiple microsatellite loci and multiple disease-related genes in the sample, and can provide more comprehensive conclusions and suggestions on prognosis, treatment, and investigation for the detected samples.
  • the inventors of the present invention found that for a microsatellite locus of a normal sample, the sequencing fragment reads a large probability of covering one or two types of repeat lengths corresponding to the sample genotype; In the sample, the microsatellite locus caused a large number of repetitive sequences to expand or contract due to the incorrect replication of DNA, so that the probability that the sequencing fragment reads to cover the corresponding genotype of the normal sample is significantly reduced.
  • the genotype corresponding to the normal sample is referred to as the target genotype. Due to the inevitable error rate of sequence scrawling and sequencing, the probability that the sequencing fragments of different samples cover the target genotype is different.
  • the present inventors have found that the coverage probability of the target genotype in the normal sample is sufficiently stable in the marker microsatellite locus, and the coverage probability of the target genotype in the microsatellite instability sample is much smaller than the normal value. Based on this finding, the inventors screened 22 loci (see Table 1 for details), and further constructed a large number of coverage ratio vectors R and target genotype coverage NT of 22 loci in a large number of normal tissue samples. The base length distribution reference set for satellite state detection.
  • Table 1 Microsatellite detection marker information related to colorectal cancer diagnosis
  • the five marker sites are BAT-26, NR-24, BAT-25, NR-22, NR-21.
  • the mean and sd listed in the table are the mean and variance of the normal range obtained by the length distribution reference set of each point. If the target genotype coverage is less than mean-3sd, the position is determined as the MSI site, where the sd The multiple of 3 is consistent for 22 sites.
  • the present invention has developed a novel method for the stability detection of microsatellites suitable for second generation sequencing (prettyMSI). Compared with the gold standard for MSI detection based on PCR electrophoresis, the detection method is faster and cheaper based on the correct rate of matching. At the same time, according to the method of the invention, a stable normal sample microsatellite length distribution reference set is constructed, and the detection can be completed without the patient providing a matching normal sample, which is of great significance in practical applications.
  • the method of the present invention relies on a high-throughput second-generation sequencing technology, and can perform multi-sample sequence analysis at one time, and complete detection of microsatellite states while detecting genomic changes such as gene mutations and chromosomal variations, without additional
  • the experimental operation greatly saves the analysis time and the cost of patient testing.
  • the multi-gene panel of the present invention further detects genes associated with colorectal cancer treatment and prognosis in the NCCN treatment guidelines, genetic susceptibility genes for colorectal cancer, and other gastrointestinal tracts identified in the NCCN genetic screening guidelines.
  • Total exon detection of tumor-associated genes including the following 36 genes: BRAF, HRAS, KRAS, NRAS, PTCH1, APCBLM, BMPR1A, CHEK2, EpCAM, GREM1, MLH1, MSH2, MSH6, MUTYH, PMS2, POLD1, POLE, PTEN, SMAD4, STK11, TP53, AKT1, ATM, BRCA1, BRCA2, CDH1, EGFR, ERBB2, KIT, MET, PDGFRA, PIK3CA, SDHB, SDHC, SDHD.
  • the invention relates to a combination of biomarkers comprising 22 microsatellite loci as shown in Table 1 or any of 15, 16, 17, 18, 19, 20, or 21 loci therein The combination.
  • the combination of biomarkers is the 22 microsatellite loci shown in Table 1.
  • the invention relates to a combination of additional biomarkers comprising a combination of a microsatellite locus and one or more genes, wherein the microsatellite loci comprise 22 microarrays as shown in Table 1.
  • the microsatellite loci are 22 microsatellite loci shown in Table 1,
  • the invention in another aspect of the invention, relates to a kit for prognostic evaluation and/or treatment regimen selection for stage II colorectal cancer, diagnosis of Lynch syndrome (HNPCC), prognosis assessment and/or treatment regimen selection
  • a genetic assay comprising a combination of detection reagents for the aforementioned microsatellite loci.
  • the invention in another aspect of the invention, relates to a kit for simultaneously performing genes including colorectal cancer prognosis and/or treatment regimen selection, colorectal cancer genetic susceptibility, and gastrointestinal tumor susceptibility
  • the assay comprises a detection reagent for the combination of the above microsatellite locus and one or more genes.
  • the kit wherein the genetic assessment comprises genetic assessment of familial adenomatous polyposis, sporadic CRC, Lynch syndrome, and/or sporadic MSI+CRC.
  • the detection reagent in the above kit is a reagent for performing second generation high-throughput sequencing (NGS).
  • the invention in another aspect of the invention, relates to an agent for detecting a combination of the above biomarkers for use in the preparation of a colorectal cancer prognostic evaluation and/or treatment protocol selection, colorectal cancer genetic susceptibility, and gastrointestinal tumors
  • the detection reagent is a reagent for performing second generation high throughput sequencing.
  • the genetic test selected for the colorectal cancer prognosis assessment and/or treatment regimen is evaluated as a genetic assessment of Lynch syndrome (HNPCC) prognostic assessment and/or treatment protocol selection.
  • HNPCC Lynch syndrome
  • the invention relates to a method for determining candidate microsatellite loci in a genetic assay capable of being used for colorectal cancer prognosis assessment and/or treatment regimen selection based on second generation high throughput sequencing, comprising the following step:
  • the NGS data statistical sequencing fragment reads the number of sequencing fragments covering different lengths of the target genotype corresponding to the locus, and the target genotype is normal.
  • the average coverage ratio of the length type is mean(NT i ) and the standard deviation sd(NT i ), wherein if the number of read fragments covering the second largest number is less than 75% of the maximum covered type, only coverage is considered.
  • the maximum length type and calculate its average coverage and standard deviation; if the second-largest number of sequencing fragments reads more than 75% of the most covered length type, consider the two most covered length types. , the average coverage at this time is the sum of the average coverage rates of the two length types;
  • the coverage of the target genotype determined is also calculated according to the above steps. If the coverage rate is ⁇ mean(NT i )-3sd(NT i ), the microsatellite locus is unstable. A microsatellite locus is identified as a candidate microsatellite locus in a genetic assay that can be used for colorectal cancer prognosis assessment and/or treatment protocol selection.
  • the microsatellite locus identified by the above method comprises 22 microsatellite loci as described in Table 1 or a combination of any of 15, 16, 17, 18, 19, 20, 21 loci.
  • the genetic test selected for the colorectal cancer prognosis assessment and/or treatment regimen is evaluated as a genetic assessment of Lynch syndrome (HNPCC) prognostic assessment and/or treatment protocol selection.
  • HNPCC Lynch syndrome
  • the invention relates to a method for determining a steady state of a microsatellite locus in a colorectal cancer sample based on second generation high throughput sequencing, comprising the steps of:
  • Multi-gene paneling based on second-generation sequencing that is, detection of microsatellite loci combination
  • step (2) For each microsatellite locus of the sample, the number of reads of the sequencing fragments of different lengths is counted by step (2), and the coverage of the target genotype is calculated according to step (3);
  • the detection method described above preferably wherein the detected microsatellite loci comprise the 22 microsatellite loci listed in Table 1.
  • the detection method described above, wherein the determination in the step (5) is: if the number of unstable microsatellite sites is >40%, the sample is determined to be a height MSI; if the number is 15%-40 %, the sample is determined to be a low MSI sample; if the number is less than ⁇ 15%, the sample is determined to be an MSS sample.
  • the above method comprises the steps of: (1) simultaneously performing a multi-gene targeted capture panel detection of a plurality of microsatellite loci in the sample based on second generation sequencing, the plurality of microsatellite loci comprising 22 microsatellite loci shown in Table 1 or a combination of any of 15, 16, 17, 18, 19, 20, 21 loci;
  • the number of microsatellite loci whose number of reads of the target genotype corresponding to the microsatellite locus corresponding to the microsatellite locus exceeds 10 is n, and the target genotype is normal.
  • any microsatellite locus in n it can be determined by the above method whether it satisfies the coverage ratio T ij ⁇ mean(NT i )-3sd(NT i )
  • the calculation can be directly performed according to the mean(NT i ) and sd(NT i ) of Table 1;
  • the sample is determined to be a high MSI sample; if the number is 15%-40 %*n, the sample is determined to be a low MSI sample; if the number of samples is ⁇ 15%*n, the sample is determined to be an MSS.
  • the plurality of microsatellite loci in the above method are 22 microsatellite loci listed in Table 1.
  • the number of sites with sufficient coverage for each sample is between 15 and 22. The most common of these is the lack of coverage of the five PCR sites, except that there are three more sites that are more randomly covered between the samples.
  • the sequencing fragment covering the target genotype corresponding to the microsatellite locus can be included in the site statistics by reading microsatellite sites with more than 10 reads.
  • the present invention relates to a method for simultaneously performing microsatellite stability and disease-related gene detection for a colorectal cancer sample, which comprises, in the above method, based on a second generation sequencing method, except for performing a microsatellite locus
  • any one or more of the following 36 genes are detected: BRAF, HRAS, KRAS, NRAS, PTCH1, APCBLM, BMPR1A, CHEK2, EpCAM, GREM1, MLH1, MSH2, MSH6, MUTYH, PMS2, POLD1, POLE, PTEN, SMAD4, STK11, TP53, AKT1, ATM, BRCA1, BRCA2, CDH1, EGFR, ERBB2, KIT, MET, PDGFRA, PIK3CA, SDHB, SDHC, SDHD, and then combined with the steady state results of microsatellite loci
  • the result of the detection of one or more genes determines the state of the sample.
  • the invention relates to a kit for use in the method of any of the above, comprising an agent for detecting a microsatellite locus and/or an agent for detecting one or more genes.
  • the kit comprises reagents for performing second generation high throughput sequencing.
  • the colorectal cancer is Hereditary Nonpolyposis Colorectal Cancer (HNPCC, also known as Lynch syndrome).
  • Figure 1 is a graph showing the results of microsatellite locus detection by PCR detection and MSI-BR1 in Table 1 for different types of samples.
  • (a) A map of the cancerous tissue of MSI-H (corresponding to RS1607586 FFP in Table 7) and its matched paracancerous tissues in (a-1) PCR detection;
  • (a-2) The sequence of fragments corresponding to the different repeat length sequences of the microsatellite locus MS-BR1 reads a histogram of the number of covers.
  • FIG. 2 is a diagram showing an example of a microsatellite locus MSI-BR2 length distribution reference set and a determination criterion.
  • Figure 3 is a histogram of the detection results of 22 microsatellite loci in a cancer tissue sample (line 135) and a paracancerous tissue sample (second 460 rows) numbered RS1611018FFP.
  • Figure 4 is a histogram of the detection results of 22 microsatellite loci in a cancer tissue sample (line 135) and a paracancerous tissue sample (second 460 rows) numbered RS1608823FFP.
  • the experimental samples involved in the examples were all from the top three hospitals for the diagnosis and treatment of colorectal cancer in China, and all the experimental samples were clearly diagnosed as IHC positive tumors and adjacent normal tissue samples. Instruments, reagents, kits, and analysis software used in the experiments are commercially available.
  • Multi-gene panel detection based on second-generation sequencing method The specific steps are as follows:
  • Tumor tissue and adjacent normal tissue DNA were extracted using QIAamp DNA FFPE tissue kit. Accurate quantification was performed using dsDNA HS assay kits from the Qubit 3.0 fluorometer. The DNA was then physically fragmented into a 180-250 bp fragment using a sonicator Covaris M220 for end repair, phosphorylation, deoxy adenine at the 3' end, and ligation. The DNA ligated to the amplification adaptor was then purified using Agencourt AMPure XP paramagnetic beads and pre-amplified using PCR polymerase, and the amplified product was hybridized with Agilent's custom multiplexed biotin-labeled probe set.
  • the multi-gene panel design includes exons and partial intron region sequences of 36 genes.
  • the successfully hybridized fragments were specifically eluted, and after amplification and amplification by PCR polymerase, the quantitative and fragment length distribution were determined, and the second generation sequencing was performed using an Illumina sequencer. Tumor tissue and adjacent normal tissue DNA were extracted using QIAamp DNA FFPE tissue kit. Quantification was performed using a Qubit 2.0 fluorometer, dsDNA HS assay kits. After disruption of DNA with Covaris M220, end repair, phosphorylation and linker ligation were performed.
  • Fragments of 200-400 bp in length were selected using the AgencourtAMPure XP kit, and hybridized with Agilent multiple capture probes designed according to the exons and partial intron region sequences of the 36 genes included on the polygene panel.
  • the successfully hybridized fragments were subjected to magnetic bead purification and PCR amplification and subjected to mass and length measurement, and then subjected to second generation sequencing using an Illumina sequencer.
  • the sequence was compared to the human genome sequence (version hg19) using BWA version 0.7.10, and local alignment optimization, mutation response and annotation were performed using GATK 3.2, MuTect and VarScan, respectively.
  • the VarScanfp filter will remove sites with a depth of 100x or less; for indel and single-point variations, at least 5 and 8 variants of the sequencing fragments need to be read, respectively.
  • Microsatellite instability detection method the specific steps are as follows:
  • Step 1 The NGS data is used to count the number of fragments that are overlaid on different repeats of the site. For each microsatellite locus, first search its position information and the sequence of both ends in the human genome, and construct all sequences with intermediate repeat sequences of 1 to L-10bp connected by the two ends as a search dictionary, L is Sequencing the length of the fragment reads.
  • Step 2 Calculate coverage and build a standard reference set for microsatellite loci:
  • Type and calculate its average coverage and standard deviation; if the number of reads that cover the second largest number of segments is greater than 75% of the type of the most covered type, consider the two types of lengths that cover the most The average coverage is the sum of the average coverage of the two length types.
  • MSI-BR01 microsatellite is a single base microscopy on chromosome 1. Satellite locus (14T, T is a repeating base, 14 is the number of repetitions), the sequences at both ends are ATTCC and GCTTT, respectively.
  • the constructed search dictionary contains ATTCCTGCTTT (repetition length is 1), ATTCCTTGCTTT (repetition length is 2) ), ATTCCTTTGCTTT (repeat length is 3), and so on.
  • Paired sequencing reads at least one end within 2 kb of the site are extracted from the sequencing result file of the cancer sample and compared to sequences in the search dictionary of the site.
  • the statistics cover the number of reads of the sequence of fragments of different length sequences in the search dictionary, and the histograms of the number of fragments of the construction of all length types of the construction site are read.
  • the a-2 and b-2 portions are the squares of the MSI-BR1 high microsatellite instability (MSI-H) and MSI-BR1 microsatellite stability (MSS) sites in cancer and paracancerous samples, respectively.
  • MSI-H high microsatellite instability
  • MSS MSI-BR1 microsatellite stability
  • the histogram of the MSI-H locus is significantly different between cancer and paracancerous samples. It can be determined from the cancer sample map in a-2 and the two graphs in b-2 that MSI-BR1 is an optional microsatellite locus.
  • FIG. 2 it is an example of a microsatellite locus MSI-BR2 length distribution reference set and a determination criterion.
  • the dot to the left of the mean-3sd line on the abscissa shows an example of a MSI-H cancer tissue sample, while the right triangle shows an example of a MSS cancer tissue sample.
  • the target genotype coverage rate conforms to the normal distribution in the reference set, and its average coverage rate is 0.91, and the standard deviation 0.02 is obtained according to the above step 2.
  • Fig. 3 and Fig. 4 it is a histogram of the detection results of 22 microsatellite loci in two different numbers of cancer tissue samples (the first three rows and five rows) and the paracancerous tissue samples (the second and fourth rows).
  • the results were MSI-H and MSS, respectively.
  • the abscissa is the length type of the target genotype, and the ordinate is the number of reads of the sequencing fragment of the target genotype.
  • the upper and lower correspondence of the same locus is only for the convenience of observation.
  • the paracancerous tissue is not required as the control sample, and only the coverage of the cancer tissue sample is required to calculate whether the coverage ratio T ij is met. ⁇ mean(NT i )-3sd(NT i ), it can be judged whether the microsatellite locus is an unstable microsatellite locus.
  • Step 3 For each microsatellite marker site i of the cancer sample j, the number of reads of the sequencing fragments of different lengths is counted by step one, and the coverage of the target genotype (T ij ) is calculated according to step two.
  • the number of microsatellite loci whose number of sequencing fragments covering the target genotype corresponding to the microsatellite locus exceeds 10 is n, and the target genotype is a normal tissue sample.
  • the microsatellite loci are 22 microsatellite loci in Table 1, they can be directly calculated according to the mean(NT i ) and sd(NT i ) of Table 1.
  • Step 4 The coverage of the microsatellite loci listed in Table 1 is detected in turn, and compared with their corresponding standard reference sets, and the stability of the microsatellite locus is determined according to step 3.
  • a cancer sample check the status of the microsatellite loci listed in Table 1. If the number of unstable microsatellite sites is >40%*n, the sample is judged to be high MSI; if the number is 15% -40%*n, the sample is determined to be a low MSI sample; if the number of samples is ⁇ 15%*n, the sample is determined to be an MSS sample.
  • the sites that are determined to be microsatellite instability are the two most covered Length type (if the second largest number of sequencing reads is less than 75% of the highest peak, only the length type corresponding to the highest peak is considered), if the length is less than 2 bp from the length of the human genome reference sequence, then The length sequence is also used as a candidate genotype, and the standard coverage rate is calculated according to the reference set construction method of step two, and the coverage ratio of the normal sample target genotype ratio vector NT i and the cancer sample is recalculated, and if this is still consistent with T ij ⁇ Mean(NT i )-3sd(NT i ), the site is determined to be an unstable microsatellite locus, otherwise the locus is only determined to be a potentially unstable microsatellite locus.
  • the multi-gene panel used in the examples also includes genes that are clearly associated with colorectal cancer treatment and prognosis in the NCCN treatment guidelines, and genetic susceptibility genes for colorectal cancer identified in the NCCN genetic screening guidelines, and All exon detection of other gastrointestinal tumor-associated genes, as follows: BRAF, HRAS, KRAS, NRAS, PTCH1, APCBLM, BMPR1A, CHEK2, EpCAM, GREM1, MLH1, MSH2, MSH6, MUTYH, PMS2, POLD1, POLE , PTEN, SMAD4, STK11, TP53, AKT1, ATM, BRCA1, BRCA2, CDH1, EGFR, ERBB2, KIT, MET, PDGFRA, PIK3CA, SDHB, SDHC, SDHD.
  • the tumor tissue of this sample was of high microsatellite instability (MSI-H) type.
  • the tumor tissue of this sample is a microsatellite stable (MSS) type.
  • the tumor tissue of this sample was of high microsatellite instability (MSI-H) type.
  • the tumor tissue of this sample was a microsatellite stable (MSS) type.
  • the inventors analyzed the distribution of 22 microsatellite loci in 65 samples, each of which satisfies the above-mentioned "sequences of sequencing fragments corresponding to the target genotype corresponding to the microsatellite loci exceeding 10".

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Abstract

提供了一种基于二代测序的同时检测微卫星位点稳定性和基因组变化的方法（prettyMSI），尤其是该检测方法在辅助诊断结直肠癌患者中的应用，以及相应的试剂盒。所述微卫星位点选自表1中所示22个微卫星位点或其中任意15、16、17、18、19、20、21个位点的组合。

Description

一种基于二代测序的同时检测微卫星位点稳定性和基因组变化的方法 技术领域
本发明涉及一种基于二代测序，同时进行微卫星稳定性和疾病相关基因检测的方法。本发明还涉及该检测方法在结直肠癌患者的辅助诊断、预后评估，或选择治疗方案中的应用，以及相应的试剂盒和检测试剂在制备试剂盒中的应用。
背景技术
结直肠癌(Colorectal Cancer，CRC)发病率在我国高居各类癌症发病率的第3位，占癌症死因的第5位，其根治性切除后5年生存率为50％左右，术后复发和转移是其死亡的重要原因。早期结直肠癌患者通常可借手术切除，一旦转移，其治疗的方法并不多，患者五年生存率也不理想。研究发现，基因组的不稳定性与结直肠癌的发病机理密切相关，基因组的不稳定性包括染色体不稳定(chromosomal instability，CI)和微卫星不稳定(microsatellite instability，MSI)。其中约80-85％的CRC表现为CIN，包括家族性腺瘤性息肉病(Familial adenomatous polyposis，FAP)(APC基因胚系突变)和散发性CRC(APC、P53、DCC、KRAS等基因突变)；而另外15-20％的CRC表现为MSI，包括遗传性非息肉病性结直肠癌(Hereditary Nonpolyposis Colorectal Cancer，HNPCC，又称Lynch综合征)(错配修复基因胚系突变)和散发性MSI(+)CRC(错配修复基因MLH1基因启动子甲基化)。
微卫星是基因上含有的重复DNA短小序列或单核苷酸区域。在肿瘤细胞中，当DNA发生甲基化或基因突变致错配修复基因缺失时，可导致微卫星重复序列错配(微卫星突变)，导致其序列缩短或延长，从而引起微卫星不稳定(microsatellite instability，MSI)。根据MSI不 稳定的程度，可分为高微卫星不稳定(MSI-H)和低微卫星不稳定(MSI-L)，正常情况下称为微卫星稳定(microsatellite stability，MSS)。
大量研究表明，MSI参与恶性肿瘤的发生发展过程，与结直肠癌、胃癌、子宫内膜癌等发生密切相关。约15％的结直肠癌患者存在MSI现象，其中典型的遗传性非息肉病性结直肠癌(hereditary nonpolyposis colerectal cancer，HNPCC)患者90％以上存在MSI，表明MSI可作为检测是否为HNPCC患者的重要标志物；与MSS(即微卫星稳定)的结直肠癌相比，携带有MSI的结直肠癌患者其预后更好，并且二者药物反应也不一样，提示MSI可作为结直肠癌预后的独立预测因子，因此，MSI检测对结直肠癌患者意义重大。
2016年最新版美国国立综合癌症网络(National Comprehensive Cancer Network，NCCN，2016 Version 2)的结直肠癌治疗指南第一次明确指出“有结/直肠癌病史的全部患者均应检测MMR(错配修复)或MSI”，因为MSI-H(即高微卫星不稳定)的II期结直肠癌预后良好(单纯手术5y-OS率为80％)，且不能从5FU辅助化疗中获益(反而有害)。并且指南首次将PD-1单抗Pembrolizumab和Nivolumab推荐用于具有dMMR/MSI-H分子表型的mCRC末线治疗，充分说明了晚期结直肠癌中检测MMR及MSI的重要性。同时，由于遗传性结直肠癌相关基因较多，在2016最新的NCCN结直肠癌遗传风险评价指南中，建议有明显家族史的患者和家属采用多基因组合(panel)测序进行首次检测。
目前，国内医院中开展的MMR基因检测为基于免疫组化检测的蛋白测试，通常仅包含MLH1和MSH2，部分同时包含MSH6以及PMS2，其阳性结果与MSI检测结果吻合率较低；仅有极少数医院开展了通过PCR法结合毛细管电泳法的MSI状态检测，且多为外送检测。该方法通常选择5-11个单核苷酸重复位点，长度为25bp左右，PCR扩增后通过毛细管电泳测量其长度分布区间，来确定样本的微卫星(不)稳定状态。该方法为目前的金标准检测方法，但需要额外的 检测样本来进行，且需要患者的正常组织作为对照来进行状态判定，因此从操作角度上而言并不便捷。
因此，如何建立一种高效便捷的MSI检测体系，并寻找高度灵敏性及特异性的用于检测结直肠癌相关的MSI位点已成为近年来研究热点。此外，如何能够同时检测样本的微卫星稳定状态和其他疾病相关基因的状态，也是目前需要解决的问题。
发明内容
本发明要解决的技术问题是，克服现有技术的不足，提供了一种基于二代测序平台的MSI检测方法，并基于该检测方法获得了高度灵敏性及特异性的用于检测结直肠癌相关的MSI位点。该方法命名为prettyMSI(Microsatellite Instability detection based on Peak Ratio Estimation using Tumor Tissue only)，其对应的中文名为“基于仅利用肿瘤组织在二代测序中目标峰高比例检测微卫星不稳定的方法”。此外，本发明建立了一种确定能够用于结直肠癌预后评估和/或治疗方案选择的基因测评中候选微卫星位点的方法。本发明还实现了样本中多个微卫星位点和多个疾病相关基因的同时检测，能够针对所检测的样本给出更加全面的预后、治疗、排查等方面的结论和建议。
本发明的发明人发现，对于正常样本的微卫星位点，测序片段读取(reads)大概率的覆盖在样本基因型对应的一种或两种重复序列长度类型上；而对于微卫星不稳定样本，其微卫星位点由于DNA的错误复制导致大量的重复序列的扩张或收缩，从而测序片段读取(reads)覆盖到正常样本对应基因型上的概率明显减少。在本发明中，正常样本对应的基因型称为目标基因型。由于实验的序列抓取和测序均存在不可避免的错误率，不同样本的测序片段读取(reads)覆盖在目标基因型上的概率有所不同。本发明发现，标志性微卫星位点在正常样本中目标基因型的覆盖概率足够稳定，而在微卫星不稳定样本中目标基因型的覆盖概率远远小于正常值。基于这一发现，发明人筛选出了 22个位点(具体参见表1)，并进一步构建了大量正常组织样本中22个位点的各个覆盖比例向量R及目标基因型覆盖率NT构成的微卫星状态检测的基础长度分布参考集。
表1与结直肠癌诊断相关的微卫星检测标志位点信息
Figure PCTCN2018074092-appb-000001
Figure PCTCN2018074092-appb-000002
注：*标记的是NGS和PCR技术进行微卫星检测均采用的5个标志位点，分别为BAT-26、NR-24、BAT-25、NR-22、NR-21。表中所列的mean和sd为各位点由长度分布参考集得到的正常范围的平均值和方差，如果目标基因型覆盖率小于mean-3sd，则该位点判定为MSI位点，其中该sd的倍数3对于22个位点一致适用。
本发明根据二代测序的序列特性，开发出了全新的适合二代测序的微卫星稳定性检测的方法(prettyMSI)。相对基于PCR电泳的MSI检测的金标准而言，该检测方法在具有匹配的正确率的基础上，速度更快，价格更低。同时，根据本发明的方法构建了稳定的正常样本微卫星长度分布参考集，无需病人提供匹配的正常样本即可完成检测，这在实际应用中具有重大意义。
进一步地，本发明的方法依赖于高通量的第二代测序技术，还可以一次完成多样本的序列分析，在检测基因突变，染色体变异等基因组变化的同时完成微卫星状态的检测，无需额外的实验操作，大大节省了分析时间和病人检测的费用。本发明中的多基因组合(panel)进一步地检测了NCCN治疗指南中明确与结直肠癌治疗和预后相关的基因、NCCN遗传筛查指南中明确的结直肠癌遗传易感基因、以及其它胃肠道肿瘤相关基因的全外显子检测，具体含有如下36种基因：BRAF，HRAS，KRAS，NRAS，PTCH1，APCBLM，BMPR1A，CHEK2，EpCAM，GREM1，MLH1，MSH2，MSH6，MUTYH，PMS2，POLD1，POLE，PTEN，SMAD4，STK11，TP53，AKT1，ATM，BRCA1，BRCA2，CDH1，EGFR，ERBB2，KIT，MET，PDGFRA，PIK3CA，SDHB，SDHC，SDHD。
本发明的技术方案具体包括如下内容：
在本发明的一个方面，本发明涉及生物标志物的组合，其包括表1中所示的22个微卫星位点或其中任意15、16、17、18、19、20、或21个位点的组合。优选，所述生物标志物的组合为表1中所示的22个微卫星位点。
在本发明的另一个方面，本发明涉及另外的生物标志物的组合，其包括微卫星位点和一种或多种基因的组合，其中微卫星位点包括表1中所示的22个微卫星位点或其中任意15、16、17、18、19、20、21个位点的组合，其中一种或多种基因为如下36种基因中的任意一种或多种：BRAF，HRAS，KRAS，NRAS，PTCH1，APCBLM，BMPR1A，CHEK2，EpCAM，GREM1，MLH1，MSH2，MSH6，MUTYH，PMS2，POLD1，POLE，PTEN，SMAD4，STK11，TP53，AKT1，ATM，BRCA1，BRCA2，CDH1，EGFR，ERBB2，KIT，MET，PDGFRA，PIK3CA，SDHB，SDHC，SDHD。优选，所述生物标志物的组合中，微卫星位点为表1中所示的22个微卫星位点，和/或其中一种或多种基因为如上36种基因。
在本发明的另一个方面，本发明涉及试剂盒，其用于II期结直肠癌的预后评估和/或治疗方案选择、Lynch综合征(HNPCC)的确诊、预后评估和/或治疗方案选择的基因测评，其包括上述微卫星位点的组合的检测试剂。
在本发明的另一个方面，本发明涉及试剂盒，其用于同时进行包括结直肠癌预后评估和/或治疗方案选择、结直肠癌遗传易感性、以及胃肠道肿瘤易感性在内的基因测评，其包括上述微卫星位点和一种或多种基因的组合的检测试剂。优选地，所述试剂盒，其中所述的基因测评包括对家族性腺瘤性息肉病、散发性CRC、Lynch综合征、和/或散发性MSI+CRC的基因测评。优选地，上述试剂盒中所述检测试剂为进行二代高通量测序(Next-generation sequencing，NGS)的试 剂。
在本发明的另一个方面，本发明涉及用于检测上述生物标志物组合的试剂在制备用于包括结直肠癌预后评估和/或治疗方案选择、结直肠癌遗传易感性、以及胃肠道肿瘤易感性在内的基因测评的试剂盒中的应用。优选，其中所述检测试剂为进行二代高通量测序的试剂。更优选，其中所述的结直肠癌预后评估和/或治疗方案选择的基因测评为Lynch综合征(HNPCC)预后评估和/或治疗方案选择的基因测评。
在本发明的另一个方面，本发明涉及一种基于二代高通量测序确定能够用于结直肠癌预后评估和/或治疗方案选择的基因测评中候选微卫星位点的方法，其包括如下步骤：
(1)基于二代测序法同时进行多个正常组织样本中多个微卫星位点的多基因靶向捕获(captured sequencing panel)检测；
(2)对于其中的任一微卫星位点i，通过NGS数据统计测序片段读取(reads)覆盖该位点所对应的目标基因型的不同长度的测序片段的个数，目标基因型即正常组织样本中该微卫星位点的基因型；
(3)根据上述测序片段的个数计算该微卫星位点对应的目标基因型的覆盖率并构建该微卫星位点的标准长度分布参考集，据此，计算覆盖最多的一种或两种长度类型的平均覆盖率mean(NT i)和标准差sd(NT i)，其中如果覆盖第二多的测序片段读取(reads)个数小于覆盖最多的长度类型的75％，则只考虑覆盖最多的长度类型，并计算其平均覆盖率和标准差；如果覆盖第二多的测序片段读取(reads)个数大于覆盖最多的长度类型的75％，则考虑该两种覆盖最多的长度类型，此时的平均覆盖率为两种长度类型的平均覆盖率之和；
(4)对结直肠癌样本，同样根据上述步骤计算所确定的目标基因型的覆盖率，如果覆盖率＜mean(NT i)-3sd(NT i)，则该微卫星位点为 不稳定的微卫星位点，确定该位点为能够用于结直肠癌预后评估和/或治疗方案选择的基因测评中候选微卫星位点。
优选，上述方法所确定的微卫星位点包含表1中所述的22个微卫星位点或其中任意15、16、17、18、19、20、21个位点的组合。优选，其中所述的结直肠癌预后评估和/或治疗方案选择的基因测评为Lynch综合征(HNPCC)预后评估和/或治疗方案选择的基因测评。
在本发明的再一个方面，本发明涉及一种基于二代高通量测序确定结直肠癌样本中微卫星位点稳定状态的方法，其包括如下步骤：
(1)基于二代测序法进行多基因组合(panel)，即微卫星位点组合的检测；
(2)通过二代测序数据统计测序片段读取(reads)覆盖在位点不同长度的重复序列上的个数；
(3)计算覆盖率并通过其在大量正常样本中的分布构建微卫星位点的标准长度分布参考集；
(4)对于样本的每个微卫星位点，通过步骤(2)统计不同长度的测序片段读取(reads)个数，并按照步骤(3)计算目标基因型的覆盖率；
(5)将计算得到的覆盖率与标准参考集进行比对，判断该微卫星位点的稳定状态，并根据不稳定的微卫星位点的比例判断样本的微卫星位点稳定状态。
上面所述的检测方法，优选其中检测的微卫星位点包含表1中所列出的22个微卫星位点。上面所述的检测方法，其中所述步骤(5)中的判断为：若不稳定的微卫星位点数占比＞40％，则该样本判定为高度MSI；如果个数占比15％-40％，则该样本判定为低MSI样本；如果个数占比＜15％，则该样本判定为MSS样本。
优选地，上述方法包括如下步骤：(1)基于二代测序法同时进行该样本中多个微卫星位点的多基因靶向捕获(captured sequencing panel)检测，所述多个微卫星位点包括表1中所示的22个微卫星位点或其中任意15、16、17、18、19、20、21个位点的组合；
(2)在所述多个微卫星位点中，覆盖微卫星位点所对应的目标基因型的测序片段读取(reads)个数超过10的微卫星位点数为n，目标基因型即正常组织样本中微卫星位点的基因型，n≥15，对于n中的任一微卫星位点，可通过上述方法确定其是否满足覆盖率T ij＜mean(NT i)-3sd(NT i)，而当微卫星位点为表1中的22个微卫星位点时，可直接根据表1的mean(NT i)和sd(NT i)进行计算；
(3)对于所述多个微卫星位点，如果不稳定的微卫星位点个数占比＞40％*n，则该样本判定为高MSI样本；如果个数占比为15％-40％*n，则该样本判定为低MSI样本；如果个数占比＜15％*n，则该样本判定为MSS。
优选，上述方法中所述多个微卫星位点为表1中所列出的22个微卫星位点。
具体地，可参见如下表8中的统计结果，65例样本中，每个样本有足够覆盖的位点数分布在15和22之间。其中最常见的是5个PCR位点的覆盖不足，除此外有3个位点会在各样本间较为随机地出现覆盖不足。但如前所述，覆盖微卫星位点所对应的目标基因型的测序片段读取(reads)个数超过10的微卫星位点即可纳入位点统计中。
在本发明的再一个方面，本发明涉及针对结直肠癌样本同时进行微卫星稳定性和疾病相关基因检测的方法，其包括在上述方法中，基于二代测序法，除了进行微卫星位点的检测外，同时对如下36种基因中的任意一种或多种进行检测：BRAF，HRAS，KRAS，NRAS，PTCH1，APCBLM，BMPR1A，CHEK2，EpCAM，GREM1，MLH1，MSH2，MSH6，MUTYH，PMS2，POLD1，POLE，PTEN，SMAD4， STK11，TP53，AKT1，ATM，BRCA1，BRCA2，CDH1，EGFR，ERBB2，KIT，MET，PDGFRA，PIK3CA，SDHB，SDHC，SDHD，然后结合微卫星位点的稳定状态结果和一种或多种基因的检测结果判断样本所处的状态。
在本发明的再一个方面，本发明涉及用于上述任一项的方法的试剂盒，其包含检测微卫星位点的试剂和/或检测一种或多种基因的试剂。优选，所述试剂盒包含的试剂为进行二代高通量测序的试剂。优选，其中所述的结直肠癌为遗传性非息肉病性结直肠癌(Hereditary Nonpolyposis Colorectal Cancer，HNPCC，又称Lynch综合征)。
附图说明
图1为不同类型样本在PCR检测和以表1中MSI-BR1命名的微卫星位点检测结果图。(a)一个MSI-H的癌组织样本(对应表7中的编号为RS1607586FFP)及其配对的癌旁组织在(a-1)PCR检测中九个标志位点的图谱；(a-2)微卫星位点MS-BR1的不同重复长度序列对应的测序片段读取(reads)覆盖个数的直方图。(b)一个MSS的癌组织样本(对应表7中的编号为RS1608839FFP)及其配对的癌旁组织在(b-1)PCR检测中九个标志位点的图谱；(b-2)微卫星位点MS-BR1的不同重复长度序列对应的测序片段读取(reads)覆盖个数的直方图。横坐标为重复长度，纵坐标为覆盖范围(测序片段数)。
图2为微卫星位点MSI-BR2长度分布参考集及判定标准示例图。
图3为编号为RS1611018FFP的癌组织样本(第一三五行)和癌旁组织样本(第二四六行)中，22个微卫星位点的检测结果直方图。
图4为编号为RS1608823FFP的癌组织样本(第一三五行)和癌旁组织样本(第二四六行)中，22个微卫星位点的检测结果直方图。
实施方式
以下结合具体实施例对本发明作进一步详细说明。
实施例
实施例中所涉及的实验样本均来自于国内结直肠癌诊疗领先的三甲医院，并且所有的实验样本均明确诊断为IHC阳性肿瘤及癌旁正常组织样本。实验中所用仪器，试剂，试剂盒，分析软件均为商购可得。
方法与步骤
1、基于二代测序法进行多基因组合(panel)检测，具体步骤如下：
使用QIAamp DNA FFPE tissue kit分别提取肿瘤组织与癌旁正常组织DNA。用Qubit 3.0荧光仪配套的dsDNA HS assay kits进行精确定量。然后用超声破碎仪Covaris M220将DNA物理性片段化到180-250bp长的片段后，进行末端修复、磷酸化，3′端加脱氧腺嘌呤，和接头连接。然后将连接上扩增接头的DNA用AgencourtAMPure XP顺磁性磁珠进行纯化，并使用PCR聚合酶进行预扩增，扩增后的纯化后产物与Agilent订制的多重生物素标记探针组进行杂交(该多基因组合(panel)设计包括36个基因的外显子及部分内含子区域序列)。杂交成功的片段经过特异性洗脱，PCR聚合酶的富集扩增后，进行定量和片段长度分布测定，使用Illumina测序仪进行二代测序。使用QIAamp DNA FFPE tissue kit分别提取肿瘤组织与癌旁正常组织DNA。用Qubit 2.0 fluorometer，dsDNA HS assay kits进行定量。以Covaris M220将DNA打断后，进行末端修复、磷酸化和接头连接。采用AgencourtAMPure XP kit选择出其中200-400bp长度的片段，与根据多基因组合(panel)上所包括的36个基因的外显子及部分内含子区域序列设计的Agilent多重捕获探针进行杂交。杂交成功的片段经磁珠纯化和PCR扩增并进行质量、长度测定后，使用Illumina测序仪进行二代测序。测得的序列采用BWA 0.7.10版比对到人类基因 组序列(版本hg19)，并分别采用GATK 3.2、MuTect和VarScan进行局部排列优化，变异响应(calling)和注释。对于变异响应(calling)，VarScanfp filter将去除覆盖深度在100x以下的位点；对于插入缺失(indel)和单位点变异，分别至少需要5条和8条变异的测序片段的读取(reads)。
2、微卫星不稳定性检测方法，具体步骤如下：
步骤一：通过NGS数据统计测序片段读取(reads)覆盖在位点不同长度的重复序列上的个数。对每一个微卫星位点，首先在人类基因组中搜索其位置信息及两端序列，并构建由两端序列连接的中间重复序列长度分别为1到L-10bp的所有序列作为搜索字典，L为测序片段读取(reads)的长度。
步骤二：计算覆盖率并构建微卫星位点的标准参考集：
根据上述测序片段的个数计算该微卫星位点对应的目标基因型的覆盖率并构建该微卫星位点的标准长度分布参考集，据此，计算覆盖最多的一种或两种长度类型的平均覆盖率mean(NT i)和标准差sd(NT i)，其中如果覆盖第二多的测序片段读取(reads)个数小于覆盖最多的长度类型的75％，则只考虑覆盖最多的长度类型，并计算其平均覆盖率和标准差；如果覆盖第二多的测序片段读取(reads)个数大于覆盖最多的长度类型的75％，则考虑该两种覆盖最多的长度类型，此时的平均覆盖率为两种长度类型的平均覆盖率之和。
以表1中命名为MSI-BR1的微卫星位点为代表性实施例说明该微卫星微位点的标准参考集的构建方式：MSI-BR01微卫星为1号染色体上某单碱基的微卫星位点(14T，T是重复的碱基，14是重复的个数)，其两端序列分别为ATTCC和GCTTT，构建的搜索字典包含ATTCCTGCTTT(重复长度为1)，ATTCCTTGCTTT(重复长度为2)，ATTCCTTTGCTTT(重复长度为3)，等等。从癌症样本的测序结果文件中提取至少一端位于位点附近2kb内的配对的测序片段(read  pairs)，并将其和该位点的搜索字典中的序列进行比对。统计覆盖搜索字典中不同长度序列的测序片段读取(reads)个数，构建位点所有长度类型的测序片段读取(reads)覆盖个数的直方图。
如图1所示，a-2和b-2部分分别是MSI-BR1高微卫星不稳定(MSI-H)和MSI-BR1微卫星稳定(MSS)位点在癌症和癌旁样本中的直方图。如图所示，MSI-H位点的直方图在癌症和癌旁样本中有明显的不同。根据a-2中的癌症样本图和b-2的两个图可以确定，MSI-BR1为可选的微卫星位点。
如图2所示，其为微卫星位点MSI-BR2长度分布参考集及判定标准示例图。横坐标上mean-3sd线左边的圆点所示为MSI-H癌组织样本的例子，而右边三角所示为MSS癌组织样本的例子。其中目标基因型覆盖率在参考集中符合正态分布，其平均覆盖率0.91，标准差0.02即根据上述步骤二统计而得。
如图3和图4所示，其为两个不同编号的癌组织样本(第一三五行)和癌旁组织样本(第二四六行)中22个微卫星位点的检测结果直方图，结果分别为MSI-H和MSS。其中横坐标为目标基因型的长度类型，纵坐标为目标基因型的测序片段读取(reads)个数。
需要说明的是，同一个位点上下对应仅是为了观察方便，事实上在实际检测过程中，不需要癌旁组织作为对照样本，而仅需要根据癌组织样本的结果计算是否符合覆盖率T ij＜mean(NT i)-3sd(NT i)，即可判断该微卫星位点是否为不稳定的微卫星位点。
步骤三：对于癌症样本j的每个微卫星标志位点i，通过步骤一统计不同长度的测序片段读取(reads)个数，并按照步骤二计算目标基因型的覆盖率(T ij)。
在所述多个微卫星位点中，覆盖微卫星位点所对应的目标基因型的测序片段读取(reads)个数超过10的微卫星位点数为n，目标基 因型即正常组织样本中微卫星位点的基因型，n≥15，对于n中的任一微卫星位点，可通过上述方法确定其是否满足覆盖率T ij＜mean(NT i)-3sd(NT i)，而当微卫星位点为表1中的22个微卫星位点时，可直接根据表1的mean(NT i)和sd(NT i)进行计算。
步骤四：依次检测表1中所列微卫星位点的覆盖率，并与其各自对应的标准参考集进行对比，依据步骤三判断该微卫星位点的稳定性。对于一个癌症样本，检测表1中所列出的微卫星位点状态，若不稳定的微卫星位点数占比＞40％*n，则该样本判定为高MSI；如果个数占比15％-40％*n，则该样本判定为低MSI样本；如果个数占比＜15％*n，则该样本判定为MSS样本。
此外，对于样本中可能的参考集中未出现的基因型(测序片段读取(reads)大量覆盖在新的长度类型上)，对判定为微卫星不稳定的位点，对于其覆盖最多的两种长度类型(如果第二多的测序片段读取(reads)个数小于最高峰的75％，则只考虑最高峰对应的长度类型)，若该长度相对人类基因组参考序列的长度偏差小于2bp，则亦将该长度序列作为候选基因型，按照步骤二的参考集构建方法计算标准覆盖率，重新计算正常样本目标基因型占比向量NT i和癌症样本的覆盖率，如果此时仍然符合T ij＜mean(NT i)-3sd(NT i)，则该位点确定为不稳定的微卫星位点，否则，该位点仅判定为可能的不稳定的微卫星位点。
3、实施例中所使用的多基因组合(panel)还包含了NCCN治疗指南中明确与结直肠癌治疗和预后相关的基因、NCCN遗传筛查指南中明确的结直肠癌遗传易感基因、以及其它胃肠道肿瘤相关基因的全外显子检测，具体如下：BRAF，HRAS，KRAS，NRAS，PTCH1，APCBLM，BMPR1A，CHEK2，EpCAM，GREM1，MLH1，MSH2，MSH6，MUTYH，PMS2，POLD1，POLE，PTEN，SMAD4，STK11，TP53，AKT1，ATM，BRCA1，BRCA2，CDH1，EGFR，ERBB2，KIT，MET，PDGFRA，PIK3CA，SDHB，SDHC，SDHD。
检测与验证结果
实施例共检测了65例IHC阳性肿瘤及癌旁正常组织样本，并验证了医院的IHC结果与微卫星不稳定性、以及MMR基因突变检测的关联度。验证结果具体参见表7和表8，根据该结果可以得出以下结论：
IHC阳性患者中，仅有小部分(44.6％)能够检出微卫星不稳定状态。换言之，即当前国内开展的IHC检测对于微卫星状态的敏感性较低。
IHC阳性且微卫星不稳定患者中，共有4名患者(13.8％)检出确定为致病或可能致病的胚系MMR基因突变，确诊为林奇综合征，建议进行基因检测进行风险控制；另有7名患者(24.1％)检出意义不明确的胚系MMR基因突变，需进一步收集家族史和血亲测序进行诊断。
所有患者中，有1人检出APC可能致病的胚系突变，为FAP综合征患者；1人检出CHEK2可能致病胚系突变，为遗传性结直肠癌患者；建议进行基因检测进行风险控制；2人分别检出ATM及MUTYH意义不明的胚系突变，需进一步收集家族史和血亲测序进行诊断。此结果说明同时检测多个遗传易感性基因的重要性。
所有患者中，有45人(67.7％)检出与诊疗指南明确与治疗预后相关的突变，为患者的后续治疗提供依据。
进一步地，对上述样本我们同时进行了传统PCR金标准检测，以验证二代测序方法的微卫星稳定性检测结果。金标准PCR方法对NR-21、BAT-26、NR-27、BAT-25、NR-24和MONO-27六个单核苷酸重复位点和Penta C、PentaD和Amelogenin三个位点进行复合扩增，在ABI 3730xl型遗传分析仪上对STR位点进行检测。PCR方法最终确定了29例MSI样本和36例MSS样本。与PCR分析结果对比发现， 本发明MSI的检测准确率达96.55％，特异性100％。其中仅有一例根据本发明的检测方法判定为MSI-L而传统方法判定为MSI-H，经分析，该例样本的肿瘤细胞占比较低，因此影响了判定结果。
PCR检测标准如下表2：
表2-PCR金标准检测的标志物和判断标准
Figure PCTCN2018074092-appb-000003
对于上述提及编号的样本，PCR分析结果如下：
表3-编号为RS1607586FFP的样本PCR分析结果表
Figure PCTCN2018074092-appb-000004
Figure PCTCN2018074092-appb-000005
按照NCI对肿瘤MSI的评判标准，该样本的肿瘤组织为高微卫星不稳定(MSI-H)型。
表4-编号为RS1608839FFP的样本PCR分析结果表
Figure PCTCN2018074092-appb-000006
按照NCI对肿瘤MSI的评判标准，该样本的肿瘤组织为微卫星稳定(MSS)型。
表5-编号为RS1611018FFP的样本PCR分析结果表
Figure PCTCN2018074092-appb-000007
Figure PCTCN2018074092-appb-000008
按照NCI对肿瘤MSI的评判标准，该样本的肿瘤组织为高微卫星不稳定(MSI-H)型。
表6-编号为RS1608823FFP的样本PCR分析结果表
Figure PCTCN2018074092-appb-000009
按照NCI对肿瘤MSI的评判标准，该样本的肿瘤组织为微卫星 稳定(MSS)型。
Figure PCTCN2018074092-appb-000010
Figure PCTCN2018074092-appb-000011
Figure PCTCN2018074092-appb-000012
Figure PCTCN2018074092-appb-000013
Figure PCTCN2018074092-appb-000014
Figure PCTCN2018074092-appb-000015
此外，发明人分析了65例样本中22个微卫星位点的分布，每个样本中满足上述“覆盖微卫星位点所对应的目标基因型的测序片段读取(reads)个数超过10的微卫星位点数”的微卫星位点覆盖数，每个微卫星位点在65例样本中的分布，以及每个样本中每个微卫星位点稳定性的判断结果。具体参见下述表8。NA表示无或不满足条件
Figure PCTCN2018074092-appb-000016
Figure PCTCN2018074092-appb-000017
Figure PCTCN2018074092-appb-000018
Figure PCTCN2018074092-appb-000019
Figure PCTCN2018074092-appb-000020
Figure PCTCN2018074092-appb-000021

Claims (18)

  1. 一种生物标志物组合，其包括表1中所示的22个微卫星位点或其中任意15、16、17、18、19、20、21个位点的组合。
  2. 权利要求1所述的生物标志物组合，其为表1中所示的22个微卫星位点。
  3. 一种生物标志物组合，其包括微卫星位点和一种或多种基因的组合，其中微卫星位点包括表1中所示的22个微卫星位点或其中任意15、16、17、18、19、20、21个位点的组合，其中一种或多种基因为如下36种基因中的任意一种或多种：BRAF，HRAS，KRAS，NRAS，PTCH1，APCBLM，BMPR1A，CHEK2，EpCAM，GREM1，MLH1，MSH2，MSH6，MUTYH，PMS2，POLD1，POLE，PTEN，SMAD4，STK11，TP53，AKT1，ATM，BRCA1，BRCA2，CDH1，EGFR，ERBB2，KIT，MET，PDGFRA，PIK3CA，SDHB，SDHC，SDHD。
  4. 权利要求3所述的生物标志物组合，其中微卫星位点为表1中所示的22个微卫星位点，和/或其中一种或多种基因为如上36种基因。
  5. 一种试剂盒，其用于II期结直肠癌的预后评估和、或治疗方案选择、Lynch综合征(HNPCC)的确诊、预后评估和/或治疗方案选择的基因测评，其特征在于，包括如权利要求1或2所述生物标志物组合的检测试剂。
  6. 一种试剂盒，其用于同时进行包括结直肠癌预后评估和/或治疗方案选择、结直肠癌遗传易感性、以及胃肠道肿瘤易感性在内的基因测评，其特征在于，包括如权利要求3或4所述生物标志物组合的检测试剂。
  7. 权利要求6的试剂盒，其中所述基因测评包括对家族性腺瘤性息肉病、散发性CRC、Lynch综合征、和/或散发性MSI+CRC的基因测评。
  8. 权利要求5-7任一项所述的试剂盒，其中所述检测试剂为进行二代高通量测序(Next-generation sequencing，NGS)的试剂。
  9. 用于检测权利要求1-4中任一项的生物标志物组合的试剂在制备用于包括结直肠癌预后评估和/或治疗方案选择、结直肠癌遗传易感性、以及胃肠道肿瘤易感性在内的基因测评的试剂盒中的应用。
  10. 权利要求9所述的应用，其中所述检测试剂为进行二代高通量测序的试剂。
  11. 权利要求9所述的应用，其中所述的结直肠癌预后评估和/或治疗方案选择的基因测评为Lynch综合征(HNPCC)预后评估和/或治疗方案选择的基因测评。
  12. 一种基于二代高通量测序确定能够用于结直肠癌预后评估和/或治疗方案选择的基因测评中候选微卫星位点的方法，其包括如下步骤：
    (1)基于二代测序法同时进行多个正常组织样本中多个微卫星位点的多基因靶向捕获(captured sequencing panel)检测；
    (2)对于其中的任一微卫星位点i，通过NGS数据统计测序片段读取(reads)覆盖该位点所对应的目标基因型的不同长度的测序片段的个数，目标基因型即正常组织样本中该微卫星位点的基因型；
    (3)根据上述测序片段的个数计算该微卫星位点对应的目标基因型的覆盖率并构建该微卫星位点的标准长度分布参考集，据此，计算覆盖最多的一种或两种长度类型的平均覆盖率mean(NT i)和标准差sd(NT i)，其中如果覆盖第二多的测序片段读取(reads)个数小于覆盖 最多的长度类型的75％，则只考虑覆盖最多的长度类型，并计算其平均覆盖率和标准差；如果覆盖第二多的测序片段读取(reads)个数大于覆盖最多的长度类型的75％，则考虑该两种覆盖最多的长度类型，此时的平均覆盖率为两种长度类型的平均覆盖率之和；
    (4)对结直肠癌样本，同样根据上述步骤计算所确定的目标基因型的覆盖率，如果覆盖率＜mean(NT i)-3sd(NT i)，则该微卫星位点为不稳定的微卫星位点，确定该位点为能够用于结直肠癌预后评估和/或治疗方案选择的基因测评中候选微卫星位点。
  13. 根据权利要求12所述的方法所确定的微卫星位点，其包含表1中所述的22个微卫星位点。
  14. 权利要求12所述的方法，其中所述的结直肠癌预后评估和/或治疗方案选择的基因测评为Lynch综合征(HNPCC)预后评估和/或治疗方案选择的基因测评。
  15. 一种基于二代高通量测序确定结直肠癌样本中微卫星位点稳定状态的方法，其包括如下步骤：
    (1)基于二代测序法同时进行该样本中多个微卫星位点的多基因靶向捕获(captured sequencing panel)检测，所述多个微卫星位点包括表1中所示的22个微卫星位点或其中任意15、16、17、18、19、20、21个位点的组合；
    (2)在所述多个微卫星位点中，覆盖微卫星位点所对应的目标基因型的测序片段读取(reads)个数超过10的微卫星位点数为n，目标基因型即正常组织样本中微卫星位点的基因型，n≥15，对于n中的任一微卫星位点，可通过权利要求12的方法确定其是否满足覆盖率T ij＜mean(NT i)-3sd(NT i)，而当微卫星位点为表1中的22个微卫星位点时，可直接根据表1的mean(NT i)和sd(NT i)进行计算；
    (3)对于所述多个微卫星位点，如果不稳定的微卫星位点个数占 比＞40％*n，则该样本判定为高MSI样本；如果个数占比为15％-40％*n，则该样本判定为低MSI样本；如果个数占比＜15％*n，则该样本判定为MSS。
  16. 权利要求15所述的方法，其中所述多个微卫星位点为表1中所列出的22个微卫星位点。
  17. 一种基于二代高通量测序同时确定患者结直肠癌样本中多个微卫星稳定性和疾病相关基因，以对该患者或家族的结直肠癌风险控制、治疗和/或预后方案提供临床指导的方法，其包括如下步骤：
    (1)同时对如权利要求15中所述的多个微卫星位点和如下36种基因中的任意一种或多种进行检测：BRAF，HRAS，KRAS，NRAS，PTCH1，APCBLM，BMPR1A，CHEK2，EpCAM，GREM1，MLH1，MSH2，MSH6，MUTYH，PMS2，POLD1，POLE，PTEN，SMAD4，STK11，TP53，AKT1，ATM，BRCA1，BRCA2，CDH1，EGFR，ERBB2，KIT，MET，PDGFRA，PIK3CA，SDHB，SDHC，SDHD；
    (2)根据权利要求15的方法确定所述样本的微卫星位点稳定状态；
    (3)根据测序结果获得所述一种或多种疾病相关基因的检测结果；
    (4)结合上述步骤(2)、(3)的结果对该患者或家族的结直肠癌风险控制、治疗和/或预后方案提供临床指导。
  18. 一种用于权利要求12-17中任一项的方法的试剂盒，其包含检测所述多个微卫星位点的试剂。
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