Abstract
BACKGROUND: N6-methyladenosine (m(6)A) and 5-methylcytosine (m(5)C) play a role in modifying long non-coding RNAs (lncRNAs) implicated in tumorigenesis and progression. This study was performed to evaluate prognostic value of m(6)A- and m(5)C-related lncRNAs and develop an efficient model for prognosis prediction in cervical cancer (CC). METHODS: Using gene expression data of TCGA set, we identified m(6)A- and m(5)C-related lncRNAs. Consensus Clustering Analysis was performed for samples subtyping based on survival-related lncRNAs, followed by analyzing tumor infiltrating immune cells (TIICs). Optimal signature lncRNAs were obtained using lasso Cox regression analysis for constructing a prognostic model and a nomogram to predict prognosis. RESULTS: We built a co-expression network of 23 m(6)A-related genes, 15 m(5)C-related genes, and 62 lncRNAs. Based on 9 m(6)A- and m(5)C-related lncRNAs significantly associated with overall survival (OS) time, two molecular subtypes were obtained, which had significantly different OS time and fractions of TIICs. A prognostic model based on six m(6)A- and m(5)C-related signature lncRNAs was constructed, which could dichotomize patients into two risk subgroups with significantly different OS time. Prognostic power of the model was successfully validated in an independent dataset. We subsequently constructed a nomogram which could accurately predict survival probabilities. Drug sensitivity analysis found preferred chemotherapeutic agents for high and low-risk patients, respectively. CONCLUSION: Our study reveals that m(6)A- and m(5)C-related lncRNAs are associated with prognosis and immune microenvironment of CC. The m(6)A- and m(5)C-related six-lncRNA signature may be a useful tool for survival stratification in CC and open new avenues for individualized therapies.