Functional genomic landscape of acute myeloid leukaemia

• Published in: Nature (London) Vol. 562; no. 7728; pp. 526 - 531
• Main Authors: Tyner, Jeffrey W., Tognon, Cristina E., Bottomly, Daniel, Wilmot, Beth, Kurtz, Stephen E., Savage, Samantha L., Long, Nicola, Schultz, Anna Reister, Traer, Elie, Abel, Melissa, Agarwal, Anupriya, Blucher, Aurora, Borate, Uma, Bryant, Jade, Burke, Russell, Carlos, Amy, Carpenter, Richie, Carroll, Joseph, Chang, Bill H., Coblentz, Cody, d’Almeida, Amanda, Cook, Rachel, Danilov, Alexey, Dao, Kim-Hien T., Degnin, Michie, Devine, Deirdre, Dibb, James, Edwards, David K., Eide, Christopher A., English, Isabel, Glover, Jason, Henson, Rachel, Ho, Hibery, Jemal, Abdusebur, Johnson, Kara, Johnson, Ryan, Junio, Brian, Kaempf, Andy, Leonard, Jessica, Lin, Chenwei, Liu, Selina Qiuying, Lo, Pierrette, Loriaux, Marc M., Luty, Samuel, Macey, Tara, MacManiman, Jason, Martinez, Jacqueline, Mori, Motomi, Nelson, Dylan, Nichols, Ceilidh, Peters, Jill, Ramsdill, Justin, Rofelty, Angela, Schuff, Robert, Searles, Robert, Segerdell, Erik, Smith, Rebecca L., Spurgeon, Stephen E., Sweeney, Tyler, Thapa, Aashis, Visser, Corinne, Wagner, Jake, Watanabe-Smith, Kevin, Werth, Kristen, Wolf, Joelle, White, Libbey, Yates, Amy, Zhang, Haijiao, Cogle, Christopher R., Collins, Robert H., Connolly, Denise C., Deininger, Michael W., Drusbosky, Leylah, Hourigan, Christopher S., Jordan, Craig T., Kropf, Patricia, Lin, Tara L., Martinez, Micaela E., Medeiros, Bruno C., Pallapati, Rachel R., Pollyea, Daniel A., Swords, Ronan T., Watts, Justin M., Weir, Scott J., Wiest, David L., Winters, Ryan M., McWeeney, Shannon K., Druker, Brian J.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.10.2018; Nature Publishing Group
• Subjects: 38/23; 38/39; 38/91; 49/98; 692/53/2423; 692/699/67/1990/283/1897; 692/699/67/69; Acute myeloid leukemia; Antineoplastic agents; Bioinformatics; Cancer; Combinatorial analysis; Core Binding Factor Alpha 2 Subunit - genetics; Datasets as Topic; Discriminant analysis; DNA (Cytosine-5-)-Methyltransferases - genetics; DNA Methyltransferase 3A; Exome - genetics; Female; Gene expression; Gene Expression Regulation, Neoplastic - genetics; Gene mutation; Gene sequencing; Generalized linear models; Genes; Genetic aspects; Genetic research; Genome, Human - genetics; Genomes; Genomics; Humanities and Social Sciences; Humans; Kinases; Leukemia; Leukemia, Myeloid, Acute - drug therapy; Leukemia, Myeloid, Acute - genetics; Leukemia, Myeloid, Acute - metabolism; Male; Medical research; Molecular Targeted Therapy; multidisciplinary; Mutation; Myeloid leukemia; Nuclear Proteins - genetics; Nucleophosmin; Patients; Pharmacology; Principal components analysis; Proto-Oncogene Proteins - genetics; Repressor Proteins - genetics; Ribonucleic acid; RNA; RNA sequencing; Science; Science (multidisciplinary); Sensitivity analysis; Sequence Analysis, RNA; Serine-Arginine Splicing Factors - genetics; Tumors; BCL6 Corepressor (BCOR); Ibrutinib; Weighted Gene Correlation Network Analysis (WGCNA); Fms-related Tyrosine Kinase (FLT3); Whole Exome Sequencing
• ISSN: 0028-0836; 1476-4687
• DOI: 10.1038/s41586-018-0623-z

The implementation of targeted therapies for acute myeloid leukaemia (AML) has been challenging because of the complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. Here we report initial findings from the Beat AML programme on a cohort of 672 tumour specimens collected from 562 patients. We assessed these specimens using whole-exome sequencing, RNA sequencing and analyses of ex vivo drug sensitivity. Our data reveal mutational events that have not previously been detected in AML. We show that the response to drugs is associated with mutational status, including instances of drug sensitivity that are specific to combinatorial mutational events. Integration with RNA sequencing also revealed gene expression signatures, which predict a role for specific gene networks in the drug response. Collectively, we have generated a dataset—accessible through the Beat AML data viewer (Vizome)—that can be leveraged to address clinical, genomic, transcriptomic and functional analyses of the biology of AML. Analyses of samples from patients with acute myeloid leukaemia reveal that drug response is associated with mutational status and gene expression; the generated dataset provides a basis for future clinical and functional studies of this disease.