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Liver hepatocellular carcinoma (LIHC) can be detected by the immune system; however, it acquires features for evasion of immune surveillance during its origin and development. Long non-coding RNAs (lncRNAs) are critical as immune regulators in cancers; nevertheless, the biological functions and mechanisms of lncRNAs in evasion of immune system by LIHC remain unclear. In this study, an integrated and computational approach was developed to identify immune-related lncRNAs and to divide LIHC patients into diverse immune-related risk groups based on the expression profiles of coding genes and lncRNAs. LIHC-specific genes and lncRNAs in 17 immune cell populations were identified and analysed. Gene and lncRNA co-expressing networks for diverse immune cell populations were constructed and analysed. Some imported immune-related lncRNAs, such as MIR9-3HG, were also identified. The LIHC patients comprised three different groups based on immune-related risk. LIHC patients possessing a greater diversity of immune cell populations had better survival prognosis. The collective data are evidence of a credible computational model that can prioritize novel immune-related lncRNAs and depict the atlas of immune-related lncRNAs in LIHC. These findings will further the understanding of lncRNA function and advance the identification of immunotherapy targets in LIHC.
Pubmed ID: 32910548
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Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.
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