Background
In cancer, the process of anoikis is intimately associated with the emergence and progression. N6-methyladenosine modification and m6A modification play an important role in regulating long non-coding RNAs. The liver hepatocellular carcinoma patients’ data, including clinical and prognostic data, were obtained via The Cancer Genome Atlas database. The univariate, multivariate Cox and Least Absolute Selection Operator (LASSO) regression were performed to gain anoikis- and m6A-related lncRNAs. The Kaplan-Meier method was employed to assess the overall survival rate for groups of high- and low risks.
Results
A signature comprising six anoikis- and m6A-related lncRNAs was constructed: AL117336.3, LINC01138, Z83851.1, NRAV, CASC19 and AC009283.1. The clinicopathological variables, the anoikis- and m6A-related lncRNA signature demonstrated superior diagnostic efficacy, with an area under the receiver operating characteristic curve of 0.810. In the high-risk group, the overall survival was shown to be inferior to that of in group of low risk, while patients were classified by distinct clinicopathological variables. The ssGSEA and CIBERSORT immune analysis demonstrated that the predictive signature was significantly associated with liver cancer patients’ immune status. The chemotherapy drugs ATRA, AUY922, bexarotene, gemcitabine, mitomycin-C, and PHA have been found to have greater sensitivity in treating high-risk patients. qRT-PCR showed that Z83851.1, NRAV and CASC19 lncRNAs were associated with poor prognosis and were high-risk factors. AC009283.1 lncRNA may have anti-cancer properties.
Conclusions
The predictive signature is capable of independently predicting the prognosis of liver cancer patients for understanding the mechanisms of anoikis- and m6A-related lncRNAs in liver hepatocellular carcinoma and offering clinical guidance to patients with liver cancer.
How to cite: Yu P, Jing S, Dhillon SK. Anoikis and m6A related lncRNAs analysis to identify prognostic indicators in liver hepatocellular carcinoma. Electron J Biotechnol 2026;79. https://doi.org/10.1016/j.ejbt.2025.100701.
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