Integrated Analysis of N6-methyladenosine- and 5-methylcytosine-related Long Non-coding RNAs for Predicting Prognosis in Cervical Cancer

Overview

Journal Hereditas

Specialty Genetics

Date 2024 Sep 16

PMID 39285452

Authors

Jie Gao

Xiuling Zhang

Anqi Xu

Wei Li

Haiyan Gao

Affiliations

Soon will be listed here.

Abstract

Background: N6-methyladenosine (mA) and 5-methylcytosine (mC) play a role in modifying long non-coding RNAs (lncRNAs) implicated in tumorigenesis and progression. This study was performed to evaluate prognostic value of mA- and mC-related lncRNAs and develop an efficient model for prognosis prediction in cervical cancer (CC).

Methods: Using gene expression data of TCGA set, we identified mA- and mC-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 mA-related genes, 15 mC-related genes, and 62 lncRNAs. Based on 9 mA- and mC-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 mA- and mC-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 mA- and mC-related lncRNAs are associated with prognosis and immune microenvironment of CC. The mA- and mC-related six-lncRNA signature may be a useful tool for survival stratification in CC and open new avenues for individualized therapies.

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