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Citation Information: J Clin Invest. 2017;127(6):2392-2406. https://doi.org/10.1172/JCI90825.
Abstract
Quiescent and proliferating leukemia cells accumulate highly lethal DNA double-strand breaks that are repaired by 2 major mechanisms: BRCA-dependent homologous recombination and DNA-dependent protein kinase–mediated (DNA-PK–mediated) nonhomologous end-joining, whereas DNA repair pathways mediated by poly(ADP)ribose polymerase 1 (PARP1) serve as backups. Here we have designed a personalized medicine approach called gene expression and mutation analysis (GEMA) to identify BRCA- and DNA-PK–deficient leukemias either directly, using reverse transcription-quantitative PCR, microarrays, and flow cytometry, or indirectly, by the presence of oncogenes such as BCR-ABL1. DNA-PK–deficient quiescent leukemia cells and BRCA/DNA-PK–deficient proliferating leukemia cells were sensitive to PARP1 inhibitors that were administered alone or in combination with current antileukemic drugs. In conclusion, GEMA-guided targeting of PARP1 resulted in dual cellular synthetic lethality in quiescent and proliferating immature leukemia cells, and is thus a potential approach to eradicate leukemia stem and progenitor cells that are responsible for initiation and manifestation of the disease. Further, an analysis of The Cancer Genome Atlas database indicated that this personalized medicine approach could also be applied to treat numerous solid tumors from individual patients.
Authors
Margaret Nieborowska-Skorska, Katherine Sullivan, Yashodhara Dasgupta, Paulina Podszywalow-Bartnicka, Grazyna Hoser, Silvia Maifrede, Esteban Martinez, Daniela Di Marcantonio, Elisabeth Bolton-Gillespie, Kimberly Cramer-Morales, Jaewong Lee, Min Li, Artur Slupianek, Daniel Gritsyuk, Sabine Cerny-Reiterer, Ilona Seferynska, Tomasz Stoklosa, Lars Bullinger, Huaqing Zhao, Vera Gorbunova, Katarzyna Piwocka, Peter Valent, Curt I. Civin, Markus Muschen, John E. Dick, Jean C.Y. Wang, Smita Bhatia, Ravi Bhatia, Kolja Eppert, Mark D. Minden, Stephen M. Sykes, Tomasz Skorski
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