Amino acid metabolism-related LncRNAs as prognostic biomarkers and predictors of immunotherapy response in hepatocellular carcinoma.

BACKGROUND: HCC has a high mortality rate among common malignancies. Finding the pathway that is involved with HCC is the main challenge in targeting metabolism for cancer therapy. METHODS: Based on transcription data from the TCGA database, Univariate Cox analysis, LASSO, and Multivariate Cox analysis were used to identify hub AAM-related lncRNAs and construct a risk model. Then K-M survival analysis, time-dependent ROC curve analysis, genetic alterations, functional enrichment, immune infiltration status, and immunotherapy response were conducted. Finally, the effect of the characteristic gene AL590681.1 across different HCC cell lines was assessed. RESULTS: 24 lncRNAs were involved in AAM and prognostic factors, and 4 lncRNAs were in our risk model. Patients in the high-risk group had a lower OS rate than patients in the low-risk group. The high-risk group had more immunosuppressive immune cells infiltrating and expressing CD276, CTLA4 and TIGIT. Patients in the high-risk group could had better survival prospects with an anti-PD1 treatment. Finally, the key gene AL590681.1 was overexpressed in various HCC cell lines and could enhance HCC cell activity. CONCLUSION: We developed a novel risk model for HCC patients with AAM-related lncRNAs, which could help predict the prognosis and response to immunotherapy.