Combined modeling of bulk and single-cell genome sequencing data to dissect clonal heterogeneity in acute myeloid leukemia

Abstract

Intra-tumor heterogeneity describes the coexistence of multiple genetically distinct subclones within the tumor of a patient resulting from somatic evolution, clonal diversification, and selection. It is a main causal driver of therapy resistance in the clinic by already containing subclones that are resistant to therapy or by subclones acquiring resistance to therapy. Therefore, the understanding of intra-tumor heterogeneity and tumor development may lead to new approaches and targets for treatment. In this thesis, I developed a method for the integrated analysis of bulk and single-cell DNA sequencing data of core-binding factor acute myeloid leukemia patients, which is defined by the presence of a RUNX1-RUNX1T1 or CBFB-MYH11 fusion gene. I generated a combined bulk and single-cell dataset of 9 core-binding factor acute myeloid leukemia patients with samples at diagnosis, complete remission and relapse. Using this method, I was able to reconstruct tumor development including somatic variants, somatic copy-number alterations and fusion genes from a single tumor sample and, if available, from merged diagnosis and relapse samples showing tumor evolution under the pressure of chemotherapy. I performed an in-depth analysis of small-scale and large-scale genomic alterations of leukemia patients and, moreover, demonstrate that my developed method can detect subclonal copy-number alterations with a higher resolution as compared to current methods.