Observational studyMedicine2019
Prediction of postoperative survival of triple-negative breast cancer based on nomogram model combined with expression of HIF-1α and c-myc.
Observational study in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Clinicopathological and prognostic value of hypoxia-inducible factor-1α in breast cancer: a meta-analysis including 5177 patients.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2020Pooled it
- Stromal hypoxia and autophagy signatures as indicators of pathologic response in triple-negative breast cancer.BMC cancer · 2026Article
- The Role of Angiogenesis in Breast Cancer and Obesity: Unravelling the Connection.International journal of breast cancer · 2026Review
- Article
- High hypoxia inducible factor-1α expression is associated with reduced survival in patients with breast cancer: A meta-analysis.World journal of clinical oncology · 2025Article
- Review
- Spatial transcriptomic analysis of tumour with high and low CAIX expression in TNBC tissue samples using GeoMx™ RNA assay.Histology and histopathology · 2024Article
- The Role of Hypoxia-Inducible Factor Isoforms in Breast Cancer and Perspectives on Their Inhibition in Therapy.Cancers · 2022Review
- Adaptation to Hypoxia May Promote Therapeutic Resistance to Androgen Receptor Inhibition in Triple-Negative Breast Cancer.International journal of molecular sciences · 2022Review
- Targeting HIF-1α Function in Cancer through the Chaperone Action of NQO1: Implications of Genetic Diversity of NQO1.Journal of personalized medicine · 2022Review
- Targeting hypoxia-inducible factors for breast cancer therapy: A narrative review.Frontiers in pharmacology · 2022Review
- Selection of RNA aptamers targeting hypoxia in cancer.Frontiers in molecular biosciences · 2022Article
- A Nomogram Based on Radiomics with Mammography Texture Analysis for the Prognostic Prediction in Patients with Triple-Negative Breast Cancer.Contrast media & molecular imaging · 2020Article
- Molecular Crosstalk Between MYC and HIF in Cancer.Frontiers in cell and developmental biology · 2020Review
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aims of this study were to explore the expression of hypoxia inducible factor-1α (HIF-1α) and c-myc protein in triple-negative breast cancer (TNBC) and its clinical prognostic significance, and to establish a prediction model for postoperative survival of TNBC based on nomogram.A total of 87 patients with TNBC at the Department of Breast Surgery, Beijing Chaoyang Hospital, Capital Medical University from January 2012 to December 2015 were enrolled in this study. Immunohistochemistry was performed to detect the expression of HIF-1α and c-myc protein in breast cancer tissues. Cox regression analyses were performed to explore the correlation between HIF-1α/c-myc expression and clinical pathological parameters as well as prognosis. Receiver-operating characteristic curve was generated for cox multivariate analysis. A nomogram was generated based on the cox multivariate analysis, and a calibration curve was prepared for the nomogram to evaluate the consistency between the predicted probability of the nomogram and the actual observed probability. The stability of nomogram model was validated with an external cohort including 39 TNBC patients.The positive expression rates of HIF-1α and c-myc protein in breast cancer tissues were 41.4% (36/87) and 55.2% (48/87), respectively. HIF-1α expression was significantly correlated with age, tumor diameter, histological grade, lymph node status, and tumor TNM stage; c-myc expression was significantly associated with tumor diameter, histological grade, lymph node status, and tumor TNM stage. Cox univariate and multivariate analyses showed that HIF-1α and c-myc protein expression, histological grade, lymph node status, and tumor TNM stage were the independent risk factors for postoperative survival in TNBC patients. The AUC of prediction model was 0.843 (0.809-0.887). The nomogram could predict the probability of 3-year disease-free survival according to each patient's condition. The calibration curve displayed good agreement of the predicted probability with the actual observed probability, indicating that the nomogram model had great value of prediction. The external validation indicated the prediction model had good stability.HIF-1α-positive expression, c-myc positive expression, histological grade III, lymph node positive, and TNM stage III tumors suggested that TNBC patients had a poor prognosis. This prediction model can be used to predict postoperative survival of TNBC.
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