Multifactorial Analysis of Prognostic and Predictive Biomarkers in Triple Negative Breast Cancer Patients
https://doi.org/10.24060/2076-3093-2025-15-2-43-52
Abstract
Triple-negative breast cancer (TNBC) represents one of the most aggressive subtypes of breast cancer, characterized by the absence of key molecular targets including estrogen receptors (ER), progesterone receptors (PR), and HER2. This molecular profile significantly limits treatment modalities, establishing chemotherapy as the definitive treatment. The high rates of recurrences and metastasis, along with the lack of specific targeted therapies, make TNBC a major clinical challenge. This article evaluates critical prognostic and predictive biomarkers of TNBC, including BRCA1/BRCA2 gene mutations, PD-L1 expression, tumor-infiltrating lymphocytes (TILs), circulating tumor cells (CTCs), and circulating tumor DNA (ctDNA). These markers are pivotal for outcome prediction and treatment optimization. Moreover, a transformative approach to TNBC treatment is represented by personalized medicine based on molecular profiling supported by artificial intelligence (AI). The integration of artificial intelligence (AI) facilitates the analysis of substantial data sets, the accurate prediction of clinical outcomes, and the formulation of customized treatment strategies for individual patients. Thus, this article analyzes current data concerning prognostic and predictive markers of TNBC, with a particular emphasis on their clinical utility and the potential for personalized therapy.
About the Authors
V. N. Pavlov
Bashkir State Medical University
Russian Federation
Russian Federation
Valentin N. Pavlov — Dr. Med. Sci., Prof., Academician of the Russian Academy of Sciences, Department of Urology and Oncology
Ufa
M. F. Urmantsev
Bashkir State Medical University
Russian Federation
Russian Federation
Marat F. Urmantsev — Cand. Sci. (Med.), Assoc. Prof., Department of Urology and Oncology
Ufa
R. F. Gilmanova
Bashkir State Medical University ; Clinic of Bashkir State Medical University
Russian Federation
Russian Federation
Rita F. Gilmanova — Cand. Sci. (Med.), Department of Urology and Oncology, Oncology Department
Ufa
J. A. Ismagilova
Bashkir State Medical University
Russian Federation
Russian Federation
Julia A. Ismagilova — 6th year student
Ufa
M. R. Bakeev
Bashkir State Medical University
Russian Federation
Russian Federation
Marat R. Bakeev — Resident, Department of Surgical Diseases, Medical Faculty
Ufa
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For citations:
Pavlov V.N., Urmantsev M.F., Gilmanova R.F., Ismagilova J.A., Bakeev M.R. Multifactorial Analysis of Prognostic and Predictive Biomarkers in Triple Negative Breast Cancer Patients. Creative surgery and oncology. 2025;15(2):139-148. (In Russ.) https://doi.org/10.24060/2076-3093-2025-15-2-43-52
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