Evidence map›Paper›PMID 42322695›Full record

ArticleTranslational oncology2026

Comprehensive investigation of hypoxia-associated genes and their predictive significance in osteosarcoma.

Shangfang Xie, Wenyao Yu, Runye Lin, Songjian Xin

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Article in Translational oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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4 authors.

Shangfang XieDepartment of Rehabilitation, The Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, China.
Wenyao YuDepartment of Rehabilitation, The Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, China.
Runye LinDepartment of Rehabilitation, The Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, China.
Songjian XinDepartment of Rehabilitation, The Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, China. Electronic address: xinsongjian8960@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn accumulation of evidence underscores the critical importance of both hypoxia and the immune microenvironment in driving the progression of osteosarcoma. Despite advancements in therapeutic strategies, osteosarcoma continues to pose a formidable challenge due to its aggressive nature and high metastatic potential. Nonetheless, the identification of reliable gene signatures that combine information on hypoxia and immune status to predict osteosarcoma prognosis remains an unmet need.

methodsTo gain a deeper understanding of the impact of hypoxia on the invasion of osteosarcoma, we devised a data-driven modeling framework, termed Cellular Hypoxia Prediction Framework (CHPF), which integrates single-cell transcriptome profiling with hypoxia gene signatures to predict cellular hypoxia status. We applied dimensionality reduction, clustering, and various analytical tools such as WGCNA, GO enrichment, and CellChat for cell-cell communication analysis.

resultsWe conducted a comprehensive analysis of the hypoxia status landscape within osteosarcoma cells and observed a distinct pattern, where hypoxic cells were predominantly confined to the tumor core region. Our analysis revealed distinct hypoxic subpopulations within osteosarcoma, with significant overexpression of genes like FGFBP2 and S100A1 in hypoxic cells. Remarkably, our investigation delved into the functional heterogeneity of tumor cells and uncovered a hypoxic subpopulation that exhibited a remarkably high invasive potential. We identified key genes (RPS28, ZC3HAV1, RPS8, S100A13, SERPINH1, EFNA5, RPL37A, USP11) that are associated with patient prognosis and developed a predictive model, which categorized patients based on their risk profiles. Hypoxia upregulates SERPINH1 expression in osteosarcoma cells in a HIF‑1α‑dependent manner, promotes proliferation and invasion, and SERPINH1 knockdown effectively reverses these hypoxia‑induced malignant phenotypes.

conclusionGenes associated with hypoxia play a pivotal role in the biology of osteosarcoma, significantly impacting tumor behavior and patient survival outcomes. Our research findings offer valuable insights into the underlying mechanisms of osteosarcoma and could potentially pave the way for the development of innovative therapeutic approaches that specifically target the hypoxic tumor microenvironment.

Indexed as

Cell-cell communicationHypoxiaOsteosarcomaPrognostic modelSingle-cell analysis

Identifiers

PMID42322695
PMCPMC13312577

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