Hypoxia-inducible factor 1α is closely linked to an aggressive phenotype in breast cancer
- 6 September 2007
- journal article
- research article
- Published by Springer Science and Business Media LLC in Breast Cancer Research and Treatment
- Vol. 110 (3), 465-475
- https://doi.org/10.1007/s10549-007-9742-1
Abstract
Purpose The aim of this study is to clarify characteristics of invasive breast cancer with expression of Hypoxia-induced factor 1α (HIF-1α) which is induced by hypoxia and signal transduction of growth factors. Experimental Design We examined, by immunohistochemical analysis, the expression of HIF-1α in normal breast tissue, benign disorders and breast cancer. In invasive breast cancer, we investigated the correlation between expression of HIF-1α and clinicopathological and biological factors. We also studied the prognostic value of HIF-1α in breast cancer. Results HIF-1α was mainly detected in tumor cell nuclei. In the 171 cases of invasive breast cancer examined, nuclear HIF-1α expression was detected in 63 (36.8%) cases. Immunoreactive nuclear HIF-1α was correlated with tumor size (p = 0.0013), lymph node metastasis (p = 0.0005), tumor stage (p = 0.0031) and histological grade (p = 0.0074). Elevated HIF-1α levels was also associated with hormone receptor negativity (p = 0.0025), HER2 overexpression (p = 0.0053), high Ki67 labeling index (p = 0.0002), increased levels of VEGF (p < 0.0001), COX-2 overexpression (p = 0.0029) and increased nuclear p53 (p = 0.0048). In terms of the possible use of HIF-1α as a prognostic indicator, patients who had increased HIF-1α levels in their tumor showed shorter disease-free survival (DFS) (p < 0.0001) and overall survival (OS) (p = 0.0002) than those lacking HIF-1α in univariate analysis. In multivariate analysis of DFS and OS, HIF-1α was identified an independent prognostic factor. Conclusions These findings suggest that HIF-1α was closely linked to an aggressive phenotype in breast cancer. It may be useful to study the expression of HIF-1α using immunohistochemical analysis for better understanding of the tumor characteristics of breast cancer.Keywords
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