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Updated: Aug 9, 2025

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Predictive significance of HIF-1α, Snail, and PD-L1 expression in breast cancer
Evgenia Zubareva1, Marina Senchukova2, Tatyana Karmakova3
1Mammological Center, Orenburg Regional Clinical Oncology Center, Orenburg, Orenburg Region, Russian Federation, 460021.
Abstract:
Currently, the prediction of breast cancer (BC) effectiveness to drug treatment is based on determining the expression level of steroid hormone receptors and human epidermal growth factor receptor type 2 (HER2). However, significant differences in individual response to drug treatment require the search for new predictive markers. Here, by comprehensively examining HIF-1α, Snail, and PD-L1 expression in BC tumor tissue, we demonstrate that high levels of these markers correlate with unfavorable factors of BC prognosis: the presence of regional and distant metastases and lymphovascular and perineural invasion. Analyzing the predictive significance of markers, we show that the most significant predictors of chemoresistant HER2-negative BC are a high PD-L1 level and a low Snail level, while in HER2-positive BC, only a high PD-L1 level is an independent predictor of chemoresistant BC. Our results suggest that using immune checkpoint inhibitors in these groups of patients may improve drug therapy effectiveness.
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