Metabolites are important indicators of cancer and mutations in genes involved in amino acid metabolism may influence tumorigenesis. Immunotherapy is an effective cancer treatment option; however, its relationship with amino acid metabolism has not been reported. In this study, RNA-seq data for 371 liver cancer patients were acquired from TCGA and used as the training set. Data for 231 liver cancer patients were obtained from ICGC and used as the validation set to establish a gene signature for predicting liver cancer overall survival outcomes and immunotherapeutic responses. Four reliable groups based on 132 amino acid metabolism-related DEGs were obtained by consistent clustering of 371 HCC patients and a four-gene signature for prediction of liver cancer survival outcomes was developed. Our data show that in different clinical groups, the overall survival outcomes in the high-risk group were markedly low relative to the low-risk group. Univariate and multivariate analyses revealed that the characteristics of the 4-gene signature were independent prognostic factors for liver cancer. The ROC curve revealed that the risk characteristic is an efficient predictor for 1-, 2-, and 3-year HCC survival outcomes. The GSVA and KEGG pathway analyses revealed that high-risk score tumors were associated with all aspects of the degree of malignancy in liver cancer. There were more mutant genes and greater immune infiltrations in the high-risk groups. Assessment of the three immunotherapeutic cohorts established that low-risk score patients significantly benefited from immunotherapy. Then, we established a prognostic nomogram based on the TCGA cohort. In conclusion, the 4-gene signature is a reliable diagnostic marker and predictor for immunotherapeutic efficacy.
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http://dx.doi.org/10.1007/s10528-023-10502-w | DOI Listing |
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