Genomics of Acute Myeloid Leukemia at Diagnosis and Remission
Yu, K.; Dillon, L. W.; Tettero, J. M.; Gui, G.; Al-Ali, R. W.; Grunwald, M. R.; Krakow, E. F.; Griffiths, E.; Gomez-Arteaga, A.; Vedula, R. S.; Solh, M.; Salhotra, A.; Bejanyan, N.; Muffly, L.; Jimenez-Jimenez, A. M.; Drazer, M. W.; Chen, Y.-B.; Logan, A.; Jayani-Kosarzycki, R. V.; Balderman, S. R.; Blachly, J. S.; Shaffer, B.; Druhan, L. J.; Yeung, C. C.; Kennedy, V. E.; Fathi, A. T.; Carraway, H. E.; Gurbuxani, S.; Tjota, M.; Sahoo, F.; Smith, M.; Barfield, D.; Guo, J.; Han, J.; Hu, J.; Jo, H.; Kudlingar, V.; Li, W. W.; Qiu, Y.; Sathyan, P.; Truong, S.; Catreux, S.; Ng, S.; Luong, K.; Zhu, Y
Show abstract
Accurate and comprehensive genetic characterization of acute myeloid leukemia (AML) is essential for diagnosis, prognostication, and treatment selection. We report here, in 255 adults with AML enrolled in a prospective clinical protocol at 18 major cancer centers across the USA, the results of whole genome DNA-sequencing (WGS) at diagnosis and post-treatment remission. WGS effectively recapitulated, and frequently identified genetic alterations missed by, conventional standard of care clinical testing. These new findings included important prognostic and predictive biomarkers, copy number alterations, regulatory element, splicing, and structural variants including partial tandem duplications within KMT2A. All patients had a pathogenic variant detected at diagnosis, and approximately ten percent also had evidence of a potential inherited myeloid malignancy predisposition. This comprehensive atlas of adult AML genomics provides novel insights into disease biology, creates an evidentiary basis to support clinical testing improvements, and is a resource for both diagnostics and drug development. <This work is embargoed, with agreement of medRxiv, until 7th December 2025>. Statement of SignificanceAcute myeloid leukemia is a diagnostic category encompassing multiple rare hematological malignances. We show, in this nationwide multicenter study, that standardized unbiased whole genome DNA-sequencing and disease-optimized bioinformatics can replicate conventional "standard of care" AML clinical testing results, while also revealing currently underdiagnosed AML disease biology and potential genetic predisposition.
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