Identification of a TRP channel-related risk model for predicting prognosis and therapeutic effects of patients with hepatocellular carcinoma.

Purpose: TRP channels have been implicated in cancer progression. Our study seeks to establish a prognostic model for hepatocellular carcinoma (HCC) by utilizing genes related to TRP channels. Methods: We used the TCGA and ICGC databases as training and validation cohorts, respectively. We calculated the risk scores using Lasso–Cox regression analysis based on the expression levels of prognostic genes and performed survival analysis to compare overall survival between high- and low-risk groups. Then we compared the clinicopathologic characteristics and conducted biological functional analysis. We also explored immune cell infiltration and compared the drug sensitivity. Results: Using bioinformatics algorithms, we identified 11 TRP-related genes and calculated the risk scores. Patients in the high-risk group demonstrated worse overall survival, as well as more advanced T stage and pathologic stage. The risk score showed a significant association with the cell cycle. The high-risk group had more ICI and RTK targets with elevated expression and showed better therapeutic effect to chemotherapy including 5-fluorouracil, camptothecin, docetaxel, doxorubicin, gemcitabine, and paclitaxel. Overall, an individualized nomogram was constructed by integrating the risk score and requisite clinicopathologic parameters to predict the overall survival of HCC patients. Conclusions: We successfully established a highly accurate prognostic model for predicting overall survival and therapeutic effects using TRP channel-related genes. [ABSTRACT FROM AUTHOR]