Monitoring chronic lymphocytic leukemia progression by whole genome sequencing reveals heterogeneous clonal evolution patterns

Abstract

Chronic lymphocytic leukemia is characterized by relapse after treatment and chemotherapy resistance. Similarly, in other malignancies leukemia cells accumulate mutations during growth, forming heterogeneous cell populations that are subject to Darwinian selection and may respond differentially to treatment. There is therefore a clinical need to monitor changes in the subclonal composition of cancers during disease progression. Here, we use whole-genome sequencing to track subclonal heterogeneity in 3 chronic lymphocytic leukemia patients subjected to repeated cycles of therapy. We reveal different somatic mutation profiles in each patient and use these to establish probable hierarchical patterns of subclonal evolution, to identify subclones that decline or expand over time, and to detect founder mutations. We show that clonal evolution patterns are heterogeneous in individual patients. We conclude that genome sequencing is a powerful and sensitive approach to monitor disease progression repeatedly at the molecular level. IntroductionDespite significant progress in the management of lymphomas and leukemias, relapse remains the major cause of death. Increased use of expensive targeted therapies and toxic chemotherapies (especially in the elderly) confronts us with an urgent need to improve response prediction for all cancer patients to reduce side effects and costs from ineffective treatment. Current diagnostic approaches to treatment selection, response monitoring, and relapse prediction are limited to single genes and apply only to a minority of hematologic cancers. This is at odds with modern concepts of tumor propagation and maintenance, which propose that every cell in an individual cancer is characterized by a combination of mutation events that comprise tumorigenic (driver) mutations, passive (passenger) mutations, and possibly predisposing germline risk variants. Cancer cells propagate and diversify during tumor growth, resulting in a heterogeneous population of genotypically and phenotypically distinct subclones that are related in a hierarchical lineage. As the composition of the local environment changes, for example as a consequence of drug treatment, tumor cell populations adapt and evolve by Darwinian selection. [1][2][3] Whole-genome sequencing (WGS) of a single tumor sample can be used to generate a comprehensive catalog of variants that provides a snapshot of the cell population en masse at a particular time point. 2,4-6 However, over time and with continued evolution of the cancer, this snapshot becomes progressively less representative of the disease. Recent reports have described whole-tumor genomes from single patients or cohorts of individuals mostly at single time points and irrespective of treatment. [7][8][9][10] This approach has enabled identification of mutations representative and in some cases highly predictive of histologic cancer type, outcome, and/or treatment response. [11][12][13][14][15] Comparison of sequence data from primary and metastatic tumor samples, or from multiple lo...

Lyapunov–Schmidt and Centre Manifold Reduction Methods for Nonlocal PDEs Modelling Animal Aggregations

“…The existence of these dominant behaviours exhibited by the u 1 or u 2 populations are consistent with the principle of competitive exclusion of clonal sub-populations in heterogeneous tumours (Egan Keats et al, 2012;Leith et al, 1989). In Fisher et al (2013) the authors interpreted the experimental data, which showed suppression and reappearance of cancer clones in myeloma patients (Keats et al, 2012) and chronic lymphocytic leukaemia patients (Schuh et al, 2012), by suggesting that two subclones can exist in a dynamic equilibrium. While all these experimental studies record the survival/suppression of tumour clones in various cancers, they do not offer a mechanistic explanation for the factors that could lead to these behaviours.…”

“…In this study, we will investigate the role of cancer mutation on the possibility of clonal competition with alternating dominance or even competitive exclusion between two cancer cell sub-populations (as discussed before, these types of competition have been observed experimentally (Leith et al, 1989;Keats et al, 2012;Schuh et al, 2012)). To this end, we will introduce a nonlocal model for cell-cell and cell-matrix adhesion for two populations of cells (this model is a generalization of the models in Armstrong et al (2006); Gerisch & Chaplain (2008); Painter et al (2015)).…”

EGR2 mutations define a new clinically aggressive subgroup of chronic lymphocytic leukemia

“…Probes targeting all coding exons or hotspot regions of 27 known CLL driver genes and/or genes previously reported in EGR2-mutated CLL 19,29,[37][38][39][40][41][42][43][44] were designed using Agilent"s SureDesign service (https://earray.chem.agilent.com/suredesign/home.htm, Supplemental Table S4). …”

Chronic lymphocytic leukemia: Time to go past genomics?

“…It is not known at the moment whether the mutation order is important for the clinical course but similar to clonal, subclonal mutations may carry prognostic value [35]. Integrating genomic data from sequential samples, three types of CLL evolution were identified, which associate with patient's course: (i) no evolution, (ii) linear evolution, and (iii) branched evolution [9,11,26,[129][130][131][132]. Branched evolution is associated with disease evolution and dismal prognosis, probably because the generated genetic diversity allows for a more efficient selection of fitted cells.…”