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Research on the correlation between lung adenocarcinoma and necrosis by sodium overload
Jianxu Yuan1, Dalin Zhou2, Shengjie Yu2
1Department of Surgery, Xinqiao Hospital of Army Medical University, Army Medical University, Chongqing, China.
Background:
Necrosis by sodium overload (NECSO), a necrotic pathway triggered by sodium overload, has been implicated in various cellular processes. Its link to lung adenocarcinoma (LUAD) remained unexplored; this study investigated the potential relationship between NECSO and LUAD.
Methods:
We interrogated the interplay between LUAD and NECSO through an integrated multi-omics workflow. First, RNA sequencing (RNA-seq) expression profiles, paired clinical annotations, and somatic mutation data were retrieved from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) and harmonized within R v4.4.1. NECSO-related genes were then mined via co-expression analysis anchored to transient receptor potential melastatin 4 (TRPM4), the established gatekeeper of NECSO. Functional implications were delineated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Subsequently, a prognostic risk-score model was constructed from survival-associated candidates and rigorously validated through Kaplan-Meier survival analysis, receiver operating characteristic (ROC) assessment, and calibration curves. Finally, we performed immune cell infiltration and drug sensitivity analyses, thereby completing a coherent pipeline from data integration to clinical translation.
Results:
Our analyses identified multiple potential NECSO-related genes in LUAD. We developed a prognostic model with 10 predictive genes (ACAD8, CORO1B, KIAA0513, PRDM16, PLEKHA6, VPS37B, B3GNT3, ZNF574, RNPEPL1, and TERF2IP) that demonstrated strong predictive performance. This model revealed significant survival differences between high- and low-risk patient groups (P<0.05). Its independent prognostic value was evaluated through univariate and multivariate Cox regression analyses, adjusted for other clinical covariates. Moreover, the model's predictive accuracy was assessed via ROC analysis. Immune cell infiltration analysis showed a significant correlation between these genes and the infiltration levels of various immune cells in LUAD tissues. Based on these genes, we also identified several potential therapeutic agents and conducted drug sensitivity analyses.
Conclusions:
This study elucidated the potential mechanisms of NECSO in LUAD and established an effective prognostic model, offering novel insights for the diagnosis and treatment of LUAD.
