surgoncoКреативная хирургия и онкологияCreative surgery and oncology2076-30932307-0501Башкирский государственный медицинский университет10.24060/2076-3093-2025-15-2-43-52surgonco-1086Research ArticleОБЗОР ЛИТЕРАТУРЫREVIEWSМногофакторный анализ прогностических и предиктивных онкомаркеров у пациентов с трижды негативным раком молочной железыMultifactorial Analysis of Prognostic and Predictive Biomarkers in Triple Negative Breast Cancer Patientshttps://orcid.org/0000-0003-2125-4897ПавловВ. Н.PavlovV. N.

Павлов Валентин Николаевич — д.м.н., профессор, академик РАН, кафедра урологии и онкологии

Республика Башкортостан, Уфа 

Valentin N. Pavlov — Dr. Med. Sci., Prof., Academician of the Russian Academy of Sciences, Department of Urology and Oncology

Ufa 

https://orcid.org/0000-0002-4657-6625УрманцевМ. Ф.UrmantsevM. F.

Урманцев Марат Фаязович — к.м.н., доцент, кафедра урологии и онкологии

Республика Башкортостан, Уфа 

Marat F. Urmantsev — Cand. Sci. (Med.), Assoc. Prof., Department of Urology and Oncology

Ufa 

https://orcid.org/0000-0002-3867-0216ГильмановаР. Ф.GilmanovaR. F.

Гильманова Рита Фларидовна — к.м.н., кафедра урологии и онкологии, онкологическое отделение

Республика Башкортостан, Уфа 

Rita F. Gilmanova — Cand. Sci. (Med.), Department of Urology and Oncology, Oncology Department

Ufa 

margaritagilmanova@mail.ruhttps://orcid.org/0009-0004-0603-7864ИсмагиловаЮ. А.IsmagilovaJ. A.

Исмагилова Юлия Альбертовна — студентка 6-го курса, лечебный факультет

Республика Башкортостан, Уфа 

Julia A. Ismagilova — 6th year student

Ufa

https://orcid.org/0000-0002-4160-2820БакеевМ. Р.BakeevM. R.

Бакеев Марат Радикович — ординатор, кафедра хирургических болезней лечебного факультета

Республика Башкортостан, Уфа 

Marat R. Bakeev — Resident, Department of Surgical Diseases, Medical Faculty

Ufa

Башкирский государственный медицинский университетРоссияBashkir State Medical UniversityRussian FederationБашкирский государственный медицинский университет ; Клиника Башкирского государственного медицинского университетаРоссияBashkir State Medical University ; Clinic of Bashkir State Medical UniversityRussian Federation202501072025152139148Copyright © Павлов В.Н., Урманцев М.Ф., Гильманова Р.Ф., Исмагилова Ю.А., Бакеев М.Р., 20252025Павлов В.Н., Урманцев М.Ф., Гильманова Р.Ф., Исмагилова Ю.А., Бакеев М.Р.Pavlov V.N., Urmantsev M.F., Gilmanova R.F., Ismagilova J.A., Bakeev M.R.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.surgonco.ru/jour/article/view/1086

Трижды негативный рак молочной железы (TNBC) представляет собой один из самых агрессивных подтипов рака молочной железы, что связано с отсутствием экспрессии ключевых молекулярных мишеней, таких как рецепторы эстрогена (ER), прогестерона (PR) и HER2. Это существенно ограничивает терапевтические опции и делает химиотерапию основным методом лечения. Высокая частота рецидивов, метастазирования и отсутствие специфичных таргетных терапий делают TNBC серьезной проблемой для онкологов. В данной статье рассматриваются ключевые прогностические и предиктивные маркеры TNBC, такие как мутации в генах BRCA1/BRCA2, экспрессия PD-L1, инфильтрация опухоли лимфоцитами (TILs), циркулирующие опухолевые клетки (CTC) и циркулирующая опухолевая ДНК (ctDNA). Эти маркеры играют ключевую роль в прогнозировании исходов и выборе оптимальной терапии. Кроме того, персонализированная медицина, основанная на молекулярном профилировании и поддерживаемая методами искусственного интеллекта (ИИ), представляет собой перспективное направление в лечении TNBC. Применение ИИ позволяет анализировать большие объемы данных и предсказывать клинические исходы с высокой точностью, что позволяет разрабатывать персонализированные стратегии лечения для каждого пациента. Таким образом, данная статья систематизирует и анализирует современные данные о прогностических и предиктивных маркерах TNBC, акцентируя внимание на их клинической значимости и перспективных подходах к персонализированной терапии.

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.

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The authors declare that there are no conflicts of interest present.