ReviewJournal of Cancer2026
Overcoming Resistance to PARP Inhibitors in BRCA-Mutated Cancers: Mechanisms and Therapeutic Strategies.
Review in Journal of Cancer, 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
No grant is acknowledged in the PubMed record.
Abstract
The tumor suppressor genes BRCA1 and BRCA2 are essential for homologous recombination (HR) repair. Mutations in BRCA1/2 compromise HR repair efficacy, resulting in heightened susceptibility of tumor cells to poly (ADP-ribose) polymerase inhibitors (PARPi) via synthetic lethality. To date, several PARPi have been approved for BRCA-mutated and HR-deficient tumors, but acquired resistance and cumulative toxicity continue to limit their long-term clinical benefit. This narrative review offers an updated mechanistic model of PARPi action and categorizes resistance mechanisms by clinical relevance and evidentiary strength. Importantly, we distinguish between standard combination therapies in the PARPi-naïve setting and interventions explicitly tailored for PARPi-exposed or PARPi-resistant disease. Building on this distinction, we propose a biomarker-guided framework that links specific resistance phenotypes to appropriate specimen types, detection assays, and candidate interventions. Through this evidence-based clinical framework, we aim to clarify the current therapeutic landscape, improve data interpretation, and guide prospective trial design.
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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 Socratic graph.