ArticleResearch in pharmaceutical sciences2022
Expression analysis of HIF-3α as a potent prognostic biomarker in various types of human cancers: a case of meta-analysis.
Article in Research in pharmaceutical sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 5 citations in OpenAlex.
- A comprehensive bioinformatics analysis of fatty acid metabolism-associated genes in the diagnosis and prognosis of head and neck squamous cell carcinoma.Research in pharmaceutical sciences · 2025Article
- A bioinformatics approach of specificity protein transcription factors in head and neck squamous cell carcinoma.Research in pharmaceutical sciences · 2024Article
- Tumor microenvironment-induced tumor cell plasticity: relationship with hypoxic stress and impact on tumor resistance.Frontiers in oncology · 2023Review
- Integrative bioinformatics analysis of ACS enzymes as candidate prognostic and diagnostic biomarkers in colon adenocarcinoma.Research in pharmaceutical sciencesArticle
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and purpose: Hypoxia-inducible factors (HIFs) are transcription factors that get activated and stabilized in the heterodimerized form under hypoxic conditions. many studies have reported the importance of the HIF-1α and HIF-2α activity in biological pathways of hypoxic cancer cells. However, the importance of HIF-3α in a variety of cancers remains unknown. Experimental approach: The expression profile of 13 different types of cancer samples from the Cancer Genome Atlas (TCGA) database were subjected to normalization, and differential gene expression analysis was performed using computational algorithms by R programming. Receiver operating characteristic tests and survival analyses were carried out for HIF-α subunits in different cancers. Findings / Results: The expression status of HIF-3α was notably less in all cancer samples in contrast to their adjacent normal tissues. The expression degree of HIF-1α varied among distinct types of cancer and the expression degree of HIF-2α was lower in nearly all types of cancers. HIF-3α had very weak diagnostic potential, while HIF-2α had better diagnostic potential in most types of cancers compared to HIF-1α. Patients who had a higher level of HIF-3α had better survival, while the higher expression level of HIF-1α and HIF-2α were associated with worse survival in many types of cancers. Conclusion and implications: Our findings showed that each HIF-α subunit had a unique heterogeneous expression pattern in different classes of cancers. The expression level of each HIF-α subunit correlated differently with the stages, tumor sizes, and survival rate of patients from different classes of TCGA cancers.
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