Currently submitted to: JMIR Medical Informatics
Date Submitted: Dec 16, 2025
Open Peer Review Period: Jan 3, 2026 - Feb 28, 2026
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Identification of Main Biomarkers in NSCLC Through a Multi-Platform Genomic Network Analysis
ABSTRACT
Background:
Non-Small Cell Lung Cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide. The identification and prioritization of molecular biomarkers involved in NSCLC pathogenesis are essential for advancing early diagnostic strategies and optimizing therapeutic interventions.
Objective:
This study aimed to utilize genomic network approaches and bioinformatics tools to prioritize clinically relevant biomarkers associated with NSCLC.
Methods:
Non-Small Cell Lung Cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide. The identification and prioritization of molecular biomarkers involved in NSCLC pathogenesis are essential for advancing early diagnostic strategies and optimizing therapeutic interventions. This study aimed to utilize genomic network approaches and bioinformatics tools to prioritize clinically relevant biomarkers associated with NSCLC.
Results:
Data integration from three major genomic repositories DisGeNET, GWAS Catalog, and cBioPortal 1,317 NSCLC associated genes. Subsequent analyses included gene ontology enrichment, pathway enrichment, and protein–protein interaction (PPI) network construction. Network-based prioritization identified ten key hub genes: TP53, MYC, PTEN, CTNNB1, ACBT, STAT3, CCND1, AKT1, ESR1, and HIP1A, with TP53, MYC, PTEN, CTNNB1 as the most prominent biomarkers according to CytoHubba scoring.
Conclusions:
This study presents a genomic network-based framework for identifying and prioritizing potential NSCLC biomarkers, offering critical insights into the molecular underpinnings of NSCLC pathogenesis.
Citation
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