Poster Presentation 41st Lorne Genome Conference 2020

Deciphering clonal competition and therapeutic resistance in AML at single-cell resolution using transcribed molecular barcodes (#265)

Dane Vassiliadis 1 2 , Katie A Fennell 1 2 , Luciano Martelotto 3 , Tom Weber 4 5 , Fernando Rossello 3 , Enid Y.N. Lam 1 2 , Shalin H Naik 4 5 , Mark A Dawson 1 2 3 6
  1. Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
  2. Sir Peter MacCallum Department of Oncology, University of Melbourne, VIC, Australia
  3. Centre for Cancer Research, University of Melbourne, Melbourne, VIC, Australia
  4. The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
  5. The Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
  6. Department of Hematology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia

For patients diagnosed with Acute Myeloid Leukaemia (AML), complete clinical remission is regularly achieved with current gold-standard therapeutic regimens, however tumours will commonly relapse with acquired resistance to the initial therapy. Relapsed AML is essentially incurable, highlighting the urgent need to understand the adaptive response mounted by residual leukaemia cells that leads to clinical relapse. Underpinning the poor prognosis of AML is a vast intra-tumoral clonal heterogeneity. Genetic heterogeneity arises via the acquisition of genetic lesions in addition to founding mutations. In contrast, epigenetic heterogeneity, a second major driver of intra-tumoral heterogeneity, results in distinct transcriptional profiles between genetically identical malignant clones. Recent genomic analyses of patient samples show that up to 40% of cases possess no relapse-specific coding mutations suggesting epigenetic heterogeneity as the mechanism of resistance. It is currently unclear how epigenetic heterogeneity impacts the ability of AML clones to colonise and expand in vivo. Moreover, the mechanism(s) that initiate and maintain stable epigenetic heterogeneity to promote clonal outgrowth and therapeutic resistance are poorly understood.

We developed a novel DNA barcoding system that can be detected with current droplet based single cell RNA and ATAC sequencing technologies to examine epigenetic heterogeneity within thousands of distinct cancer subclones over time. Using this toolkit, we modelled clonal competition between three genetically distinct AML subtypes by following the performance of individual clones during in vivo competition scenarios. Second, we modelled epigenetic resistance to targeted and conventional chemotherapies in populations of barcoded AML cells to determine the specific transcriptional features of resistant clones that are required to establish and maintain epigenetic therapeutic resistance. Overall, this work has identified key epigenetic and transcriptional drivers that are predictive of clonal dominance and therapeutic resistance. This work will inform the development of approaches that limit the ability of malignant clones to utilise these epigenetic pathways.