An immune infiltration-related long non-coding RNAs signature predicts prognosis for hepatocellular carcinoma - Li, Gen; Xu, Shaodian; Yang, Shuai; Wu, Cong; Zhang, Liangliang; Wang, Hongbing (Frontiers in Genetics, 2022)
Background: As one of the most common malignancies in the world, hepatocellular carcinoma (HCC) has a poor prognosis. Immunotherapy is a new method of treating tumors, which has the effect of prolonging the overall survival (OS) of patients from person to person. For a more effective prognosis and treatment of HCC, we are committed to identifying immune infiltration-related long non-coding RNAs (IIRLs) with prognostic value in hepatocellular carcinoma. Methods: In this study, we calculated immune scores of 369 hepatocellular carcinoma samples from the Cancer Genome Atlas (TCGA) database by using an estimation algorithm, and obtained long non-coding RNAs (lncRNAs) associated with immune infiltration by using Weighted Gene Co-expression Network analysis (WGCNA). For training cohort, univariate Cox, least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analysis were applied to identify prognostic IIRLs and then we construct a prognostic IIRLs signature. Testing cohort and entire cohort were applied to verify the prognostic signature. The nomogram was used to predict the prognosis of different clinicopathological stages and risk scores. In addition, Immune cell infiltration analysis and prediction of therapeutic drugs were performed. Results: 93 IIRLs were obtained by WGCNA. Furthermore, univariate Cox, Lasso and multivariate Cox analysis were used to assess the prognostic value of these IIRLs. A prognostic risk model of four IIRLs was constructed. Time-related receiver operating characteristic (ROC) curve revealed that this model had an acceptable prognostic value for HCC patients. Through univariate and multivariate Cox regression analysis, by combining clinical pathologic features, this risk model was validated as a new independent prognostic factor for HCC, and the nomogram we made showed good predictions. Except for that, the treatment with immune checkpoint inhibitors (ICI) was likely to be more effective for patients in the low-risk group. Conclusion: This study constructed a prognostic model based on four immune infiltration-related lncRNAs, which showed good accuracy in predicting OS. This study also provided valuable references for Immunotherapy of hepatocellular carcinoma.