Prognostic signature analysis and survival prediction of esophageal cancer based on N6-methyladenosine associated lncRNAs

Jul 19, 2023Briefings in functional genomics

Predicting esophageal cancer survival using long non-coding RNAs linked to N6-methyladenosine

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Abstract

Five m6A-associated long non-coding RNAs (m6A-lncRNAs) were identified as potential prognostic biomarkers for esophageal cancer.

Univariate Cox analysis revealed significant differences in overall survival and clinical traits across different clusters of m6A-lncRNAs.
Risk score derived from the m6A-lncRNAs was associated with N stage, tumor stage, and various immune cell types, including M2 macrophages and naive B cells.
Risk score and tumor stage were identified as independent prognostic variables.
A nomogram model constructed using the risk score demonstrated high accuracy in predicting patient prognosis.

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Esophageal cancer (ESCA) has a bad prognosis. Long non-coding RNA (lncRNA) impacts on cell proliferation. However, the prognosis function of N6-methyladenosine (m6A)-associated lncRNAs (m6A-lncRNAs) in ESCA remains unknown. Univariate Cox analysis was applied to investigate prognosis related m6A-lncRNAs, based on which the samples were clustered. Wilcoxon rank and Chi-square tests were adopted to compare the clinical traits, survival, pathway activity and immune infiltration in different clusters where overall survival, clinical traits (N stage), tumor-invasive immune cells and pathway activity were found significantly different. Through least absolute shrinkage and selection operator and proportional hazard (Lasso-Cox) model, five m6A-lncRNAs were selected to construct the prognostic signature (m6A-lncSig) and risk score. To investigate the link between risk score and clinical traits or immunological microenvironments, Chi-square test and Spearman correlation analysis were utilized. Risk score was found connected with N stage, tumor stage, different clusters, macrophages M2, B cells naive and T cells CD4 memory resting. Risk score and tumor stage were found as independent prognostic variables. And the constructed nomogram model had high accuracy in predicting prognosis. The obtained m6A-lncSig could be taken as potential prognostic biomarker for ESCA patients. This study offers a theoretical foundation for clinical diagnosis and prognosis of ESCA.

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Prognostic signature analysis and survival prediction of esophageal cancer based on N6-methyladenosine associated lncRNAs

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