| 1. |
|
|
| 2. |
- Halldorsdottir, Anna Margret, et al.
(författare)
-
Mantle cell lymphoma displays a homogenous methylation profile : A comparative analysis with chronic lymphocytic leukemia
- 2012
-
Ingår i: American Journal of Hematology. - : John Wiley & Sons. - 0361-8609 .- 1096-8652. ; 87:4, s. 361-367
-
Tidskriftsartikel (refereegranskat)abstract
- Mantle cell lymphoma (MCL) and chronic lymphocytic leukemia (CLL) are mature CD5(+) B-cell malignancies with different biological/clinical characteristics. We recently reported an association between different prognostic subgroups of CLL (i.e., IGHV mutated and unmutated) and genomic methylation pattern. However, the relationship between DNA methylation and prognostic markers, such as the proliferation gene expression signature, has not been investigated in MCL. We applied high-resolution methylation microarrays (27,578 CpG sites) to assess the global DNA methylation profiles in 20 MCL (10 each with high/low proliferation signature) and 30 CLL (15 poor-prognostic IGHV unmutated subset #1 and 15 good-prognostic IGHV mutated subset #4) samples. Notably, MCL and each CLL subset displayed distinct genomic methylation profiles. After unsupervised hierarchical clustering, 17/20 MCL cases formed a cluster separate from CLL, while CLL subsets #1 and #4 formed subclusters. Surprisingly, few differentially methylated genes (n = 6) were identified between high vs. low proliferation MCL. In contrast, distinct methylation profiles were demonstrated for MCL and CLL. Importantly, certain functional classes of genes were preferentially methylated in either disease. For instance, developmental genes, in particular homeobox transcription factor genes (e.g., HLXB9, HOXA13), were more highly methylated in MCL, whereas apoptosis-related genes were enriched among targets methylated in CLL (e.g., CYFIP2, NR4A1). Results were validated using pyrosequencing, RQ-PCR and reexpression of specific genes. In summary, the methylation profile of MCL was homogeneous and no correlation with the proliferation signature was observed. Compared to CLL, however, marked differences were discovered such as the preferential methylation of homeobox genes in MCL.
|
|
| 3. |
- Kanduri, Meena, 1974, et al.
(författare)
-
Distinct transcriptional control in major immunogenetic subsets of chronic lymphocytic leukemia exhibiting subset-biased global DNA methylation profiles.
- 2012
-
Ingår i: Epigenetics. - : Informa UK Limited. - 1559-2294 .- 1559-2308. ; 7:12, s. 1435-42
-
Tidskriftsartikel (refereegranskat)abstract
- Chronic lymphocytic leukemia (CLL) can be divided into prognostic subgroups based on the IGHV gene mutational status, and is further characterized by multiple subsets of cases with quasi-identical or stereotyped B cell receptors that also share clinical and biological features. We recently reported differential DNA methylation profiles in IGHV-mutated and IGHV-unmutated CLL subgroups. For the first time, we here explore the global methylation profiles of stereotyped subsets with different prognosis, by applying high-resolution methylation arrays on CLL samples from three major stereotyped subsets: the poor-prognostic subsets #1 (n = 15) and #2 (n = 9) and the favorable-prognostic subset #4 (n = 15). Overall, the three subsets exhibited significantly different methylation profiles, which only partially overlapped with those observed in our previous study according to IGHV gene mutational status. Specifically, gene ontology analysis of the differentially methylated genes revealed a clear enrichment of genes involved in immune response, such as B cell activation (e.g., CD80, CD86 and IL10), with higher methylation levels in subset #1 than subsets #2 and #4. Accordingly, higher expression of the co-stimulatory molecules CD80 and CD86 was demonstrated in subset #4 vs. subset #1, pointing to a key role for these molecules in the crosstalk of CLL subset #4 cells with the microenvironment. In summary, investigation of three prototypic, stereotyped CLL subsets revealed distinct DNA methylation profiles for each subset, which suggests subset-biased patterns of transcriptional control and highlights a key role for epigenetics during leukemogenesis.
|
|
| 4. |
|
|
| 5. |
- Marincevic, Millaray, 1983-, et al.
(författare)
-
Distinct gene expression profiles in subsets of chronic lymphocytic leukemia expressing stereotyped IGHV4-34 B cell receptors
- 2010
-
Ingår i: Haematologica. - : Ferrata Storti Foundation (Haematologica). - 0390-6078 .- 1592-8721. ; 95:12, s. 2072-2079
-
Tidskriftsartikel (refereegranskat)abstract
- Background Numerous subsets of patients with chronic lymphocytic leukemia display similar immunoglobulin gene usage with almost identical complementarity determining region 3 sequences. Among IGHV4-34 cases, two such subsets with "stereotyped" B-cell receptors were recently identified, i.e. subset #4 (IGHV4-34/IGKV2-30) and subset #16 (IGHV4-34/IGKV3-20). Subset #4 patients appear to share biological and clinical features, e.g. young age at diagnosis and indolent disease, whereas little is known about subset #16 at a clinical level. DESIGN AND METHODS: We investigated the global gene expression pattern in sorted chronic lymphocytic leukemia cells from 25 subset/non-subset IGHV4-34 patients using Affymetrix gene expression arrays. RESULTS: Although generally few differences were found when comparing subset to non-subset 4/16 IGHV4-34 cases, distinct gene expression profiles were revealed for subset #4 versus subset #16. The differentially expressed genes, predominantly with lower expression in subset #4 patients, are involved in important cell regulatory pathways including cell-cycle control, proliferation and immune response, which may partly explain the low-proliferative disease observed in subset #4 patients. Conclusions Our novel data demonstrate distinct gene expression profiles among patients with stereotyped IGHV4-34 B-cell receptors, providing further evidence for biological differences in the pathogenesis of these subsets and underscoring the functional relevance of subset assignment based on B-cell receptor sequence features.
|
|
| 6. |
- Marincevic, Millaray, 1983-, et al.
(författare)
-
High-density screening reveals a different spectrum of genomic aberrations in chronic lymphocytic leukemia patients with 'stereotyped' IGHV3-21 and IGHV4-34 B-cell receptors
- 2010
-
Ingår i: Haematologica. - : Ferrata Storti Foundation (Haematologica). - 1592-8721 .- 0390-6078. ; 95:9, s. 1519-1525
-
Tidskriftsartikel (refereegranskat)abstract
- Background The existence of multiple subsets of chronic lymphocytic leukemia expressing 'stereotyped' B-cell receptors implies the involvement of antigen(s) in leukemogenesis. Studies also indicate that 'stereotypy' may influence the clinical course of patients with chronic lymphocytic leukemia, for example, in subsets with stereotyped IGHV3-21 and IGHV4-34 B-cell receptors; however, little is known regarding the genomic profile of patients in these subsets. Design and Methods We applied 250K single nucleotide polymorphism-arrays to study copy-number aberrations and copy-number neutral loss-of-heterozygosity in patients with stereotyped IGHV3-21 (subset #2, n=29), stereotyped IGHV4-34 (subset #4, n=17; subset #16, n=8) and non-subset #2 ICHV3-21 (n=13) and non-subset #4/16 IGHV4-34 (n=34) patients. Results Over 90% of patients in subset #2 and non-subset #2 carried copy-number aberrations, whereas 75-76% of patients in subset #4 and subset #16 showed copy-number aberrations. Subset #2 and non-subset #2 patients also displayed a higher average number of aberrations compared to patients in subset #4. Deletion of 13q was the only known recurrent aberration detected in subset #4 (35%); this aberration was even more frequent in subset #2 (79%). del(11q) was more frequent in subset #2 and non-subset #2 (31% and 23%) patients than in subset #4 and non-subset #4/16 patients. Recurrent copy-number neutral loss-of-heterozygosity was mainly detected on chromosome 13q, independently of B-cell receptor stereotypy. Conclusions Genomic aberrations were more common in subset #2 and non-subset #2 than in subset #4. The particularly high frequency of del(11q) in subset #2 may be linked to the adverse outcome reported for patients in this subset. Conversely, the lower prevalence of copy-number aberrations and the absence of poor-prognostic aberrations in subset #4 may reflect an inherently low-proliferative disease, which would prevent accumulation of genomic alterations.
|
|
| 7. |
- Rosenquist, Richard, et al.
(författare)
-
Genome-Wide DNA Methylation Profiling of Chronic Lymphocytic Leukemia Subsets Carrying Stereotyped B Cell Receptors
- 2017
-
Ingår i: Blood. - 0006-4971. ; 130:Suppl 1, s. 57-57
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)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.
|
|
