Differential gene expression analysis and machine learning identified structural, TFs, cytokine and glycoproteins, including SOX2, TOP2A, SPP1, COL1A1, and TIMP1 as potential drivers of lung cancer.
Journal:
Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals
PMID:
39888730
Abstract
BACKGROUND: Lung cancer is a primary global health concern, responsible for a considerable portion of cancer-related fatalities worldwide. Understanding its molecular complexities is crucial for identifying potential targets for treatment. The goal is to slow disease progression and intervene early to prevent the development of advanced lung cancer cases. Hence, there's an urgent need for new biomarkers that can detect lung cancer in its early stages.
Authors
Keywords
Biomarkers, Tumor
Collagen Type I
Collagen Type I, alpha 1 Chain
DNA Topoisomerases, Type II
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Gene Regulatory Networks
Humans
Lung Neoplasms
Machine Learning
Osteopontin
Poly-ADP-Ribose Binding Proteins
Protein Interaction Maps
SOXB1 Transcription Factors
Tissue Inhibitor of Metalloproteinase-1