Genome-Wide DNA Methylation Profiling of Chronic Lymphocytic Leukemia Subsets Carrying Stereotyped B Cell Receptors

In recent years, subsets of chronic lymphocytic leukemia (CLL) patients carrying quasi-identical or stereotyped B cell receptors (BcRs) have been identified that share clinicobiological features and disease outcome. While these stereotyped subsets show distinct gene expression and genomic profiles, the DNA methylation landscape remains largely unexplored. By applying high-resolution 450K methylation arrays, we investigated 176 CLL subset cases belonging to: (i) the clinically aggressive, IGHV-unmutated (U-CLL) subsets #1 (clan I genes/IGKV(D)1-39, n=37) and #8 (IGHV4-39/IGKV1(D)-39, n=21); (ii) the IGHV1-69-expressing U-CLL subsets #3 (n=12), #5 (n=9), #6 (n=22), and #7 (n=12); and, (iii) the indolent, IGHV-mutated (M-CLL) subset #4 (IGHV4-34/IGKV2-30, n=28). In addition, we included subset #2 cases (IGHV3-21/IGLV3-21, mixed mutation status, n=35) that have a poor outcome independent of IGHV mutation status. For comparative purposes, we included a cohort of CLL cases that do not express stereotyped BcRs ('non-subset', n=325). These patients were subgrouped according to the recently proposed epigenetic classification of CLL, i.e. poor-prognostic, naïve-like CLL (n-CLL, n=102), favorable-prognostic, memory-like CLL (m-CLL; n=176), broadly corresponding to U-CLL and M-CLL, respectively, and a third intermediate CLL subgroup (i-CLL; n=47), which express borderline mutated IGHV genes and have an intermediate prognosis. Finally, a series of sorted normal subpopulations spanning different stages of B-cell differentiation [precursors (n=22), naïve B cells (n=19) and germinal center/memory B-cells (n=33)] were also included in the analysis. Overall, unsupervised analysis of subset vs. non-subset CLL revealed that all U-CLL subsets clustered with n-CLL, subset #4 clustered with m-CLL, while subset #2 clustered separately with i-CLL (Figure 1). Supervised analysis revealed a limited number of CpG sites that were differentially methylated when comparing each U-CLL or M-CLL subset with non-subset cases. In contrast, almost all subset #2 cases clustered separately from i-CLL in supervised analysis, indicating that this subset might represent a distinct subgroup of i-CLL. We recently demonstrated that the number of epigenetic changes that a tumor acquires, compared to its cellular origin (i.e. 'epigenetic burden'), may be a powerful predictor of clinical aggressiveness (Queiros et al, Cancer Cell 2016). When adopting this approach in CLL, comparison of specific subsets vs. their non-subset cases matched by epigenetic subgroup, revealed significant differences in the epigenetic burden amongst the various groupings; for instance, in subset #1 vs. n-CLL (72K vs. 67K, p<0.05) and in subset #2 vs. i-CLL (76K vs. 68K, p=0.001), while no difference was observed between subset #4 vs. m-CLL (83K vs. 82K, p=not significant). Subset #2 cases frequently carry del(11q) and harbor SF3B1 mutations, however, neither the IGHV mutation status nor the presence of del(11q) or SF3B1 mutations had any impact on the epigenetic burden within subset #2. In conclusion, U-CLL and M-CLL subsets generally clustered with n-CLL and m-CLL categories, respectively, implying common cellular origins. In contrast, subset #2 emerged as the first defined member of the i-CLL group, which in turn alludes to a distinct cellular origin and/or pathogenetic process for subset #2 and i-CLL patients.

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