Characterization of the fatty acid metabolism in colorectal cancer to guide clinical therapy
Chengsheng Ding, Zezhi Shan, Mengcheng Li, Hongqi Chen, Xinxiang Li, Zhiming Jin
Abstract
Colorectal cancer (CRC) is one of the most common malignant tumors, with the second-highest mortality of all 36 cancers worldwide. The roles of fatty acid metabolism in CRC were investigated to explore potential therapeutic strategies. The data files were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to construct a prognostic risk score model with fatty acid metabolism-related genes for predicting prognosis in CRC. Patients with a high-risk score had a poorer prognosis in TCGA cohort than those with a low-risk score and were confirmed in the GEO cohort. Further analysis using the “pRRophetic” R package revealed that low-risk patients were more sensitive to 5-fluorouracil. A comprehensive evaluation of the association between prognostic risk score model and tumor microenvironment (TME) characteristics showed that high-risk patients were suitable for activating a type I/II interferon (IFN) response and inflammation-promoting function. Tumor Immune Dysfunction and Exclusion (TIDE) and SubMap algorithm results also demonstrated that high-risk patients are more suitable for anti-CTLA4 immunotherapy. Therefore, the evaluation of the fatty acid metabolism pattern promotes our comprehension of TME infiltration characteristics, thus guiding effective immunotherapy regimens. Colorectal cancer (CRC) is one of the most common malignant tumors, with the second-highest mortality of all 36 cancers worldwide. The roles of fatty acid metabolism in CRC were investigated to explore potential therapeutic strategies. The data files were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to construct a prognostic risk score model with fatty acid metabolism-related genes for predicting prognosis in CRC. Patients with a high-risk score had a poorer prognosis in TCGA cohort than those with a low-risk score and were confirmed in the GEO cohort. Further analysis using the “pRRophetic” R package revealed that low-risk patients were more sensitive to 5-fluorouracil. A comprehensive evaluation of the association between prognostic risk score model and tumor microenvironment (TME) characteristics showed that high-risk patients were suitable for activating a type I/II interferon (IFN) response and inflammation-promoting function. Tumor Immune Dysfunction and Exclusion (TIDE) and SubMap algorithm results also demonstrated that high-risk patients are more suitable for anti-CTLA4 immunotherapy. Therefore, the evaluation of the fatty acid metabolism pattern promotes our comprehension of TME infiltration characteristics, thus guiding effective immunotherapy regimens.