AUTHOR=Xu Xiao , Fa Liangling , Sun Xiaoxiao , Yang Fangfang , Liu Yongrui , Song Jifu , Zhao Yongli , Dong Jigang 

TITLE=Integrative analysis of ferroptosis in the hypoxic microenvironment of gastric cancer unveils the immune landscape and personalized therapeutic strategies

JOURNAL=Frontiers in Oncology

VOLUME=Volume 14 - 2024

YEAR=2025

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2024.1499580

DOI=10.3389/fonc.2024.1499580

ISSN=2234-943X

ABSTRACT=BackgroundFerroptosis is a cell death mode caused by excessive accumulation of lipid peroxides caused by disturbance of intracellular metabolic pathway, which is closely related to iron and cholesterol metabolism homeostasis. Its regulation within the hypoxic metabolic tumor microenvironment (TME) has the potential to improve the effectiveness of tumor immunotherapy. The predictive role of ferroptosis in gastric cancer (GC) hypoxia TME, particularly in relation to TME immune cell infiltration, has not been fully explained.MethodsBy analyzing the mRNA expression data of ferroptosis and hypoxia-related genes, a prediction model was constructed to evaluate further the predictive value of immune cell infiltration, clinical characteristics, and immunotherapy efficacy of gastric cancer, and the essential genes were validated.ResultsTwo distinct molecular states of ferroptosis-hypoxia were identified in GC. Notably, patients with high ferroptosis-hypoxia risk scores (FHRS) displayed significant levels of hypoxia and epithelial-mesenchymal transition (EMT), which were associated with unfavorable prognosis, increased chemoresistance, and heightened immunosuppression.ConclusionsThis study demonstrates that ferroptosis under hypoxic conditions significantly affects the modulation of the tumor immune microenvironment. The FHRS can independently predict prognosis in gastric cancer. Assessing the molecular status of ferroptosis-hypoxia in individual patients will help in selecting more suitable immunotherapy regimens by providing a better understanding of TME characteristics and predicting immunotherapeutic outcomes.