Genomic and epigenomic heterogeneity in chronic lymphocytic leukemia

Abstract

Defining features of chronic lymphocytic leukemia (CLL) are not only its immunophenotype of CD19(+)CD5(+)CD23(+)sIgdim expressing clonal mature B cells but also its highly variable clinical course. In recent years, advances in massively parallel sequencing technologies have led to rapid progress in our understanding of the CLL genome and epigenome. Overall, these studies have clearly demarcated not only the vast degree of genetic and epigenetic heterogeneity among individuals with CLL but also even within individual patient leukemias. We herein review the rapidly growing series of studies assessing the genetic and epigenetic features of CLL within clinically defined periods of its growth. These studies strongly suggest an evolving spectrum of lesions over time and that these features may have clinical impact.

Figure 1

The mutational landscape of CLL. (A) The discovery of recurrently CLL mutated genes has become more sensitive with increased cohort size, with the estimated sensitivity calculated through saturation analysis^,,; (B) Frequency of gene mutations depending on the course of the disease. “Early” (newly diagnosed and untreated patients); “Frontline” (untreated patients with symptomatic CLL requiring therapy); and “R/R” (relapsing or refractory patients). Unselected cohorts have been included from: DFCI/Broad Institute, Amedeo Avogadro University of Eastern Piedmont, Novara and Sapieza University (Rome, Italy)/Columbia University (New York); ERIC ; MLL; and SCALE. Reported are also series from clinical trials: UK LRF CLL4^,; GCLLSG CLL8, CLL2H, and CLL3X; GCFLLC/MW-GOELAMS ICLL01, and UK NCRN CLL201 and CLL202. DCFI, Dana-Farber Cancer Institute; ERIC, European Research Initiative on CLL; GCFLLC/MW-GOELAMS, French CLL Intergroup; GCLLSG, German CLL Study Group; MLL, Munich Leukemia Laboratory; SCALE, Scandinavian Lymphoma Etiology; UK LRF, United Kingdom Lymphoma Research Foundation; UK NCRN, United Kingdom National Cancer Research Network.

Figure 2

Putative core cellular pathways affected by significantly mutated genes in CLL. Blue-genes identified from CLL series by Wang et al, Puente et al, and Quesada et al (n = 4 to 105 samples); orange-genes identified by Landau et al (n = 160 subjects); black-genes affected by 262 subjects; yellow gene mutations identified in relationship to drug resistance.^, Several of the affected pathways likely serve as an important bridge with the microenvironment, which is of particular importance in CLL (crucial actors of the CLL microenvironment are represented by NLCs, MSCs, and T cells. NLCs, nurse-like cells; NF-κB, nuclear factor-κB; MSCs, marrow stroma cells; mTOR, mammalian target of rapamycin; TLR, toll-like receptor.

Figure 3

Heterogenous evolutionary trajectories through CLL course and therapeutic intervention. (A) Typical CLL disease course; (B) phylogenetic tree of CLL leukemogenesis (each arrow represents the acquisition of a genetic event); (C) evolution of the CLL phylogenetic tree at various stages of the CLL disease course.^,,-

Figure 4

Model of clonal diversification and selection in CLL. (A) Locally disordered DNA methylation is higher in CLL and cancer tissues compared with normal tissues, including B cells (adapted from Landau et al); (B) Adverse impact of locally disordered DNA methylation on failure-free survival; (C) Clonal diversification may result from synergic effects of disordered DNA methylation and genomic instability (left). Clonal selection related to therapeutic and microenvironment pressure shapes the subclonal composition that ranges from clonal equilibrium to clonal competition (right). High level of clonal diversification could lead to the emergence of fitter subclones competing within CLL bulk and is responsible for more aggressive/resistant disease associated with poor survival.