Gene sets and scoring model for evaluating tumor microenvironment, and application of gene sets
A tumor microenvironment and gene set technology, applied in the field of bioinformatics, can solve the problems of neglect of evaluation, low response rate, and incomplete mechanism of immunotherapy.
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Embodiment 1
[0062] Example 1 The multigene scoring model of the tumor microenvironment of the present invention and its construction method
[0063] A method for constructing a polygene scoring model for evaluating the tumor microenvironment, the steps are as follows:
[0064] (1) Affymetrix chip normalized data of 300 patients with gastric cancer; the data is derived from GSE62254 (obtained from NCBI public database);
[0065] (2) Evaluate the composition of immune cells in the tumor microenvironment on the sequencing data through CIBERSORT and MCP-counter algorithms, and obtain the composition evaluation results of 23 kinds of immune cells;
[0066] (3) Unsupervised clustering of immune cells in the tumor microenvironment by consensuclusterplus2 to obtain different types of tumor microenvironment;
[0067] (4) Through pairwise difference analysis and random forest dimension reduction, 244 gene sets that can evaluate the tumor microenvironment score are finally determined;
[0068] (5)...
Embodiment 3
[0090] Example 3 Efficacy Evaluation of the Tumor Microenvironment Score Model in Predicting the Prognosis of Patients
[0091] The above-mentioned tumor microenvironment scoring system was applied to multiple gastric cancer patient cohorts with survival data, and the prognostic value of the tumor microenvironment was analyzed. The steps are as follows:
[0092] ① Obtain the transcriptome microarray data (GSE84437, GSE15459, GSE34942, GSE57303, GSE62254) of gastric cancer patients from the website (https: / / www.ncbi.nlm.nih.gov / geo / ), we downloaded the original microarray data of the patients and Use affy to standardize and correct the data (Reference 14: L.Gautier, L.Cope, B.M.Bolstad, R.A. Irizarry, affy--analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 20, 307-315 (2004));
[0093] ② Extract the data of 44 tumor microenvironment genes in the gene expression matrix, and calculate the tumor immune score, tumor interstitial score and For the tumor microe...
Embodiment 4
[0097] Example 4 Efficacy Evaluation of the Tumor Microenvironment Score Model in Predicting the Immunotherapy Response of Cancer Patients
[0098] To verify the efficacy of TMEscore_plus in predicting immunotherapy, the steps are as follows:
[0099] ① Download the RNAseq next-generation sequencing data of PRJEB25780 (https: / / www.ebi.ac.uk / ena / browser / view / PRJEB25780), and use the TPM method to standardize the sample data;
[0100] ② Extract the data of 44 tumor microenvironment genes in the gene expression matrix, and standardize the sample data so that the mean value of each gene is 0 and the standard deviation is 1, and assign the expression matrix to the eset object in R;
[0101] ③ Install the TMEscore R package, and use the following code to calculate the tumor microenvironment score:
[0102] #Install the TMEscore package
[0103] devtools::install_github("DongqiangZeng0808 / TMEScore")
[0104] #load the R package
[0105] library('TMEScore')
[0106] #Enter the ge...
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