Amino acid metabolism genes associated with immunotherapy responses and clinical prognosis of colorectal cancer

Abstract

Based on amino acid metabolism-related genes (AAMRGs), this study aimed at screening out key prognosis-related genes and finding the underlying correlation between the amino acid metabolism and tumor immune microenvironment of colorectal cancer. A total of 448 amino acid metabolism-related genes were obtained from MsigDB. The risk signature was built based on differential expression genes, univariate Cox, and LASSO analyses with 403 patients’ data downloaded from the TCGA database. Survival analysis and independence tests were performed to confirm the validity of the risk signature. Single-sample gene set enrichment analysis (ssGSEA), tumor mutation burden (TMB), the score of tumor immune dysfunction and exclusion (TIDE), the immunophenoscore obtained from The Cancer Immunome Atlas database, and the IC50 of drugs were used to find the relationship among the risk signature, immune status, immunotherapy response, and drug sensitivity of colorectal cancer. We identified five amino acid metabolism-related genes for the construction of the risk signature, including ENOPH1, ACAT1, ALDH4A1, FAS, and ASPG. The low-risk group was significantly associated with a better prognosis (p < 0.0001). In the entire set, the area under the curve (AUC) for 1, 3, and 5 years was 0.717, 0.734, and 0.764, respectively. We also discovered that the low-risk subgroup was related to more activity of immune cells, had higher expression of some immune checkpoints, and was more likely to benefit from immunotherapy. ssGSEA revealed that except the processes of glutamine histidine, lysine, tyrosine, and L-phenylalanine metabolism, the other amino acid metabolism pathways were more active in the samples with the low risk scores, whereas the activities of synthesis and transportation of most amino acids were similar. Hedgehog signaling, WNT/β-catenin signaling, mitotic, notch signaling, and TGF-β signaling were the top five pathways positively associated with the risk score. To sum up, AAMRGs were associated with the immune microenvironment of CRC patients and could be applied as biomarkers to predict the prognosis and immunotherapy response of patients.