Abstract
BACKGROUND: Hypoxia contributes to the proliferation, migration, and chemotherapy resistance of lung adenocarcinoma (LUAD). This study aimed to identify hypoxia-related genes (HRGs) in LUAD that were positively correlated with hypoxia-inducible factor 1 alpha (HIF1A), to advance the diagnosis and treatment of this specific type of cancer. METHODS: The transcriptome data were retrieved from the Gene Expression Omnibus (GEO). Multiple bioinformatics analysis methods were employed to identify HRGs that were upregulated in LUAD samples and positively correlated with the expression of HIF1A. Machine Learning algorithms were utilized for optimized selection, filtering out core HRGs highly associated with the disease. Finally, in vitro experiments confirmed the expression of these core HRGs in LUAD cells under hypoxic conditions. RESULTS: The study revealed five core HRGs that exhibit a positive correlation with HIF1A [collagen type I alpha 1 chain (COL1A1), interleukin 11 (IL11), matrix metallopeptidase 14 (MMP14), notch receptor 3 (NOTCH3), and thymocyte differentiation antigen 1 (THY1)]. In vitro experiments conducted on A549 cells demonstrated a marked increase in mRNA expression for both the identified core HRGs and HIF1A following chronic intermittent hypoxia (CIH) treatment. The developed model exhibits substantial predictive efficacy for assessing the prognosis of LUAD patients experiencing concurrent hypoxia. CONCLUSIONS: The five HRGs that we have identified as positively associated with HIF1A may serve as crucial targets for promoting the progression of LUAD under hypoxic conditions. This discovery offers valuable insights into the diagnosis and treatment of clinical hypoxic disease in patients with LUAD.