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

Daniel Bottomly, Nicola Long, Anna Reister Schultz, Stephen Kurtz, Cristina Tognon, Kara Johnson, Melissa Abel, Anupriya Agarwal, Sammantha Avaylon, Erik Benton, Aurora Blucher, Uma Borate, Theodore P. Braun, Jordana Brown, Jade Bryant, Russell Burke, Amy Carlos, Bill Chang, Hyun Jun Cho, Stephen ChristyCody Coblentz, Aaron M. Cohen, Amanda d'Almeida, Rachel Cook, Alexey Danilov, Kim-Hien 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, Hyunjung Lee, Jessica Leonard, Chenwei Lin, Evan Lind, Selina Qiuying Liu, Pierrette Lo, Marc Loriaux, Samuel Luty, Julia Maxson, Tara Macey, Jacqueline Martinez, Jessica Minnier, Andrea Monteblanco, Motomi (Tomi) Mori, Quinlan Morrow, Dylan Nelson, Justin Ramsdill, Angela Rofelty, Alexandra Rogers, Kyle A. Romine, Peter Ryabinin, Jennifer Saultz, David A. Sampson, Samantha L. Savage, Robert Schuff, Robert Searles, Rebecca L. Smith, Stephen Spurgeon, Tyler Sweeney, Ronan 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 E. Martinez, Rachel R. Pallapati, Daniel A. Pollyea, Anthony D. Pomicter, Justin M. Watts, Scott J. Weir, Brian Druker, Shannon McWeeney, Jeffrey Tyner

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)850-864.e9
JournalCancer Cell
Issue number8
StatePublished - Aug 8 2022


  • cell state
  • eigengene
  • hematologic malignancy
  • JEDI
  • leukemia stem cell
  • LSC17
  • MEGF12
  • monocyte
  • targeted therapy

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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