Authors
Divya Sharma, Peeyush Bhardwaj, Kaushalendra Kumar Mishra, Niharika Mishra, Anadi Tiwari
Published in
Cancer treatment and research communications. Volume 48. Pages 101344. Jul 31, 2026. Epub Jul 31, 2026.
Abstract
Breast cancer is a complex and heterogeneous disease that remains a major global health challenge. Recent progress in molecular biology, artificial intelligence (AI), and precision medicine has transformed its diagnosis and treatment. Conventional biomarkers such as ER, PR, HER2, and BRCA mutations continue to guide therapeutic decisions, while emerging biomarkers including TP53, PTEN, and STK11 offer new insights into tumor behavior and drug resistance. AI-based technologies, including machine learning and deep learning, have improved early detection and diagnostic accuracy through advanced medical imaging and multimodal analysis. Current treatment strategies extend beyond conventional chemotherapy and surgery to include targeted therapy, endocrine therapy, immunotherapy, antibody-drug conjugates, and gene-based approaches. Novel therapeutics such as CDK4/6 inhibitors, PARP inhibitors, PI3K inhibitors, and selective estrogen receptor degraders have demonstrated promising clinical outcomes in advanced breast cancer. Additionally, emerging technologies such as CRISPR/Cas9 gene editing and nanotechnology-based drug delivery systems show significant potential for personalized cancer therapy. This review summarizes recent advancements in breast cancer biomarkers, AI-assisted diagnostics, and modern therapeutic strategies aimed at improving precision medicine and patient outcomes.
PMID:
42542076
Bibliographic data and abstract were imported from PubMed on 02 Aug 2026.
Read full publication at:
Please sign in
to see all details.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 4
- Comments 0