Molecular Subtyping of Colorectal Cancer, Survival Risk Gene Cluster, and Diagnostic Products and Applications

Abstract

A group of gene clusters capable of evaluating the molecular typing and survival risk of colorectal cancer is disclosed; the application of a reagent for detecting the gene expression levels of the gene clusters in the preparation of a product for determining the molecular typing of colorectal cancer and evaluating the survival risk of colorectal cancer patients is disclosed; the product includes a next-generation sequencing (NGS) detection kit, a fluorescence quantitative PCR detection kit, a gene chip, and a protein chip. A method for molecular typing of colorectal cancer and survival risk assessment using the detection kit is also disclosed.

Description

[0001] This application claims the priority of Chinese Patent Application No. 202011561310.2, titled "Molecular Typing of Colorectal Cancer, Survival Risk Gene Cluster, Diagnostic Products and Applications", filed on December 25, 2020, the content of which is incorporated herein by reference in its entirety. Technical Field

[0002] The present invention belongs to the field of biotechnology, and particularly relates to the subtype typing of colorectal cancer, a gene cluster for evaluating the survival risk of colorectal cancer patients, and its in vitro diagnostic products and applications. Background Art

[0003] The clinical stage of colon cancer is closely related to the treatment plan. The treatment of stage I and stage IV colon cancer is generally relatively clear. Stage I is mainly treated by surgery without adjuvant chemotherapy, while stage IV requires comprehensive treatment mainly based on chemotherapy. However, the treatment of stage II and stage III colon cancer is relatively complex, and there is currently no good predictive index for the benefit of postoperative chemotherapy in current clinical or case diagnoses. Even for patients with the same pathological tissue type and the same clinical stage, using the same treatment method, their prognoses are also different. New biological indicators are needed to guide the adjuvant treatment after surgery or neoadjuvant treatment before surgery for this part of patients. In recent years, the development of tumor molecular diagnostic products based on gene expression profiles has provided a new direction for the precision treatment of colon cancer.

[0004] The NCCN Clinical Practice Guidelines in Oncology (2020.v4) propose three colon cancer molecular diagnostic products based on gene expression profiles, Oncotype Dx, ColoPrint, and ColDx, which can predict the risk of distant metastasis after colon cancer surgery and the probability of benefit from adjuvant chemotherapy. Oncotype Dx predicts the recurrence risk of stage II and III colorectal cancer by detecting the expression profiles of 12 genes, as well as whether chemotherapy is needed after surgery and the selection of chemotherapy regimens, and can also evaluate the survival after stage II rectal cancer surgery (see Reimers, M.S. et al., 2014, Journal of the National Cancer Institute, 106); ColoPrint is a detection method based on the expression profiles of 18 genes and is also used for the recurrence risk assessment of stage II colon cancer; ColDx is a detection method based on the expression profiles of 643 genes using chip technology for the recurrence risk assessment of stage II colon cancer. The common feature of the three products is that the risk assessment index is an independent prognostic indicator and is not affected by other risk factors, including TNM staging, tumor grade, lymph node metastasis, mismatch repair (MMR) status, perforation, etc.

[0005] In addition to recurrence risk assessment, colorectal molecular typing based on expression profiles can classify it into different molecular subtypes, further describe the molecular characteristics and possible mechanisms of tumorigenesis, and then formulate clinical treatment plans or provide research directions for the development of targeted drugs accordingly. A research consortium formed by 6 institutions engaged in the study of molecular typing of colorectal cancer based on gene expression integrated their respective research results and proposed a consensus molecular typing method, "CMS" (see Guinney J. et al., The consensus molecular subtypes of colorectal cancer [J]. Nature medicine. 2015, 21(11): 1350-6). The CMS molecular typing includes: CMS1 (microsatellite instability plus immune activation type, 14%), characterized by high mutation, microsatellite instability (MSI), and strong immune activation; CMS2 (classical type, 37%), characterized by epithelial type, chromosomal instability, and activation of WNT and MYC signaling pathways; CMS3 (metabolic type, 13%), characterized by epithelial type and obvious metabolic disorders; CMS4 (mesenchymal type, 23%), characterized by TGFβ activation, invasion of stroma, and angiogenesis; and the mixed type (13%), which may represent unknown subtypes or intratumoral heterogeneity. However, in the CMS typing system, there are no significant differences in survival data (OS, DFS) among subtypes, especially between CMS1 and CMS3. Summary of the Invention

[0006] In one aspect, the present invention provides a group of genes for determining the molecular typing of colorectal cancer and / or assessing the survival risk of colorectal cancer patients, which includes genes related to molecular typing and survival risk assessment. In one embodiment, the group of genes further includes reference genes. The molecular typing of colorectal cancer includes CRC1, CRC2, CRC3, CRC4, CRC5, and the mixed subtype.

[0007] In one aspect, the present invention also provides a reagent for detecting the expression level of the genes in the group of genes of the present invention. In a preferred embodiment, the reagent is a reagent for detecting the amount of RNA transcribed from the genes of the present invention, especially mRNA; or it is a reagent for detecting the amount of cDNA complementary to mRNA. In a specific embodiment, the reagent is a primer, a probe, or a combination thereof.

[0008] On the other hand, the present invention also provides a product for molecular typing and / or survival risk assessment of colorectal cancer, which comprises the reagent of the present invention. The present invention also provides the application of the gene group or reagent of the present invention in the preparation of a product. The product is used to determine the molecular typing of colorectal cancer and / or evaluate the survival risk of patients with colorectal cancer. In one embodiment, the product is a next-generation sequencing kit, a real-time fluorescence quantitative PCR detection kit, a gene chip, a protein chip, an ELISA diagnostic kit or an immunohistochemistry (IHC) kit. In a preferred embodiment, the product is a next-generation sequencing kit or a real-time fluorescence quantitative PCR detection kit.

[0009] On the one hand, the present invention also provides a method for determining the molecular typing and / or survival risk of colorectal cancer in a subject, the method comprising: (1) providing a sample of the subject; (2) measuring the expression level of the genes in the gene group of the present invention in the sample; (3) determining the molecular typing of the colorectal cancer of the subject and / or the risk of survival. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A heatmap showing the expression of genes related to molecular typing of colorectal cancer and survival risk (proliferation-related genes, extracellular matrix-related genes, intracellular matrix-related genes, immune-related genes, immunoglobulin-related genes) in CRC1, CRC2, CRC3, CRC4, CRC5 and Mixed subtypes.

[0011] Figure 2 A heatmap showing the results of survival analysis of 1091 colorectal cancer cases (divided into CRC1, CRC2, CRC3, CRC4, CRC5 and mixed subtypes) using the Kaplan-Meier method, indicating that the survival risk of each subtype of colorectal cancer is different. Among them, the 10-year distant metastasis-free survival rate of the CRC2 subtype is better, the 10-year distant metastasis-free survival rates of the CRC1 subtype and the CRC5 subtype are relatively poor, and the prognoses of the CRC3 subtype and the CRC4 subtype are medium.

[0012] Figure 3 A heatmap showing the results of survival analysis of 1091 colorectal cancer cases (divided into two groups with strong and weak immunoglobulin indices) using the Kaplan-Meier method, indicating that the immunoglobulin index can indicate the prognosis of colorectal cancer. According to the immunoglobulin index, colorectal cancer cases can be divided into two groups with strong and weak immunoglobulin indices, and the 10-year distant metastasis-free survival rate of the group with a strong immunoglobulin index is higher.

[0013] Figure 4The results of establishing a risk assessment model using the Cox model and performing survival analysis on 1091 colorectal cancer cases (divided into low- and high-risk groups) are shown, indicating that the colorectal cancer recurrence risk index can indicate the survival risk. The overall survival rate without distant metastasis in the low-risk group (recurrence risk index 0-65) is relatively high, while the 10-year overall survival rate without distant metastasis in the high-risk group (recurrence risk index 66-100) is relatively low.

[0014] Figure 5A The results of performing survival analysis on stage III colon cancer cases (divided into two groups: receiving chemotherapy and not receiving chemotherapy) with a high survival risk assessment (173 cases) using the Kaplan-Meier method are shown, indicating that for stage III colon cancer cases with a high survival risk assessment, the 10-year overall survival rate without distant metastasis in the case group receiving chemotherapy is higher than that in the case group not receiving chemotherapy.

[0015] Figure 5B The results of performing survival analysis on stage III colon cancer cases (divided into two groups: receiving chemotherapy and not receiving chemotherapy) with a low survival risk assessment (108 cases) using the Kaplan-Meier method are shown, indicating that for stage III colon cancer cases with a low survival risk assessment, there is no significant difference in the 10-year overall survival rate without distant metastasis between the case group receiving chemotherapy and the case group not receiving chemotherapy. Detailed implementation manners

[0016] General Definitions and Terms

[0017] The present invention will be further described in detail below. It should be understood that the terms are intended to describe the purpose and not to limit the present invention.

[0018] Unless otherwise specified, the technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention pertains. In case of contradiction, the definitions provided in this application shall prevail. For experimental methods not specified with specific conditions, they can generally be carried out under the conditions described in Sambrook et al., Molecular Cloning: A Laboratory Manual, 4th ed, Cold Spring Harbor, N.Y., 2012, or according to the conditions recommended by the manufacturer.

[0019] When a quantity, concentration, or other value or parameter is expressed in the form of a range, a preferred range, or a preferred upper limit of a value and a preferred lower limit of a value, it should be understood that any range formed by combining any upper limit of the range or a preferred value with any lower limit of the range or a preferred value is specifically disclosed, regardless of whether the range is specifically disclosed. Unless otherwise specified, the numerical ranges listed herein are intended to include the endpoints of the range and all integers and fractions (decimals) within the range.

[0020] When the terms "about" or "approximately" are used in conjunction with a variable of numerical value, they generally refer to the numerical value of the variable and all numerical values of the variable within the experimental error (e.g., within the 95% confidence interval for the mean value) or within ±10% of the specified numerical value, or within a wider range.

[0021] The term "optionally" or "optionally present" means that the subsequently described event or situation may or may not occur, and this description includes the occurrence and non-occurrence of the described event or situation.

[0022] The expression "comprising" or similar expressions synonymous therewith, such as "including", "containing", and "having", etc., are open-ended and do not exclude additional unenumerated elements, steps, or components. The expression "consisting of" excludes any element, step, or component not specified. The expression "consisting essentially of" means that the scope is limited to the specified elements, steps, or components, plus optionally present elements, steps, or components that do not materially affect the basic and novel features of the claimed subject matter. It should be understood that the expression "comprising" encompasses the expressions "consisting essentially of" and "consisting of".

[0023] The expression "at least one (kind)" or "one (kind) or more (kinds)" can represent 1, 2, 3, 4, 5, 6, 7, 8, 9 or more (kinds).

[0024] The detection of the gene expression level described herein can be achieved, for example, by detecting the target nucleic acid (e.g., RNA transcript), or can also be achieved, for example, by detecting the amount of the target polypeptide (e.g., the encoded protein), such as detecting the protein expression level by proteomic methods. The amount of the target polypeptide, such as the amount of the polypeptide, protein, or protein fragment encoded by the target gene, can be normalized against the amount of the total protein in the sample or the amount of the polypeptide encoded by a reference gene. The amount of the target nucleic acid, such as the amount of the DNA of the target gene, its RNA transcript, or the cDNA complementary to the RNA transcript, can be normalized against the amount of the total DNA, total RNA, or total cDNA in the sample or against the amount of the DNA, RNA transcript, or cDNA complementary to the RNA transcript of a set of reference genes.

[0025] In this article, the term "polypeptide" refers to a compound composed of amino acids linked by peptide bonds, including the full length of the polypeptide or amino acid fragments. In this article, "polypeptide" and "protein" can be used interchangeably.

[0026] The term "nucleotide" includes deoxyribonucleotides and ribonucleotides. The term "nucleic acid" refers to a polymer composed of two or more nucleotides, covering deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and nucleic acid analogs.

[0027] The term "RNA transcript" refers to total RNA, i.e., coding or non-coding RNA, including RNA directly from tissue or peripheral blood samples, as well as RNA indirectly from tissue or blood samples after cell lysis. Total RNA includes tRNA, mRNA, and rRNA, where mRNA includes mRNA transcribed from target genes and also mRNA from other non-target genes. The term "mRNA" can include precursor mRNA and mature mRNA, which can be either full-length mRNA or fragments thereof. In this article, the RNA that can be used for detection is preferably mRNA, more preferably mature mRNA. The term "cDNA" refers to DNA having a base sequence complementary to RNA. Those skilled in the art can obtain its RNA transcript and / or cDNA complementary to its RNA transcript from the DNA of a gene using methods known in the art, for example, by chemical synthesis methods or molecular cloning methods.

[0028] In this article, a target nucleic acid (such as an RNA transcript) can be detected and quantified, for example, by methods such as hybridization, amplification, or sequencing. For example, an RNA transcript is hybridized with a probe or primer to form a complex, and the amount of the target nucleic acid is obtained by detecting the amount of the complex. The term "hybridization" refers to the process in which two nucleic acid fragments bind through stable and specific hydrogen bonds to form a double helix complex under appropriate conditions.

[0029] The term "amplification primer" or "primer" refers to a nucleic acid fragment containing 5 to 100 nucleotides, preferably containing 15 to 30 nucleotides that can initiate an enzymatic reaction (such as an enzymatic amplification reaction).

[0030] The term "(hybridization) probe" refers to a nucleic acid sequence (which can be DNA or RNA) including at least 5 nucleotides, for example, containing 5 to 100 nucleotides, which can hybridize with a target nucleic acid (such as an RNA transcript of a target gene or an amplification product of an RNA transcript, or cDNA complementary to an RNA transcript) to form a complex under specified conditions. A hybridization probe can also include a marker for detection. The term "TaqMan probe" is a probe based on TaqMan technology, with a fluorescent group carried at its 5'-end, such as FAM, TET, HEX, NED, VIC, or Cy5, etc., and a fluorescent quenching group (such as TAMRA and BHQ groups) or a non-fluorescent quenching group (TaqMan MGB probe) carried at its 3'-end, having a nucleotide sequence capable of hybridizing with a target nucleic acid, and can report the amount of nucleic acid forming a complex with it when applied to real-time fluorescence quantitative PCR (RT-PCR).

[0031] The term "reference gene" or "internal reference gene" herein refers to a gene that can be used as a reference to correct and standardize the expression level of a target gene. The criteria for including a reference gene that can be considered are: (1) stably expressed in tissues, and its expression level is not affected or minimally affected by pathological conditions or drug treatments; (2) the expression level should not be too high to avoid being overly represented in the data obtained from expression data (such as those obtained through next-generation sequencing), which may affect the accuracy of data detection and interpretation of other genes. Therefore, reagents that can be used to detect the expression level of the reference gene of the present invention are also within the scope of protection of the present invention. Reference genes that can be used in the present invention include, but are not limited to, "housekeeping genes". In this article, "reference gene", "internal reference gene" and "housekeeping gene" can be used interchangeably.

[0032] The term "housekeeping gene" refers to a class of genes whose products are essential for maintaining the basic life activities of cells, are continuously expressed in most or almost all tissues at all stages of individual growth, and the expression level is less affected by environmental factors.

[0033] In this article, the term "colorectal cancer" is also known as large bowel cancer, rectal cancer, colorectal cancer, colon cancer, or bowel cancer, and is a cancer originating from the colon or rectum. Due to abnormal cell growth, it may invade or metastasize to other parts of the body.

[0034] In this article, the term "molecular classification of colorectal cancer" refers to a classification method of colorectal cancer established based on the gene expression profile of colorectal cancer tumor tissues.

[0035] In this article, the term "prognosis" refers to the prediction of the course and development outcome of colorectal cancer, including but not limited to the prediction of the survival risk of colorectal cancer. Colorectal cancer with a lower survival risk has a better prognosis, and vice versa.

[0036] "Survival risk assessment" herein refers to the assessment of the likelihood of disease progression or death due to colorectal cancer and its related causes in colorectal cancer patients during a specified period starting from random. In this article, "disease progression" includes but is not limited to an increase in tumor cells, recurrence, and metastasis. In this article, "survival risk assessment" and "recurrence risk assessment" can be used interchangeably. In this article, the terms "recurrence risk" and "survival risk" can be used interchangeably. In this article, survival risk assessment is performed by calculating the recurrence risk score (also called the recurrence risk index).

[0037] Gene Cluster of the Present Invention

[0038] In one general aspect, the present invention provides a group of gene clusters, which include genes related to the molecular classification of colorectal cancer and survival risk assessment.

[0039] The genes related to the molecular typing of colorectal cancer and survival risk assessment of the present invention may include: (1) 21 proliferation-related genes, (2) 17 extracellular matrix-related genes, (3) 16 intracellular matrix-related genes, (4) 13 immune-related genes, and (5) 9 immunoglobulin-related genes.

[0040] (1) Proliferation-related genes: CCNB2, MKI67, RRM1, SPAG5, TOP2A, CKS1B, DNMT1, DTYMK, EZH2, FOXM1, MAD2L1, MCM2, MCM3, MCM6, PCLAF, PLK1, PSRC1, RFC5, SMC4, TMPO, and UBE2S;

[0041] (2) Extracellular matrix-related genes: AEBP1, COL6A3, HTRA1, MMP2, TIMP3, CLIC4, DPYSL3, EFEMP1, GJA1, LGALS1, LUM, MSN, PALLD, SERPING1, TIMP1, TNC, and VIM;

[0042] (3) Intracellular matrix-related genes: ADNP, MAPRE1, TMEM189-UBE2V1, CSE1L, EIF2S2, EIF6, NCOA6, PPP1R3D, PRPF6, PSMA7, RALY, RBM39, RNF114, RPS21, TOMM34, and ZMYND8;

[0043] (4) Immune-related genes: CCL5, CD2, CXCL13, GZMA, MNDA, BCL2A1, CCL3, CSF2RB, LCP2, PLA2G7, RASGRP1, RHOH, and TLR2;

[0044] (5) Immunoglobulin-related genes: CD79A, IGKV1-17, IGKV2-28, CD27, IGHM, IGKV4-1, JCHAIN, POU2AF1, and TNFRSF17.

[0045] In a specific aspect, the present invention provides a group of gene clusters, which include genes related to the molecular typing of colorectal cancer and survival risk assessment, namely: (1) one or more of the 21 proliferation-related genes, (2) one or more of the 17 extracellular matrix-related genes, (3) one or more of the 16 intracellular matrix-related genes, (4) one or more of the 13 immune-related genes, and (5) one or more of the 9 immunoglobulin-related genes as described above.

[0046] In one embodiment, the gene panel includes 76 genes related to molecular typing and survival risk assessment of colorectal cancer (see Table 1), which includes 21 proliferation-related genes, 17 extracellular matrix-related genes, 16 intracellular matrix-related genes, 13 immune-related genes, and 9 immunoglobulin-related genes as described above.

[0047] In another embodiment, the gene panel includes 21 genes related to molecular typing and survival risk assessment of colorectal cancer (see Table 2), which includes 5 proliferation-related genes (CCNB2, MKI67, RRM1, SPAG5, and TOP2A), 5 extracellular matrix-related genes (AEBP1, COL6A3, HTRA1, MMP2, and TIMP3), 3 intracellular matrix-related genes (ADNP, MAPRE1, and TMEM189-UBE2V1), 5 immune-related genes (CCL5, CD2, CXCL13, GZMA, and MNDA), and 3 immunoglobulin-related genes (CD79A, IGKV1-17, and IGKV2-28).

[0048] In a preferred embodiment, the gene panel may further include reference genes. Preferably, the reference genes are housekeeping genes. Housekeeping genes that can be used in the present invention include, but are not limited to, one or more of the following: GAPDH, GUSB, TFRC, MRPL19, PSMC4, and SF3A1. In one embodiment, the gene panel of the present invention may further include at least one reference gene (such as 1, 2, 3, 4, 5, or 6), preferably at least 3, and most preferably 6 of the following: GAPDH, GUSB, TFRC, MRPL19, PSMC4, and SF3A1. In a specific embodiment, the reference genes include GAPDH, GUSB, TFRC, MRPL19, PSMC4, and SF3A1. In another specific embodiment, the reference genes include GAPDH, GUSB, and TFRC.

[0049] In a preferred embodiment, the gene panel of the present invention includes 76 genes related to molecular typing and survival risk assessment as described above, and reference genes. In a specific embodiment, the reference genes include GAPDH, GUSB, TFRC, MRPL19, PSMC4, and SF3A1, and the gene panel is as shown in Table 1.

[0050] In yet another preferred embodiment, the gene panel of the present invention includes the 21 molecular typing and survival risk assessment-related genes as described above, as well as reference genes. In one embodiment, the reference genes include three of GAPDH, GUSB, MRPL19, PSMC4, SF3A1, and TFRC. In a specific embodiment, the reference genes include GAPDH, GUSB, and TFRC, and the gene panel is shown in Table 2.

[0051] Table 1

[0052]

[0053]

[0054]

[0055] Table 2

[0056]

[0057]

[0058] In a specific embodiment, the gene panel of the present invention can be used to determine the molecular typing (subtype typing) of colorectal cancer and / or evaluate the survival risk of colorectal cancer patients.

[0059] The molecular typing of colorectal cancer may include CRC1, CRC2, CRC3, CRC4, CRC5, and mixed subtypes. The survival risk may include low risk and high risk.

[0060] Those skilled in the art should understand that the gene panel of the present invention is not limited to the combinations listed above. In view of the disclosure of the present invention, those skilled in the art should be able to combine the molecular typing and survival risk assessment-related genes and reference genes of the present invention to obtain gene panels containing different combinations of genes, and these gene panels are also within the protection scope of the present invention.

[0061] Diagnostic Products of the Present Invention

[0062] In yet another aspect, the present invention relates to reagents for detecting the expression levels of genes in the gene panel of the present invention and their applications in the preparation of detection / diagnostic products. The gene panel is as described above.

[0063] The reagent or the detection / diagnosis product can be used to determine the molecular typing of colorectal cancer and / or evaluate the survival risk of colorectal cancer patients. Those skilled in the art should understand that the selection in the reagent or product can each correspond to the genes in the gene group of the present invention. As an example, when listing multiple selections, such as primers of SEQ ID NO.165 - SEQ ID NO.212 or probes of SEQ ID NO.213 - SEQ ID NO.236, it does not mean that the reagent or product of the present invention must contain all of these primers or probes, but rather means that the reagent or product will contain those primers or probes corresponding to the genes covered therein.

[0064] In a preferred embodiment, the reagent is used to detect the amount of a target nucleic acid (such as DNA, RNA transcript, or cDNA complementary to the RNA transcript of a gene in the gene group of the present invention). Preferably, it is used to detect the amount of the RNA transcript, especially mRNA, of a gene in the gene group of the present invention, or to detect the amount of cDNA complementary to the mRNA. In one embodiment, the reagent is a reagent for detecting the amount of the RNA transcript, especially mRNA, of a target gene (i.e., a gene in the gene group of the present invention). In yet another embodiment, the reagent is a reagent for detecting the amount of cDNA complementary to the mRNA.

[0065] In a preferred embodiment, the reagent is a probe or a primer or a combination thereof, which can hybridize with a partial sequence of a target nucleic acid (such as a gene in the gene group of the present invention, its RNA transcript, or cDNA complementary to the RNA transcript) to form a complex. Preferably, the probe and the primer are highly specific for the target nucleic acid. The probe and the primer can be artificially synthesized.

[0066] In one embodiment, the reagent is a primer. In one embodiment, the primer has a sequence as shown in SEQ ID NO.1 - SEQ ID NO.152 or SEQ ID NO.1 - SEQ ID NO.164 (see also Table 3). In another embodiment, the primer has a sequence as shown in SEQ ID NO.165 - SEQ ID NO.206 or SEQ ID NO.165 - SEQ ID NO.212 (see also Table 4).

[0067] In a preferred embodiment, the primer is used for next-generation sequencing, preferably for targeted sequencing. In a specific embodiment, the primer is used for targeted sequencing and has a sequence as shown in SEQ ID NO.1 - SEQ ID NO.152 or SEQ ID NO.1 - SEQ ID NO.164 (Table 3).

[0068] In another preferred embodiment, the primers are used for quantitative PCR, preferably real-time fluorescence quantitative PCR (RT-PCR), such as SYBR Green RT-PCR based on SYBR Green dye and TaqMan RT-PCR based on TaqMan technology. TaqMan RT-PCR can be, for example, multiplex RT-PCR and singleplex RT-PCR. In one embodiment, the primers are used for SYBR Green RT-PCR and have the sequences shown in SEQ ID NO.165 - SEQ ID NO.206 or SEQ ID NO.165 - SEQ ID NO.212 (see also Table 4). In another embodiment, the primers are used for TaqMan RT-PCR and have the sequences shown in SEQ ID NO.165 - SEQ ID NO.206 or SEQ ID NO.165 - SEQ ID NO.212 (Table 4). In a specific embodiment, the primers are used for singleplex or multiplex RT-PCR and have the sequences shown in SEQ ID NO.165 - SEQ ID NO.206 or SEQ ID NO.165 - SEQ ID NO.212 (Table 4).

[0069] In one embodiment, the primers are used for preparing a detection / diagnosis product, which is a next-generation sequencing kit or a real-time fluorescence quantitative PCR kit based on targeted sequencing.

[0070] In another embodiment, the reagent is a probe, including but not limited to probes for detections such as RT-PCR, in situ hybridization (ISH), DNA blotting or RNA blotting, gene chip technology, etc.

[0071] In one aspect, the probe is a probe capable of being used for in situ hybridization. Probes for in situ hybridization can be, for example, probes for dual-color silver staining in situ hybridization (DISH), DNA fluorescence in situ hybridization (DNA-FISH), RNA fluorescence in situ hybridization (RNA-FISH), chromogenic in situ hybridization (CISH), etc. The probe can carry a label, and the label can be a fluorescent group (such as Alexa Fluor dye, FITC, Texas Red, Cy3, Cy5, etc.), biotin, digoxin, etc. In another aspect, the probe is capable of being used for gene chip detection, and the probe can also carry a label, and the label can be a fluorescent group. In a specific embodiment, the probe can be used for preparing a detection / diagnosis product, which is a gene chip.

[0072] In a preferred embodiment, the probe is used for RT-PCR. In one embodiment, the probe is used for TaqMan RT-PCR. In one embodiment, the probe is a TaqMan probe. In one embodiment, the probe has a sequence as shown in SEQ ID NO.213 - SEQ ID NO.233 or SEQ ID NO.213 - SEQ ID NO.236 (see also Table 4). In a specific embodiment, the probe is a TaqMan probe having a sequence as shown in SEQ ID NO.213 - SEQ ID NO.233 or SEQ ID NO.213 - SEQ ID NO.236.

[0073] In one embodiment, the probe can be used to prepare a detection / diagnostic product, which is a real-time fluorescence quantitative PCR detection kit.

[0074] In yet another embodiment, the reagent is a combination of primers and a probe. Preferably, the probe is a TaqMan probe. In one embodiment, the combination of primers and the probe is used for RT-PCR, such as singleplex or multiplex RT-PCR. In one embodiment, the primers have a sequence as shown in SEQ ID NO.165 - SEQ ID NO.206 or SEQ ID NO.165 - SEQ ID NO.212. In one embodiment, the probe has a sequence as shown in SEQ ID NO.213 - SEQ ID NO.233 or SEQ ID NO.213 - SEQ ID NO.236. In a specific embodiment, the primers have a sequence as shown in SEQ ID NO.165 - SEQ ID NO.206, and the probe is a TaqMan probe having a sequence as shown in SEQ ID NO.213 - SEQ ID NO.233. In a specific embodiment, the primers have a sequence as shown in SEQ ID NO.165 - SEQ ID NO.212, and the probe is a TaqMan probe having a sequence as shown in SEQ ID NO.213 - SEQ ID NO.236 (see also Table 4).

[0075] In one embodiment, the probe and primers can be used to prepare a diagnostic product, which is a real-time fluorescence quantitative PCR detection kit, such as a multiplex or singleplex real-time fluorescence quantitative PCR detection kit.

[0076] In an alternative embodiment, the reagent is used to detect the amount of the polypeptide encoded by the target gene (a gene in the gene group of the present invention). Preferably, the reagent is an antibody, an antibody fragment or an affinity protein that can specifically bind to the polypeptide encoded by the target gene. More preferably, the reagent is an antibody or an antibody fragment that can specifically bind to the polypeptide encoded by the target gene. The antibody, antibody fragment or affinity protein may also be labeled with a marker for detection, such as an enzyme (e.g., horseradish peroxidase), a radioisotope, a fluorescent label (e.g., Alexa Fluor dye, FITC, TexasRed, Cy3, Cy5, etc.), a chemiluminescent substance (e.g., luminol), biotin, a quantum dot label (Qdot), etc. Thus, in a preferred embodiment, the reagent is an antibody or an antibody fragment that can specifically bind to the polypeptide encoded by the target gene, and optionally labeled with a marker for detection, the marker being selected from an enzyme, a radioisotope, a fluorescent label, a chemiluminescent substance, biotin, a quantum dot label. In one embodiment, the reagent is used to prepare a detection / diagnosis product, which is a protein chip (e.g., protein microarray), an ELISA diagnostic kit or an immunohistochemistry (IHC) kit.

[0077] Thus, on the other hand, the present invention provides a product that can be used to determine the molecular subtype of colorectal cancer and / or evaluate the survival risk of colorectal cancer patients. The product contains the reagent of the present invention. The product can be a next-generation sequencing kit based on targeted sequencing, a real-time fluorescence quantitative PCR kit, a gene chip, a protein chip, an ELISA diagnostic kit or an immunohistochemistry (IHC) kit or a combination thereof.

[0078] In one embodiment, the product is a next-generation sequencing (NGS)-based diagnostic product. In a specific embodiment, the product comprises reagents for detecting the expression levels of genes in the gene panel of the present invention. In one embodiment, the gene panel includes 82 genes, namely the 76 molecular typing and survival risk assessment-related genes as described above and 6 housekeeping genes (see also Table 1). In one embodiment, the gene panel of the present invention includes 24 genes, namely the 21 molecular typing and survival risk assessment-related genes as described above and 3 housekeeping genes, and the 3 housekeeping genes include three of GAPDH, GUSB, TFRC, MRPL19, PSMC4, and SF3A1. In yet another embodiment, the gene panel of the present invention includes 24 genes, namely the 21 molecular typing and survival risk assessment-related genes as described above and 3 housekeeping genes (see also Table 2). In a specific embodiment, the next-generation sequencing (NGS)-based diagnostic product comprises primers having the sequences shown in SEQ ID NO.1-SEQ ID NO.152 or SEQ ID NO.1-SEQ ID NO.164 (see also Table 3).

[0079] In yet another embodiment, the diagnostic product is a fluorescence quantitative PCR-based diagnostic product, preferably real-time fluorescence quantitative PCR (RT-PCR), such as SYBR Green RT-PCR and TaqMan RT-PCR. TaqMan RT-PCR can be, for example, multiplex RT-PCR and singleplex RT-PCR. In one embodiment, the diagnostic product contains reagents for detecting the expression levels of the genes in the gene panel of the present invention. In one embodiment, the gene panel includes 82 genes, namely the 76 molecular typing and survival risk assessment-related genes as described above and 6 housekeeping genes (see also Table 1). In one embodiment, the gene panel includes 24 genes, namely the 21 molecular typing and survival risk assessment-related genes as described above and 3 housekeeping genes (see also Table 2). In a specific embodiment, the fluorescence quantitative PCR-based diagnostic product contains primers having sequences as shown in SEQ ID NO.165 - SEQ ID NO.206 or SEQ ID NO.165 - SEQ ID NO.212. In another specific embodiment, the fluorescence quantitative PCR-based diagnostic product contains TaqMan probes having sequences as shown in SEQ ID NO.213 - SEQ ID NO.233 or SEQ ID NO.213 - SEQ ID NO.236. In a preferred embodiment, the fluorescence quantitative PCR-based diagnostic product contains primers having sequences as shown in SEQ ID NO.165 - SEQ ID NO.206, and TaqMan probes having sequences as shown in SEQ ID NO.213 - SEQ ID NO.233. In a preferred embodiment, the fluorescence quantitative PCR-based diagnostic product contains primers having sequences as shown in SEQ ID NO.165 - SEQ ID NO.212, and TaqMan probes having sequences as shown in SEQ ID NO.213 - SEQ ID NO.236 (see also Table 4).

[0080] In one embodiment, the product is an in vitro diagnostic product. In a specific embodiment, the product is a diagnostic kit.

[0081] In one embodiment, the product is used to determine the subtype classification of colorectal cancer and / or evaluate the survival risk of colorectal cancer patients.

[0082] In a preferred embodiment, the product further contains total RNA extraction reagents, reverse transcription reagents, next-generation sequencing reagents, and / or quantitative PCR reagents.

[0083] The total RNA extraction reagent may be a conventional total RNA extraction reagent in the art. Examples thereof include but are not limited to RNA storm CD201, Qiagen 73504, Invitrogen K156002, and ABI AM1975.

[0084] The reverse transcription reagent may be a conventional reverse transcription reagent in the art, and preferably contains a dNTP solution and / or an RNA reverse transcriptase. Examples of the reverse transcription reagent include but are not limited to NEB M0368L, Thermo K1622, and ABI4366596.

[0085] The next-generation sequencing reagent may be a reagent conventionally used in the art, as long as it can meet the requirements for performing next-generation sequencing on the obtained sequences. The next-generation sequencing reagent may be a commercially available product. Examples thereof include but are not limited to Reagent Kit v3(150cycle)(MS-102-3001), Targeted RNA Index KitA-96Indices(384Samples)(RT-402-1001). Next-generation sequencing is conventional next-generation sequencing in the art, such as targeted RNA-seq technology. Therefore, the next-generation sequencing reagent may also contain reagents customized by Illumina for constructing a library for targeted RNA-seq, such as Targeted RNA Custom Panel Kit(96Samples)(RT-102-1001).

[0086] The quantitative PCR reagent is a reagent conventionally used in the art, as long as it can meet the requirements for performing quantitative PCR on the obtained sequences. The quantitative PCR reagent may be commercially available. The quantitative PCR technology is conventional quantitative PCR technology in the art, preferably real-time fluorescence quantitative PCR technology, such as SYBR Green RT-PCR and Taqman RT-PCR technologies. The PCR reagent preferably further contains reagents for constructing a library for quantitative PCR. Preferably, the quantitative PCR reagent may further contain real-time fluorescence quantitative PCR reagents, such as reagents for SYBR Green RT-PCR (such as SYBR Green premix, such as SYBR Green PCR Master Mix) and reagents for Taqman RT-PCR (such as Taqman RT-PCRMaster Mix). Those skilled in the art can select appropriate quantitative PCR reagents according to the quantitative PCR technology used. The detection platform for quantitative PCR detection may be an ABI7500 real-time fluorescence quantitative PCR instrument or Roche A 480Ⅱ real-time fluorescence quantitative PCR instrument or any other PCR instrument capable of performing real-time fluorescence quantitative detection.

[0087] In a specific embodiment, the product is a second-generation sequencing kit based on targeted RNA-seq, which contains primers with the sequences shown in Table 3 (SEQ ID NO.1-SEQ ID NO.152 or SEQ ID NO.1-SEQ ID NO.164). Optionally, it further contains one or more selected from the following: total RNA extraction reagent, reverse transcription reagent, and second-generation sequencing reagent. Preferably, the second-generation sequencing reagent is a reagent customized by Illumina for constructing a targeted RNA-seq library.

[0088] In another specific embodiment, the product is a SYBR Green RT-PCR kit, which contains primers with the sequences shown in Table 4 (SEQ ID NO.165-SEQ ID NO.206 or SEQ ID NO.165-SEQ ID NO.212). Optionally, it further contains one or more selected from the following: total RNA extraction reagent, reverse transcription reagent, and reagent for SYBR Green RT-PCR.

[0089] In another specific embodiment, the product is a TaqMan RT-PCR detection kit, which contains primers with the sequences shown in Table 4 (SEQ ID NO.165-SEQ ID NO.206 or SEQ ID NO.165-SEQ ID NO.212) and TaqMan probes (SEQ ID NO.213-SEQ ID NO.233 or SEQ ID NO.213-SEQ ID NO.236). Optionally, it further contains one or more selected from the following: total RNA extraction reagent, reverse transcription reagent, and reagent for TaqMan RT-PCR.

[0090] The diagnostic product of the present invention (preferably in the form of a kit) also preferably contains an instrument for extracting a test sample from a subject; for example, an instrument for extracting tissue or blood from a subject, preferably any blood collection needle, syringe, etc. that can be used for blood collection. The subject is a mammal, preferably a human, especially a patient suffering from colorectal cancer.

[0091] Methods and Applications of the Present Invention

[0092] In another aspect, the present invention also relates to a method for determining the molecular subtype and / or survival risk of colorectal cancer in a subject, the method comprising

[0093] (1) providing a sample of the subject,

[0094] (2) Measure the expression levels of the genes in the gene group of the present invention in the sample.

[0095] (3) Determine the molecular subtype and / or recurrence risk of colorectal cancer in the subject.

[0096] The method of the present invention can be used for diagnostic or non-diagnostic purposes.

[0097] The subject for the method of the present invention is a mammal, preferably a human, especially a patient with colorectal cancer.

[0098] The sample used in step (1) is not particularly limited as long as the expression levels of the genes in the gene group can be obtained therefrom. For example, total RNA, total protein, etc. of the subject can be extracted from the sample, and preferably total RNA. The sample is preferably a sample of tissue, blood, plasma, body fluid or a combination thereof, preferably a tissue sample, especially a paraffin tissue sample. In a preferred embodiment, the sample is a tumor tissue sample or a tissue sample containing tumor cells. In a preferred embodiment, the sample is a tissue with a high content of tumor cells.

[0099] In step (2), the methods known in the art for measuring gene expression levels can be used. Those skilled in the art can select the type and amount of the sample in step (1) as needed and select the conventional techniques in the art to implement the measurement described in step (2). Preferably, the expression levels of the target genes (such as the genes related to the molecular subtype and survival risk assessment of the present invention) are normalized according to the expression levels of the reference genes. The methods for normalizing the expression levels of genes are well known to those skilled in the art.

[0100] In one embodiment, step (2) can be achieved by detecting the amount of the polypeptide encoded by the target gene (the gene in the gene group of the present invention). The detection can be achieved by the reagents as described above and the techniques known in the art, wherein the techniques include but are not limited to enzyme-linked immunosorbent assay (ELISA), chemiluminescence immunoassay (such as immunochemiluminescence assay, chemiluminescent enzyme immunoassay, electrochemiluminescence immunoassay), flow cytometry, immunohistochemistry (IHC).

[0101] In a preferred embodiment, step (2) can be achieved by detecting the amount of the target nucleic acid. The detection can be achieved by the reagents as described above and techniques known in the art, including but not limited to molecular hybridization techniques, quantitative PCR techniques, or nucleic acid sequencing techniques, etc. Molecular hybridization techniques include but are not limited to ISH techniques (such as DISH, DNA-FISH, RNA-FISH, CISH techniques, etc.), DNA blotting or RNA blotting techniques, gene chip techniques (such as microarray chips or microfluidic chip techniques), etc., and in situ hybridization techniques are preferred. Quantitative PCR techniques include but are not limited to semi-quantitative PCR and RT-PCR techniques, and RT-PCR techniques are preferred, such as SYBR Green RT-PCR technique, TaqMan RT-PCR technique. Nucleic acid sequencing techniques include but are not limited to Sanger sequencing, next-generation sequencing (NGS), third-generation sequencing, single-cell sequencing techniques, etc., and next-generation sequencing is preferred, and targeted RNA-seq technique is more preferred. More preferably, the detection is achieved using the reagents of the present invention.

[0102] In a preferred embodiment, in step (2), the expression levels of the genes in the gene group of the present invention are determined by next-generation sequencing technology. In one embodiment, the genes of the gene group are shown in Table 1 or Table 2. In one embodiment, the gene group includes 76 molecular typing and survival risk assessment-related genes and 6 housekeeping genes as described above, and reference can also be made to Table 1. In yet another embodiment, the gene group includes 21 molecular typing and survival risk assessment-related genes and 3 housekeeping genes as described above, and reference can also be made to Table 2.

[0103] In a specific embodiment, step (2) may include:

[0104] (2a-1) Extract total RNA from the sample;

[0105] (2a-2) Optionally purify the total RNA and convert it into cDNA, and then prepare it into a library for next-generation sequencing;

[0106] (2a-3) Sequence the library obtained in step (2a-2), and optionally standardize the expression levels of the molecular typing and survival risk assessment-related genes according to the expression levels of the housekeeping genes.

[0107] The extraction in step (2a-1) can be carried out by conventional methods in the art. Preferably, a commercially available RNA extraction kit is used to extract the total RNA from the fresh frozen tissue or paraffin-embedded tissue of the subject. In a more preferred embodiment, RNA storm CD201 or Qiagen 73504 can be used for extraction.

[0108] In a preferred embodiment, step (2a-2) may include the following steps:

[0109] (i) Reverse transcribe the extracted total RNA to generate cDNA of the gene of interest;

[0110] (ii) Prepare the obtained cDNA into a library for sequencing.

[0111] In a preferred embodiment, the primers shown in Table 3 are used in step (2a-2) to amplify the cDNA to prepare a library for sequencing.

[0112] Step (2a-3) can be completed by RNA sequencing. The sequencing method can be a conventional RNA-seq sequencing method in the art for determining gene expression levels. Preferably, second-generation sequencing is performed using an Illumina NextSeq / MiSeq / MiniSeq / iSeq series sequencer. The genes in the gene group of the present invention are amplified using the primers in the kit, and according to the differences in the libraries prepared in step (2a-2), second-generation sequencing can be performed on the obtained gene sequences. In one embodiment, second-generation sequencing is performed on the genes shown in Table 1 using the primers shown in Table 3. Preferably, second-generation sequencing is a targeted RNA-seq technology, and paired-end sequencing or single-end sequencing is performed using an Illumina NextSeq / MiSeq / MiniSeq / iSeq sequencer. Such a process can be automatically completed by the instrument itself.

[0113] In step (2), the fluorescence quantitative PCR method can also be used to measure the expression levels of the genes in the gene group of the present invention. In one embodiment, the gene group includes 21 molecular typing and survival risk assessment-related genes and 3 housekeeping genes as described above, and reference can also be made to Table 2.

[0114] In a specific embodiment, step (2) may include:

[0115] (2b-1) Extract the total RNA from the sample;

[0116] (2b-2) Reverse transcribe the total RNA described in (2-1) into cDNA;

[0117] (2b-3) Perform real-time fluorescence quantitative PCR (RT-PCR) detection on the obtained cDNA, and optionally normalize the expression levels of the molecular typing and survival risk assessment-related genes according to the expression levels of the housekeeping genes.

[0118] The extraction in step (2b-1) can be carried out by conventional methods in the art. Preferably, a commercially available RNA extraction kit is used to extract total RNA from fresh frozen tissue or paraffin-embedded tissue of a subject. In a more preferred embodiment, RNA storm CD201 or Qiagen 73504 can be used for extraction. The reverse transcription in step (2b-2) can be carried out using a commercially available reverse transcription kit. In a preferred embodiment, the RT-PCR method in step (2b-3) is TaqMan RT-PCR. Preferably, RT-PCR detection can be carried out on the genes shown in Table 2 using primer and probe pairs respectively, and the probe is a TaqMan probe. Preferably, the sequences of the primers and probes are shown in Table 4. In an embodiment, singleplex or multiplex RT-PCR detection is carried out using the primers and probes shown in Table 4.

[0119] In an alternative embodiment, the RT-PCR method in step (2b-3) is SYBR Green RT-PCR, and the genes shown in Table 2 can be detected separately or simultaneously using primers and a commercially available SYBR Green premix. Preferably, the sequences of the primers are as shown in SEQ ID NO.165 - SEQ ID NO.212 (see also Table 4).

[0120] The above RT-PCR detection can be carried out using an ABI 7500 real-time fluorescence quantitative PCR instrument (Applied Biosystems) or Roche's 480Ⅱ). After the reaction is completed, the Ct value of each gene is recorded, which represents the expression level of each gene.

[0121] In an embodiment of the present invention, step (3) can be completed by statistically analyzing the expression levels of the genes in the gene group of the present invention in the sample obtained in step (2). Optionally, colorectal cancer molecular typing and recurrence risk prediction can be carried out according to the single sample predictor (SSP) pioneered by Hu et al. (see Hu Z, et al., BMC genomics. 2006, 7:96) and the method optimized by Parker et al. (see Parker JS, et al, Journal of clinical oncology: official journal of the American Society of Clinical Oncology. 2009, 27(8):1160 - 7). The gene expression data obtained in step (2) is analyzed to obtain the subtype classification of a single sample, and the recurrence risk can be calculated.

[0122] In one embodiment, step (3) includes molecular typing of colorectal cancer, which includes determining the molecular typing of the colorectal cancer of the subject according to the expression levels of each gene in the sample of the subject obtained in step (2).

[0123] The inventors analyzed the gene expression levels of 1,091 colorectal cancers with clinical information in the Affymatrics gene chip expression profile database through the EPIG gene expression profile analysis program (see Zhou T, et al., 2006. Environ Health Perspect 114(4), 553-559; Chou JW, et al., 2007. BMC Bioinformatics 8, 427) to obtain the expression profile of the gene of the present invention. Further, according to the gene expression profile, the hierarchical clustering method was used to compare the similarities between the detected genes, group the genes; compare the similarities of the expression profiles between colorectal cancer samples, group the colorectal cancers, and divide the colorectal cancers into CRC1, CRC2, CRC3, CRC4, CRC5 and mixed subtypes; use the gene expression profiles of the colorectal cancer molecular subtypes as standard test data for molecular typing and survival risk assessment of the samples.

[0124] The molecular subtypes of colorectal cancer may include CRC1, CRC2, CRC3, CRC4, CRC5 and mixed subtypes:

[0125] The main characteristics of the CRC1 subtype are low expression of proliferation-related genes, high expression of extracellular matrix-related genes, low expression of immune-related genes, low expression of intracellular matrix-related genes, and low 10-year distant metastasis-free survival rate;

[0126] The main characteristics of the CRC2 subtype are medium expression of proliferation-related genes, low expression of extracellular matrix-related genes, high expression of immune-related genes, low expression of intracellular matrix-related genes, and the highest 10-year distant metastasis-free survival rate;

[0127] The main characteristics of the CRC3 subtype are high expression of proliferation-related genes, low expression of extracellular matrix-related genes, low expression of immune-related genes, high expression of intracellular matrix-related genes, and medium 10-year distant metastasis-free survival rate;

[0128] The main characteristics of the CRC4 subtype are low expression of proliferation-related genes, low expression of extracellular matrix-related genes, high expression of immune-related genes, low expression of intracellular matrix-related genes, and medium 10-year distant metastasis-free survival rate;

[0129] The main characteristics of the CRC5 subtype are medium expression of proliferation-related genes, high expression of extracellular matrix-related genes, low expression of immune-related genes, medium expression of intracellular matrix-related genes, and low 10-year distant metastasis-free survival rate;

[0130] The mixed subtype is colorectal cancer that does not belong to the CRC1, CRC2, CRC3, CRC4, and CRC5 subtypes.

[0131] In a specific embodiment, step (3) may include determining the molecular subtype of colorectal cancer in the subject, which includes:

[0132] (3-1) Based on the expression data of the gene group of the present invention in a statistically significant number of colorectal cancer samples (training set), establish the expression profiles of the gene group of the present invention in the CRC1, CRC2, CRC3, CRC4, and CRC5 subtypes as standard test data;

[0133] (3-2) According to the expression levels of the genes in the gene group of the present invention in the sample obtained in step (2), use the Pearson correlation analysis method to calculate the Pearson correlation coefficient between the expression profile of the gene group of the present invention in the sample and the gene expression profiles in the CRC1, CRC2, CRC3, CRC4, or CRC5 subtypes of the standard test data (i.e., the Pearson correlation coefficient between the sample and the tumors of the CRC1, CRC2, CRC3, CRC4, or CRC5 subtypes);

[0134] (3-3) When the correlation coefficient between the sample gene expression profile and the gene expression profile in the X subtype (X is selected from CRC1, CRC2, CRC3, CRC4, and CRC5) is the highest and the confidence limit is greater than or equal to 0.8, the sample can be determined to be the X subtype; when the confidence level is lower than 0.8, the sample is determined to be the mixed (Mixed) subtype.

[0135] In another embodiment, step (3) further includes determining the survival risk of the subject, which includes:

[0136] (3a) Determine the immunoglobulin index of the subject according to the expression level of the immunoglobulin-related gene;

[0137] (3b) Determine the MMR index of the subject according to the mismatch repair status; and

[0138] (3c) Calculate the survival risk of the colorectal cancer patient.

[0139] In one embodiment, step (3a) includes the following steps:

[0140] (3a-1) Based on the expression data of immunoglobulin-related genes in the gene cluster according to the present invention in a statistically significant number of colorectal cancer samples (training set), calculate the weighted average of the expression levels of immunoglobulin-related genes in the training set. Combining the survival data, perform survival analysis using statistical software known in the art (such as x-tile software, SPSS, or other analysis software capable of calculating critical values, preferably x-tile software) to obtain the weighted average that can maximize the difference in survival curves as the critical value;

[0141] (3a-2) According to the expression levels of immunoglobulin-related genes obtained in step (2), calculate the weighted average of the expression levels of immunoglobulin-related genes in the sample of the subject, that is, the immunoglobulin index of the subject. Based on the critical value described in step (3a-1), determine whether the immunoglobulin index is strong (the expression level of immunoglobulin-related genes obtained in step (2) > critical value) or weak (the expression level of immunoglobulin-related genes obtained in step (2) ≤ critical value);

[0142] (3a-3) Perform recurrence risk assessment according to the immunoglobulin index obtained in step (3a-2): If the immunoglobulin index of the subject is strong, the immune function of the subject is strong, the recurrence risk is low, and the prognosis is good; if the immunoglobulin index of the subject is weak, the immune function of the subject is weak, the recurrence risk is high, and the prognosis is poor.

[0143] The immunoglobulin index can be calculated by the following formula:

[0144]

[0145] Where n is the number of immunoglobulin-related genes used to calculate the immunoglobulin index, which is an integer from 1 to 9. In one embodiment, n = 9, and the immunoglobulin-related genes include: CD79A, IGKV1-17, IGKV2-28, CD27, IGHM, IGKV4-1, JCHAIN, POU2AF1, and TNFRSF17 (see also the relevant information in Table 1). In another embodiment, n = 3, and the immunoglobulin-related genes include: CD79A, IGKV1-17, and IGKV2-28 (see also Table 2).

[0146] After obtaining the data of the expression levels of the genes in the gene cluster of the present invention, those skilled in the art can apply the techniques known in the art to obtain the weighted average of the expression levels of each group of genes, and combine the survival data to obtain the weighted average that can maximize the difference in survival curves as the critical value.

[0147] In one embodiment, step (3b) includes the following steps:

[0148] (3b-1) Determine the mismatch repair (MMR) status of a subject sample; and

[0149] (3b-2) Determine the MMR index of the subject based on the MMR status, where the MMR index can be assigned by the following formula:

[0150] When the MMR status is proficient mismatch repair (pMMR), MMR index = 1;

[0151] When the MMR status is deficient mismatch repair (dMMR), MMR index = -1.

[0152] As used herein, "mismatch repair (MMR)" refers to the process of correcting nucleotide mismatches caused by DNA replication errors, recombination, and certain types of base modifications. MMR proteins (such as MLH1, PMS2, MSH2, and MSH6, etc.) perform the function of recognizing and repairing mismatches. Generally speaking, the MMR status can include deficient mismatch repair (dMMR) and proficient mismatch repair (pMMR).

[0153] As used herein, "microsatellite instability (MSI)" refers to any change in the length of a microsatellite due to the insertion or deletion of repeat units compared to a normal microsatellite (MS). It is generally believed that MSI is caused by deficient mismatch repair.

[0154] The method for determining the MMR status can be carried out using methods known in the art, and can include, for example: by detecting the expression of MMR proteins (such as by immunohistochemistry) and by detecting microsatellite locus instability (such as by PCR). In some embodiments, the MMR proteins include MLH1, PMS2, MSH2, and MSH6. In some embodiments, the microsatellite loci include BAT25, BAT26, D5S346, D2S123, and D17S250. In some embodiments, step (3b-1) is achieved by detecting the expression of MLH1, PMS2, MSH2, and MSH6 using immunohistochemistry and / or detecting BAT25, BAT26, D5S346, D2S123, and D17S250 using PCR.

[0155] Methods for determining the MMR status of a sample can refer to, for example, the Bethesda guideline criteria (J Natl Cancer Inst. 2004 Feb 18; 96(4): 261–268.). For example, immunohistochemistry can be used to detect the expression of MLH1, PMS2, MSH2, and MSH6 in the sample. When: the expression of any one of the proteins is completely absent, the MMR status of the sample is determined to be MMR-deficient (dMMR); when there is no absence of MMR protein expression, the MMR status of the sample is determined to be MMR-proficient (pMMR). Alternatively, PCR methods can be used to detect microsatellite loci BAT25, BAT26, D5S346, D2S123, and D17S250 and compare them with normal MS. When: at least 2 loci (e.g., 2, 3, 4, or 5 loci) (i.e., more than 40%) show instability, the MSI of the sample is determined to be high-frequency microsatellite instability (MSI-H), and the MMR status is dMMR; when 1 locus shows instability, the MSI of the sample is determined to be low-frequency microsatellite instability (MSI-L), and the MMR status is pMMR; when no instability is detected, the MSI of the sample is determined to be microsatellite stable (MSS), and the MMR status is pMMR.

[0156] In one embodiment, step (3) further includes (3c) calculating the survival risk of colorectal cancer patients, which includes the following steps:

[0157] (3c-1) Using the Cox model, with the occurrence or non-occurrence of disease progression or death and the time of occurrence as the observation endpoints, determine the corresponding coefficients according to the Pearson correlation coefficient between the sample obtained in step (3-2) and tumors of CRC1, CRC2, CRC3, CRC4, or CRC5 subtypes, the immunoglobulin index obtained in step (3a-2), and the relative risk of the MMR index obtained in step (3b-2) affecting survival, and calculate the recurrence risk score (Risk of Recurrence, ROR) of the subject;

[0158] (3c-2) According to the recurrence risk score (also known as the recurrence risk index) calculated in step (3c-1), determine the survival risk of the subject: low risk (recurrence risk score of 0-65) and high risk (recurrence risk score of 66-100).

[0159] In a specific embodiment, 82 colorectal cancer molecular typing and survival risk-related genes (see also Table 1) are used in step (3c-1) to calculate the recurrence risk score of the subject.

[0160] ROR = (0.18 * CRC1) + (-0.09 * CRC2) + (-0.09 * CRC3) + (0.07 * CRC4) + (0.27 * CRC5) + (-0.15 * Immunoglobulin Index) + (0.32 * MMR Index); where,

[0161] "CRC1" represents the Pearson correlation coefficient between this tumor and tumors of the CRC1 subtype; "CRC2" represents the Pearson correlation coefficient between this tumor and tumors of the CRC2 subtype; "CRC3" represents the Pearson correlation coefficient between this tumor and tumors of the CRC3 subtype; "CRC4" represents the Pearson correlation coefficient between this tumor and tumors of the CRC4 subtype; "CRC5" represents the Pearson correlation coefficient between this tumor and tumors of the CRC5 subtype; the "Immunoglobulin Index" is the immunoglobulin index calculated from 9 immunoglobulin-related genes in Table 1; the "MMR Index" is the MMR index determined based on the mismatch repair status, and the method for determining the MMR index is as described above.

[0162] In another specific embodiment, in step (3c-1), a recurrence risk score is calculated using 21 colorectal cancer molecular typing and survival risk-related genes (see also Table 2).

[0163] ROR = (0.10 * CRC1) + (-0.16 * CRC2) + (-0.14 * CRC3) + (0.21 * CRC4) + (0.10 * CRC5) + (-0.24 * Immunoglobulin Index) + (0.27 * MMR Index); where,

[0164] "CRC1", "CRC2", "CRC3", "CRC4", "CRC5" and "MMR Index" are defined as above; the "Immunoglobulin Index" is the immunoglobulin index calculated from 3 immunoglobulin-related genes in Table 2.

[0165] Accordingly, the present invention also provides the use of the gene group of the present invention or a reagent for detecting the expression level of genes in the gene group of the present invention in molecular typing of colorectal cancer and / or evaluating the survival risk of colorectal cancer patients. The present invention also provides the use of the gene group of the present invention and a reagent for detecting the expression level of genes in the gene group of the present invention in the preparation of a product for molecular typing of colorectal cancer and / or evaluating the survival risk of colorectal cancer patients. In a preferred embodiment, the product is a detection / diagnostic kit. In one embodiment, the product is an in vitro diagnostic product. The reagent is as described above. The product is as described above. According to the method or application of the present invention, colorectal cancer can be classified into different molecular subtypes, and the molecular subtypes of colorectal cancer may include CRC1, CRC2, CRC3, CRC4, CRC5 and a mixed subtype. According to the method or application of the present invention, the survival risk of colorectal cancer patients can be evaluated, and the survival risk may include low risk and high risk.

[0166] On the other hand, the present invention also relates to a group of immunoglobulin-related genes, including: CD79A, IGKV1-17, IGKV2-28, CD27, IGHM, IGKV4-1, JCHAIN, POU2AF1 and TNFRSF17 (see also the relevant information in Table 1).

[0167] The present invention also relates to detecting the expression level of the above-mentioned immunoglobulin-related genes and calculating an immunoglobulin index; wherein, the immunoglobulin index can be used to evaluate the immune status of colorectal cancer patients and guide the cellular immunotherapy of colorectal cancer. Therefore, the present invention also relates to the use of the immunoglobulin-related genes or a reagent for detecting their expression level in evaluating the survival risk of colorectal cancer patients.

[0168] Embodiments of the present invention can also be enumerated as follows.

[0169] 1. A group of gene groups for determining the molecular typing of colorectal cancer and / or evaluating the survival risk of colorectal cancer patients, including genes related to molecular typing and survival risk assessment, wherein the genes related to molecular typing and survival risk assessment include:

[0170] (1) One or more of the following proliferation-related genes: CCNB2, MKI67, RRM1, SPAG5, TOP2A, CKS1B, DNMT1, DTYMK, EZH2, FOXM1, MAD2L1, MCM2, MCM3, MCM6, PCLAF, PLK1, PSRC1, RFC5, SMC4, TMPO and UBE2S;

[0171] (2) One or more of the following extracellular matrix-related genes: AEBP1, COL6A3, HTRA1, MMP2, TIMP3, CLIC4, DPYSL3, EFEMP1, GJA1, LGALS1, LUM, MSN, PALLD, SERPING1, TIMP1, TNC, and VIM;

[0172] (3) One or more of the following intracellular matrix-related genes: ADNP, MAPRE1, TMEM189-UBE2V1, CSE1L, EIF2S2, EIF6, NCOA6, PPP1R3D, PRPF6, PSMA7, RALY, RBM39, RNF114, RPS21, TOMM34, and ZMYND8;

[0173] (4) One or more of the following immune-related genes: CCL5, CD2, CXCL13, GZMA, MNDA, BCL2A1, CCL3, CSF2RB, LCP2, PLA2G7, RASGRP1, RHOH, and TLR2; and

[0174] (5) One or more of the following immunoglobulin-related genes: CD79A, IGKV1-17, IGKV2-28, CD27, IGHM, IGKV4-1, JCHAIN, POU2AF1, and TNFRSF17.

[0175] 2. The gene group according to item 1, which includes 21 molecular typing and survival risk assessment-related genes, and the molecular typing and survival risk assessment-related genes include:

[0176] (1) Proliferation-related genes: CCNB2, MKI67, RRM1, SPAG5, and TOP2A;

[0177] (2) Extracellular matrix-related genes: AEBP1, COL6A3, HTRA1, MMP2, and TIMP3;

[0178] (3) Intracellular matrix-related genes: ADNP, MAPRE1, and TMEM189-UBE2V1;

[0179] (4) Immune-related genes: CCL5, CD2, CXCL13, GZMA, and MNDA; and

[0180] (5) Immunoglobulin-related genes: CD79A, IGKV1-17, and IGKV2-28.

[0181] 3. The gene group according to item 1, which includes 76 molecular typing and survival risk assessment-related genes, and the molecular typing and survival risk assessment-related genes include:

[0182] (1) Proliferation-related genes: CCNB2, MKI67, RRM1, SPAG5, TOP2A, CKS1B, DNMT1, DTYMK, EZH2, FOXM1, MAD2L1, MCM2, MCM3, MCM6, PCLAF, PLK1, PSRC1, RFC5, SMC4, TMPO, and UBE2S;

[0183] (2) Extracellular matrix-related genes: AEBP1, COL6A3, HTRA1, MMP2, TIMP3, CLIC4, DPYSL3, EFEMP1, GJA1, LGALS1, LUM, MSN, PALLD, SERPING1, TIMP1, TNC, and VIM;

[0184] (3) Intracellular matrix-related genes: ADNP, MAPRE1, TMEM189-UBE2V1, CSE1L, EIF2S2, EIF6, NCOA6, PPP1R3D, PRPF6, PSMA7, RALY, RBM39, RNF114, RPS21, TOMM34, and ZMYND8;

[0185] (4) Immunity-related genes: CCL5, CD2, CXCL13, GZMA, MNDA, BCL2A1, CCL3, CSF2RB, LCP2, PLA2G7, RASGRP1, RHOH, and TLR2; and

[0186] (5) Immunoglobulin-related genes: CD79A, IGKV1-17, IGKV2-28, CD27, IGHM, IGKV4-1, JCHAIN, POU2AF1, and TNFRSF17.

[0187] 4. The gene group according to any one of items 1-3, which further includes a reference gene;

[0188] Preferably, the reference gene includes 1, more preferably 3, and most preferably 6 of the following: GAPDH, GUSB, TFRC, MRPL19, PSMC4, and SF3A1.

[0189] 5. The gene group according to item 2, which further includes a reference gene; preferably, the reference gene includes three of GAPDH, GUSB, TFRC, MRPL19, PSMC4, and SF3A1; more preferably, the reference gene includes GAPDH, GUSB, and TFRC.

[0190] 6. The gene group described in item 3 further includes a reference gene; preferably, the reference gene includes GAPDH, GUSB, TFRC, MRPL19, PSMC4, and SF3A1.

[0191] 7. A reagent for detecting the expression level of the genes in the gene group described in any one of items 1-6.

[0192] 8. The reagent described in item 7, which is a reagent for detecting the amount of RNA transcribed from the gene, especially mRNA; or, it is a reagent for detecting the amount of cDNA complementary to mRNA.

[0193] 9. The reagent described in item 7 or 8, which is a primer, a probe, or a combination thereof.

[0194] 10. The reagent described in item 9, which is a primer;

[0195] Preferably, the primer has the sequences shown in SEQ ID NO.1-SEQ ID NO.164, or has the sequences shown in SEQ ID NO.165-SEQ ID NO.212.

[0196] 11. The reagent described in item 9, which is a probe;

[0197] Preferably, the probe is a TaqMan probe;

[0198] More preferably, the probe has the sequences shown in SEQ ID NO.213-SEQ ID NO.236;

[0199] Most preferably, the probe is a TaqMan probe having the sequences shown in SEQ ID NO.213-SEQ ID NO.236.

[0200] 12. The reagent described in item 9, which is a combination of a primer and a probe,

[0201] Preferably, the primer has the sequences shown in SEQ ID NO.165-SEQ ID NO.212, and the probe is a TaqMan probe having the sequences shown in SEQ ID NO.213-SEQ ID NO.236.

[0202] 13. The reagent described in item 7, which is a reagent for detecting the amount of the polypeptide encoded by the gene, preferably, the reagent is an antibody, an antibody fragment, or an affinity protein.

[0203] 14. A product for molecular typing and / or survival risk assessment of colorectal cancer, which contains the reagent described in any one of items 7-13.

[0204] 15. Use of the gene group according to any one of Items 1-6, the reagent according to any one of Items 7-13, or the product according to Item 14 in determining the molecular subtype of colorectal cancer and / or evaluating the survival risk of colorectal cancer patients.

[0205] 16. Use of the gene group according to any one of Items 1-6 or the reagent according to any one of Items 7-13 in preparing a product for determining the molecular subtype of colorectal cancer and / or evaluating the survival risk of colorectal cancer patients.

[0206] 17. The product according to Item 14 or the use according to Item 16, wherein the product is in the form of an in vitro diagnostic product, preferably in the form of a diagnostic kit.

[0207] 18. The product according to Item 14 or the use according to Item 16, wherein the product is a next-generation sequencing kit, a real-time fluorescence quantitative PCR detection kit, a gene chip, a protein chip, an ELISA diagnostic kit, or an immunohistochemistry (IHC) kit, or a combination thereof.

[0208] 19. The product or use according to Item 18, wherein the product is a next-generation sequencing kit, which contains primers having the sequences shown in SEQ ID NO.1-SEQ ID NO.164, and optionally contains one or more selected from the following: total RNA extraction reagent, reverse transcription reagent, and next-generation sequencing reagent.

[0209] 20. The product or use according to Item 18, wherein the product is a real-time fluorescence quantitative PCR detection kit, which contains primers having the sequences shown in SEQ ID NO.165-SEQ ID NO.212.

[0210] 21. The product or use according to Item 20, wherein the real-time fluorescence quantitative PCR detection kit further contains TaqMan probes, and optionally contains one or more selected from the following: total RNA extraction reagent, reverse transcription reagent, and reagents for TaqMan RT-PCR.

[0211] 22. The product or use according to Item 21, wherein the real-time fluorescence quantitative PCR detection kit contains primers having the sequences shown in SEQ ID NO.165-SEQ ID NO.212 and TaqMan probes having the sequences shown in SEQ ID NO.213-SEQ ID NO.236.

[0212] 23. The product or application according to item 20, wherein the real-time fluorescence quantitative PCR detection kit further comprises one or more selected from the following: total RNA extraction reagent, reverse transcription reagent, and reagent for SYBR Green RT-PCR.

[0213] 24. The gene group according to any one of items 1-6, the reagent according to any one of items 7-13, the product according to any one of items 14 and 17-23, the application according to any one of items 15-23, characterized in that

[0214] the colorectal cancer includes CRC type 1, CRC type 2, CRC type 3, CRC type 4, CRC type 5, and the mixed type.

[0215] Beneficial Effects

[0216] The present invention relates to a gene group for performing molecular typing and / or survival risk assessment of colorectal cancer, a reagent for detecting the expression level of genes in the gene group, and a method and product for performing molecular typing and / or survival risk assessment of colorectal cancer.

[0217] According to the expression level of genes in the gene group of the present invention in colorectal cancer samples, a system for molecular typing of colorectal cancer can be established, which can classify colorectal cancer into different subtypes and provide more targeted individualized treatment for colorectal cancer patients belonging to different subtypes. On the other hand, according to the method and application of the present invention, the recurrence risk of colorectal cancer patients can be well predicted and the immune status of tumors can be effectively evaluated, which has important guiding significance for clinical treatment. Combining the subtype, immunoglobulin index, MMR index, and risk score can make a judgment on the prognosis of colorectal cancer patients. Performing molecular typing and risk assessment of colorectal cancer patients can screen out the advantageous population of different treatment regimens and provide potential treatment approaches. For patients with low recurrence risk, radiotherapy and chemotherapy may not be considered, reducing the occurrence of adverse reactions and the economic burden of treatment; for patients with high recurrence risk, chemotherapy, radiotherapy, or biological treatment should be promptly supplemented in order to achieve the maximum clinical benefit. For advanced patients who are unable to undergo surgery, molecular diagnosis based on the expression profile can help identify the population that can benefit from a treatment regimen, improve the treatment efficiency, and avoid ineffective treatment.

[0218] Compared with the current methods for molecular typing of colorectal cancer, the advantages of the present invention are that it not only subtypes colorectal cancer, but also evaluates the immunoglobulin index and recurrence risk of tumor patients, comprehensively evaluates the prognosis of colorectal cancer patients and the possible benefits of treatment. Another advantage of the present invention is that it provides multiple alternative genes or gene combinations as supplementary implementation schemes. When the present invention is applied to cancer patients, if the detection of the expression level of a certain gene or certain genes is invalid or fails due to the patient's pathological condition or other reasons (such as abnormal expression of one or some genes), multiple alternative schemes can be used for supplementation, making the detection results based on the present invention more stable and reliable.

[0219] Examples

[0220] The present invention will be further illustrated by the following examples, but the present invention is not limited to the scope of the described examples. For the experimental methods without specific conditions noted in the following examples, they are carried out according to conventional methods and conditions, or selected according to the product instructions. The reagents and instruments used in the examples herein are all commercially available.

[0221] Example 1: Screening of gene groups related to subtype classification of colorectal cancer and survival risk

[0222] Method: Analyze the gene expression levels of 1091 colorectal cancer cases with clinical information in the Affymatrics gene chip expression profile database through the EPIG gene expression profile analysis program (see Zhou, Chou et al, 2006. Environ Health Perspect 114(4), 553 - 559; Chou, Zhou et al, 2007. BMC Bioinformatics 8, 427), screen out proliferation-related genes, extracellular matrix-related genes, intracellular matrix-related genes, immune-related genes, and immunoglobulin-related genes that are closely related to the recurrence risk of colorectal cancer, and calculate and optimize the genes with a large contribution rate to typing and recurrence risk in each group of genes.

[0223] Result: A total of 76 genes and 6 housekeeping genes related to subtype classification of colorectal cancer and survival risk were screened, that is, a test combination of 82 genes. The gene list is shown in Table 1.

[0224] Verify the effectiveness and stability of the 82 screened genes in the data of the TCGA database of 419 colorectal cancer cases. Colorectal cancer can be divided into CRC1, CRC2, CRC3, CRC4, CRC5 or mixed subtypes:

[0225] The main characteristics of the CRC1 subtype are low expression of proliferation-related genes, high expression of extracellular matrix-related genes, low expression of immune-related genes, low expression of intracellular matrix-related genes, and low 10-year distant metastasis-free survival rate;

[0226] The main characteristics of the CRC2 subtype are moderate expression of proliferation-related genes, low expression of extracellular matrix-related genes, high expression of immune-related genes, low expression of intracellular matrix-related genes, and the highest 10-year distant metastasis-free survival rate;

[0227] The main characteristics of the CRC3 subtype are high expression of proliferation-related genes, low expression of extracellular matrix-related genes, low expression of immune-related genes, high expression of intracellular matrix-related genes, and moderate 10-year distant metastasis-free survival rate;

[0228] The main characteristics of the CRC4 subtype are low expression of proliferation-related genes, low expression of extracellular matrix-related genes, high expression of immune-related genes, low expression of intracellular matrix-related genes, and moderate 10-year distant metastasis-free survival rate;

[0229] The main characteristics of the CRC5 subtype are moderate expression of proliferation-related genes, high expression of extracellular matrix-related genes, low expression of immune-related genes, moderate expression of intracellular matrix-related genes, and low 10-year distant metastasis-free survival rate;

[0230] The mixed subtype is colorectal cancer that does not belong to the CRC1, CRC2, CRC3, CRC4, and CRC5 subtypes.

[0231] Example 2: Gene test panel for molecular typing and survival risk assessment of colorectal cancer

[0232] The test panel of 82 genes screened according to Example 1 is used for molecular typing and survival risk assessment of colorectal cancer.

[0233] 82-gene test panel:

[0234] Experimental method: An 82-gene test panel was used (see Table 1), including 76 genes related to molecular classification and survival risk of colorectal cancer (proliferation-related genes: CCNB2, MKI67, RRM1, SPAG5, TOP2A, CKS1B, DNMT1, DTYMK, EZH2, FOXM1, MAD2L1, MCM2, MCM3, MCM6, PCLAF, PLK1, PSRC1, RFC5, SMC4, TMPO, and UBE2S; extracellular matrix-related genes: AEBP1, COL6A3, HTRA1, MMP2, TIMP3, CLIC4, DPYSL3, EFEMP1, GJA1, LGALS1, LUM, MSN, PALLD, SERPING1, TIMP1, TNC, and VIM; intracellular matrix-related genes: ADNP, MAPRE1, TMEM189-UBE2V1, CSE1L, EIF2S2, EIF6, NCOA6, PPP1R3D, PRPF6, PSMA7, RALY, RBM39, RNF114, RPS21, TOMM34, and ZMYND8; immune-related genes: CCL5, CD2, CXCL13, GZMA, MNDA, BCL2A1, CCL3, CSF2RB, LCP2, PLA2G7, RASGRP1, RHOH, and TLR2; immunoglobulin-related genes: CD79A, IGKV1-17, IGKV2-28, CD27, IGHM, IGKV4-1, JCHAIN, POU2AF1, and TNFRSF17) to determine the molecular classification of colorectal cancer and evaluate the survival risk of colorectal cancer patients. Six reference genes (including GAPDH, GUSB, TFRC, MRPL19, PSMC4, and SF3A1) were used as internal standards to normalize the expression levels of genes related to molecular classification and survival risk. The 76 genes related to molecular classification and survival risk of colorectal cancer in Table 1 were used to calculate the recurrence risk index.

[0235] Experimental results:

[0236] Based on the standard test data obtained in Example 1, using the colorectal cancer molecular classification method as described above (see steps (3-1) to (3-3) in the "Methods and Applications of the Present Invention" section), the expression levels of the 76 genes related to molecular classification and survival risk of colorectal cancer shown in Table 1 (normalized by the expression levels of GAPDH, GUSB, TFRC, MRPL19, PSMC4, and SF3A1) were used to classify 1091 colorectal cancer cases molecularly, and the colorectal cancer tumors were divided into CRC1, CRC2, CRC3, CRC4, CRC5, or mixed subtypes.

[0237] By calculating the number and time of survival of different subtypes, taking the occurrence of distant metastasis of tumors observed within 10 years in colorectal cancer cases as the observation event, the Kaplan-Meier survival curve can be plotted to obtain the 10-year distant metastasis-free survival rate, indicating the recurrence risk of each subtype. The recurrence risks of each subtype are different, indicating that the recurrence risk of each subtype of colorectal cancer is different.

[0238] The main characteristics of the CRC1 subtype are low expression of proliferation-related genes, high expression of extracellular matrix-related genes, low expression of immune-related genes, and low expression of intracellular matrix-related genes, with a low 10-year distant metastasis-free survival rate;

[0239] The main characteristics of the CRC2 subtype are moderate expression of proliferation-related genes, low expression of extracellular matrix-related genes, high expression of immune-related genes, and low expression of intracellular matrix-related genes, with the highest 10-year distant metastasis-free survival rate;

[0240] The main characteristics of the CRC3 subtype are high expression of proliferation-related genes, low expression of extracellular matrix-related genes, low expression of immune-related genes, and high expression of intracellular matrix-related genes, with a moderate 10-year distant metastasis-free survival rate;

[0241] The main characteristics of the CRC4 subtype are low expression of proliferation-related genes, low expression of extracellular matrix-related genes, high expression of immune-related genes, and low expression of intracellular matrix-related genes, with a moderate 10-year distant metastasis-free survival rate;

[0242] The main characteristics of the CRC5 subtype are moderate expression of proliferation-related genes, high expression of extracellular matrix-related genes, low expression of immune-related genes, and moderate expression of intracellular matrix-related genes, with a low 10-year distant metastasis-free survival rate;

[0243] The mixed subtype is colorectal cancer that does not belong to the CRC1, CRC2, CRC3, CRC4, and CRC5 subtypes.

[0244] 2. Immunoglobulin index

[0245] Based on the standard test data obtained in Example 1, using the immunoglobulin index calculation method as described above (see steps (3a-1) to (3a-3) in the "Methods and Applications of the Present Invention" section), the immunoglobulin index was calculated according to the expression levels of 9 immunoglobulin-related genes, namely CD79A, IGKV1-17, IGKV2-28, CD27, IGHM, IGKV4-1, JCHAIN, POU2AF1, and TNFRSF17. Each subtype could be further divided into two groups according to the immunoglobulin index, namely the strong immunoglobulin index group and the weak immunoglobulin index group, and the survival differences between the two groups were observed. The results showed that the immunoglobulin index could indicate the prognosis of colorectal cancer. The 10-year distant metastasis-free survival rate of the case group with a strong immunoglobulin index was relatively high, and the prognosis was relatively good.

[0246]

[0247] 3. MMR Index

[0248] Using the MMR index determination method as described above (see steps (3b-1) to (3b-3) in the "Methods and Applications of the Present Invention" section), immunohistochemistry was used to detect the expression of MMR proteins MLH1, PMS2, MSH2, and MSH6 and / or PCR was used to detect microsatellite loci BAT25, BAT26, D5S346, D2S123, and D17S250 to determine the MMR status and judge the MMR index.

[0249] 4. Recurrence Risk Assessment

[0250] The Cox model was used to calculate the tumor recurrence risk. With the occurrence of distant metastasis of the tumor as the observation endpoint, the corresponding coefficients were determined according to the Pearson correlation coefficient between the tumor and each subtype, the immunoglobulin number, and the relative risk of the MMR index affecting survival, and the recurrence risk score was calculated. The calculation method was as follows:

[0251] Calculation of the recurrence risk score (Risk of Recurrence, ROR): The range of ROR is 0-100, where: 0-65, low risk; 66-100, high risk;

[0252] ROR = (0.18 * CRC1) + (-0.09 * CRC2) + (-0.09 * CRC3) + (0.07 * CRC4) + (0.27 * CRC5) + (-0.15 * immunoglobulin index) + (0.32 * MMR index); where,

[0253] "CRC1" represents the Pearson correlation coefficient between this tumor and tumors of the CRC1 subtype; "CRC2" represents the Pearson correlation coefficient between this tumor and tumors of the CRC2 subtype; "CRC3" represents the Pearson correlation coefficient between this tumor and tumors of the CRC3 subtype; "CRC4" represents the Pearson correlation coefficient between this tumor and tumors of the CRC4 subtype; "CRC5" represents the Pearson correlation coefficient between this tumor and tumors of the CRC5 subtype; the "immunoglobulin index" is the immunoglobulin index calculated from 9 immunoglobulin-related genes in Table 1; the "MMR index" is the MMR index determined according to the mismatch repair status: when the MMR status is pMMR, the MMR index = 1; when the MMR status is dMMR, the MMR index = -1.

[0254] Based on the calculated recurrence risk score, the tumor recurrence risk can be divided into two groups, low risk (0 - 65) and high risk (66 - 100). The results show that the recurrence risk index can indicate the survival risk of colorectal cancer patients: the 10-year distant metastasis-free survival rate of the low-risk group is higher, and the 10-year distant metastasis-free survival rate of the high-risk group is lower.

[0255] 24-gene test panel:

[0256] The method for molecular typing of colorectal cancer, the calculation method of the immunoglobulin index, the MMR index, and the survival risk score of the 24-gene test panel are similar to those of the 82-gene test panel. The 24-gene test panel (see Table 2) includes: 21 gene groups related to molecular typing and survival risk of colorectal cancer (proliferation-related genes: CCNB2, MKI67, RRM1, SPAG5, and TOP2A; extracellular matrix-related genes: AEBP1, COL6A3, HTRA1, MMP2, and TIMP3; intracellular matrix-related genes: ADNP, MAPRE1, and TMEM189-UBE2V1; immune-related genes: CCL5, CD2, CXCL13, GZMA, and MNDA; immunoglobulin-related genes: CD79A, IGKV1-17, and IGKV2-28), which are used to determine the molecular typing of colorectal cancer and evaluate the survival risk of colorectal cancer patients; and 3 reference genes (including GAPDH, GUSB, and TFRC) as internal standards, which are used to standardize the expression levels of genes related to molecular typing and survival risk. When calculating the recurrence risk index, 21 genes related to molecular typing and survival risk of colorectal cancer in Table 2 are used.

[0257] Experimental results:

[0258] 1. Molecular typing of colorectal cancer

[0259] Using the expression levels of 21 colorectal cancer molecular subtypes and survival risk-related genes shown in Table 2 (normalized by the expression levels of GAPDH, GUSB, and TFRC), 1091 colorectal cancer cases were molecularly typed, and colorectal cancer tumors were classified into CRC1, CRC2, CRC3, CRC4, CRC5, or mixed subtypes ( Figure 1 , 2 ). The results were similar to those of the 82-gene test panel.

[0260] 2. Immunoglobulin index

[0261] The immunoglobulin index was calculated based on the expression levels of three immunoglobulin-related genes, CD79A, IGKV1-17, and IGKV2-28. Each subtype could be further divided into two groups, the strong immunoglobulin index group and the weak immunoglobulin index group, according to the immunoglobulin index, and the survival differences between the two groups were observed ( Figure 3 ). The results were similar to those of the 82-gene test panel.

[0262]

[0263] 3. MMR index

[0264] The previously described MMR index determination method was used (see steps (3b-1) to (3b-3) in the "Methods and Applications of the Present Invention" section). Immunohistochemistry was used to detect the expression of MMR proteins MLH1, PMS2, MSH2, and MSH6 and / or PCR was used to detect microsatellite loci BAT25, BAT26, D5S346, D2S123, and D17S250 to determine the MMR status and the MMR index.

[0265] 4. Recurrence risk assessment

[0266] The Cox model was used to calculate the tumor recurrence risk. With distant metastasis of the tumor as the observation endpoint, the corresponding coefficients were determined according to the relative risk of the tumor subtype, immunoglobulin index, and MMR index on survival, and the recurrence risk score was calculated. The calculation method was as follows:

[0267] ROR = (0.10 * CRC1) + (-0.16 * CRC2) + (-0.14 * CRC3) + (0.21 * CRC4) + (0.10 * CRC5) + (-0.24 * immunoglobulin index) + (0.27 * MMR index); where

[0268] "CRC1", "CRC2", "CRC3", "CRC4", "CRC5", and "MMR index" are defined as above; "immunoglobulin index" is the immunoglobulin index calculated from the three immunoglobulin-related genes in Table 2.

[0269] Based on the calculated recurrence risk score, the tumor recurrence risk can be divided into two groups, low risk (0 - 65) and high risk (66 - 100). Figure 4 ) The results are similar to those of the 82 - gene test panel.

[0270] Example 3: Next - generation sequencing detection kit for determining the molecular subtypes of colorectal cancer and assessing the survival risk of colorectal cancer patients

[0271] According to the 82 - gene test panel in Example 2, a next - generation sequencing detection kit was designed, which contains primers for specifically amplifying the cDNA of the 82 genes. The primer sequences are shown in Table 3. The method for using the next - generation sequencing detection kit to determine the molecular subtypes of colorectal cancer and assess the survival risk of colorectal cancer patients is described as follows.

[0272] Step 1: Take the tumor or paraffin - embedded tissue of the test subject, and use the method in the detection kit to obtain the area with a high content of tumor cells in the test subject as the original material.

[0273] Step 2: Extract total RNA from the tissue. RNA storm CD201RNA or Qiagen RNeaseFFPE kit RNA extraction kit can be used for extraction.

[0274] Step 3: Prepare a library for sequencing from the obtained RNA. Prepare a library for next - generation sequencing by targeted RNA - seq technology from the RNA of the obtained tissue. The library preparation method includes the following steps:

[0275] (3 - 1): Use Reverse Transcriptase II (New England Biolabs, #M0368L) to reverse - transcribe the RNA extracted in step (2) into cDNA.

[0276] (3 - 2): Use Illumina's The Targeted RNA library construction kit (#15034457) processes the obtained cDNA into a library for sequencing. The specific steps are as follows: (i) Hybridization: Add 4.5 μl of TOP (see Table 3 for specific composition), mix well, then add 21 μl of OB1, heat to 70 °C and slowly cool down to 30 °C in a gradient; (ii) Extension and ligation: After adsorbing the product in (i) with a magnetic stand and discarding the supernatant, wash twice with AM1 and UB1 in the kit and then discard the supernatant, add 36 μl of ELM4, and incubate at 37 °C for 45 minutes in a PCR instrument or a metal bath; (iii) Ligate sequencing tags (Index) to the product obtained in (ii), and then perform PCR: After adsorbing the product obtained in (ii) with a magnetic stand and discarding the supernatant, add 18 μl of HP3 diluted 40 times, adsorb with a magnetic stand and aspirate 16 μl, add 17.3 μl of TDP1, 0.3 μl of PMM2, and 6.4 μl of Index, mix well and perform 32 cycles of PCR amplification; (iv) Purify the DNA using a Gnome DNA (QuestGenomics, Nanjing) purification kit to obtain the library.

[0277] Step 4: Perform next-generation sequencing on the obtained DNA library using NextSeq / MiSeq / MiniSeq / iSeq. Perform paired-end sequencing or single-end sequencing using an Illumina NextSeq / MiSeq / MiniSeq / iSeq sequencer. This process is automatically completed by the instrument itself (Illumina).

[0278] Step 5: Statistical analysis of results. Perform statistical analysis on the obtained sequencing results. Then use the method described in Example 2 to perform molecular typing of the colorectal cancer of the subject, calculate the immunoglobulin index and the recurrence risk score, and predict the survival risk of the subject.

[0279] Table 3

[0280]

[0281]

[0282]

[0283]

[0284] Example 4: Quantitative PCR detection kit for determining the molecular typing of colorectal cancer and evaluating the survival risk of colorectal cancer patients

[0285] According to the 24-gene test panel in Example 2, a quantitative PCR detection kit was designed, which contains primers for PCR amplification of the 24 genes and TaqMan probes for quantification of the amplification products. The sequences of the primers and probes are shown in Table 4. The kit can be used for single or multiplex RT-PCR detection. The method for colorectal cancer molecular typing and recurrence risk assessment by single RT-PCR detection using the kit is described as follows.

[0286] Experimental method: Colorectal cancer tumor tissues were taken, and RNA in tumor cells was extracted. Using TaqMan RT-PCR technology and the primers and probes shown in Table 4, the expression levels of the genes were detected respectively. The steps are as follows:

[0287] Step 1: Take the tumor or paraffin-embedded tissue of the detection object, and use the method in the detection kit to obtain the area with high tumor cells in the detection object as the original material.

[0288] Step 2: Extract total RNA from the tissue. RNAstorm CD201RNA or Qiagen RNease FFPEkit RNA extraction kit can be used for extraction.

[0289] Step 3: RT-PCR detection. The method of the RT-PCR detection is Taqman RT-PCR, and the genes shown in Table 4 are respectively subjected to RT-PCR detection. The steps are as follows:

[0290] (3-1): Extract the total RNA of the detection object;

[0291] (3-2): Reverse transcribe the RNA obtained in (3-1). The specific steps are as follows: Take about 2 μg of sample RNA in total (for example, take 11 μl of sample RNA at about 200 ng / μl), and reverse transcribe it together with 11 μl of reference RNA (Thermo K1622 reverse transcription kit) to obtain sample cDNA and reference cDNA; Add 80 μl of RNase-free water to the sample cDNA to dilute it 5-fold, and add 180 μl of RNase-free water to the reference cDNA to dilute it 10-fold;

[0292] (3-3): Perform TaqMan RT-PCR detection on the cDNA samples corresponding to each gene obtained in (3-2). Detect 21 colorectal cancer molecular typing and survival risk-related genes and 3 reference genes (see Table 2) respectively. The steps are as follows: (i) Prepare the reaction system per well: 2 μl of the cDNA sample obtained in (3-2) (total amount 100-400 ng), 1.4 μl in total of the forward and reverse specific primers and TaqMan fluorescent probe (10 μM) as shown in Table 4, 10 μl of the reaction premix, and 6.6 μl of DEPC water; (ii) Inactivate the reverse transcriptase at 95 °C for 2 minutes; (iii) Amplification and detection: Denature at 95 °C for 25 seconds, anneal, extend, and perform fluorescence detection at 60 °C for 60 seconds, perform 45 cycles, and the hold period is 60 seconds at 60 °C; after the amplification reaction is completed, record the Ct value of each gene, which represents the expression level of each gene.

[0293] Step 4: Statistical analysis of results. Perform statistical analysis on the obtained sequencing results. Then, use the method described in Example 2 to perform molecular typing on the colorectal cancer of the subject, calculate the immunoglobulin index and recurrence risk score, and predict the survival risk.

[0294] Table 4

[0295]

[0296]

[0297]

[0298] Example 5: Predict the chemotherapy benefit of colon cancer patients according to the results of colorectal cancer molecular typing and risk assessment

[0299] Method: Use the 24-gene test panel for colorectal cancer molecular typing and risk assessment to perform risk assessment on 281 cases of stage III colon cancer. Specifically, use the method described in Example 2 to perform recurrence risk assessment for each colon cancer case; then use the Kaplan-Meier method to compare the differences in survival curves between the chemotherapy group and the non-chemotherapy group.

[0300] Results: Perform recurrence risk assessment on 281 cases of stage III colon cancer, and the cases can be divided into a low-risk group (108 cases) and a high-risk group (173 cases) (Table 5).

[0301] Using the Kaplan-Meier method, the results of survival analysis for the high-risk group cases are shown in Figure 5A and the results of survival analysis for the low-risk group cases are shown in Figure 5B . The results show that for stage III colon cancer cases with a high recurrence risk assessment, the 10-year distant metastasis-free survival rate of the case group receiving chemotherapy is higher than that of the case group not receiving chemotherapy (Figure 5A ); for stage III colon cancer cases with a low recurrence risk assessment, there was no significant difference in the 10-year distant metastasis-free survival rate between the case groups with and without chemotherapy ( Figure 5B ). That is to say, according to the method of the present invention, stage III colon cancer patients evaluated as high risk are expected to benefit from chemotherapy. Therefore, the gene panel of the present invention can be used to determine the molecular subtype of colorectal cancer and / or evaluate the survival risk of colorectal cancer patients. According to the evaluation result of the survival risk, it can be predicted whether colorectal cancer patients can benefit from chemotherapy.

[0302] Table 5

[0303] Risk Group Quantity Low Risk 108 High Risk 173 Total 281

[0304] Example 6: Distribution of Colorectal Cancer Gene Mutations in Different Molecular Subtypes

[0305] Method: Use a 24-gene test panel for molecular typing of colorectal cancer and risk assessment to perform molecular typing on 364 colon cancer cases. Specifically, use the method described in Example 2 to perform molecular typing for each colon cancer case; then, according to the gene mutation information in the TCGA database, statistically analyze the distribution of gene mutations in each molecular subtype.

[0306] Result: Molecular typing was performed on 364 colon cancer cases, and the cases could be divided into CRC1, CRC2, CRC3, CRC4, CRC5, and mixed subtypes. The gene mutations of BRAF, ERBB2, KDR, KRAS, and VEGFA were distributed differently among different subtypes (Table 6).

[0307] Table 6

[0308]

Claims

1. A product for molecular typing and / or survival risk assessment of colorectal cancer, comprising reagents for detecting the expression levels of genes in a gene panel, wherein the gene panel consists of 21 genes related to molecular typing and survival risk assessment, and the 21 genes related to molecular typing and survival risk assessment are as follows: (1) Proliferation-related genes: CCNB2, MKI67, RRM1, SPAG5, and TOP2A; (2) Extracellular matrix-related genes: AEBP1, COL6A3, HTRA1, MMP2, and TIMP3; (3) Intracellular matrix-related genes: ADNP, MAPRE1, and TMEM189-UBE2V1; (4) Immune-related genes: CCL5, CD2, CXCL13, GZMA, and MNDA; and (5) Immunoglobulin-related genes: CD79A, IGKV1-17, and IGKV2-28; wherein the molecular typing of colorectal cancer includes CRC1, CRC2, CRC3, CRC4, CRC5, and a mixed subtype, and the mixed subtype is colorectal cancer that does not belong to the CRC1, CRC2, CRC3, CRC4, and CRC5 subtypes.

2. A product for molecular typing and / or survival risk assessment of colorectal cancer, comprising reagents for detecting the expression levels of genes in a gene panel, wherein the gene panel consists of 21 genes related to molecular typing and survival risk assessment and reference genes, and the 21 genes related to molecular typing and survival risk assessment are as follows: (1) Proliferation-related genes: CCNB2, MKI67, RRM1, SPAG5, and TOP2A; (2) Extracellular matrix-related genes: AEBP1, COL6A3, HTRA1, MMP2, and TIMP3; (3) Intracellular matrix-related genes: ADNP, MAPRE1, and TMEM189-UBE2V1; (4) Immune-related genes: CCL5, CD2, CXCL13, GZMA, and MNDA; and (5) Immunoglobulin-related genes: CD79A, IGKV1-17, and IGKV2-28; the reference genes are: GAPDH, GUSB, and TFRC; wherein the molecular typing of colorectal cancer includes CRC1, CRC2, CRC3, CRC4, CRC5, and a mixed subtype, and the mixed subtype is colorectal cancer that does not belong to the CRC1, CRC2, CRC3, CRC4, and CRC5 subtypes.

3. A product for molecular typing and / or survival risk assessment of colorectal cancer, comprising reagents for detecting the expression levels of genes in a gene panel, wherein the gene panel consists of 76 genes related to molecular typing and survival risk assessment, and the 76 genes related to molecular typing and survival risk assessment are as follows: (1) Proliferation-related genes: CCNB2, MKI67, RRM1, SPAG5, TOP2A, CKS1B, DNMT1, DTYMK, EZH2, FOXM1, MAD2L1, MCM2, MCM3, MCM6, PCLAF, PLK1, PSRC1, RFC5, SMC4, TMPO, and UBE2S; (2) Extracellular matrix-related genes: AEBP1, COL6A3, HTRA1, MMP2, TIMP3, CLIC4, DPYSL3, EFEMP1, GJA1, LGALS1, LUM, MSN, PALLD, SERPING1, TIMP1, TNC, and VIM; (3) Intracellular matrix-related genes: ADNP, MAPRE1, TMEM189-UBE2V1, CSE1L, EIF2S2, EIF6, NCOA6, PPP1R3D, PRPF6, PSMA7, RALY, RBM39, RNF114, RPS21, TOMM34, and ZMYND8; (4) Immunity-related genes: CCL5, CD2, CXCL13, GZMA, MNDA, BCL2A1, CCL3, CSF2RB, LCP2, PLA2G7, RASGRP1, RHOH, and TLR2; and (5) Immunoglobulin-related genes: CD79A, IGKV1-17, IGKV2-28, CD27, IGHM, IGKV4-1, JCHAIN, POU2AF1, and TNFRSF17; wherein the molecular subtypes of colorectal cancer include CRC1, CRC2, CRC3, CRC4, CRC5, and a mixed subtype, and the mixed subtype is colorectal cancer that does not belong to the CRC1, CRC2, CRC3, CRC4, and CRC5 subtypes.

4. A product for molecular subtyping and / or survival risk assessment of colorectal cancer, which comprises a reagent for detecting the expression levels of genes in a gene panel, wherein the gene panel consists of 76 molecular subtyping and survival risk assessment-related genes and reference genes, and wherein the 76 molecular subtyping and survival risk assessment-related genes are: (1) Proliferation-related genes: CCNB2, MKI67, RRM1, SPAG5, TOP2A, CKS1B, DNMT1, DTYMK, EZH2, FOXM1, MAD2L1, MCM2, MCM3, MCM6, PCLAF, PLK1, PSRC1, RFC5, SMC4, TMPO, and UBE2S; (2) Extracellular matrix-related genes: AEBP1, COL6A3, HTRA1, MMP2, TIMP3, CLIC4, DPYSL3, EFEMP1, GJA1, LGALS1, LUM, MSN, PALLD, SERPING1, TIMP1, TNC, and VIM; (3) Intracellular matrix-related genes: ADNP, MAPRE1, TMEM189-UBE2V1, CSE1L, EIF2S2, EIF6, NCOA6, PPP1R3D, PRPF6, PSMA7, RALY, RBM39, RNF114, RPS21, TOMM34, and ZMYND8; (4) Immune-related genes: CCL5, CD2, CXCL13, GZMA, MNDA, BCL2A1, CCL3, CSF2RB, LCP2, PLA2G7, RASGRP1, RHOH, and TLR2; and (5) Immunoglobulin-related genes: CD79A, IGKV1-17, IGKV2-28, CD27, IGHM, IGKV4-1, JCHAIN, POU2AF1, and TNFRSF17; The reference genes are: GAPDH, GUSB, TFRC, MRPL19, PSMC4, and SF3A1; Wherein the molecular subtypes of colorectal cancer include CRC1, CRC2, CRC3, CRC4, CRC5, and a mixed subtype, and the mixed subtype is colorectal cancer that does not belong to the CRC1, CRC2, CRC3, CRC4, and CRC5 subtypes.

5. The product according to any one of claims 1-4, wherein The reagent is a reagent for detecting the amount of mRNA transcribed from the gene; or, The reagent is a reagent for detecting the amount of cDNA complementary to mRNA.

6. The product according to any one of claims 1-4, wherein the reagent is a primer, a probe, or a combination thereof.

7. The product according to any one of claims 1-4, wherein the reagent is a primer.

8. The product according to claim 3, wherein the reagent is a primer, and the sequences of the primer are shown in SEQ ID NO.1-SEQ ID NO.

152.

9. The product according to claim 4, wherein the reagent is a primer, and the sequences of the primer are shown in SEQ ID NO.1-SEQ ID NO.

164.

10. The product according to claim 1, wherein the reagent is a primer, and the sequences of the primer are shown in SEQ ID NO.165-SEQ ID NO.

206.

11. The product according to claim 2, wherein the reagent is a primer, and the sequences of the primer are shown in SEQ ID NO.165-SEQ ID NO.

212.

12. The product according to any one of claims 1-4, wherein the reagent is a probe.

13. The product according to any one of claims 1-4, wherein the reagent is a TaqMan probe.

14. The product according to claim 1, wherein the reagent is a probe, and the sequences of the probe are shown in SEQ ID NO.213-SEQ ID NO.

233.

15. The product according to claim 1, wherein the reagent is a TaqMan probe, and the sequences of the TaqMan probe are shown in SEQ ID NO.213-SEQ ID NO.

233.

16. The product according to claim 2, wherein the reagent is a probe, and the sequence of the probe is as shown in SEQ ID NO.213 - SEQ ID NO.

236.

17. The product according to claim 2, wherein the reagent is a TaqMan probe, and the sequence of the TaqMan probe is as shown in SEQ ID NO.213 - SEQ ID NO.

236.

18. The product according to any one of claims 1 - 4, wherein the reagent is a combination of a primer and a probe.

19. The product according to claim 1, wherein the reagent is a combination of a primer and a probe, the sequence of the primer is as shown in SEQ ID NO.165 - SEQ ID NO.206, the probe is a TaqMan probe, and the sequence of the TaqMan probe is as shown in SEQ ID NO.213 - SEQ ID NO.

233.

20. The product according to claim 2, wherein the reagent is a combination of a primer and a probe, the sequence of the primer is as shown in SEQ ID NO.165 - SEQ ID NO.212, the probe is a TaqMan probe, and the sequence of the TaqMan probe is as shown in SEQ ID NO.213 - SEQ ID NO.

236.

21. The product according to any one of claims 1 - 4, wherein the reagent is a reagent for detecting the amount of the polypeptide encoded by the gene.

22. The product according to any one of claims 1 - 4, wherein the reagent is an antibody, an antibody fragment or an affinity protein.

23. The product according to any one of claims 1 - 4, which is in the form of an in vitro diagnostic product.

24. The product according to any one of claims 1 - 4, which is in the form of a diagnostic kit.

25. The product according to any one of claims 1 - 4, which is a next-generation sequencing kit, a real-time fluorescence quantitative PCR detection kit, a gene chip, a protein chip, an ELISA diagnostic kit or an immunohistochemistry (IHC) kit or a combination thereof.

26. The product according to claim 3, which is a next-generation sequencing kit, which contains primers and optionally contains one or more selected from the following: total RNA extraction reagent, reverse transcription reagent and next-generation sequencing reagent, and the sequence of the primers is as shown in SEQ ID NO.1 - SEQ ID NO.

152.

27. The product according to claim 4, which is a next-generation sequencing kit, which contains primers and optionally contains one or more selected from the following: total RNA extraction reagent, reverse transcription reagent and next-generation sequencing reagent, and the sequence of the primers is as shown in SEQ ID NO.1 - SEQ ID NO.

164.

28. The product according to claim 1, which is a real-time fluorescence quantitative PCR detection kit, which contains primers, and the sequence of the primers is as shown in SEQ ID NO.165 - SEQ ID NO.

206.

29. The product according to claim 2, which is a real-time fluorescence quantitative PCR detection kit, comprising primers, and the sequences of the primers are shown as SEQ ID NO.165 - SEQ ID NO.

212.

30. The product according to claim 28 or 29, wherein the real-time fluorescence quantitative PCR detection kit further comprises TaqMan probes, and optionally comprises one or more selected from the following: total RNA extraction reagent, reverse transcription reagent, and reagent for TaqMan RT-PCR.

31. The product according to claim 28, wherein the real-time fluorescence quantitative PCR detection kit comprises primers and TaqMan probes, the sequences of the primers are shown as SEQ ID NO.165 - SEQ ID NO.206, and the sequences of the TaqMan probes are shown as SEQ ID NO.213 - SEQ ID NO.

233.

32. The product according to claim 29, wherein the real-time fluorescence quantitative PCR detection kit comprises primers and TaqMan probes, the sequences of the primers are shown as SEQ ID NO.165 - SEQ ID NO.212, and the sequences of the TaqMan probes are shown as SEQ ID NO.213 - SEQ ID NO.

236.

33. The product according to claim 28 or 29, wherein the real-time fluorescence quantitative PCR detection kit further comprises one or more selected from the following: total RNA extraction reagent, reverse transcription reagent, and reagent for SYBR Green RT-PCR.

34. Use of the product according to any one of claims 1 - 33 in the preparation of a product for determining the molecular typing of colorectal cancer and / or evaluating the survival risk of colorectal cancer patients.

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