Assessment of HIF1α gene expression and function in gastric cancer using in silico approaches

Amini-Ghahfarokhi, Marziye; Kalantari-Dehaghi, Maryam; Emadi-Baygi, Modjtaba

doi:10.48307/FMSJ.2025.29.6.2

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Volume 29, Issue 6 (Bimonthly 2025)

Feyz Med Sci J 2025, 29(6): 552-566

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Assessment of HIF1α gene expression and function in gastric cancer using in silico approaches

Marziye Amini-Ghahfarokhi

, Maryam Kalantari-Dehaghi

, Modjtaba Emadi-Baygi ^*

Department of Genetics, Faculty of Basic Sciences, Shahrekord University, Shahrekord, Iran & Department of Genetics, Faculty of Basic Sciences, Shahrekord University, Shahrekord, Iran , emadi-m@sku.ac.ir

Abstract: (721 Views)

Background and Aim: Hypoxia-Inducible Factor 1 Alpha (HIF1α) is a heterodimeric transcription factor activated under hypoxic conditions, regulating the expression of genes involved in cellular adaptation. HIF1 plays a key role in modulating hypoxia response pathways, angiogenesis, epithelial-mesenchymal transition (EMT), and metastasis. This study aimed to evaluate the role of HIF1α in invasion, EMT, and prognosis in patients with gastric cancer.
Methods: In this retrospective computational cohort study, gene expression and clinical data from gastric cancer patients were obtained from The Cancer Genome Atlas (TCGA) database. Patients were stratified into high and low HIF1A expression groups based on gene expression levels. Differential gene expression analysis was performed using the limma package. Survival analysis was conducted using the Kaplan–Meier method and univariate/multivariate Cox regression. Weighted Gene Co-expression Network Analysis (WGCNA) was employed to identify gene modules associated with HIF1A expression. Functional pathway enrichment analysis was performed using enrichR. Additionally, predictive performance was assessed using Receiver Operating Characteristic (ROC) curves and nomograms constructed based on HIF1A expression and clinical variables.
Results: A total of 15,060 differentially expressed genes were identified between the high and low HIF1A expression groups. Among invasion- and metastasis-related genes, 10 genes, including CD44, COL1A1, SLC12A3, and NT5E, showed significant associations with patient survival. The blue module identified by WGCNA exhibited the strongest correlation with HIF1A expression and was enriched in pathways such as cytokine signaling, immune responses, VEGF regulation, and extracellular matrix organization. Survival analysis revealed that patients with high HIF1A expression had shorter overall survival. The predictive models based on nomograms demonstrated high accuracy in predicting 3- and 5-year survival outcomes.
Conclusion: The findings indicate that HIF1α not only contributes to gastric cancer progression through the regulation of EMT, angiogenesis, and inflammation pathways but also serves as an independent molecular marker with strong prognostic value. Therefore, HIF1α may be regarded both as a prognostic biomarker and a promising therapeutic target for personalized treatment strategies in gastric cancer.

Keywords: Gastric cancer, HIF1α, Hypoxia, Epithelial-mesenchymal transition (EMT), Survival analysis

Type of Study: Research | Subject: General
Received: 2025/07/18 | Revised: 2025/12/29 | Accepted: 2025/10/25 | Published: 2025/12/30

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Amini-Ghahfarokhi M, Kalantari-Dehaghi M, Emadi-Baygi M. Assessment of HIF1α gene expression and function in gastric cancer using in silico approaches. Feyz Med Sci J 2025; 29 (6) :552-566
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