Abstract
Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small-cell lung cancer and is frequently diagnosed at advanced stages with metastasis, contributing to its poor prognosis. Identifying key metastasis-related biomarkers is critical for improving early diagnosis and therapeutic targeting. Methods: We analyzed four GEO microarray datasets (GSE32863, GSE27262, GSE40275, and GSE33356) and TCGA data to identify differentially expressed genes (DEGs) in LUAD. Functional enrichment of DEGs was analyzed using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, and a Cancer Hallmark Enrichment Plot. Hub gene analysis was conducted using Cytoscape. Hub genes were evaluated for their expression, prognostic significance (via the Kaplan-Meier plotter), and clinical correlation using additional platforms (TCGA, Lung Cancer Explorer, TNMplot, and the Human Protein Atlas). Results: A total of 333 consistently dysregulated DEGs were identified, enriched in pathways related to metastasis, including angiogenesis, immune escape, and ECM interaction. Ten hub genes (AURKA, TOP2A, CCNB2, CENPF, MCM4, TPX2, KIF20A, ASPM, MELK, and NEK2) were identified through network analysis. Among these, MCM4 showed strong upregulation in LUAD and was significantly associated with poor overall survival. Notably, MCM4 expression also correlated with post-progression survival and markers of invasiveness. Immunohistochemistry and transcriptomic analyses confirmed MCM4 overexpression at both mRNA and protein levels. Additionally, MCM4 expression was positively correlated with various matrix metalloproteinases, supporting its role in promoting tumor invasiveness. Conclusions:MCM4 is a novel potential biomarker for LUAD metastasis and prognosis. Its consistent upregulation, association with metastatic markers, and clinical significance suggest it may serve as a candidate target for diagnostic use or therapeutic intervention in advanced LUAD.