Integrative multiomic and immune profiling of lung adenocarcinoma: molecular landscapes, gene expression, and treatment response insights.

ABSTRACT:

Background

Lung adenocarcinoma (LUAD) is a major cause of cancer death. Traditional histopathological classification overlooks molecular heterogeneity, limiting personalized treatment. This study used multiomic data to define LUAD subtypes, assess prognostic significance, and analyze immune features, aiming to improve targeted therapy and clinical outcomes.

Methods

This study used Consensus Clustering and Gap Statistics to analyze LUAD multiomic data, including mRNA, lncRNA, miRNA, DNA methylation, and mutations. Clustering was validated by silhouette plots and heatmaps. Molecular characterization involved regulon activity, immune and metabolic profiling. Functional assays (qPCR, WB, CCK-8, flow cytometry) assessed neuronal differentiation factor (NDNF)'s role in LUAD.

Re

SUBMITTER: Dong H 

PROVIDER: S-EPMC12526892 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature