ArticleTechnology in cancer research & treatment
Establishment of a Prognostic Model for Pancreatic Cancer Based on Hypoxia-Related Genes.
Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Hypoxic Tumor Microenvironment Targeting: Opportunities and Challenges for Pancreatic Cancer Immunotherapy.International journal of molecular sciences · 2026Review
- Investigation of the synergistic effect of metformin and FX11 on PANC-1 cell lines.Biological research · 2025Article
- UBC4: A Repurposed Drug Regimen for Adjunctive Use During Bladder Cancer Treatment.Biomedicines · 2025Review
- Polyallylamine Hydrochloride-Modified Bovine Serum Albumin Nanoparticles Loaded with α-Solanine for Chemotherapy of Pancreatic Cancer.International journal of nanomedicine · 2025Article
- Development of a hypoxia-responsive macrophage prognostic model using single-cell and bulk RNA sequencing in pancreatic cancer.PloS one · 2025Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesPancreatic cancer presents a formidable challenge with its aggressive nature and dismal prognosis, often hampered by elusive early symptoms. The tumor microenvironment (TME) emerges as a pivotal player in pancreatic cancer progression and treatment responses, characterized notably by hypoxia and immunosuppression. In this study, we aimed to identify hypoxia-related genes and develop a prognostic model for pancreatic cancer leveraging these genes.
methodsThrough analysis of gene expression data from The Cancer Genome Atlas (TCGA) and subsequent GO/KEGG enrichment analysis, hypoxia-related pathways were identified. We constructed a prognostic model using lasso regression and validated it using an independent dataset.
resultsOur results showed that expression levels of PLAU, SLC2A1, and CA9 exhibited significant associations with prognosis in pancreatic cancer. The prognostic model, built upon these genes, displayed robust predictive accuracy and was validated in an independent dataset. Furthermore, we found a correlation between the risk score of the prognostic model and clinical parameters of pancreatic cancer patients. At the same time, we also explored the relationship between the established hypoxia-related prognostic model and the immune microenvironment at the single-cell level. RT-qPCR results showed notable differences in the expression of hypoxia pathway-related genes between normal PANC-1 and hypoxic-treated PANC-1 cells.
conclusionOur study provides insights into the role of the hypoxic microenvironment in pancreatic cancer and offers a promising prognostic tool for clinical application.
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