Comprehensive Analysis of m6A-Related Programmed Cell Death Genes Unveils a Novel Prognostic Model for Lung Adenocarcinoma

Abstract

Lung adenocarcinoma (LUAD) involves complex dysregulated cellular processes, including programmed cell death (PCD), influenced by N6-methyladenosine (m6A) RNA modification. This study integrates bulk RNA and single-cell sequencing data to identify 43 prognostically valuable m6A-related PCD genes, forming the basis of a 13-gene risk model (m6A-related PCD signature [mPCDS]) developed using machine-learning algorithms, including CoxBoost and SuperPC. The mPCDS demonstrated significant predictive performance across multiple validation datasets. In addition to its prognostic accuracy, mPCDS revealed distinct genomic profiles, pathway activations, associations with the tumour microenvironment and potential for predicting drug sensitivity. Experimental validation identified RCN1 as a potential oncogene driving LUAD progression and a promising therapeutic target. The mPCDS offers a new approach for LUAD risk stratification and personalised treatment strategies.