AI Article Synopsis
- The study focuses on identifying long non-coding RNAs (lncRNAs) related to the prognosis of liver hepatocellular carcinoma (LIHC) through N-methyladenosine (mA) modification.
- A significant number of differentially expressed (DE) mRNAs and lncRNAs were identified, leading to the construction of an 11-lncRNA prognostic model that can predict survival outcomes for LIHC patients.
- The findings suggest that immune cells and mA-related genes could be explored as potential new therapeutic targets for treating LIHC.
Article Abstract
Background: Liver hepatocellular carcinoma (LIHC) is a lethal cancer. This study aimed to identify the N -methyladenosine (m A)-targeted long non-coding RNA (lncRNA) related to LIHC prognosis and to develop an m A-targeted lncRNA model for prognosis prediction in LIHC.
Methods: The expression matrix of mRNA and lncRNA was obtained, and differentially expressed (DE) mRNAs and lncRNAs between tumor and normal samples were identified. Univariate Cox and pathway enrichment analyses were performed on the m A-targeted lncRNAs and the LIHC prognosis-related m A-targeted lncRNAs. Prognostic analysis, immune infiltration, and gene DE analyses were performed on LIHC subgroups, which were obtained from unsupervised clustering analysis. Additionally, a multi-factor Cox analysis was used to construct a prognostic risk model based on the lncRNAs from the LASSO Cox model. Univariate and multivariate Cox analyses were used to assess prognostic independence.
Results: A total of 5031 significant DEmRNAs and 292 significant DElncRNAs were screened, and 72 LIHC-specific m A-targeted binding lncRNAs were screened. Moreover, a total of 29 LIHC prognosis-related m A-targeted lncRNAs were obtained and enriched in cytoskeletal, spliceosome, and cell cycle pathways. An 11-m A-lncRNA prognostic model was constructed and verified; the top 10 lncRNAs included LINC00152, RP6-65G23.3, RP11-620J15.3, RP11-290F5.1, RP11-147L13.13, RP11-923I11.6, AC092171.4, KB-1460A1.5, LINC00339, and RP11-119D9.1. Additionally, the two LIHC subgroups, Cluster 1 and Cluster 2, showed significant differences in the immune microenvironment, m A enzyme genes, and prognosis of LIHC.
Conclusion: The m A-lncRNA prognostic model accurately and effectively predicted the prognostic survival of LIHC. Immune cells, immune checkpoints (ICs), and m A enzyme genes could act as novel therapeutic targets for LIHC.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8649367 | PMC |
| http://dx.doi.org/10.1002/jcla.24071 | DOI Listing |
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