ReviewMolecular biology reports2026
Decoding PARP roles in breast cancer therapy resistance.
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.
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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.
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Authors and funding
10 authors.
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Abstract
Poly(ADP-ribose) polymerase (PARP) inhibitors have made significant advances in the treatment of breast cancer, especially in tumors with homologous recombination deficiency such as BRCA1/2-mutated cancers. Nevertheless, intrinsic and acquired resistance restrict their clinical usefulness in the long term. This review synthesizes existing evidence about the biological roles of PARPs and the molecular aspects of resistance to PARP inhibition in breast cancer. The major mechanisms of resistance are restoration of homologous recombination, loss of 53BP1, stabilization of replication forks, increased drug efflux, loss of PARG and epigenetic changes. We also discuss the interaction of PARP signaling with key therapeutic pathways, including endocrine, HER2-targeted, and PI3K/AKT signaling and contributes to the tumor microenvironment modulation and immune evasion. Notably, the next-generation PARP1-selective inhibitors, rational combination therapies, and biomarker-guided treatment approaches are emerging strategies that can be used to overcome resistance. All of these observations point towards the necessity to combine mechanistic knowledge with clinical innovation to enhance the selection of patients and the sustainability of therapy. The development of biomarker-mediated and combination approaches will play a vital part in increasing the efficacy of PARP inhibitors and the results achieved among patients with breast cancer.
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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.