Decoding breast cancer: insights into molecular pathways & therapeutic approaches Tanjima Tarique Laskar, Hasina Mehnaj Laskar, Jiaul Ahmed Mazumder, Rupajit Bhattacharjee, Md Ikbal Husain, Bandana Das, Panchami Das, Paromita Dutta Choudhury, Monica Arora, Sudarshana Borah, Debarupa Chakraborty, Prithviraj Chakraborty, Amlan Das Discover Oncology, 2025 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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MOST CITED SCHOLAR PUBLICATIONS
Decoding breast cancer: insights into molecular pathways & therapeutic approaches L Tanjima Tarique, Hasina ML, JA Mazumder, R Bhattacharjee, Md Ikbal Husain ... Discover Oncology 16 (1), 1-43 , 2025 2025.0 Citations: 9
Unveiling the Anticancer Potential of Curcuma Caesia Roxb. Against Ovarian Cancer: An Indigenous Plant of Assam K Barman, S Borah, B Das, TT Laskar, DD Chakraborty, P Chakraborty, ... Journal of Neonatal Surgery 14 (8s) , 2025 2025.0 Citations: 2
Bilosomes as Novel Nanocarrier: A Review. Sch Acad J Pharm MI Husain, S Sarkar, D Nilimanka Scholars Academic Journal of Pharmacy 2, 32-41 , 2026 2026.0
Machine Learning-Based Design of Lipid Nanoparticles for mRNA Delivery: A Review MDI HUSAIN, M JONGKEY, N CHAKMA, P DEBNATH, S ROUTH, ... 2026.0
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Essential Oil-Based Microemulsions In Antimicrobial Applications: A Natural Approach ACMI Husain International Journal of Creative Research Thoughts 13 (11), 55-58 , 2025 2025.0
Targeting Breast Cancer Complexity: Molecular Signalling, Microenvironment and Next-Generation Therapeutic Strategies TT Laskar, M Arora, JA Mazumder, R Bhattacharjee, MI Husain, B Das, ... Studies in Science of Science| ISSN: 1003-2053 43 (8), 464-506 , 2025 2025.0
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