Decoding breast cancer: insights into molecular pathways & therapeutic approaches

Breast cancer is a highly heterogeneous malignancy encompassing distinct molecular subtypes such as Luminal A & B, HER2 enriched and triple negative breast cancer, each characterized by unique genomic, transcriptomic and proteomic landscapes that dictate differential prognosis and therapeutic response. This review delineates the complex signalling pathways underlying breast cancer including estrogen receptor, progesterone receptor and HER2 pathways and their downstream effectors such as PI3K/AKT/mTOR, RAS/MAPK, Notch, Wnt/β-catenin and JAK/STAT cascades. The interconnectivity of these pathways not only governs tumor cell proliferation, survival and metastasis but also contributes to intrinsic and acquired resistance mechanisms against standard-of-care therapies including endocrine agents, HER2-targeted antibodies and chemotherapy. Emerging therapeutic strategies such as next-generation selective estrogen receptor degraders, proteolysis-targeting chimeras, antibody-drug conjugates, immune checkpoint inhibitors and pathway-specific small-molecule inhibitors highlights their mechanistic rationale, clinical evidence and biomarker-guided applicability. Resistance mechanisms involving ESR1 mutations, PTEN loss, p95HER2 expression, BRCA reversions and tumor microenvironment-mediated immunosuppression contributes to therapy resistance. The review explores molecular subtypes, oncogenic signalling pathways, treatment approaches, resistance mechanisms including acquired resistance & crosstalk, metabolic reprogramming, epigenetic modifications, immune modulations and tumor microenvironment, spatial transcriptomics insights into immune cell subsets & treatment response biomarkers and the role of artificial intelligence in breast cancer treatment. The integration of artificial intelligence-based predictive modelling and rational drug combinations offers a promising paradigm for overcoming resistance and tailoring precision oncology approaches. By comprehensively mapping these oncogenic factors and therapeutic intersections, this review provides a strategic framework for optimizing breast cancer management in the era of molecular medicine.

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Publication Details

Journal
Discover Oncology
Published
2025-11-14
DOI
https://doi.org/10.1007/s12672-025-03764-w
Citations
2
Primary Topic
Breast Cancer Treatment Studies
Type
article
Field-Weighted Citation Impact
1.87
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article

Decoding breast cancer: insights into molecular pathways & therapeutic approaches

Mohammad Husain, Sudarshana Borah, Debarupa Dutta Chakraborty, Paromita Dutta Choudhury et al.
2 citations
Discover Oncology
Breast Cancer Treatment Studies
1.87
article

Decoding breast cancer: insights into molecular pathways & therapeutic approaches

Mohammad Husain, Sudarshana Borah, Debarupa Dutta Chakraborty, Paromita Dutta Choudhury, Rana Bhattacharjee, Amlan Kumar Das, Prithviraj Chakraborty, Bandana Nabis Das, Pradip Kumar Das, Monica Arora, Jiaul Ahmed Mazumder, Hasina Mehnaj Laskar
article en
2 citations

Abstract

Breast cancer is a highly heterogeneous malignancy encompassing distinct molecular subtypes such as Luminal A & B, HER2 enriched and triple negative breast cancer, each characterized by unique genomic, transcriptomic and proteomic landscapes that dictate differential prognosis and therapeutic response. This review delineates the complex signalling pathways underlying breast cancer including estrogen receptor, progesterone receptor and HER2 pathways and their downstream effectors such as PI3K/AKT/mTOR, RAS/MAPK, Notch, Wnt/β-catenin and JAK/STAT cascades. The interconnectivity of these pathways not only governs tumor cell proliferation, survival and metastasis but also contributes to intrinsic and acquired resistance mechanisms against standard-of-care therapies including endocrine agents, HER2-targeted antibodies and chemotherapy. Emerging therapeutic strategies such as next-generation selective estrogen receptor degraders, proteolysis-targeting chimeras, antibody-drug conjugates, immune checkpoint inhibitors and pathway-specific small-molecule inhibitors highlights their mechanistic rationale, clinical evidence and biomarker-guided applicability. Resistance mechanisms involving ESR1 mutations, PTEN loss, p95HER2 expression, BRCA reversions and tumor microenvironment-mediated immunosuppression contributes to therapy resistance. The review explores molecular subtypes, oncogenic signalling pathways, treatment approaches, resistance mechanisms including acquired resistance & crosstalk, metabolic reprogramming, epigenetic modifications, immune modulations and tumor microenvironment, spatial transcriptomics insights into immune cell subsets & treatment response biomarkers and the role of artificial intelligence in breast cancer treatment. The integration of artificial intelligence-based predictive modelling and rational drug combinations offers a promising paradigm for overcoming resistance and tailoring precision oncology approaches. By comprehensively mapping these oncogenic factors and therapeutic intersections, this review provides a strategic framework for optimizing breast cancer management in the era of molecular medicine.

Discover OncologyVol. 16(1)
University of Delhi (IN), Gauhati University (IN), National Institute of Technology Agartala (IN), Maldives National University (MV), University of Science and Technology, Meghalaya (IN), Maharaja Bir Bikram University (IN), Assam Down Town University (IN), Al-Ameen College of Pharmacy (IN), Global University (LB)
Openalex Percentile: Top 12%
Breast Cancer Treatment Studies
1.87
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