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Integrative analysis of drug response and clinical outcome in acute myeloid leukemia

2022; Cell Press; Volume: 40; Issue: 8 Linguagem: Inglês

10.1016/j.ccell.2022.07.002

1878-3686

Daniel Bottomly, Nicola Long, Anna Reister Schultz, Stephen E. Kurtz, Cristina E. Tognon, Kara Johnson, Melissa L. Abel, Anupriya Agarwal, Sammantha Avaylon, Erik Benton, Aurora Blucher, Uma Borate, Theodore P. Braun, Jordana Brown, Jade Bryant, Russell T. Burke, Amy Carlos, Bill H. Chang, Hyun Cho, Stephen Christy, Cody Coblentz, Aaron Cohen, Amanda d’Almeida, Rachel J. Cook, Alexey V. Danilov, Kim‐Hien T. Dao, Michie Degnin, James Dibb, Christopher A. Eide, Isabel English, Stuart Hagler, Heath Harrelson, Rachel Henson, Hibery Ho, Sunil K. Joshi, Brian Junio, Andy Kaempf, Yoko Kosaka, Ted Laderas, Matt Lawhead, Hyun-Jung Lee, Jessica T. Leonard, Chenwei Lin, Evan Lind, Selina Qiuying Liu, Pierrette Lo, Marc Loriaux, Samuel B. Luty, Julia E. Maxson, Tara A. Macey, Jacqueline Martinez, Jessica Minnier, Andrea Monteblanco, Motomi Mori, Quinlan Morrow, Dylan Nelson, Justin Ramsdill, Angela Rofelty, Alexandra Rogers, Kyle A. Romine, Peter Ryabinin, Jennifer N. Saultz, David A. Sampson, Samantha L. Savage, Robert Schuff, Robert P. Searles, Rebecca L. Smith, Stephen E. Spurgeon, Tyler Sweeney, Ronan T. Swords, Aashis Thapa, Karina Thiel-Klare, Elie Traer, Jake Wagner, Beth Wilmot, Joelle Wolf, Guanming Wu, Amy Yates, Haijiao Zhang, Christopher R. Cogle, Robert H. Collins, Michael W. Deininger, Christopher S. Hourigan, Craig T. Jordan, Tara L. Lin, Micaela Martínez, Rachel R. Pallapati, Daniel A. Pollyea, Anthony D. Pomicter, Justin M. Watts, Scott J. Weir, Brian J. Druker, Shannon K. McWeeney, Jeffrey W. Tyner,

Epigenetics and DNA Methylation

Acute myeloid leukemia (AML) is a cancer of myeloid-lineage cells with limited therapeutic options. We previously combined ex vivo drug sensitivity with genomic, transcriptomic, and clinical annotations for a large cohort of AML patients, which facilitated discovery of functional genomic correlates. Here, we present a dataset that has been harmonized with our initial report to yield a cumulative cohort of 805 patients (942 specimens). We show strong cross-cohort concordance and identify features of drug response. Further, deconvoluting transcriptomic data shows that drug sensitivity is governed broadly by AML cell differentiation state, sometimes conditionally affecting other correlates of response. Finally, modeling of clinical outcome reveals a single gene, PEAR1, to be among the strongest predictors of patient survival, especially for young patients. Collectively, this report expands a large functional genomic resource, offers avenues for mechanistic exploration and drug development, and reveals tools for predicting outcome in AML.