Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:2.4.2.30 (PARP)
 13,611 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Breast Cancer Type 1 Susceptibility Protein (BRCA1)-deficient cells have compromised DNA repair and are sensitive to poly(ADP-ribose) polymerase (PARP) inhibitors. Despite initial responses, the development of resistance limits clinical efficacy. Mutations in the BRCA C-terminal (BRCT) domain of BRCA1 frequently create protein products unable to fold that are subject to protease-mediated degradation. Here, we show HSP90-mediated stabilization of a BRCT domain mutant BRCA1 protein under PARP inhibitor selection pressure. The stabilized mutant BRCA1 protein interacted with PALB2-BRCA2-RAD51, was essential for RAD51 focus formation, and conferred PARP inhibitor as well as cisplatin resistance. Treatment of resistant cells with the HSP90 inhibitor 17-dimethylaminoethylamino-17-demethoxygeldanamycin reduced mutant BRCA1 protein levels and restored their sensitivity to PARP inhibition. Resistant cells also acquired a TP53BP1 mutation that facilitated DNA end resection in the absence of a BRCA1 protein capable of binding CtIP. Finally, concomitant increased mutant BRCA1 and decreased 53BP1 protein expression occur in clinical samples of BRCA1-mutated recurrent ovarian carcinomas that have developed resistance to platinum. These results provide evidence for a two-event mechanism by which BRCA1-mutant tumors acquire anticancer therapy resistance.
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PMID:Stabilization of mutant BRCA1 protein confers PARP inhibitor and platinum resistance. 2408 45

Cancer aggressiveness and its effect on patient survival depends on mutations in the tumor genome. Epistatic interactions between the mutated genes may guide the choice of anticancer therapy and set predictive factors of its success. Inhibitors targeting synthetic lethal partners of genes mutated in tumors are already utilized for efficient and specific treatment in the clinic. The space of possible epistatic interactions, however, is overwhelming, and computational methods are needed to limit the experimental effort of validating the interactions for therapy and characterizing their biomarkers. Here, we introduce SurvLRT, a statistical likelihood ratio test for identifying epistatic gene pairs and triplets from cancer patient genomic and survival data. Compared to established approaches, SurvLRT performed favorable in predicting known, experimentally verified synthetic lethal partners of PARP1 from TCGA data. Our approach is the first to test for epistasis between triplets of genes to identify biomarkers of synthetic lethality-based therapy. SurvLRT proved successful in identifying the known gene TP53BP1 as the biomarker of success of the therapy targeting PARP in BRCA1 deficient tumors. Search for other biomarkers for the same interaction revealed a region whose deletion was a more significant biomarker than deletion of TP53BP1. With the ability to detect not only pairwise but twelve different types of triple epistasis, applicability of SurvLRT goes beyond cancer therapy, to the level of characterization of shapes of fitness landscapes.
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PMID:Epistasis in genomic and survival data of cancer patients. 3081 79