Use TCGA Database To Mine Cell Glycolysis-related Genes To Predict The Survival Prognosis Of Colon Adenocarcinoma Patients

Research background:Colon Adenocarcinoma(COAD)is a malignant tumor of the digestive tract that usually occurs in the left colon.According to the WHO 2018 annual report,there are approximately 1.8 million colon cancer patients worldwide,and 881,000 people died of the disease in 2018.Among the prevalence factors of colon adenocarcinoma,high-fat and low-fiber diet can affect the incidence of colon adenocarcinoma.In addition to the impact of diet on colon adenocarcinoma,glycolysis-related processes also occur in the malignant progression of colon adenocarcinoma.To the pivotal role.Cancer needs glycolysis process to provide energy for it.Cancer cells that have lost glycolysis function cannot complete the energy required for proliferation.Therefore,glycolysis process is one of the metabolic characteristics of colon adenocarcinoma,which is the progression of colon adenocarcinoma.Played an important role in.Relevant studies have shown that lactic acid produced by glycolysis can affect the microenvironment of tumors and regulate various signaling pathways of tumors.When the body is under hypoxia,glycolysis will become the main energy supply method.Therefore,it has been suggested that hypoxia-related genes can also regulate the glycolysis process,thereby affecting the progression of tumors.In the past research,through the bioinformatics database,many genes affecting the survival and prognosis of colon adenocarcinoma were discovered.However,using a single gene to predict disease prognosis is not an accurate method.In this study,we established a predictive model to better predict the prognosis of colon adenocarcinoma through the analysis method of Cox regression.GSEA is a calculation method for gene enrichment analysis,which can be used for the biological function analysis of gene sets.It can screen the specific gene sets that need to be studied according to the biological function classification.The Genome Data Sharing Area(TCGA GDC)is a research project of the National Cancer Institute(NCI).The mission of TCGA GDC is to provide a unified database for the cancer research community,which enables data sharing of multiple tumor genomes to support precision medicine.Research method:The TCGA GDC database has abundant and standardized clinical data,a large number of clinical samples and the expression of various genes,so we are included in this study.Use gene set enrichment analysis(GSEA)to analyze the colorectal adenocarcinoma gene data downloaded from the Cancer Genome Atlas(TCGA GDC)to obtain the glycolytic functional genes that need to be studied.Cox regression analysis is also known as the proportional hazard regression model.This model uses survival data as the dependent variable to analyze various factors that affect survival data.It is often used in the analysis of tumor research to explore factors that affect tumor survival and prognosis.Therefore,using Cox regression analysis,glycolytic genes that affect the survival and prognosis of colon cancer patients can be identified,and a predictive model composed of multiple genes can be established through this analysis.The risk score of the model is correlated with clinical data to obtain the analysis results of the model and data such as survival rate and tumor characteristics.Research results:The results of the GESA data screening showed that the expression of the three glycolysis data sets of GO GLYCOLYTIC PROCESS;HALLMARK GLYCOLYSIS;REACTOME GLYCOLYSIS in colon adenocarcinoma was significantly higher than that in normal colon tissue.After deleting duplicate genes,a total of 253 glycolytic genes can be used in this study.Through univariate Cox regression analysis,the relationship between 253 glycolytic genes and the survival prognosis of patients with colon adenocarcinoma was analyzed.The results showed that the genes ENO3,PPARGC1A,P4HA1,STC2,IDUA,ANKZF1,DLAT,G6PC2,ENO2,PPFIA4,GPC1 can affect the survival and prognosis of patients with colon adenocarcinoma.These genes were further analyzed by multivariate Cox regression analysis,and a prediction model consisting of 7 glycolytic genes(PPARGC1A,P4HA1,STC2,ANKZF1,DLAT,G6PC2,GPC1)was obtained,which can predict the survival prognosis of patients with colon adenocarcinoma.Finally,we carried out biological function enrichment and immune microenvironment correlation analysis of these seven genes,and found that the expression of these genes has a certain trend relationship with the content of immune microenvironment cells.Research conclusion:Using 7 glycolytic genes(PPARGC1A,DLAT,G6PC2,P4HA1,STC2,ANKZF1 and GPC1)to construct a model that can predict the survival and prognosis of patients with colon adenocarcinoma.