Table_1_Comprehensive Analysis of Glycolysis-Related Genes for Prognosis, Immune Features, and Candidate Drug Development in Colon Cancer.XLSX (11.91 kB)
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Table_1_Comprehensive Analysis of Glycolysis-Related Genes for Prognosis, Immune Features, and Candidate Drug Development in Colon Cancer.XLSX

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posted on 06.08.2021, 04:52 by Zhongqi Cui, Guifeng Sun, Ramesh Bhandari, Jiayi Lu, Mengmei Zhang, Rajeev Bhandari, Fenyong Sun, Zhongchen Liu, Shasha Zhao

The dysregulated expression of glycolysis-related genes (GRGs) is closely related to the occurrence of diverse tumors and regarded as a novel target of tumor therapy. However, the role of GRGs in colon cancer is unclear. We obtained 226 differential GRGs (DE-GRGs) from The Cancer Genome Atlas (TCGA) database. Cox regression analysis was used to construct a DE-GRG prognostic model, including P4HA1, PMM2, PGM2, PPARGC1A, PPP2CB, STC2, ENO3, and CHPF2. The model could accurately predict the overall survival rate of TCGA and GSE17536 patient cohorts. The risk score of the model was closely related to a variety of clinical traits and was an independent risk factor for prognosis. Enrichment analysis revealed the activation of a variety of glycolysis metabolism and immune-related signaling pathways in the high-risk group. High-risk patients displayed low expression of CD4+ memory resting T cells and resting dendritic cells and high expression of macrophages M0 compared with the expression levels in the low-risk patients. Furthermore, patients in the high-risk group had a higher tumor mutation load and tumor stem cell index and were less sensitive to a variety of chemotherapeutic drugs. Quantitative reverse transcription polymerase chain reaction and immunohistochemistry analyses validated the expression of eight GRGs in 43 paired clinical samples. This is the first multi-omics study on the GRGs of colon cancer. The establishment of the risk model may benefit the prognosis and drug treatment of patients.

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