ReviewMolecular biology reports2026
Protein-protein interactions as therapeutic targets in breast cancer: integrated computational and experimental advances, mechanisms and clinical translation.
Review in Molecular biology reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Breast cancer is a highly heterogeneous malignant tumour, whose initiation and progression are closely associated with aberrant rewiring of protein-protein interactions (PPIs). This review systematically summarizes the core regulatory mechanisms of PPIs in breast cancer: focusing on neomorphic interactions (neoPPIs) and hypomorphic interactions (hypoPPIs) induced by driver mutations, and dissecting their regulatory effects on key pathways such as apoptotic pathways, DNA damage repair, and hormone receptor signalling. It also summarizes the application progress of critical technologies for PPI research in breast cancer. Furthermore, the review highlights the clinical translational value of PPIs as diagnostic biomarkers and therapeutic targets, along with the development and clinical exploration of targeted strategies such as BCL-2 inhibitors and molecular glues. Finally, it discusses the current challenges in breast cancer PPI research, including heterogeneity and drug resistance mechanisms, and prospects future directions such as single-cell level dynamic analysis and artificial intelligence (AI)-assisted drug design. This review provides a new theoretical basis and technical support for the precision treatment of breast cancer.
Indexed as
Identifiers
42684521What Socratic 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 Socratic graph.