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2749 Evolution of Clinically Relevant Subclones during Chemotherapy Treatment of ALL As Determined By Single-Cell DNA and RNA Sequencing

Program: Oral and Poster Abstracts
Session: 618. Acute Lymphoblastic Leukemia: Biology, Cytogenetics, and Molecular Markers in Diagnosis and Prognosis: Poster II
Hematology Disease Topics & Pathways:
Diseases, Leukemia, ALL, Lymphoid Malignancies
Sunday, December 8, 2019, 6:00 PM-8:00 PM
Hall B, Level 2 (Orange County Convention Center)

Llucia Albertí Servera, PhD1*, Sofie Demeyer, PhD1*, Inge Govaerts, MD, PhD1*, Olga Gielen1*, Heidi Segers, MD, PhD2*, Anne Uyttebroeck, MD2*, Nancy Boeckx2*, Johan A. Maertens, MD, PhD2*, Kim De Keersmaecker, PhD3 and Jan Cools, PhD1

1Center for Cancer Biology, VIB-KU Leuven, Leuven, Belgium
2University Hospital Leuven, Leuven, Belgium
3Laboratory for Disease Mechanisms in Cancer, KU Leuven, Leuven, Belgium

Acute lymphoblastic leukemia (ALL), which is the most common cancer in children, shows extensive genetic intra-tumoral heterogeneity. This heterogeneity might be the underlying reason for an incomplete response to treatment and for the development of relapse. In order to envision the clinical implementation of a refined risk-category strategy based on ALL subclonal composition, it is essential to first generate a reference single-cell map and accumulate evidence on how the subclonal composition affects the response to treatment. For that, we performed large-scale and integrative single-cell genome and transcriptome profiling of pediatric samples at diagnosis, during drug treatment and in case of relapse. We used the 10x Genomics platform for single-cell RNA-sequencing analysis (around 4000 cells per sample) and the Tapestri Platform (Mission Bio) for targeted single-cell DNA-sequencing (around 5000 cells per sample) of the most mutated genomic regions in ALL. For the later, we developed a custom panel that covers 305 ALL mutational hotspots across 110 genes.

We have determined a reference single-cell map of the cellular (based on the gene expression profile) and the clonal composition (based on the co-occurrence of mutations at each individual cell) for pediatric ALL at diagnosis (8 T-ALL and 10 B-ALL patients). We have also reconstructed the tumor phylogeny highlighting the order of mutational acquisition and the most likely pattern of evolution. Moreover, we have studied how T-ALL evolves during drug treatment at single-cell resolution in 4 patients, unraveling which are the most sensitive clones to the therapy, which are the most resistant ones and when relapse clones originated. Single-cell RNA-sequencing also provided information on how normal hematopoiesis recovers during chemotherapy treatment.

The results show that ALL is typically composed by a major clone and 5-10 smaller clones that have different sensitivities to the therapy. We have been able to detect minor clones (<1% of the cells) at diagnosis that are clinically relevant. These very rare clones are either not responding to the therapy (present at minimal residual disease) or form the relapsed leukemia. These findings could have clinical implications for improved risk-stratification methods based on individualized patient’s molecular profiles.

Disclosures: Maertens: Gilead Sciences: Other: Grants, personal fees and non-financial support; Cidara: Other: Personal fees and non-financial support; Amplyx: Other: Personal fees and non-financial support; F2G: Other: Personal fees and non-financial support; Merck: Other: Personal fees and non-financial support; Pfizer: Other: Grant and personal fees; Astellas Pharma: Other: Personal fees and non-financial support.

*signifies non-member of ASH