Journal of Microbiology and Biotechnology

The Korean Society for Microbiology and Biotechnology (한국미생물·생명공학회)
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Prognostic Value of an Immune Long Non-Coding RNA Signature in Liver Hepatocellular Carcinoma

  • Rui Kong (Department of Gastroenterology, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University) ;
  • Nan Wang (Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine) ;
  • Chun li Zhou (Department of Gastroenterology, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University) ;
  • Jie Lu (Department of Gastroenterology, Pu Dong Area Gongli Hospital, School of Medicine, Shanghai University)
  • Received : 2023.08.14
  • Accepted : 2024.01.18
  • Published : 2024.04.28
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Abstract

In recent years, there has been a growing recognition of the important role that long non-coding RNAs (lncRNAs) play in the immunological process of hepatocellular carcinoma (LIHC). An increasing number of studies have shown that certain lncRNAs hold great potential as viable options for diagnosis and treatment in clinical practice. The primary objective of our investigation was to devise an immune lncRNA profile to explore the significance of immune-associated lncRNAs in the accurate diagnosis and prognosis of LIHC. Gene expression profiles of LIHC samples obtained from TCGA database were screened for immune-related genes. The optimal immune-related lncRNA signature was built via correlational analysis, univariate and multivariate Cox analysis. Then, the Kaplan-Meier plot, ROC curve, clinical analysis, gene set enrichment analysis, and principal component analysis were performed to evaluate the capability of the immune lncRNA signature as a prognostic indicator. Six long non-coding RNAs were identified via correlation analysis and Cox regression analysis considering their interactions with immune genes. Subsequently, tumor samples were categorized into two distinct risk groups based on different clinical outcomes. Stratification analysis indicated that the prognostic ability of this signature acted as an independent factor. The Kaplan-Meier method was employed to conduct survival analysis, results showed a significant difference between the two risk groups. The predictive performance of this signature was validated by principal component analysis (PCA). Additionally, data obtained from gene set enrichment analysis (GSEA) revealed several potential biological processes in which these biomarkers may be involved. To summarize, this study demonstrated that this six-lncRNA signature could be identified as a potential factor that can independently predict the prognosis of LIHC patients.

Keywords

Acknowledgement

This study was supported by : (1) "Special Project for Scientific Research and Cultivation of Young Physician" of Gusu School, Nanjing Medical University (GSKY20230503) to Rui Kong. (2) Shanghai "Rising Stars of Medical Talent" Youth Development Program-Outstanding Youth Medical Talents (No.SHWJRS2021-99) to Jie Lu. (3) Shanghai Pudong New Area Science and Technology Commission (No.PKJ2021-Y10) to Jie Lu. (4) Specialty Feature Construction Project of Pudong Health and Family Planning Commission of Shanghai?PWZzb2022-14) to Jie Lu.

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