ArticleFrontiers in immunology2025
Integrative bioinformatics and experimental validation unveil CRISP3 as a hypoxia-, epithelial mesenchymal transition-, and immune-related prognostic biomarker and therapeutic target in breast cancer.
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Exploration of the mechanism of Xinjiang Rosa laxa Retz.Fruit extract on IgA nephropathy by bioinformatics and machine learning methods.Bioresources and bioprocessing · 2026Article
- CRISP3, a Potential Tumor Suppressor, Inhibits the Progression of High-Grade Serous Ovarian Carcinoma by Modulating the PI3K/AKT Pathway.Biomedicines · 2026Article
- AINR: attention-guided implicit neural representations for spatial domain identification in spatial transcriptomics.Bioinformatics advances · 2026Article
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10 authors.
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Abstract
Introduction: Breast cancer (BC) remains a widespread malignancy and ranks as the second leading cause of cancer-related mortality among women worldwide. Hypoxia, epithelial-mesenchymal transition (EMT), and immune-related processes have been increasingly recognized as critical contributors to BC pathogenesis. However, a prognostic model integrating hypoxia-, EMT-, and immune-related genes (HEMTIRGs) to predict BC outcomes has not yet been established. Methods: Gene expression datasets of BC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Prognostic genes were identified using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis. A prognostic model was developed based on these genes. Immune infiltration was assessed using CIBERSORT and ssGSEA analyses. Immunotherapy response was predicted using the tumor immune dysfunction and exclusion (TIDE) algorithm. Functional roles of HEMTIRGs in BC malignancy were validated through Results: In this study, four HEMTIRGs (PAX7, DCD, CRISP3, and FGG) were identified and used to develop a prognostic model. Patients were stratified into high- and low-risk groups based on median risk scores. A nomogram based on this model accurately predicted overall survival (OS), consistent with the observed outcomes. Notably, patients in the high-risk group exhibited increased immune cell infiltration but a lower predicted response to immunotherapy. Immunohistochemistry (IHC) further confirmed that HEMTIRGs expression levels were strongly associated with breast cancer, with CRISP3 showing the most pronounced upregulation. Conclusion: This study establishes a novel HEMTIRGs-based prognostic model for BC, offering a robust tool for predicting patient prognosis and immunotherapy efficacy. Additionally, our findings provide new insights into BC pathogenesis, highlighting potential therapeutic targets.
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