Citations

Abstract Abstract 2883 CLL-like monoclonal B-cell lymphocytosis (MBL) shares common immunophenotypic features and cytogenetic abnormalities with CLL and is generally perceived as its premalignant state. The World Health Organization has set a consensus cut-off of 5×109/L circulating B cells to discriminate between what constitutes ‘disease’ and what not. However, the clonal size within MBL is extremely variable. High-count (HC), clinical MBL is associated with absolute lymphocytosis and progresses to CLL requiring treatment at a rate of 1–2% per year, whereas low-count (LC) MBL is found in the general population through high-sensitivity techniques and carries a risk of progression that is limited if any. Given the high frequency of CLL-like MBL in the general population, it is important to understand the underlying mechanisms and also identify biological markers endowing malignant potential that may distinguish between the different forms. To this end, we performed a detailed immunogenetic profiling of 334 CLL-like MBL cases (78 LC and 256 HC) for a total of 355 productive VDJ rearrangements (including double rearrangements), 91 from LC MBL and 264 from HC MBL. We also compared the immunoglobulin (IG) gene repertoires of MBL to 544 CLL Rai Stage 0 (CLL-0) that were part of an IG sequence dataset of 7424 CLL cases previously analyzed by our group. LC and HC MBL had distinct IG gene repertoires, with over-representation of the IGHV1–69 and IGHV4–34 genes in HC and the IGHV4–59/61 genes in LC MBL, respectively (p<0.001). The HC MBL repertoire exhibited clear similarities to CLL-0 in terms of IGHV gene usage (similar frequencies of IGHV1–69 and IGHV4–34). Regarding somatic hypermutation, no differences were identified between LC MBL versus HC MBL versus CLL-0, in that the frequency of mutated rearrangements (<98% identity to the germline) was overall similar (LC MBL: 72.5%, HC MBL: 76.1%, CLL-0: 75%). In this respect, all the aforementioned subgroups differed significantly (p<0.001) from the frequency previously reported by us in CLL where only 55% of rearrangements carried mutated IGHV genes. We finally analyzed the expression of stereotyped B cell receptor (BcR) IGs, identified through a cluster analysis of the MBL sequences together with all CLL sequences from our cohort and 5494 non-CLL IG sequences retrieved from public databases. Overall, only 6/91 (5.5%) LC MBL rearrangements could be clustered with other sequences in subsets with stereotyped BcRs. Two of these six LC MBL cases were clustered together with IG sequences from various entities, including CLL, other lymphomas and autoimmune diseases; thus, they were considered to carry ‘public’ BcR stereotypes. In contrast, HC MBL showed a significantly (p=0.0002) higher frequency of ‘CLL-specific’ BcR stereotypes versus LC MBL, with 60/264 (22.7%) HC MBL cases carrying stereotyped VH CDR3s. This frequency was comparable to the one observed in CLL-0 (20.2%). Notably, a gradation was observed in the frequency of BcR IG stereotypy depending on the absolute count of CLL-like cells, starting with 5.5% in LC MBL, raising to 22.7–20.2% in in HC MBL/CLL-0 and, finally, peaking at 30.4% in the entire CLL cohort as previously reported. Altogether, these findings suggest that rather than a true premalignant condition, LC MBL may merely reflect immune senescence or result from persistent antigen stimulation. On the other hand, HC MBL appears to be a continuum with Rai stage 0 in the evolution to clinically overt CLL, being maybe one step behind where it requires either additional genetic hits or simply extra time to cross the numerical border that discriminates it from CLL. Hence, the identification of molecular genetic markers that may predict progression of HC MBL/CLL-0 into full-fledged CLL is strongly warranted. Disclosures: Shanafelt: Genentech: Research Funding; GlaxoSmith Klein: Research Funding; Teva/Cephalon: Research Funding; Celgene: 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.

Abstract 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<0.001); gender distribution (male/female ratios ranging from 0.85-4.4, p<0.001); the frequency of advanced stage disease (Binet C) at diagnosis (ranging from 9-21%, p<0.001); CD38 positivity (median percentage of positive cells ranging from 2-73%, p<0.05). Moving to cytogenetic findings, we detected subset-biased spectra of FISH-detected aberrations which can be summarized as follows: (i) isolated del(13q) varied from 10% in subset #8 (U-CLL), to 29% in subsets #59 (U-CLL) and #16 (M-CLL), and >75% in M-CLL subsets #77 and #148 (p<0.001); (ii) trisomy 12 was absent in subsets #31 (U-CLL) and #77 (M-CLL), in 20% of subset #201 (M-CLL) and, 60% in subset #8 (U-CLL) (p<0.001); (iii) del(11q) ranged from 69% in subset #31 (U-CLL) to 12% in subset #8 (U-CLL) and 0% in M-CLL subsets #16 and #201 (p<0.001); (iv) del(17p): absent from all M-CLL subsets except #148 (7.5%); absent from U-CLL subsets #5 and #59, and present in 19% and 17% of stereotyped subset #8 and #6 cases, respectively (p<0.05). We considered subset #2 separately since it included both M-CLL and U-CLL and identified a distinctive clinicobiological profile characterized by a constellation of features, including high incidence of Binet stage C disease (21%), CD38 positivity (41%) and certain cytogenetic abnormalities i.e. del(13q) (56%) and del(11q) (23%) and, in contrast, low frequency of del(17p) (4.5%). Notably, no differences were found between U-CLL versus M-CLL subset #2 cases regarding the incidence of these parameters. Survival analysis for time-to-first-treatment (TTFT) revealed that each stereotyped subset exhibited a distinct clinical course, different from that of other subsets even with similar IGHV gene mutational status and/or expressing the same IGHV gene. Interestingly, subsets #1 and #2 demonstrated a similar TTFT to that of del(17p) positive cases, while within subset #2 the clinical outcome was independent of IGHV mutational status. By integrating BcR IG stereotypy into the Döhner cytogenetic prognostication model, we found that subsets #1, #2 and #4, collectively accounting for ~7% of our series, and representing both U-CLL and M-CLL, constituted distinct clinical entities, with the latter exhibiting a particularly indolent disease even when compared to isolated del(13q) cases or cases with no cytogenetic aberrations. Finally, in multivariate analysis for TTFT, assignment to subset #2 emerged as a new independent unfavorable factor (p=0.002); furthermore, when restricting the analysis to Binet A cases, subset #2 exhibited the second highest hazard ratio after U-CLL. In conclusion, the molecular classification of CLL based on BcR IG stereotypy refines prognostication beyond IG mutational status and improves the Döhner hierarchical model. Hence, we suggest that a compartmentalized approach focusing on and comparing different subsets sheds light on CLL clinical behavior and biology and that BcR IG stereotypy represents a companion molecular diagnostic for personalized medicine in CLL. Disclosures Montillo: Janssen: Honoraria.

Abstract BACKGROUND. The detection of minimal residual disease (MRD) at the level of 0.01%/10-4 or above is a strong independent predictor of reduced progression-free (PFS) and overall survival (OS) in patients with CLL treated with chemoimmunotherapy. Although newer agents such as B-cell receptor pathway inhibitors can result in prolonged survival without achieving complete response, there remains a important role for MRD analysis in assessing therapeutic strategies aimed at disease eradication and cure. This is particularly important in front-line trials for fit patients which now require at least five years of follow-up if PFS is used as an endpoint. The feasibility of using MRD as a surrogate or intermediate endpoint for accelerated approval of new treatments is under review by regulatory agencies but further prospective validation is required. At the same time technology is rapidly evolving and high-throughput sequencing (HTS) technologies now detect MRD at the 0.0001%/10-6 level. It is therefore important to determine the most effective approaches for quantifying MRD that are compatible with previous studies but sufficiently sensitive for current treatments. AIMS. This collaborative project had two objectives. First, to identify the simplest and most flexible flow cytometry panel capable of detecting MRD at the 0.01%/10-4 or lower, that is compatible with published data and independent of instrument/reagent manufacturer. Second, to compare the flow cytometry approach with HTS analysis using the ClonoSEQ assay (Adaptive Biotechnologies, Seattle, WA). METHODS AND RESULTS. A core panel of antibodies for MRD detection was identified by testing an 8-marker combination in 52 samples (27 post-treatment and 25 dilution study) and re-analysing data with serial exclusion of single markers to determine redundancy. A 1-tube core panel of CD19, CD20, CD5, CD43, CD79b, and CD81 was identified and validated against the previously published 2-tube 6-marker and 4-tube 4-marker ERIC panels in 76 samples (19 post-treatment and 57 dilution study). The results showed good concordance (for log-transformed data above the LoQ, linearity=0.977, Pearson correlation co-efficient=0.983, average difference=0.026 log, 95% limit of agreement 0.20log) and a limit of detection of 0.001%/10-5 for the 1-tube core panel. Inter-operator variation was similar to CML MRD monitoring with both experienced operators, or inexperienced cytometrists after ~1 hour of specific education, achieving a 95% limit of agreement less than 0.3log in samples with MRD levels ranging from 0.0001 – 100%. The flow cytometry approach was compared with the ClonoSEQ HTS assay in 109 samples (21 dilution study and 88 post-treatment samples, complete data currently available on 13/88). The assay was applicable to the vast majority CLL patients, often with two clonal markers. There was 94% concordance at the 0.01% (10-4) threshold (15 samples with ≥0.01% CLL by both methods, 14 samples with <0.01% by both methods, 1 sample with 0.03% CLL by HTS and <0.003% CLL by flow cytometry, and 1 sample with 0.005% CLL by HTS and 0.012% by flow cytometry. HTS detected CLL IGH sequences in 22% (7/31) samples with no detectable CLL cells by flow cytometry (i.e. CLL level 0.0001-0.001%, 3/13 patient samples and 4/18 dilution samples). HTS demonstrated a relatively high variability in quantification, as seen in previous studies, but with a clear superiority in the limit of detection and good linearity (linearity=0.905, Pearson correlation co-efficient=0.870, average difference=0.078 log, 95% limit of agreement 1.5 log). CONCLUSIONS. The 1-tube 6-marker flow cytometry core panel is compatible with published studies, manufacturer-independent and flexible, providing directly quantitative results to 0.001%/10-5 without requiring a pre-treatment sample. HTS requires further work to standardise the quantitative analysis and prospective validation but the ClonoSEQ assay is applicable to >95% of CLL patients, does not require viable cells and is extremely sensitive, detecting residual disease in a significant proportion of cases with <0.01% CLL. The results indicate that flow cytometry and HTS are complementary technologies with a combined approach offering the most reliable way of quantifying CLL at the 0.01%/10-4 threshold while allowing higher sensitivity in clinical trials aimed at disease eradication. Disclosures Rawstron: Roche: Honoraria; Biogen Idec: Consultancy; Gilead: Consultancy, Honoraria; Abbvie: Honoraria; BD Biosciences: Intrasure reagent Patents & Royalties; Celgene: Honoraria; GSK: Honoraria. Williamson:Adaptive Biotechnologies: Employment, Equity Ownership. Sanders:Adaptive Biotechnologies: Employment, Equity Ownership. Robins:Adaptive Biotechnologies: Consultancy, Equity Ownership, Patents & Royalties. Hallek:Celgene: Honoraria, Research Funding; Mundipharma: Honoraria, Research Funding; Roche: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; GSK: Honoraria; Gilead: Honoraria. Hillmen:Roche: Honoraria, Research Funding; GSK: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; Gilead: Honoraria, Research Funding.

Abstract 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.

SummaryIbrutinib, a Bruton tyrosine kinase inhibitor, is approved for treatment of various B‐cell malignancies. In ibrutinib clinical studies, low‐grade haemorrhage was common, whereas major haemorrhage (MH) was infrequent. We analysed the incidence of and risk factors for MH from 15 ibrutinib clinical studies (N = 1768), including 4 randomised controlled trials (RCTs). Rates of any‐grade bleeding were similar for single‐agent ibrutinib and ibrutinib combinations (39% and 40%). Low‐grade bleeding was more common in ibrutinib‐treated than comparator‐treated patients (35% and 15%), and early low‐grade bleeding was not associated with MH. The proportion of MH in RCTs was higher with ibrutinib than comparators (4.4% vs. 2.8%), but after adjusting for longer exposure with ibrutinib (median 13 months vs. 6 months), the incidence of MH was similar (3.2 vs. 3.1 per 1000 person‐months). MH led to treatment discontinuation in 1% of all ibrutinib‐treated patients. Use of anticoagulants and/or antiplatelets (AC/AP) during the study was common (~50% of patients) and had an increased exposure‐adjusted relative risk for MH in both the total ibrutinib‐treated population (1.9; 95% confidence interval, 1.2–3.0) and RCT comparator‐treated patients (2.4; 95% confidence interval, 1.0–5.6), indicating that ibrutinib may not alter the effect of AC/AP on the risk of MH in B‐cell malignancies.

Abstract Purpose: We sought to investigate whether B cell receptor immunoglobulin (BcR IG) stereotypy is associated with particular clinicobiological features among chronic lymphocytic leukemia (CLL) patients expressing mutated BcR IG (M-CLL) encoded by the IGHV4-34 gene, and also ascertain whether these associations could refine prognostication. Experimental Design: In a series of 19,907 CLL cases with available immunogenetic information, we identified 339 IGHV4-34–expressing cases assigned to one of the four largest stereotyped M-CLL subsets, namely subsets #4, #16, #29 and #201, and investigated in detail their clinicobiological characteristics and disease outcomes. Results: We identified shared and subset-specific patterns of somatic hypermutation (SHM) among patients assigned to these subsets. The greatest similarity was observed between subsets #4 and #16, both including IgG-switched cases (IgG-CLL). In contrast, the least similarity was detected between subsets #16 and #201, the latter concerning IgM/D-expressing CLL. Significant differences between subsets also involved disease stage at diagnosis and the presence of specific genomic aberrations. IgG subsets #4 and #16 emerged as particularly indolent with a significantly (P &lt; 0.05) longer time-to-first-treatment (TTFT; median TTFT: not yet reached) compared with the IgM/D subsets #29 and #201 (median TTFT: 11 and 12 years, respectively). Conclusions: Our findings support the notion that BcR IG stereotypy further refines prognostication in CLL, superseding the immunogenetic distinction based solely on SHM load. In addition, the observed distinct genetic aberration landscapes and clinical heterogeneity suggest that not all M-CLL cases are equal, prompting further research into the underlying biological background with the ultimate aim of tailored patient management. Clin Cancer Res; 23(17); 5292–301. ©2017 AACR.

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.

Key Points Low-count and high-count monoclonal B-cell lymphocytosis (MBL) have distinct immunogenetic signatures, with only the latter resembling CLL. Rather than a true premalignant condition, low-count MBL may merely reflect immune senescence or result from persistent antigen stimulation.

AbstractImmune-related deficiencies are well-known complications of chronic lymphocytic leukemia (CLL). Although recent data indicate that almost all CLL patients are preceded by a monoclonal B-cell lymphocytosis precursor state, patterns of immune defects preceding CLL diagnosis are unclear. We identified 109 persons who developed CLL from the prospective and nationwide Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial with 77 469 participants, with serially collected prediagnostic serum samples. We assayed monoclonal (M)–proteins, κ/λ free light chains (FLCs) in prediagnostic obtained up to 9.8 years before CLL diagnosis. The prevalence of an abnormal FLC ratio, M-protein, and hypogamma-globulinemia before CLL diagnosis was 38% (95% confidence interval, 29%-47%), 13% (7%-21%), and 3% (1%-8%), respectively. M-proteins and abnormal FLC ratios were detected up to 9.8 years before CLL diagnosis in a total of 48 persons (44%). Hypogammaglobulinemia was not present until 3 years before the diagnosis of CLL. Among 37 patients with information on tumor cell immunophenotype, an association between immunophenotype and involved FLC (P = .024, Fisher exact test) was observed. Among 61 persons with a normal FLC ratio and without an M-protein, 17 had elevated κ and/or λ FLC levels, indicating polyclonal B-cell activation in 17 of 109 (16%) patients. These findings support a role for chronic immune stimulation in CLL genesis.