Construction of a five-gene prognostic model involving T cell exhaustion and metabolic reprogramming for predicting hepatocellular carcinoma risk using LASSO: insights into immune infiltration and drug sensitivity - Nature
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AbstractHepatocellular carcinoma (HCC) ranks as one of the most common and deadly malignancies in the world. Its pathogenesis is closely correlated with T cell exhaustion and metabolic reprogramming, these two critical yet underexplored mechanisms can profoundly shape the tumor immune microenvironment (TIME) and drive disease progression. This study was designed for constructing a prognosis risk model for HCC and elucidating its correlations with immune infiltration and drug sensitivity by integrating these two biological processes. An integrated bioinformatics analysis was performed by using data from two datasets such as Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) and Gene Expression Omnibus (GEO, including GSE76427 and GSE10186). Fifty seven overlapping genes associated with both T cell exhaustion and metabolic reprogramming were screened.
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