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

Research output: Contribution to journalPublished meeting abstract


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, naive-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), naive 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, plt;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.Disclosures Papakonstantinou: Janssen Pharmaceuticals: Research Funding; Gilead: Research Funding. Smedby: Janssen: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees. Gaidano: Roche: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Ghia: AbbVie: Consultancy; Adaptive: Consultancy; Gilead: Consultancy, Research Funding, Speakers Bureau; Janssen: Consultancy, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy; Roche: Consultancy; Novartis: Research Funding. Stamatopoulos: Novartis SA: Research Funding; Gilead: Consultancy, Honoraria, Research Funding; Janssen Pharmaceuticals: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding.↵* Asterisk with author names denotes non-ASH members.


  • Richard Rosenquist
  • Larry Mansouri
  • Sujata Bhoi
  • Giancarlo Castellano
  • Lesley Ann Sutton
  • Nikos Papakonstantinou
  • Ana Queirós
  • Panagiotis Baliakas
  • Karla Plevova
  • Stavroula Ntoufa
  • Zadie Davis
  • Emma Young
  • Hanna Goransson-Kultima
  • Anders Isaksson
  • Karin E Smedby
  • Gianluca Gaidano
  • Anton W Langerak
  • Frederic Davi
  • Davide Rossi
  • David Oscier
  • Sarka Pospisilova
  • Paolo Ghia
  • Elias Campo
  • Kostas Stamatopoulos
  • Inaki Martin Subero
External organisations
  • Uppsala University
  • Institutd' Investigacions Biomèdiques August Pi iSunyer (IDIBAPS)
  • Center for Research and Technology Hellas
  • Masaryk University
  • University of Eastern Piedmont
  • Royal Bournemouth Hospital
  • Karolinska Institutet
  • Erasmus University Medical Center
  • Pierre and Marie Curie University
  • Institute of Oncology Research (IOR)
  • Vita-Salute San Raffaele University
  • Hospital Clínic of Barcelona
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Hematology
Original languageEnglish
Pages (from-to)57-57
Number of pages1
Issue numberSuppl 1
Publication statusPublished - 2017
Publication categoryResearch
Event59th American Society of Hematology (ASH) Annual Meeting - Atlanta, United States
Duration: 2017 Dec 92017 Dec 12