ALBERT

Description: Chronic lymphocytic leukemia (CLL) is characterized by the existence of subsets of patients with (quasi)identical, stereotyped B cell receptor immunoglobulins (BcR IG). Patients in certain major stereotyped subsets often display remarkably consistent clinicobiological profiles, suggesting that the study of BcR IG 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 IG stereotypy and major subsets, as well as the existence of higher-order connections between individual subsets. In order 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.

Description: 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

Description: The human IGHV4-34 gene encodes antibodies which are intrinsically autoreactive when the VH domain is unmutated. Therefore, B cells expressing IGHV4-34 B-cell receptor immunoglobulins (BcR IG) are normally under close scrutiny in order to avoid unwanted autoreactivity, especially against DNA. The IGHV4-34 gene is frequently utilized in chronic lymphocytic leukemia (CLL), where, typically, it shows a high load of somatic hypermutation (SHM). We have previously reported distinctive SHM patterns amongst IGHV4-34 CLL, especially for subsets with stereotyped BcR IG. However, although a large number of cases (~2000) was previously studied, since even the largest subsets account for only ~3% of CLL, meaningful conclusions could not be reached for smaller subsets. Here we revisit this issue in a series of 16,528 CLL cases and focus on IGHV4-34 expressing subsets: #4 (IGHV4-34/IGHD5-18/IGHJ6 | 156 cases, 0.9%); #11 (IGHV4-34/IGHD3-10/IGHJ4 | 16 cases, 0.1%); #16 (IGHV4-34/IGHD2-15/IGHJ6 | 41 cases, 0.25%); #29 (IGHV4-34/IGHD: unassignable/IGHJ3 | 39 cases, 0.24%); and #201 (IGHV4-34/IGHD: unassignable/IGHJ3 | 43 cases 0.26%). Focusing on codons 27-104 within the VH domain (from CDR1-IMGT to FR3-IMGT), we calculated the sequence distance between subsets and the corresponding IGHV4-34 germline sequence based on a pairwise qualitative and quantitative comparison of the respective amino acid composition. The minimum distance calculated, and hence the greatest identity, was observed between subsets #4 and #16, both concerning IgG-switched cases (IgG-CLL), which is notable given the overall rarity of IgG-CLL. In contrast, the maximum distance, implying the least identity, was between subsets #16 and #201, the latter concerning IgM/D-CLL. Extreme variations between subsets were noted in codons spanning the entire VH domain. This result is consistent with our finding of a subset-biased distribution of mutations over the VH domain. More specifically, while subsets #11, #16, #29 and #201 had a lower frequency of mutations within VH CDR1 compared to VH CDR2, the exact opposite was seen in subset #4, with 40% of mutations in VH CDR1 versus 27% in VH CDR2. In addition, subsets #4, #11, #16 and #29 had a similar distribution of mutations in VH FR2 and VH FR3, in contrast to subset #201 that showed a preference for VH FR3 over VH FR2. Consequently, we noted that certain positions were targeted in a subset-specific manner e.g. codon 28 in VH CDR1 was heavily targeted in subsets #4 (68.6%) and #16 (87.8%), with most cases carrying an acidic amino acid (AA) introduced by SHM, glycine to glutamic acid, G〉E: 51.3% for subset #4 and 78% for subset #16. The high prevalence of acidic AA introduced by SHM in these subsets is notable considering the electropositive nature of their VH CDR3 (especially of subset #4), strongly recalling edited anti-DNA antibodies. Interestingly, the G〉E change was identified at a much lower frequency in other IGHV4-34 subsets: 18.75% for subset #11; 2.6% for subset #29; 7% for subset #201, all of which carried electronegative VH CDR3. Further, we noted that certain positions were heavily targeted in all subsets e.g. 56-86% targeting for SHM at codon 92 in VH FR3 where serine is encoded by the agc triplet, the ”hottest of hotspots”. This result could be viewed as sequence- rather than subset-dependent and linked to the molecular features of this codon, which is supported by the low targeting of codon 93 (0-6%), also encoding serine by the tct triplet. Other positions were targeted in all subsets but at vastly different frequencies e.g. codon 64 was targeted in 37.8% in subset #4 rising to 100% in subset #29. Finally, positions heavily targeted by SHM in certain subsets were unmutated in other subsets e.g. codon 36 in VH CDR1 remained unmutated in subset #16, in contrast 76.9% of subset #29 were mutated at this position resulting in an AA change. In conclusion, we document different spectra of SHM and AA changes between stereotyped IGHV4-34 CLL subsets. The finding of subset-biased, recurrent AA changes at certain codons indicates that the respective progenitor cells may have responded in a specific manner to the selecting antigen(s), despite expressing the same IGHV gene, indicating a functional purpose for these modifications. This is exemplified by the molecular characteristics of the recurrent AA changes in subset #4, thereby offering interesting pathogenetic hints. Disclosures No relevant conflicts of interest to declare.

Description: In chronic lymphocytic leukemia (CLL), the molecular features of the clonotypic B-cell receptor immunoglobulins (BcR IG) are set from the birth of the clone and in contrast to genetic aberrations, remain stable overtime, rendering the BcR IG a reference biomarker that is usually not significantly affected by clonal evolution. Approximately 30% of CLL cases carry quasi-identical BcR IGs and can be assigned to distinct stereotyped subsets. While preliminary evidence alludes to BcR IG stereotypy being relevant from a clinical viewpoint, this aspect has never been explored systematically or in a cohort of adequate size to enable meaningful conclusions. In order to assess the clinical implications of BcR IG stereotypy, we evaluated clinicobiological data from 8593 CLL patients, particularly focusing on 14 major stereotyped subsets of cases with unmutated (U-CLL) or mutated IGHV genes (M-CLL). The largest subset was #2 (n=254, 3%), within which 156 and 98 cases were M-CLL and U-CLL, respectively, followed by U-CLL subsets #1 (n=173, 2%) and #7 (n=123, 1.4%). Amongst M-CLL, the largest subsets were #4 (n=94, 1.1%) and #148 (n=92, 1%). Stereotyped subsets, even of the same mutational category i.e. U-CLL or M-CLL, exhibited significant clinicobiological differences regarding: age at diagnosis (median age ranging from 53-68 years, p

Description: B cells residing the marginal zone (MZ) provide a first line of defense against blood borne pathogens, producing the greater part of circulating natural antibodies conferring protection against infection. Dysregulated homeostasis and function of MZ B cells has been implicated in a wide range of B lymphoproliferations, encompassing the distinct MZ lymphomas recognized by the WHO Classification, the related provisional entities and even chronic lymphocytic leukemia (CLL), for which a MZ derivation has been proposed. Here, taking advantage of a large multi-institutional series, we aimed at obtaining insight into the ontogenetic relationship of MZ lymphoproliferations, related entities and CLL through cross-comparison of their B cell receptor immunoglobulin (BcR IG) gene repertoires. Our sequence dataset included 3660 unique IGHV-IGHD-IGHJ gene rearrangement sequences from our collaborative centers and/or public databases derived from: (1) MZ lymphomas: splenic (SMZL), n=379; nodal (NMZL), n=37; extranodal (ENMZL), n=95; (2) provisional entities of postulated MZ origin, including splenic diffuse red pulp lymphoma (SDRL, n=16) and clonal B cell lymphocytosis of MZ origin (CBL-MZ, n=60); (3) persistent polyclonal B cell lymphocytosis (PPBL), n=286 (from 2 cases); (4) MZ cells isolated from six spleen specimens free of neoplastic cells at histological inspection (non-malignant MZ), obtained at surgery for cancer, n=489; (5) autoimmune conditions, n=1243; (6) various types of normal B cells, n=1055. The most pronounced IG gene repertoire skewing was observed in SMZL with the IGHV1-2*04 gene accounting for 26% of cases. Restrictions, though less striking, were also identified in the other MZ lymphomas as well: (i) the IGHV4-34 gene predominated in NMZL (14.3%); and, (ii) the IGHV1-69 gene predominated in ENMZL (14.6%), albeit with significantly different distribution depending on the primary site of involvement, ranging from 38% in salivary ENMZL to 11% in gastric ENMZL to 4% in ocular adnexa ENMZL (p

Description: Key Points CLL stereotyped subset #2 (IGHV3-21/IGLV3-21) is uniformly aggressive independently of somatic hypermutation status. The prognosis for non–subset #2/IGHV3-21 CLL resembles that of the remaining CLL cases with similar somatic hypermutation status.

Description: 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.