Development of a novel colon adenocarcinoma m6A-related lncRNA pair prognostic model

Abstract

Abstract Background: Colon adenocarcinoma (COAD) is among the most prevalent malignancies. N6-methyladenosine (m6A) alterations, the most prevalent RNA modification, can influence COAD progress. In addition, long noncoding RNA (lncRNA) plays an important role in COAD and is closely related to m6A modification. However, the prognostic value of lncRNAs associated to m6A in COAD is unknown. Methods: In present study, the information from The Cancer Genome Atlas (TCGA) was employed to examine the predictive relevance of m6A-related lncRNA pair signatures in COAD. M6A-related lncRNAs was identified based on co-expression analysis utilizing the Pearson correlation. Then, the lncRNAs paired related to prognosis were identified, followed by univariate Cox regression analysis. The receiver operating characteristic (ROC) curves for predicting overall survival (OS) were conducted by using the least absolute shrinkage and selection operator (LASSO) penalized Cox analysis to identify and construct a risk score prognostic model. After determining if it was an independent prognostic factor, relationships between the risk score model and clinical traits, immune-related factors, and medication sensitivity analysis were analysed. Results: A total of 319 m6A-related lncRNA pairs were found, and 35 of which were connected to a predictive pattern for risk scores. The risk score model was proven to be an independent predictive factor and was notably superior to the clinicopathological features. Correlation analyses revealed differences between high- and low-risk groups in clinicopathological characteristics, immune-related factors, and drug sensitivity analysis. Conclusions: The novel COAD prognostic model based on paired differentially expressed m6A-related lncRNAs showed promising clinical predictive value. Conclusions: The novel COAD prognostic model based on paired differentially expressed m6A-related lncRNAs showed promising clinical predictive value.