Abstract 3529: Detection of genomic structural variations associated with drug sensitivities and resistance in AML using novel whole genome imaging

Abstract

Abstract Acute myeloid leukemia (AML) is a particularly devastating collection of hematological cancers and whilst somewhat rare, the patient survival rate is abysmal without bone marrow transplantation. Traditional chemotherapies administered to AML patients cause significant and devastating side effects. Additionally, more than 30% of patients fail to respond to these initial treatments and most patients that do respond will eventually relapse within 5 years. As such, understanding the evolution of AML to identify novel targets, and therefore drug treatment regimens, is a significant medical need. Genomic rearrangements and other Structural Variations (SVs) have long been known to be causative and pathogenic in multiple cancers, including leukemias. Indeed the discovery of the “Philadelphia chromosome” (eventually identified as a BCR-ABL translocation) as causative in Chronic Myeloid Leukemia has prompted much research into SVs in cancers, including the development of targeted therapeutics against oncogenic proteins resulting from genomic rearrangements. These SVs may be involved in cancer initiation, progression, clonal evolution, and drug resistance, and a better understanding of SVs from individual AML patients may help guide therapeutic options. Here we show utilization of an innovative whole genome imaging technology to detect known, and novel, SVs in AML patients' samples. Importantly, this new technology provides an unprecedented level of granularity and quantitation unavailable to other current techniques and it allows an unbiased detection of novel SVs, which may be relevant for disease pathogenesis and/ or drug resistance. Coupled with standard gene expression analyses we have also assessed the chemosensitivities of these samples to 120 FDA approved oncology drugs and 335 epigenetic modulating agents. Here we show how integrative analysis of these diverse datasets is used to associate the detected genomic rearrangements with drug sensitivity profiles, potentially identifying novel therapeutic targets for individual AML patients. Citation Format: Darren Finlay, Rabi Murad, Karl Hong, Joyce Lee, Andy Pang, Chi-Yu Lai, Carol Burian, James Mason, Alex Hastie, Jun Yin, Kristiina Vuori. Detection of genomic structural variations associated with drug sensitivities and resistance in AML using novel whole genome imaging [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3529.