Prognostic biomarker HIF1α and its correlation with immune infiltration in gliomas

Certain glioma subtypes, such as glioblastoma multiforme or low-grade glioma, are common malignant intracranial tumors with high rates of relapse and malignant progression even after standard therapy. The overall survival (OS) is poor in patients with gliomas; hence, effective prognostic prediction is crucial. Herein, the present study aimed to explore the potential role of hypoxia-inducible factor 1 subunit alpha (HIF1α) in gliomas and investigate the association between HIF1α and infiltrating immune cells in gliomas. Data from The Cancer Genome Atlas were evaluated via RNA sequencing, clinicopathological, immunological checkpoint, immune infiltration and functional enrichment analyses. Validation of protein abundance was performed using paraffin-embedded samples from patients with glioma. A nomogram model was created to forecast the OS rates at 1, 3 and 5 years after cancer diagnosis. The association between OS and HIF1α expression was estimated using Kaplan-Meier survival analysis and the log-rank test. Finally, HIF1α expression was validated using western blotting, reverse transcription-quantitative PCR, Cell Counting Kit-8 and Transwell assays. The results demonstrated that HIF1α expression was significantly upregulated in gliomas compared with normal human brain glial cells. Immunohistochemistry staining demonstrated differential expression of the HIF1α protein. Moreover, glioma cell viability and migration were inhibited via HIF1α downregulation. HIF1α impacted DNA replication, cell cycling, DNA repair and the immune microenvironment in glioma. HIF1α expression was also positively associated with several types of immune cells and immunological checkpoints and with neutrophils, plasmacytoid dendritic cells and CD56^bright cells. The Kaplan-Meier survival analyses further demonstrated a strong association between high HIF1α expression and poor prognosis in patients with glioma. Analysis of the receiver operating characteristic curves demonstrated that HIF1α expression accurately differentiated paired normal brain cells from tumor tissues. Collectively, these findings suggested the potential for HIF1α to be used as a novel prognostic indicator for patients with glioma and that OS prediction models may help in the future to develop effective follow-up and treatment strategies for these patients.