Construction of an HCC recurrence model basedon the investigation of immune-relatedlncRNAs and related mechanisms

基于免疫相关lncRNA及其相关机制的研究,构建肝细胞癌复发模型

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Abstract

Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and play fundamental roles in immune regulation. Growing evidence suggests that immune-related genes and lncRNAs can serve as markers to predict the prognosis of patients with cancers, including hepatocellular carcinoma (HCC). This study aimed to contract an immune-related lncRNA (IR-lncRNA) signature for prospective assessment to predict early recurrence of HCC. A total of 319 HCC samples under radical resection were randomly divided into a training cohort (161 samples) and a testing cohort (158 samples). In the training dataset, univariate, lasso, and multivariate Cox regression analyses identified a 9-IR-lncRNA signature closely related to disease-free survival. Kaplan-Meier analysis, principal component analysis, gene set enrichment analysis, and nomogram were used to evaluate the risk model. The results were further confirmed in the testing cohort. Furthermore, we constructed a competitive endogenous RNA regulatory network. The results of the present study indicated that this 9-IR-lncRNA signature has important clinical implications for improving predictive outcomes and guiding individualized treatment in HCC patients. These IR-lncRNAs and regulated genes may be potential biomarkers associated with the prognosis of HCC.

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