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Review Special Issue Open Access

Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review)

This article is part of the special Issue: Significance of molecular analyses in the era of personalized tumor therapy
  • Authors:
    • Wenhui Hao
    • Barani Kumar Rajendran
    • Tingting Cui
    • Jiayi Sun
    • Yingchun Zhao
    • Thirunavukkarasu Palaniyandi
    • Masilamani Selvam
  • View Affiliations

    Affiliations: Xinjiang Key Laboratory of Molecular Biology for Endemic Diseases, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang 830017, P.R. China, Department of Pathology, Yale School of Medicine, Yale University, New Haven, CT 06510, USA, Xinjiang Key Laboratory of Molecular Biology for Endemic Diseases, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang 830017, P.R. China, Department of Biotechnology, Dr. M.G.R Educational and Research Institute, Chennai 600095, India, Department of Biotechnology, Sathyabama Institute of Science and Technology, Chennai 600119, India
  • Published online on: October 24, 2024     https://doi.org/10.3892/ijmm.2024.5447
  • Article Number: 6
  • Copyright: © Hao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

In the modern era of medicine, prognosis and treatment, options for a number of cancer types including breast cancer have been improved by the identification of cancer‑specific biomarkers. The availability of high‑throughput sequencing and analysis platforms, the growth of publicly available cancer databases and molecular and histological profiling facilitate the development of new drugs through a precision medicine approach. However, only a fraction of patients with breast cancer with few actionable mutations typically benefit from the precision medicine approach. In the present review, the current development in breast cancer driver gene identification, actionable breast cancer mutations, as well as the available therapeutic options, challenges and applications of breast precision oncology are systematically described. Breast cancer driver mutation‑based precision oncology helps to screen key drivers involved in disease development and progression, drug sensitivity and the genes responsible for drug resistance. Advances in precision oncology will provide more targeted therapeutic options for patients with breast cancer, improving disease‑free survival and potentially leading to significant successes in breast cancer treatment in the near future. Identification of driver mutations has allowed new targeted therapeutic approaches in combination with standard chemo‑ and immunotherapies in breast cancer. Developing new driver mutation identification strategies will help to define new therapeutic targets and improve the overall and disease‑free survival of patients with breast cancer through efficient medicine.
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Copy and paste a formatted citation
Spandidos Publications style
Hao W, Rajendran BK, Cui T, Sun J, Zhao Y, Palaniyandi T and Selvam M: Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review). Int J Mol Med 55: 6, 2025.
APA
Hao, W., Rajendran, B.K., Cui, T., Sun, J., Zhao, Y., Palaniyandi, T., & Selvam, M. (2025). Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review). International Journal of Molecular Medicine, 55, 6. https://doi.org/10.3892/ijmm.2024.5447
MLA
Hao, W., Rajendran, B. K., Cui, T., Sun, J., Zhao, Y., Palaniyandi, T., Selvam, M."Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review)". International Journal of Molecular Medicine 55.1 (2025): 6.
Chicago
Hao, W., Rajendran, B. K., Cui, T., Sun, J., Zhao, Y., Palaniyandi, T., Selvam, M."Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review)". International Journal of Molecular Medicine 55, no. 1 (2025): 6. https://doi.org/10.3892/ijmm.2024.5447
Copy and paste a formatted citation
x
Spandidos Publications style
Hao W, Rajendran BK, Cui T, Sun J, Zhao Y, Palaniyandi T and Selvam M: Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review). Int J Mol Med 55: 6, 2025.
APA
Hao, W., Rajendran, B.K., Cui, T., Sun, J., Zhao, Y., Palaniyandi, T., & Selvam, M. (2025). Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review). International Journal of Molecular Medicine, 55, 6. https://doi.org/10.3892/ijmm.2024.5447
MLA
Hao, W., Rajendran, B. K., Cui, T., Sun, J., Zhao, Y., Palaniyandi, T., Selvam, M."Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review)". International Journal of Molecular Medicine 55.1 (2025): 6.
Chicago
Hao, W., Rajendran, B. K., Cui, T., Sun, J., Zhao, Y., Palaniyandi, T., Selvam, M."Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review)". International Journal of Molecular Medicine 55, no. 1 (2025): 6. https://doi.org/10.3892/ijmm.2024.5447
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