CN113106158A - CSMD family gene prediction of advanced lung adenocarcinoma immunotherapy efficacy - Google Patents

CSMD family gene prediction of advanced lung adenocarcinoma immunotherapy efficacy Download PDF

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CN113106158A
CN113106158A CN202110663393.4A CN202110663393A CN113106158A CN 113106158 A CN113106158 A CN 113106158A CN 202110663393 A CN202110663393 A CN 202110663393A CN 113106158 A CN113106158 A CN 113106158A
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csmd
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王凯
张昭
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Shanghai Zhiben Medical Laboratory Co ltd
Origimed Technology Shanghai Co ltd
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Abstract

The invention relates to the field of precise medical clinical molecular diagnosis. In particular, the present invention relates to a method, kit, system and computing device for predicting the efficacy of immunotherapy (e.g. immune checkpoint inhibitor therapy) for advanced lung adenocarcinoma.

Description

CSMD family gene prediction of advanced lung adenocarcinoma immunotherapy efficacy
Technical Field
The present invention is in the field of precision medical clinical molecular diagnostics and relates to a method, kit, system and computing device for predicting the efficacy of immunotherapy for advanced lung adenocarcinoma, e.g., immunotherapy using immune checkpoint inhibitors.
Background
Non-small cell lung cancer is one of the most common and deadly cancer species in the chinese population, with lung adenocarcinoma being the most common subtype (accounting for about 60-70%). The advanced lung adenocarcinoma classical treatment means is chemotherapy and/or radiotherapy, and when sensitive mutations such as EGFR, ALK, ROS1 and the like exist, targeted drugs such as receptor Tyrosine Kinase Inhibitors (TKIs) and the like have better treatment effects. However, the main problem faced by these treatments is that the benefited population is limited to cancer patients carrying specific genetic mutations and as the course of treatment progresses, cancer cells eventually adapt and develop corresponding resistance to the drug.
Immunotherapy, particularly biomacromolecule drugs represented by Immune Checkpoint Inhibitors (ICIs), has brought about a great revolution in the treatment of advanced lung adenocarcinoma. However, only a fraction of patients with advanced lung adenocarcinoma (around 20-30%) benefit from this treatment, and there is a need for effective biomarkers to predict clinically beneficial populations. Currently, clinically common immunotherapy efficacy prediction biomarkers including PD-L1 and TMB have shown certain prediction efficacy, but still have many limitations including higher detection cost (TMB) and higher sample requirement (PD-L1).
Immunotherapy recognizes antigens from tumor cells (tumor neoantigens) by reactivating the human adaptive immune system, particularly CD8+ T cells. These neoantigens are derived from abnormal amino acid sequences resulting from somatic non-synonymous mutations that occur in tumor cells and specifically recognize and bind to HLA class I. There is generally a significant positive correlation between tumor neoantigen number and tumor mutational burden.
And (3) TMB detection: TMB is collectively called "tumor gene mutation burden" (tumor), and is a biotherapeutic biomarker (biorarker) recommended by the NCCN guidelines. The whole or specific gene coding region of tumor tissue or peripheral blood free tumor DNA (ctDNA) is deeply sequenced through Whole Exome Sequencing (WES) or large gene panel (such as MSK-IMPACT, Foundation One, and the like), and the number of somatic nonsynonymous mutations in each Mb gene region is calculated through certain bioinformatics variation identification software. Multiple independent clinical studies have shown that there is a significant positive correlation between TMB and the efficacy of immunotherapy in a number of cancer species, including melanoma and non-small cell lung cancer.
However, TMB detection requires a high technical platform, a long working period, and high sequencing costs (high requirements on patient economic conditions).
PD-L1 detection: PD-L1 is a protein expressed on the surface of cell membranes and is encoded by the human CD274 gene. Effector T cells are inhibited by binding to PD-1 and B7.1 on CD8+ T cells, transmitting immunosuppressive signals. Clinically, tumor tissues obtained after operation or puncture are subjected to section staining by an immunohistochemical method, and expression is evaluated according to the depth of staining by microscopic observation. Generally, the response rate to immunotherapy is higher for solid tumor patients with high expression of PD-L1 protein. However, the results of multiple clinical trials showed that the prediction ability of PD-L1 expression on the therapeutic effect of immunotherapy was not consistent, and some PD-L1 negative patients still benefited from immunotherapy and sustained remission time was not inferior to PD-L1 positive patients.
Therefore, there is still a great need for more new predictive biomarkers or methods to predict cancer immunotherapy efficacy in the clinic.
Disclosure of Invention
The invention provides an important gene family CSMD1/2/3 which is obviously positively correlated with TMB, the phenomenon of obvious common mutation is found, the gene family can effectively predict the curative effect of immunotherapy by being verified in a public data set, and meanwhile, the detection cost and the analysis time are reduced. Unlike the continuum variable TMB, the efficacy assessment cohorts were divided only by the presence or absence of CSMD family gene mutations.
Specifically, the invention finds that the somatic non-synonymous mutation state of the CSMD family gene (CSMD1/2/3) can effectively predict the treatment effect of the immune checkpoint inhibitor on the advanced lung adenocarcinoma through public data mining and aiming at the gene detection data and the immunotherapy effect evaluation data of the advanced lung adenocarcinoma. Therefore, the invention provides a low-cost and high-efficiency detection means for effectively predicting the curative effect of the advanced lung adenocarcinoma immunotherapy.
First, in a first aspect, the present invention relates to a biomarker for predicting the sensitivity of an advanced lung adenocarcinoma patient to immunotherapy (e.g. with an immune checkpoint inhibitor) to predict the efficacy of the immunotherapy, the biomarker comprising a CSMD family gene; further, there are three genes CSMD1, CSMD2, and CSMD 3.
The term "biomarker" refers to an indicator of a patient's phenotype (e.g., a pathological state or likely responsiveness to a therapeutic agent) that can be detected in a biological sample from the patient. Biomarkers include, but are not limited to, molecular markers based on DNA, RNA, protein, carbohydrate, or glycolipids.
In particular, the biomarkers of the invention are the DNA-based gene families CSMD1, CSMD2, CSMD 3; to predict or judge the effectiveness of a treatment in a target population. Three members of the CSMD protein family (CUB and sushi multiple domain protein family) all have very similar protein structures (comprising 14 CUB domains separated by sushi domains, another uninterrupted sushi domain, a transmembrane protein, and a short cytoplasmic tail). The corresponding three encoding genes CSMD1/2/3 are respectively located on human chromosomes 8p23.2, 1p35.1 and 8q23.3, and the expression deletion or dysfunction of the genes is mostly reported to be closely related to mental diseases and has close relation with the occurrence and development of various tumors. As a class of candidate cancer suppressor genes, the relevance of CSMD family genes to cancer and its treatment remains to be studied further.
The term "prediction" refers to the likelihood that a patient will benefit from a certain drug, therapeutic agent, or treatment regimen. In one treatment regimen, the prediction involves: whether and/or how likely a patient will survive, improve, or persist for a certain period of time without relapse after treatment with, for example, a particular therapeutic agent. The prediction method of the present invention may be used clinically to determine or exclude the use of a certain treatment regimen by the prediction.
In another aspect, the present invention provides a kit for predicting the efficacy of immunotherapy for advanced lung adenocarcinoma, the kit comprising reagents for specifically detecting mutations in CSMD1, CSMD2, and CSMD3 genes.
In some embodiments, the kit comprises one or more selected from the group consisting of nucleic acid extraction reagents, gene specific primers or probes, PCR reagents, nucleic acid sequencing reagents.
In some embodiments, the sequencing is high-throughput sequencing, also known as next-generation sequencing (NGS sequencing). NGS sequencing platforms useful in the present invention are commercially available and include, but are not limited to, Roche/454 FLX, Illumina/Solexa Genome Analyzer, and Applied Biosystems SOLID system, among others.
Exome sequencing is a genome analysis method of high-throughput sequencing after capturing and enriching genomic exome region DNA by using a sequence capture technology. Because of its high sensitivity to common and rare mutations, only 2% of the genome need be sequenced to find most disease-associated mutations in exon regions. The high throughput sequencing can be whole exome sequencing or sequencing of a portion of a gene or region in a genome. Specifically, in the present invention, sequencing can be performed on CSMD1/2/3 gene.
In some preferred embodiments, the kit further comprises a sample treatment agent, such as a sample lysis reagent, a sample purification reagent, a nucleic acid extraction reagent, and the like.
In another aspect, the present invention provides a method for predicting the efficacy of an advanced lung adenocarcinoma immunotherapy, such as an immune checkpoint inhibitor therapy, comprising the steps of:
a) assessing somatic non-synonymous mutations of CSMD1, CSMD2, and CSMD3 genes in tumor tissue of patients with advanced lung adenocarcinoma;
b) classifying according to the evaluation result of the step a): (ii) a CSMD =1 group if at least one somatic non-synonymous mutation occurs in at least one of the CSMD1, CSMD2, and CSMD3 genes; if no somatic non-synonymous mutation occurred in any of the three genes, or a mutation occurred only in the non-coding region, the three genes were classified as CSMD = 0; wherein, if at least one gene in the three genes has somatic non-synonymous mutation in a coding region, the three genes are classified into CSMD =1 group regardless of the number and type of the mutation;
c) based on the classification result of step b), a judgment is made that CSMD =1 group immunotherapy is effective and CSMD =0 group immunotherapy is ineffective.
In the present invention, the non-synonymous mutation of the gene may include a point mutation (point mutation) and a fragment mutation (fragment mutation); the point mutation can be Single Nucleotide Polymorphism (SNP), base substitution, single base insertion or base deletion, and splicing mutation; fragment mutations may be fusion/rearrangement mutations, amplification mutations, insertion/deletion and truncation mutations.
In some embodiments, the immunotherapy is an immunotherapy with an immune checkpoint inhibitor.
As used herein, the term "immune checkpoint" refers to some inhibitory signaling pathway present in the immune system. Under normal conditions, the immune checkpoint can maintain immune tolerance by adjusting the strength of autoimmune reaction, however, when the organism is invaded by tumor, the activation of the immune checkpoint can inhibit autoimmunity, which is beneficial to the growth and escape of tumor cells. By using the immune checkpoint inhibitor, the normal anti-tumor immune response of the body can be restored, so that the tumor can be controlled and eliminated. A variety of immune checkpoint inhibitors are known in the art for use in tumor therapy.
The immune checkpoint of the invention is PD-1, PD-L1 and/or CTLA-4. The immune checkpoint inhibitors of the present invention include, but are not limited to, PD1 inhibitors, PD-L1 inhibitors, and/or CTLA-4 inhibitors, such as pappaluzumab (Pembrolizumab, trade name Keytruda), Nivolumab (Nivolumab, trade name optodivvo), astuzumab (atemorphia, trade name Tecentriq), Ipilimumab (Ipilimumab, trade name Yervoy), and dewalimumab (Durvalumab, trade name infinzi), among others.
In some embodiments, the somatic non-synonymous mutations of the CSMD1, CSMD2, and CSMD3 genes in tumor tissue are assessed by comparing sequencing data, e.g., whole exome sequencing or CSMD 1/2/3-targeted sequencing data, of the tumor tissue to control tissue.
In some embodiments, the tumor tissue is a cancer tissue; further, the tumor tissue is a primary focus or a metastatic focus.
In some embodiments, the control tissue is normal tissue (non-tumor tissue) from the subject, such as paracancerous tissue or leukocytes, and the like.
In some embodiments, evaluating CSMD1, CSMD2, and CSMD3 gene mutation information includes determining whether non-synonymous mutations, such as frameshift, missense, splicing, frameshift, or stop-gain mutations, are present in their coding regions.
In some embodiments, the CSMD1, CSMD2, and CSMD3 gene mutation status are assessed by high throughput sequencing techniques. Various methods known in the art for detecting mutations in a particular gene can be used in the present invention.
The term "mutational burden", in the context of a tumor, is also referred to herein as "tumor mutational burden" or "TMB". Tumor Mutational Burden (TMB) is defined as the number of somatic non-synonymous mutations detected per million bases, including the total number of mutations, such as missense mutations, frameshift, or in-frame insertions or deletions. TMB is generally expressed as the total number of non-synonymous mutations divided by the measured gene interval size, i.e.the number of non-synonymous mutations per 1Mb (1 megabase) (mutans/Mb).
In some embodiments, the immunotherapy is predicted to be effective if at least one of the i) somatic non-synonymous mutations in the CSMD1, CSMD2, and CSMD3 genes is present. In other embodiments, the immunotherapy is predicted to be ineffective if ii) no somatic non-synonymous mutations or mutations in CSMD1, CSMD2, and CSMD3 genes occur in non-coding regions.
In the invention, by taking the mutation states of CSMD1, CSMD2 and CSMD3 genes into consideration, the population sensitive to the immune checkpoint inhibitor in the patient with advanced lung adenocarcinoma can be accurately predicted, blind medication is avoided, and the economic performance of the treatment of the immune checkpoint inhibitor is improved.
In another aspect, the invention provides a system or device for predicting the efficacy of an immunotherapy, such as an immune checkpoint inhibitor therapy, for advanced lung adenocarcinoma, the system or device comprising the following three modules:
assessment module I) assessing a somatic non-synonymous mutation of CSMD1, CSMD2, and CSMD3 genes in tumor tissue of a patient with advanced lung adenocarcinoma;
a calculation module II) for classifying according to the evaluation result of the evaluation module I): (ii) a CSMD =1 group if at least one somatic non-synonymous mutation occurs in any one of the CSMD1, CSMD2, and CSMD3 genes; if no somatic non-synonymous mutation occurred in any of the three genes, or a mutation occurred only in the non-coding region, the three genes were classified as CSMD = 0; wherein, if at least one gene in the three genes has somatic non-synonymous mutation in a coding region, the three genes are classified into CSMD =1 group regardless of the number and type of the mutation;
judgment module III), based on the result of the calculation module, a judgment is made that CSMD =1 group immunotherapy is effective and CSMD =0 group immunotherapy is ineffective.
In some embodiments, the evaluating module I) evaluates the somatic non-synonymous mutations of the CSMD1, CSMD2, and CSMD3 genes by comparing sequencing data, e.g., whole exome sequencing or targeted sequencing data, of tumor tissue to control tissue.
In some preferred embodiments, assessment module I) determines whether the coding regions of the CSMD1, CSMD2, and CSMD3 genes are somatically mutated, e.g., a frameshift mutation, missense, splice, frameshift, or stop-gain mutation, etc.
In some embodiments, the immunotherapy is judged to be effective if i) at least one somatic non-synonymous mutation to the coding region of the CSMD1, CSMD2, and CSMD3 genes is present; in other embodiments, the immunotherapy is judged to be ineffective if ii) the CSMD1, CSMD2, and CSMD3 genes are free of somatic non-synonymous mutations in the coding region.
In another aspect, the invention also relates to the use of reagents for specifically detecting mutations in the CSMD1/2/3 gene in kits, systems and devices for predicting the efficacy of immunotherapy for advanced lung adenocarcinoma.
In some embodiments, the reagents are, for example, gene sequencing reagents, gene specific primers or probes, and the like.
Further, the kit is the kit described above; the system and apparatus are as described above.
Those skilled in the art will appreciate that all or part of the functions of the above-described method steps may be implemented by hardware, or may be implemented by a computer program.
When all or part of the functions of the above method steps are implemented by means of a computer program, the program may be stored in a computer-readable storage medium, and the storage medium may include: a read only memory, a random access memory, a magnetic disk, an optical disk, a hard disk, etc., and the program is executed by a computer to realize the above functions. For example, the program may be stored in a memory of the device, and when the program in the memory is executed by the processor, all or part of the functions described above may be implemented. In addition, when all or part of the functions in the above embodiments are implemented by a computer program, the program may be stored in a storage medium such as a server, another computer, a magnetic disk, an optical disk, a flash disk, or a removable hard disk, and may be downloaded or copied to a memory of a local device, or may be version-updated in a system of the local device, and when the program in the memory is executed by a processor, all or part of the functions in the above embodiments may be implemented.
In another aspect, the present invention also provides a computing device comprising:
at least one processing unit; and at least one memory coupled to the processing unit and storing instructions for execution by the processing unit, the instructions when executed enable the apparatus to implement the method of predicting the efficacy of an immunotherapy for advanced lung adenocarcinoma described above.
In another aspect, the present invention relates to a computer readable storage medium storing a computer program executable by a machine to perform the method of predicting the efficacy of an immunotherapy for advanced lung adenocarcinoma of the present invention as described above.
The invention has the beneficial effects that:
the invention provides a low-cost and high-efficiency detection means for effectively predicting the curative effect of immunotherapy of advanced lung adenocarcinoma. Compared with the method that PD-L1 detection requires manual interpretation of immunohistochemical tablets, the method only evaluates grouping by the presence or absence of CSMD family somatic gene mutation to predict curative effect; compared with TMB detection with higher cost, the invention can simplify the detection content, reduce the detection cost and accelerate the detection report issuing efficiency. The detection of the gene mutation state is simple, direct, reliable and efficient.
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To more clearly illustrate the detailed description of the invention or the prior art, reference will now be made in detail to the accompanying drawings, which are needed in the description of the detailed description or the prior art. The drawings in the following description are some embodiments of the invention, and it is obvious to those skilled in the art that other drawings can be obtained from them without inventive effort.
FIG. 1: detailed analytical flow charts of the method of the invention.
FIG. 2: association of CSMD mutation status with TMB: FIG. 2A shows the association of TMB with CSMD mutations in the TCGA data queue; figure 2B shows the association of TMB with CSMD mutations in 89 cohorts of advanced lung adenocarcinoma.
FIG. 3: probability of Survival (Survival viability) results plot.
FIG. 4: and (5) multi-factor analysis results.
Detailed Description
The present invention will be described in detail with reference to the following embodiments and accompanying drawings.
Example 1: there was significant co-mutation of CSMD1/2/3 and significant positive correlation with TMB
Analysis of 567 advanced lung adenocarcinoma (LUAD) data in TCGA data revealed that the mutation frequencies of the three genes of the CSMD family from high to low were CSMD3 (36.5%), CSMD1 (19.2%) and CSMD2 (13.2%), respectively. Meanwhile, the CSMD family genes are found to have a remarkable co-mutation phenomenon (two genes are mutated at the same time), which indicates that certain overlapping complementation exists in structure and function. The details are shown in Table 1.
Figure 544491DEST_PATH_IMAGE001
Cases with at least one somatic non-synonymous mutation among the three genes CSMD1/2/3 were classified as CSMD =1 group; while the CSMD =0 group was classified as the case where no somatic non-synonymous mutation was present in any of the three genes CSMD1/2/3, or only a mutation occurred in a non-coding region.
The TMB in TCGA data for CSMD =1 group was found to be significantly higher than CSMD =0 group (wilcoxon test P <2.2e-16, see fig. 2A). It is known that the CSMD1/2/3 three genes all have direct proportion to the total number of somatic mutation loads (TMB), and the CSMD mutations (i.e., at least one of the CSMD1/2/3 genes has somatic nonsynonymous mutation) are similar to the TMB and can be used as biomarkers for immunotherapy prognosis.
Example 2: CSMD1/2/3 mutations predict the efficacy of lung adenocarcinoma (LUAD) immunotherapy
Two phase III clinical study datasets, CheckMate-012 (treatment: Nawuliu Uuzumab + Epipilimumab, N = 59) and KeyNote-001 (treatment: Paboclizumab, N = 30), for a total of 89 advanced lung adenocarcinoma (LUAD) patients, were selected for clinical data and gene testing data. These include gene mutation data, treatment regimen data, and Progression Free Survival (PFS) data.
With reference to the calculation method described above, the CSMD =1 group and the CSMD =0 group are divided. As can be seen from fig. 2B, similarly to fig. 2A, in 89 advanced lung adenocarcinoma (LUAD) patients, the TMB of CSMD =1 group was also significantly higher than that of CSMD =0 group (wilcoxon test P <8.7 e-09).
In addition, significant clinical PFS benefit was observed for the CSMD =1 group (HR: 0.49 (95% CI: 0.28-0.86); log-rank test, P = 0.01). The specific survival analysis results are shown in fig. 3.
Further, considering the effect of age, sex and therapeutic drugs on PFS together, multi-factor COX analysis was performed thereon, and the results still showed that CSMD =1 group PFS was significantly better than CSMD =0 group. The specific results are shown in FIG. 4.
From the above analysis, the CSMD family gene is an effective biomarker for predicting the curative effect of immunotherapy in advanced lung adenocarcinoma.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (10)

1. A biomarker for predicting the efficacy of immunotherapy for advanced lung adenocarcinoma, comprising three genes of the CSMD family of genes: CSMD1, CSMD2, CSMD 3.
2. A kit for predicting the efficacy of immunotherapy for advanced lung adenocarcinoma, comprising reagents for specifically detecting mutations in CSMD1, CSMD2, and CSMD3 genes.
3. The kit of claim 2, wherein the kit comprises one or more selected from the group consisting of nucleic acid extraction reagents, gene specific primers or probes, PCR reagents, nucleic acid sequencing reagents.
4. A system for predicting the efficacy of immunotherapy for advanced lung adenocarcinoma, the system comprising the following three modules:
assessment module I) assessing a somatic non-synonymous mutation of CSMD1, CSMD2, and CSMD3 genes in tumor tissue of a patient with advanced lung adenocarcinoma;
a calculation module II) for classifying according to the evaluation result of the evaluation module I): (ii) a CSMD =1 group if at least one of the CSMD1, CSMD2, and CSMD3 genes has at least one somatic non-synonymous mutation; if no somatic non-synonymous mutation occurred in any of the three genes, or a mutation occurred only in the non-coding region, the three genes were classified as CSMD = 0;
wherein, if at least one gene in the three genes has somatic non-synonymous mutation in a coding region, the three genes are classified into CSMD =1 group no matter the number and type of the mutation;
a judgment module III), based on the result of the calculation module II), judging: the CSMD =1 group was judged to be effective in immunotherapy, and the CSMD =0 group was judged to be ineffective in immunotherapy.
5. The system of claim 4, wherein the evaluating is comparing sequencing data of tumor tissue and control tissue to obtain somatic non-synonymous mutation information for CSMD1, CSMD2, and CSMD3 genes.
6. Use of an agent that specifically detects mutations in CSMD1, CSMD2, and CSMD3 genes in a kit or system for predicting the efficacy of immunotherapy for advanced lung adenocarcinoma.
7. The use of claim 6, wherein the agent is selected from a gene sequencing agent, a gene specific primer or a probe.
8. The use according to claim 6 or 7, wherein the kit is a kit according to claim 2 or 3; the system is the system of claim 4 or 5.
9. A computing device, comprising:
at least one processing unit; and
at least one memory coupled to the processing unit and storing instructions for execution by the processing unit, the instructions when executed, the apparatus capable of enabling prediction of immunotherapy efficacy for advanced lung adenocarcinoma, the prediction comprising the steps of:
a) comparing the sequencing data of the tumor tissue to control tissue, assessing somatic non-synonymous mutations of CSMD1, CSMD2, and CSMD3 genes in the tumor tissue of patients with advanced lung adenocarcinoma;
b) classifying according to the evaluation result of the step a): (ii) a CSMD =1 group if at least one somatic non-synonymous mutation occurs in at least one of the CSMD1, CSMD2, and CSMD3 genes; if no somatic non-synonymous mutation occurred in any of the three genes, or a mutation occurred only in the non-coding region, the three genes were classified as CSMD = 0;
wherein, if at least one gene in the three genes has somatic non-synonymous mutation in a coding region, the three genes are classified into CSMD =1 group no matter the number and type of the mutation;
c) based on the classification result of step b), making a prediction: CSMD =1 group was predicted to be effective in immunotherapy, while CSMD =0 group was predicted to be ineffective in immunotherapy.
10. A computer-readable storage medium storing a computer program executable by a machine to perform steps for predicting the efficacy of immunotherapy for advanced lung adenocarcinoma, the steps comprising,
a) comparing the sequencing data of the tumor tissue to control tissue, assessing somatic non-synonymous mutations of CSMD1, CSMD2, and CSMD3 genes in the tumor tissue of patients with advanced lung adenocarcinoma;
b) classifying according to the step a): (ii) a CSMD =1 group if at least one somatic non-synonymous mutation occurs in at least one of the CSMD1, CSMD2, and CSMD3 genes; if no somatic non-synonymous mutation occurred in any of the three genes, or a mutation occurred only in the non-coding region, the three genes were classified as CSMD = 0;
wherein, if at least one gene in the three genes has somatic non-synonymous mutation in a coding region, the three genes are classified into CSMD =1 group regardless of the number and type of the mutation;
c) based on the classification result of step b), making a prediction: CSMD =1 group was predicted to be effective in immunotherapy, while CSMD =0 group was not effective in immunotherapy.
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