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The Role of Heat Shock Protein 90 (Hsp90) in the Prediction and Diagnosis of Breast Carcinoma

Year: 2026
Type: article
Study design: Observational Study
Abstract: The heterogeneity of biology in breast cancer and the drawbacks of traditional diagnosing strategies such as imaging and invasive biopsy have remained as obstacles to an early diagnosis and an accurate prognosis prediction. Non-invasive biomarkers for the diagnosis of breast carcinoma are thus highly desirable. Heat shock protein 90 (Hsp90) is a molecular chaperone which is responsible for the stabilization and maturation of many oncogenic proteins, and has become one of the representative cancer biomarkers. Herein we investigated the prediction and diagnostic value of circulating Hsp90 for breast carcinoma. Patients and Methods: A cross-sectional diagnostic study was performed at the Al-Forat Al-Awsat Oncology Center in Al-Najaf City, Iraq between March 2025 to September 2025. The patients studied comprised 125 suspected cases of breast carcinoma and 75 apparently normal controls. Plasma levels of Hsp90 before any therapeutic intervention were quantified by enzyme linked immunosorbent assay (ELISA). The diagnosis was further confirmed by histopathology and breast imaging as the gold standard. Predictive and diagnostic performance of Hsp90 was evaluated using logistic regression and ROC (receiver operating characteristic) curve analysis. Results: Serum Hsp90 levels were significantly higher in breast carcinoma patients than in healthy subjects (p < 0.003). Logistic regression analysis was performed demonstrating Hsp90 as an independent factor for breast cancer (odds ratio = 6.49, 95 % CI: 2.69–15.63; P < 0.001). Then, the ROC curve analysis showed good diagnostic performance of AUC = 0.89 with a sensitivity of 85.6% and specificity of 82.3% in optimal cut-off value. Conclusions: Circulating Hsp90 appears to be a promising non-invasive pre- and clinical marker for the prediction and diagnosis of breast carcinoma, which can help in diagnosis for early detection and decision making.
DOI: 10.5281/zenodo.18429605
Language: English
Open Access status: green
OpenAlex ID: W7126220449
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