| Background and purpose:Colorectal cancer has become the third most common malignant tumor in the world,after breast cancer and lung cancer,and the second largest cause of malignant tumor death,accounting for 9.4%of all malignant tumor deaths.According to the statistics of the World Health Organization’s International Agency for Research on Cancer on global cancer in 2020,there are more than 550,000 new colorectal cancer patients in China,accounting for 28.8%of the new cases of colorectal cancer patients in the world,and the number of deaths reached 280,000,accounting for 30.6%of the global colon cancer deaths.With the socio-economic development of China,the incidence of colorectal cancer is also increasing year by year.So far,most studies have focused on tumor glycolysis.However,the biological effects affected by tumor glycolysis,especially its immuno-inflammatory modulatory,have not been well elucidated,and only a few comprehensive analyses have explored the role and relationship between tumor glycolysis and immune cells in the development of colon cancer.There is a lack of systematic research on the relationship between tumor metabolism and tumor immunity in colon cancer.The purpose of this study is to explore the relationship between glycolysis in colon cancer and the composition of immune cells and the expression of immune genes.Methods:In this study,the transcriptome data of colon cancer were obtained from the TCGA tumor database,the DGRG was obtained by the glycolytic gene of the GSEA dataset and known literature,the biological function of DGRG was viewed by GO/KEGG enrichment analysis,and then the protein interaction network was constructed to understand the interaction relationship between genes.GRGs related to prognosis were screened out by univariate Cox analysis and multivariate Cox analysis,and were divided into high-risk group and low-risk group according to risk score,and the relevant gene expression relationship and survival differences between the groups were verified.Through the construction and evaluation of prognostic models,a robust model that can be used to predict the prognosis of colon cancer was established.Independent prognostic analysis of clinical data and risk scores was performed.Then,tumor microenvironment immunity score,tumor purity,matrix score are calculated.The relationship between prognosis-related GRG expression and immune cell distribution types in colon cancer was analyzed by ssGSEA,and the relationship between risk score and immune cell infiltration,and the relationship between risk score and immune cell infiltration,and the relationship between independent prognostic factors and immune cell infiltration was analyzed by using Cibersort.Immune genes were obtained through TIP,the expression differences of immune genes between high and low risk groups were studied,and the protein interaction network construction of statistically significant immune genes and prognosis-related GRGs was carried out,and the expression relationship between immune genes and GRG was analyzed.At the same time,the expression of immune genes in the high and low risk groups was analyzed to obtain the relationship between immune gene expression and prognosis.The expression analysis of immune checkpoints between high and low risk groups was carried out to explore whether there were differences in immune checkpoint expression between high and low risk groups.Finally,through chemotherapy drug susceptibility analysis,sensitive drugs were found.Results:1.PPARGC1A,SLC2A3,SLC16A8,CLDN9,and ANKZF1 are genes related to the prognosis of glycolysis in colon cancer,and the risk scores constructed can be independent of other clinical properties and evaluate the clinical prognosis of colon cancer.2.γδT cells,resting memory C4T cells,resting NK cells,resting DC cells,Tregs,M There were statistically significant differences in the infiltration of 0 macrophages among the risk score groups.3.There were statistical differences in the invasion of various immune cells in different ages and stages of colon cancer.4.There were 24 immune genes with statistically different expressions in the high and low risk groups,and there was direct or indirect protein interaction expression with prognosis-related GRG.5.There were 28 immune checkpoint-related genes with statistically significant differences in the expression of high and low risk groups.6.There were 26 clinical differences in IC50 of chemotherapy drugs between high-and low-risk groups;Conclusion:The prognostic risk score model based on five prognosis-related colon cancer GRG can be independent of other clinical traits and has a good prognostic assessment effect,and it is sensitive to a variety of chemotherapy drugs.The differences in immune cell infiltration and the expression of immune checkpoints between colon cancer glycolysis risk scores may provide a new direction for the development of chemotherapy drugs and targeted drugs for colon cancer. |
PDF Full Text Request