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Daniel Bottomly, Nicola Long, Anna Reister Schultz, Stephen E Kurtz, Cristina E 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 H Chang, Hyun Jun Cho, Stephen Christy, Cody Coblentz, Aaron M Cohen, Amanda d'Almeida, Rachel Cook, Alexey 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, Hyunjung Lee, Jessica T Leonard, Chenwei Lin, Evan F Lind, Selina Qiuying Liu, Pierrette Lo, Marc M Loriaux, Samuel Luty, Julia E Maxson, Tara 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 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 E Martinez, Rachel R Pallapati, Daniel A Pollyea, Anthony D Pomicter, Justin M Watts, Scott J Weir, Brian J Druker, Shannon K McWeeney, Jeffrey W Tyner
Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA.
Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, USA; Division of Hematology & Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, OR 97239, USA.
Cancer Cell. 2022 Aug 8;40(8):850-864.e9. doi: 10.1016/j.ccell.2022.07.002. Epub 2022 Jul 21.
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.
急性髓系白血病 (AML) 是一种骨髓谱系细胞的癌症，治疗选择有限。我们之前将体外药物敏感性与基因组、转录组和临床注释相结合，对一大群 AML 患者进行了研究，这有助于发现功能基因组相关性。在这里，我们提供了一个与我们最初报告相协调的数据集，得到了一个包含 805 名患者（942 个样本）的累积队列。我们显示了强烈的跨队列一致性，并确定了药物反应的特征。此外，对转录组数据的去卷积表明，药物敏感性广泛受 AML 细胞分化状态的控制，有时会对其他反应相关因素产生条件影响。最后，对临床结果的建模表明，单个基因 PEAR1 是预测患者生存的最强预测因子之一，尤其是对年轻患者。总的来说，本报告扩展了一个大型的功能基因组资源，为机制探索和药物开发提供了途径，并揭示了预测 AML 患者预后的工具。
