Campo, Elı́as

Abstract Most human cancers converge to a deregulated methylome with reduced global levels and elevated methylation at select CpG islands. To investigate the emergence and dynamics of the cancer methylome, we characterized genome-wide DNA methylation in preneoplastic monoclonal B-cell lymphocytosis (MBL) and chronic lymphocytic leukemia (CLL), including serial samples collected across disease course. We detected the aberrant tumor-associated methylation landscape at CLL diagnosis and found no significant differentially methylated regions in the high-count MBL-to-CLL transition. Patient methylomes showed remarkable stability with natural disease and posttherapy progression. Single CLL cells were consistently aberrantly methylated, indicating a homogeneous transition to the altered epigenetic state and a distinct expression profile together with MBL cells compared with normal B cells. Our longitudinal analysis reveals the cancer methylome to emerge early, which may provide a platform for subsequent genetically driven growth dynamics, and, together with its persistent presence, suggests a central role in disease onset. Significance: DNA methylation data from a large cohort of patients with MBL and CLL show that epigenetic transformation emerges early and persists throughout disease stages with limited subsequent changes. Our results indicate an early role for this aberrant landscape in the normal-to-preneoplastic transition that may reflect a pan-cancer mechanism. See related commentary by Rossi, p. 6. This article is highlighted in the In This Issue feature, p. 1

Abstract Purpose: Mantle cell lymphoma (MCL) is characterized by the t(11;14)(q13;q32) translocation leading to cyclin D1 overexpression. Cyclin D1 is a major cell-cycle regulator and also regulates transcription, but the impact of cyclin D1–mediated transcriptional dysregulation on MCL pathogenesis remains poorly understood. The aim of this study was to define a cyclin D1–dependent gene expression program and analyze its prognostic value. Experimental Design: We integrated genome-wide expression analysis of cyclin D1–silenced and overexpressing cells with cyclin D1 chromatin-binding profiles to identify a cyclin D1–dependent transcriptional program in MCL cells. We analyzed this gene program in two MCL series of peripheral blood samples (n = 53) and lymphoid tissues (n = 106) to determine its biological and clinical relevance. We then obtained a simplified signature of this program and evaluated a third series of peripheral blood MCL samples (n = 81) by NanoString gene expression profiling to validate our findings. Results: We identified a cyclin D1–dependent transcriptional program composed of 295 genes that were mainly involved in cell-cycle control. The cyclin D1–dependent gene program was overexpressed in MCL tumors directly proportional to cyclin D1 levels. High expression of this program conferred an adverse prognosis with significant shorter overall survival of the patients. These observations were validated in an independent cohort of patients using a simplified 37-gene cyclin D1 signature. The cyclin D1–dependent transcriptional program was also present in multiple myeloma and breast tumors with cyclin D1 overexpression. Conclusions: We identified a cyclin D1–dependent transcriptional program that is overexpressed in MCL and predicts clinical outcome.

Abstract Chronic lymphocytic leukemia (CLL) is characterized by the existence of subsets of patients with (quasi)identical, stereotyped B-cell receptor (BcR) immunoglobulins. Patients in certain major stereotyped subsets often display remarkably consistent clinicobiological profiles, suggesting that the study of BcR immunoglobulin stereotypy in CLL has important implications for understanding disease pathophysiology and refining clinical decision-making. Nevertheless, several issues remain open, especially pertaining to the actual frequency of BcR immunoglobulin stereotypy and major subsets, as well as the existence of higher-order connections between individual subsets. To address these issues, we investigated clonotypic IGHV-IGHD-IGHJ gene rearrangements in a series of 29 856 patients with CLL, by far the largest series worldwide. We report that the stereotyped fraction of CLL peaks at 41% of the entire cohort and that all 19 previously identified major subsets retained their relative size and ranking, while 10 new ones emerged; overall, major stereotyped subsets had a cumulative frequency of 13.5%. Higher-level relationships were evident between subsets, particularly for major stereotyped subsets with unmutated IGHV genes (U-CLL), for which close relations with other subsets, termed “satellites,” were identified. Satellite subsets accounted for 3% of the entire cohort. These results confirm our previous notion that major subsets can be robustly identified and are consistent in relative size, hence representing distinct disease variants amenable to compartmentalized research with the potential of overcoming the pronounced heterogeneity of CLL. Furthermore, the existence of satellite subsets reveals a novel aspect of repertoire restriction with implications for refined molecular classification of CLL.

Abstract Pediatric large B-cell lymphomas (LBCLs) share morphological and phenotypic features with adult types but have better prognosis. The higher frequency of some subtypes such as LBCL with IRF4 rearrangement (LBCL-IRF4) in children suggests that some age-related biological differences may exist. To characterize the genetic and molecular heterogeneity of these tumors, we studied 31 diffuse LBCLs (DLBCLs), not otherwise specified (NOS); 20 LBCL-IRF4 cases; and 12 cases of high-grade B-cell lymphoma (HGBCL), NOS in patients ≤25 years using an integrated approach, including targeted gene sequencing, copy-number arrays, and gene expression profiling. Each subgroup displayed different molecular profiles. LBCL-IRF4 had frequent mutations in IRF4 and NF-κB pathway genes (CARD11, CD79B, and MYD88), losses of 17p13 and gains of chromosome 7, 11q12.3-q25, whereas DLBCL, NOS was predominantly of germinal center B-cell (GCB) subtype and carried gene mutations similar to the adult counterpart (eg, SOCS1 and KMT2D), gains of 2p16/REL, and losses of 19p13/CD70. A subset of HGBCL, NOS displayed recurrent alterations of Burkitt lymphoma–related genes such as MYC, ID3, and DDX3X and homozygous deletions of 9p21/CDKN2A, whereas other cases were genetically closer to GCB DLBCL. Factors related to unfavorable outcome were age >18 years; activated B-cell (ABC) DLBCL profile, HGBCL, NOS, high genetic complexity, 1q21-q44 gains, 2p16/REL gains/amplifications, 19p13/CD70 homozygous deletions, and TP53 and MYC mutations. In conclusion, these findings further unravel the molecular heterogeneity of pediatric and young adult LBCL, improve the classification of this group of tumors, and provide new parameters for risk stratification.

Abstract The IGHV4-34 gene is very frequent (~10%) in the B cell receptor immunoglobulin (BcR IG) gene repertoire of chronic lymphocytic leukemia (CLL). Over 30% of IGHV4-34 CLL cases can be assigned to different subsets with stereotyped BcR IG. The largest is subset #4 which represents ~1% of all CLL and ~10% of IGHV4-34 CLL and is considered a prototype for indolent disease. The BcR IG of a great majority (~85%) of IGHV4-34 CLL cases carry a significant load of somatic hypermutation (SHM), often with distinctive SHM patterns. This holds especially true for stereotyped subsets and is suggestive of particular modes of interactions with the selecting antigen(s). In detail, subsets #4 and #16, both involving IgG-switched cases (IgG-CLL), exhibit the greatest sequence similarity in SHM profiles, whereas they differ in this respect from IgM/D subsets #29 and #201. Prompted by these observations, here we explored the extent that these subset-biased SHM profiles in different IGHV4-34 stereotyped subsets were reflected in distinct demographics, clinical presentation, genomic aberrations and outcomes. Within a multi-institutional series of 20,331 CLL patients, 1790 (8.8%) expressed IGHV4-34 BcR IG. Following established bioinformatics approaches for the identification of BcR IG stereotypy, 573/1790 IGHV4-34 CLL cases (32%) were assigned to stereotyped subsets; of these, 340 cases (19% of all IGHV4-34 CLL and 60% of stereotyped IGHV4-34 cases) belonged to subsets #4, #16, #29 and #201, all concerning IGHV-mutated CLL (M-CLL). Clinicobiological information was available for 275/340 patients: #4, n=150; #16, n=44; #29, n=39; and #201, n=42. Comparisons between subsets revealed no differences in gender and age distribution. Interestingly, however, 36-43% of each subset cases were young for CLL (defined as patients aged ≤55 years), which is higher compared to general CLL cohorts, where young patients generally account for ~25% of cases. In contrast, significant differences were identified between subsets regarding: (i) disease stage at diagnosis, with >90% of IgG subsets #4 and #16 diagnosed at Binet stage A versus 83% in subset #201 and 74% in subset #29 (p=0.029); (ii) CD38 expression, ranging from 1% in subset #4 to 10% in subset #201 (p=0.013); (iii) the distribution of del(13q), peaking at a remarkable 92% in subset #29 versus only 37% in subset #16 (p<0.0001). Regarding other genomic aberrations, they were either absent (NOTCH1 mutations) or rare (SF3B1 mutations, trisomy 12, del(11q), TP53 aberrations due to either del(17p) and/or TP53 mutations). The sole exception concerned a high frequency (14%) of TP53 aberrations in subset #29 (p<0.05 compared with the other subsets), which is notable for M-CLL cases in general. Time to first treatment (TTFT) could be analyzed in 228 cases. IgG subsets #4 and #16 had significantly (p=0.036) longer TTFT (median TTFT: not yet reached) compared to the IgM/D subsets #29 and #201 (median TTFT: 11 and 12 years, respectively). In conclusion, we have identified distinct clinicobiological profiles for different stereotyped IGHV4-34 M-CLL subsets, highlighting subsets #4 and #16 as particularly indolent, which is important for both medical and social reasons, especially considering that a significant proportion of patients in these subsets are diagnosed at younger ages. Our findings support the notion that BcR IG stereotypy refines prognostication in CLL, superseding the crude immunogenetic distinction based on SHM load only. Additionally, the observed heterogeneity suggests that not all M-CLL are equal, prompting further research into the underlying biological background with the ultimate aim of tailored patient management. Disclosures Tausch: Gilead: Other: Travel support. Shanafelt:Glaxo-Smith_Kline: Research Funding; Genentech: Research Funding; Celgene: Research Funding; Polyphenon E Int'l: Research Funding; Hospira: Research Funding; Janssen: Research Funding; Pharmactckucs: Research Funding; Cephalon: Research Funding. Niemann:Gilead: Consultancy; Janssen: Consultancy; Roche: Consultancy; Novartis: Other: Travel grant. Langerak:InVivoScribe: Patents & Royalties: Licensing of IP and Patent on BIOMED-2-based methods for PCR-based Clonality Diagnostics.; DAKO: Patents & Royalties: Licensing of IP and Patent on Split-Signal FISH. Royalties for Dept. of Immunology, Erasmus MC, Rotterdam, NL; Roche: Other: Lab services in the field of MRD diagnostics provided by Dept of Immunology, Erasmus MC (Rotterdam). Hallek:Celgene: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; AbbVie: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Roche: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Boehringher Ingelheim: Honoraria, Other: Speakers Bureau and/or Advisory Boards; Pharmacyclics: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Mundipharma: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Janssen: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding; Gilead: Honoraria, Other: Speakers Bureau and/or Advisory Boards, Research Funding. Ghia:Janssen Pharmaceuticals: Research Funding.

Abstract The existence of stereotyped B cell receptor immunoglobulins (BcR IG) in chronic lymphocytic leukemia (CLL) strongly implicated antigen selection in disease ontogeny. We have previously shown that the stereotyped fraction encompasses ~30% of all CLL and includes multiple subsets with distinct BcR IG configuration and variable size. Eventually, certain major subsets emerged as distinct clinical entities, exemplified by subset #2 (IGHV3-21/IGLV3-21, ~2.5-3% of all CLL, mixed somatic hypermutation (SHM) status) of a particularly aggressive clinical course, thus, sharply contrasting subset #4 (IGHV4-34/IGKV2-30, ~1% of all CLL, mutated IGHV genes, M-CLL), a prototype for indolent disease. Here, taking advantage of a multi-institutional cohort of 21,123 CLL IG rearrangements, almost three times the size of the largest previous study, and the availability of validated, purpose-built immunoinformatics methods, we reappraised BcR IG stereotypy especially focusing on major subsets and the degree of their sequence similarity to related minor subsets. Stereotypy discovery was performed with ARResT/Teiresias, while stereotypy assignment to existing subsets previously deemed as major was performed with ARResT/AssignSubsets (http://bat.infspire.org/arrest/). In the present study, a subset was characterized as major if representing > 0.2% of the cohort (i.e. at least 50 cases). Minor subsets closely related to major ones (termed satellite) were identified applying the following criteria: (i) usage of IGHV genes from the same phylogenetic clan; (ii) VH CDR3 length difference ranging from -2 to +2 compared to the respective major subset; (iii) shared VH CDR3 sequence motif; and, (iv) -2 to +2 difference in the offset of the VH CDR3 motif compared to the respective major subset. In total, 7378/21123 (34.9%) IG sequences were grouped into subsets with stereotyped VH CDR3, with the previously characterized 19 major subsets accounting collectively for 2594 sequences (12.3%) of the cohort: of these, 12 included cases with unmutated IGHV genes (U-CLL), 6 concerned M-CLL and 1 (subset #2) included cases with mixed SHM status. Four additional subsets exceeded 50 cases, and, thus, were also considered as 'major'. These results reinforce the notion that not all CLL will end up being stereotyped but rather that a plateau for stereotypy exists at ~1/3 of the cohort. Subset #2 was the largest subset (n=572, 2.7%), while subset #1 (IGHV clan I (IGHV1,5,7 subgroups)/IGKV1(D)-39) was the most frequent subset within U-CLL (n=515, 2.4%) and subset #4 the most common M-CLL subset (n=192, 0.9%), hence displaying remarkable consistency regarding their frequency in all cohorts published since the pioneering studies. Altogether, Teiresias and AssignSubsets gave concordant results for previously identified major subsets, illustrating the validity of our approach. Satellite subsets were sought for individually for each major subset. In general, few satellite subsets were identified, most of which concerned U-CLL major subsets. That notwithstanding, notable cases of satellite subsets were exemplified by major subset #1 and its satellite subset #99 from which it differed only in VH CDR3 length (13 aminoacids in subset #1 versus 14 in subset #99); interestingly, both subsets displayed equally aggressive clinical course. Another example concerned subset #8 (IGHV4-39/IGKV1(D)-39, U-CLL), an aggressive subset with very high risk for Richter's transformation, that, except for a one-aminoacid difference in VH CDR3 length, was otherwise identical to satellite subset #215, also displaying clinical aggressiveness. Overall, our results confirm that major subsets can be robustly identified and are consistent in relative size, hence representing distinct disease subgroups amenable to compartmentalized research with the potential of overcoming the pronounced heterogeneity of CLL. Most major subsets display unique sequence motifs, however satellite subsets exist, especially within U-CLL. Considering ever-increasing evidence that major stereotyped subsets may represent distinct disease subgroups, the existence of satellite subsets reveals a novel aspect of repertoire restriction and has implications for refined molecular classification of CLL. Disclosures Shanafelt: Genentech: Research Funding; GlaxoSmithkKine: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Pharmacyclics: Research Funding; Cephalon: Research Funding; Hospira: Research Funding. Gaidano:Roche: Consultancy, Honoraria, Speakers Bureau; Karyopharm: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau. Niemann:Janssen: Consultancy; Abbvie: Consultancy; Roche: Consultancy; Gilead: Consultancy. Langerak:F. Hofmann-LaRoche, Genentech: Research Funding; InVivoScribe Technologies: Patents & Royalties: Royalties are provided to European Network (EuroClonality). Jaeger:Roche: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Kater:Celgene: Research Funding; Gilead: Research Funding; Janssen: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Abbvie: Consultancy, Research Funding. Stilgenbauer:Amgen: Consultancy, Honoraria, Other: Travel grants, Research Funding; Gilead: Consultancy, Honoraria, Other: Travel grants , Research Funding; Genentech: Consultancy, Honoraria, Other: Travel grants , Research Funding; Celgene: Consultancy, Honoraria, Other: Travel grants , Research Funding; Boehringer Ingelheim: Consultancy, Honoraria, Other: Travel grants , Research Funding; Genzyme: Consultancy, Honoraria, Other: Travel grants , Research Funding; AbbVie: Consultancy, Honoraria, Other: Travel grants, Research Funding; GSK: Consultancy, Honoraria, Other: Travel grants , Research Funding; Janssen: Consultancy, Honoraria, Other: Travel grants , Research Funding; Mundipharma: Consultancy, Honoraria, Other: Travel grants , Research Funding; Novartis: Consultancy, Honoraria, Other: Travel grants , Research Funding; Pharmacyclics: Consultancy, Honoraria, Other: Travel grants , Research Funding; Hoffmann-La Roche: Consultancy, Honoraria, Other: Travel grants , Research Funding; Sanofi: Consultancy, Honoraria, Other: Travel grants , Research Funding. Hallek:Gilead: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; F. Hoffmann-LaRoche: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Mundipharma: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau. Rosenquist:Gilead Sciences: Speakers Bureau. Ghia:Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Roche: Honoraria, Research Funding; Adaptive: Consultancy; Abbvie: Consultancy, Honoraria. Stamatopoulos:Novartis: Honoraria, Research Funding; Abbvie: Honoraria, Other: Travel expenses; Janssen: Honoraria, Other: Travel expenses, Research Funding; Gilead: Consultancy, Honoraria, Research Funding.

One-third of peripheral T-cell lymphomas are “not otherwise specified” (PTCL-NOS), but they have been subdivided into 2 subgroups based on gene expression profiling. Amador and colleagues generated an immunohistochemical algorithm that parallels the molecular separation of PTCL-NOS and provides useful prognostic information.

Abstract Primary mediastinal large B-cell lymphoma (PMBCL) is recognized as a distinct entity in the World Health Organization classification. Currently, the diagnosis relies on consensus of histopathology, clinical variables, and presentation, giving rise to diagnostic inaccuracy in routine practice. Previous studies have demonstrated that PMBCL can be distinguished from subtypes of diffuse large B-cell lymphoma (DLBCL) based on gene expression signatures. However, requirement of fresh-frozen biopsy material has precluded the transfer of gene expression–based assays to the clinic. Here, we developed a robust and accurate molecular classification assay (Lymph3Cx) for the distinction of PMBCL from DLBCL subtypes based on gene expression measurements in formalin-fixed, paraffin-embedded tissue. A probabilistic model accounting for classification error, comprising 58 gene features, was trained on 68 cases of PMBCL and DLBCL. Performance of the model was subsequently evaluated in an independent validation cohort of 158 cases and showed high agreement of the Lymph3Cx molecular classification with the clinicopathological diagnosis of an expert panel (frank misclassification rate, 3.8%). Furthermore, we demonstrate reproducibility of the assay with 100% concordance of subtype assignments at 2 independent laboratories. Future studies will determine Lymph3Cx’s utility for routine diagnostic purposes and therapeutic decision making.