ReviewDiscover oncology2025
Decoding breast cancer: insights into molecular pathways & therapeutic approaches.
Review in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- MXRA5 promotes the progression and metastasis of breast cancerThe Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2026Article
- Surgical Decision-Making in Breast Cancer: A Retrospective Comparative Study from a Tertiary Center.Journal of clinical medicine · 2026Article
- Bio-magnetic nanomedicine for targeted drug delivery of breast cancer: green synthesis, functional design, and translational challenges.Breast cancer research : BCR · 2026Review
- Bioinformatics Analysis of microRNAs Associated with Metastatic Potential in Breast Cancer.Biology · 2026Article
- Tumor microenvironment and key signaling pathways in breast cancer progression and therapy resistance: A review.Biomolecules & biomedicine · 2026Review
- MiRNAs: a call to arms that shapes the plasticity of tumor associated macrophages in breast cancer.Frontiers in immunology · 2026Review
- Circular RNAs in Plasma and Beyond: Potential Biomarkers for Breast Cancer.Oncology research · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.