Prognostic signature and immune landscape of 5-methylcytosine-related long non-coding RNAs in gastric cancer.

Background: Long non-coding RNAs (lncRNAs) have been demonstrated to be useful in assessing the prognosis of cancer patients. However, few studies have focused on 5-methylcytosine-related lncRNAs (m5C-lncRNAs) in gastric cancer (GC). In this study, we aimed to establish a m5C-lncRNAs prognostic signature (m5C-LPS) and explore its potential impact on guiding clinical practice for GC.

Methods: RNA-sequence and clinicopathological data were retrieved from The Cancer Genome Atlas (TCGA) database, while the coexpression of long non-coding RNAs (lncRNAs) was determined using Pearson's correlation analysis. A m5C-LPS model was constructed using univariate and Lasso Cox regression, and its prognostic value and accuracy were subsequently validated. Subsequently, the expression of 11 m5C-lncRNAs was verified via quantitative real-time PCR (qRT-PCR) in gastric cancer (GC) cell lines. The potential biological mechanism of this signature was elucidated using Gene Set Enrichment Analysis (GSEA). Based on the GSEA findings, CIBERSORT and ESTIMATE algorithms were utilized to conduct a comprehensive investigation of the tumor immune microenvironment (TIME) in GC. Additionally, pRRophetic and TIDE algorithms were employed to predict drug sensitivity and the efficacy of immunotherapy for GC patients.

Results: 280 lncRNAs were identified as m5C-lncRNAs, including RHPN1-AS1, AC093752.3, TSC22D1-AS1, AL391152.1, MAGI2-AS3, AC048382.2, AL033527.3, AC007405.2, AC036103.1, CCDC183-AS1, and ADORA2A-AS1. Their prognostic value was validated, and the expression of these 11 lncRNAs was confirmed in four gastric cancer cell lines using quantitative reverse transcription PCR (qRT-PCR). A nomogram incorporating a risk score was developed to provide more precise clinical decision-making. Gene Set Enrichment Analysis (GSEA) showed that many classical signaling pathways related to tumor progression were enriched in this signature. Analyses related to immunity and drug sensitivity demonstrated distinct differences in features between high-risk and low-risk subgroups.

Conclusion: The m5C-LPS can predict the survival of gastric cancer (GC) patients, provide novel therapeutic targets, and thus offer more thoughtful perspectives for future clinical decisions regarding GC.