Jelinek, Diane F.

Abstract Multiple myeloma (MM) is a malignant disease of plasma cells that accumulate in the bone marrow. The survival mechanisms of myeloma cells are still not fully understood. There are several cytokines that are known to support the survival and growth of myeloma cells, such as IL-6, IGF-I, TNF-a, and IL-1β. Recent evidence has also shown that the TNF family member, B lymphocyte stimulator (BLyS), is critical for normal B cell development and homeostasis, as well as for survival of malignant B cells, including MM. However, it should be noted that the precise mechanisms by which BLyS promotes the survival of MM cells remain uncertain. Our group has already reported that MM cell lines and primary myeloma cells can express BLyS and its receptors. Thus, exogenous BLyS augmented the survival of MM cells, including the IL-6 dependent MM cell line, KAS-6/1. To better study the mechanism underlying BLyS-mediated survival of myeloma cells, we sought to establish a KAS-6/1 cell line variant which was solely dependent on exogenous BLyS for growth and survival. We have previously reported that KAS-6/1 cells do not appear to express autocrine IL-6, and therefore are highly dependent on exogenous IL-6 for survival. To establish a BLyS-dependent KAS-6/1 variant, cells were cultured long-term in RPMI containing 0.5% BSA or 1% FCS in the absence of exogenous IL-6, and in the presence or absence of exogenous BLyS. KAS-6/1 cells cultured in the absence of cytokines were non-viable after two weeks of culture, whereas KAS-6/1 cells cultured with BLyS alone remained viable and proliferated, albeit at a lower rate than parental KAS-6/1 cells maintained with IL-6. We next focused on identifying the mechanisms of BLyS-dependent survival of the KAS-6/1/BLyS (KAS-6/B) variant cell line. Of interest, KAS-6/B cells placed in short term culture exhibited cytokine independent survival and proliferation and this was completely inhibited using a neutralizing IL-6 antibody. These results therefore suggested that the mechanism underlying BLyS-mediated survival and proliferation of the KAS-6/B cells is induction of an autocrine IL-6 pathway. This notion is further supported by the ability of BLyS to induce IL-6 expression at the transcriptional level, and at the protein level as revealed by an IL-6 specific ELISA. Consistent with the concept that BLyS induced autocrine IL-6 expression in the KAS-6/B cells, we also observed that STAT-3 was constitutively activated in these cells. In addition, we tested the ability of BLyS-conditioned media obtained from KAS-6/B cells to stimulate the proliferation of a different IL-6 dependent MM cell line, JMW. Whereas BLyS alone failed to stimulate JMW cell proliferation, BLyS-conditioned media obtained from the KAS-6/B cells stimulated proliferation, and in a manner that was inhibited by a neutralizing IL-6 antibody. Finally, BLyS stimulation of primary patient MM cells similarly resulted in increased IL-6 expression. IL-6 is known to play a major role in the malignant progression of MM by regulating the growth and survival of tumor cells. IL-6 levels often increase during disease progression, and it has been demonstrated that IL-6 may derive from the tumor cells themselves or from other cell types in the bone marrow. Because of this, it is important to fully understand what signals are capable of inducing IL-6 expression in this disease. In summary, our results demonstrate for the first time the ability of BLyS to maintain myeloma cell survival via the induction of an autocrine IL-6 pathway. Our results underscore the importance of IL-6 in this disease, and further demonstrate the complexity of the deregulated cytokine network in this disease.

Abstract The protein tyrosine kinase ZAP-70, known to be critical for T cell development and T cell receptor signaling, has become a potential prognostic tool for B cell chronic lymphocytic leukemia (B-CLL). Recent studies have suggested that those patients with ZAP-70 positive leukemic cells have a poorer disease prognosis than do patients whose leukemic cells lack ZAP-70 expression. In addition, ZAP-70 expression occurs more frequently in CLL B cells that express unmutated immunoglobulin (Ig) VH region genes. However, several questions remain regarding ZAP-70 expression in B-CLL. First, is ZAP-70 expression in some patients with B-CLL the consequence of malignant transformation or do normal human B cells express ZAP-70 under certain conditions of stimulation? Secondly, does the expression of ZAP-70 reflect a more activated phenotype, thus resulting in the more aggressive phenotype of ZAP-70+ B-CLL? To begin to address these questions, we focused our studies on ZAP-70 expression in normal, human B cells. CD19+ B cells were isolated by magnetic bead separation from normal human peripheral blood (PB) or tonsil and spleen surgical waste tissue. We first used three-color flow cytometry to evaluate ZAP-70 expression in CD19+ versus CD3+ lymphocytes. While PB B cells were negative for ZAP-70 expression, we were able to detect a subset of CD19+/ZAP-70+ cells in both spleen and tonsil and this subset expressed ZAP-70 at levels comparable to those of CD3+ T cells. To verify the flow cytometry results, we evaluated total ZAP-70 expression by immunoblotting and observed readily detectable ZAP-70 in both splenic and tonsillar CD19+ cells. Based on the observation that ZAP-70 was found in B cells of tonsil and spleen, but not PB, we hypothesized that ZAP-70 may be associated with activation status since tonsillar and splenic B cells will include a population of activated B cells. To examine this issue, we sorted CD19+/CD38+ from CD19+/CD38− tonsillar cells and again evaluated ZAP-70 expression. Whereas both populations expressed ZAP-70, CD38+ B cells expressed ZAP-70 at a higher level suggesting that ZAP-70 may be associated with a more activated phenotype. To address the issue of activation, we activated CD19+ PB B cells with a cocktail of CD40L, IL-10, IL-4 and IL-6 for 3 days and analyzed ZAP-70 expression. Indeed, we were able to induce ZAP-70 expression in a subpopulation of blood B cells. We also assessed ZAP-70 phosphorylation following tonsillar B cell receptor (BCR) ligation and we observed that phosphorylation of ZAP-70 (tyrosine 493) occurred within 10 min. of BCR stimulation. Finally, we assessed whether ZAP-70 expression in B-CLL could be associated with an activated cell phenotype. By stimulating Ig VH non-mutated and mutated B-CLL patient samples with the CD40L cocktail, we observed an increase in ZAP-70 expression in non-mutated CLL by immunoblotting. These results demonstrate expression of ZAP-70 in a subset of normal B cells that express an activated phenotype. Moreover, our results also suggest that ZAP-70 levels in CLL B cells may also be increased following cellular activation. Given that non-mutated type B-CLL expresses ZAP-70 more frequently than mutated type B-CLL, ZAP-70 expression may simply reflect a more activated population of leukemic cells that may correlate with progressive disease. Continuing investigation into the role of ZAP-70 in normal B cell development and B-CLL is clearly warranted.

BACKGROUND: Chemoimmunotherapy with fludarabine, cyclophosphamide, and rituximab (FCR) has been the standard therapy for younger patients with CLL. FCR therapy is particularly effective in patients with immunoglobulin heavy chain variable region (IGHV) mutated CLL. Approximately half of IGHV mutated patients are progression free 8 years after FCR therapy. At the ASH 2018 meeting, we reported the initial results of the ECOG 1912 (E1912) trial, a phase 3 trial comparing the FCR regimen to the combination of ibrutinib and rituximab (IR) for previously untreated CLL patients age 70 or younger who required therapy. With median follow-up of approximately 34 months, the trial demonstrated both a progression-free survival (PFS) and an overall survival (OS) benefit relative to FCR. On sub-set analysis by IGHV mutation status, the difference in PFS was statistically significant for IGHV unmutated patients but, with current follow-up, not IGHV mutated patients. Here, we present updated results for PFS in the E1912 trial. METHODS: As previously reported, eligible patients were treatment-naive individuals with CLL age 70 or younger. Patients with deletion 17p- were excluded from participating in the E1912 trial given their known poor response to FCR therapy. Patients were randomly assigned in a two-to-one ratio to receive ibrutinib (420 mg/day until disease progression or unacceptable toxicity) and rituximab (50 mg/m2 on day 1 of cycle 2, 325 mg/m2 on day 2 of cycle 2, and then 500 mg/m2 on day 1 of cycles 3-7) or six courses of intravenous fludarabine (25 mg/m2 days 1-3), cyclophosphamide (250 mg/m2 days 1-3) and rituximab (50 mg/m2 on day 1 of cycle 1, 325 mg/m2 on day 2 of cycle 1, and then 500 mg/m2 on day 1 of cycles 2-6) every 28-days. Adverse events (AEs) were graded according to the NCI Common Toxicity Criteria (version 4). Dose adjustments for cytopenias were based on the IWCLL CLL Working Group grading scale. The primary endpoint of the trial was PFS with OS a secondary endpoint. Analysis was by intention to treat. RESULTS: With median follow-up of 45 months, 257 (73%) of 354 patients randomized to IR remain on ibrutinib. With extended follow-up, grade 3 and above treatment-related AEs were observed in 70% of IR and 80% of FCR treated patients (OR=0.56; 95% CI 0.34 - 0.90; p=0.013). Among IR-treated patients, the median time on treatment is currently 43 months (range=0.2-61). Among the 95 patients who have discontinued ibrutinib, the reason for discontinuation was progression or death in 23 (7% of patients who started IR; 24% of those who discontinued treatment), AE or complication in 48 (14% of patients who started IR; 51% of those who discontinued treatment), and withdrawal of consent or other reasons in 24 (7% of patients who started IR; 25% of those who discontinued treatment). On multivariable Cox regression adjusting for Timed Up and Go test score, Cumulative Illness Rating Scale (CIRS) score, age, gender, ECOG performance status, creatinine clearance, and baseline anemia/thrombocytopenia, only CIRS score (range 0 - 14) predicted discontinuation of ibrutinib for a reason other than progression or death (HR=1.13 per unit increase; 95% CI 1.03 - 1.23; p=0.009). Among the 72 patients who discontinued ibrutinib for a reason other than progression or death, the median time on ibrutinib was 15.1 months (range 0.2-58.2 months). The median time from ibrutinib discontinuation to disease progression or death was 23 months. With current follow-up, we observed 110 PFS events. The hazard ratio (HR) for PFS favored IR over FCR (HR=0.39; 95% CI 0.26-0.57; p<0.0001). Updated analysis of OS will be presented. On sub-group analysis by IGHV mutation status, IR was superior to FCR for IGHV unmutated patients (HR=0.28; 95% CI 0.17-0.48; p<0.0001). With current follow-up the difference is not significant in IGHV mutated patients (HR=0.42; 95% CI 0.16-1.16; p=0.086). Kaplan-Meier estimates for PFS are shown in Figure 1. CONCLUSIONS: Although less than 7% of ibrutinib treated patients progressed while on therapy, roughly 1 in 5 patients have discontinued ibrutinib for a reason other than progression or death. The only parameter significantly associated with discontinuation for a reason other than progression was increased baseline CIRS score. With extended follow-up, the combination of ibrutinib and rituximab continues to provide superior PFS compared to FCR for younger patients with previously untreated CLL. Disclosures Shanafelt: Pharmacyclics: Research Funding; Patent: Patents & Royalties: US14/292,075 on green tea extract epigallocatechin gallate in combination with chemotherapy for chronic lymphocytic leukemia; Polyphenon E International: Research Funding; Merck: Research Funding; Abbvie: Research Funding; Genentech: Research Funding; Celgene: Research Funding; Glaxo-SmithKline: Research Funding; Hospira: Research Funding; Cephalon: Research Funding. Kay:MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Agios: Other: DSMB. O'Brien:Janssen: Consultancy, Honoraria; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Astellas: Consultancy; Aptose Biosciences, Inc: Consultancy; Amgen: Consultancy; Alexion: Consultancy; Acerta: Research Funding; Eisai: Consultancy; Gilead: Consultancy, Research Funding; GlaxoSmithKline: Consultancy; Verastem: Consultancy; Celgene: Consultancy; Sunesis: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Vaniam Group LLC: Consultancy; Regeneron: Research Funding; Kite: Research Funding. Barrientos:AbbVie: Consultancy, Research Funding; AstraZeneca: Consultancy; Genentech: Consultancy; Bayer: Consultancy; Gilead: Consultancy; Janssen: Honoraria; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; Sandoz: Consultancy; Oncternal Therapeutics: Research Funding. Coutre:Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Gilead: Research Funding; BeiGene: Other: Travel, Accommodations, Expenses & Data Safety Monitoring Committee; Genentech: Consultancy. Barr:Pharmacyclics LLC, an AbbVie company: Consultancy, Research Funding; Gilead: Consultancy; Verastem: Consultancy; Genentech: Consultancy; Seattle Genetics: Consultancy; Merck: Consultancy; Celgene: Consultancy; Janssen: Consultancy; AbbVie: Consultancy; Astra Zeneca: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding. Cashen:Celgene: Other: Speaker's Bureau; Seattle Genetics: Other: Speaker's Bureau; Novartis: Other: Speaker's Bureau. Mato:AstraZeneca: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Sunesis: Consultancy, Research Funding; Celgene: Consultancy; Johnson & Johnson: Consultancy, Research Funding; TG Therapeutics: Consultancy, Other: DSMB member , Research Funding; LOXO: Consultancy, Research Funding; DTRM Biopharma: Research Funding; Genentech: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Gilead: Research Funding; Acerta: Consultancy; Janssen: Consultancy. Erba:Amgen: Consultancy; MacroGenics: Consultancy, Other: Lecture fees, Research Funding; MacroGenics: Consultancy, Other: Lecture fees, Research Funding; Novartis: Consultancy, Research Funding, Speakers Bureau; Novartis: Consultancy, Research Funding, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; ImmunoGen: Consultancy, Research Funding; Astellas Pharma: Consultancy; Astellas Pharma: Consultancy; Amgen: Consultancy; GlycoMimetics: Consultancy, Other: Chair, data and safety monitoring board, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Celgene: Consultancy, Other: chair, AML Registry Scientific Steering Committee, Speakers Bureau; ImmunoGen: Consultancy, Research Funding; AbbVie: Consultancy, Other: Chair, IRC for phase III studies, Research Funding; GlycoMimetics: Consultancy, Other: Chair, data and safety monitoring board, Research Funding; Covance: Other: Fees for serving as chair on an independent review board for AbbVie Phase III studies; Covance: Other: Fees for serving as chair on an independent review board for AbbVie Phase III studies; AbbVie: Consultancy, Other: Chair, IRC for phase III studies, Research Funding; Celgene: Consultancy, Other: chair, AML Registry Scientific Steering Committee, Speakers Bureau; Pfizer: Consultancy; Pfizer: Consultancy; Seattle Genetics: Consultancy; Seattle Genetics: Consultancy; Daiichi Sankyo: Consultancy, Research Funding. Stone:Arog Pharmaceuticals: Consultancy, Honoraria, Research Funding; Otsuka-Astex Pharmaceuticals: Consultancy; Fujifilm: Consultancy; AstraZeneca: Consultancy; Celator Pharmaceuticals: Consultancy; Abbvie: Consultancy, Research Funding; Ono Pharmaceutical-Theradex Oncology: Consultancy; Cornerstone Pharmaceuticals: Consultancy; Daiichi Sankyo: Consultancy; Takeda: Other: Fees for serving on a data and safety monitoring board ; Orsenix: Consultancy; MacroGenics: Consultancy; Jazz Pharmaceuticals: Consultancy; Agios: Consultancy, Research Funding; Stemline Therapeutics: Consultancy; Pfizer: Consultancy; Celgene: Consultancy, Other: Fees for serving on a steering committee, and fees for serving on a data and safety monitoring board; Novartis: Consultancy, Research Funding; Actinium Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Astellas Pharma: Membership on an entity's Board of Directors or advisory committees; Argenx: Other: Fees for serving on a data and safety monitoring board ; Roche: Consultancy. Tallman:Jazz Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncolyze: Consultancy, Membership on an entity's Board of Directors or advisory committees.

The ability to visualize and quantify the spatial arrangement and geographic proximity of immune cells with tumor cells provides valuable insight into the complex mechanisms underlying cancer biology and progression. Multiplexing, which involves immunofluorescence labeling and the visualization of multiple epitopes within formalin-fixed paraffin embedded tissue sections, is a methodology that is being increasingly employed. Despite the power of immunofluorescence multiplex analysis, application of this technology to bone marrow core biopsies has not yet been realized. Given our specific long term goal to identify immune cells in proximity to bone marrow malignant plasma cells in multiple myeloma patients, we describe in this study adaptation of multiplex immunofluorescence analysis to this tissue. We first identified a blocking strategy that quenched autofluorescence. We next employed a multiplex strategy that uses a simple stripping solution to remove primary and secondary antibodies prior to subsequent rounds of staining. This method was found to be highly efficient and did not significantly alter antigenicity or tissue integrity. Our studies illustrate for the first time that immunofluorescence multiplexing is achievable in bone marrow core biopsies and will provide a novel opportunity to analyze the role of the immune contexture in disease progression of the monoclonal gammopathies.

Abstract BACKGROUND: Chronic lymphocytic leukemia (CLL) is a heterogeneous B cell malignancy with patients being categorized into disease subsets based on several key biologic parameters, e.g., mutation status (mutated, M; or unmutated, UM) of the immunoglobulin heavy chain variable region (IGHV), acquired chromosomal abnormalities, and expression of CD38 and CD49d. Furthermore, about one third of CLL patients express stereotyped B cell receptors and/or may acquire high risk common mutations in genes such as NOTCH1 and SF3B1 suggesting ongoing genetic evolution as drivers of disease development. Critical to this concept, those CLL patients with trisomy 12 (T12) defects have a higher incidence of mutations in NOTCH1 and often have a stereotyped receptor. However, T12 patients may have a variable clinical course that appears to be unrelated to these 2 drivers suggesting an additional, possibly non-coding genetic component that may further impact disease progression in these patients. One potentially relevant genetic factor that could influence T12 clinical course is long non-coding RNAs (lncRNAs). LncRNAs are transcripts longer than 200 nucleotides that can affect a number of cellular processes. Importantly, lncRNAs have been implicated in various cancers including malignant hematopoiesis indicating they could be therapeutic targets and/or clinically useful biomarkers. METHODS: To pursue a role for lncRNAs in T12 we used v3.0 Arraystar Human LncRNA Microarrays to assess the global profile of lncRNA expression in CLL with an emphasis on patients with T12. Two cohorts of 6 patients with T12 were selected for comparison: one defined as progressive with a short time to treatment (TTT) (treatment ≤1 year after diagnosis) and one as indolent (no treatment > 5 years after diagnosis). Each cohort included 3 patients with M and 3 with UM IGHV status. RNA from normal CD5+ and CD5- B cells was included as a control. To compensate for the small sample size in each cohort, a significant difference in lncRNA expression between the groups was defined as a fold change (FC) ≥5.0, p-value ≤0.05 and false discovery rate (FDR) ≤ 0.05. RESULTS: An initial global comparison of CD5+/CD5- normal B cells vs all CLL samples found that 609 lncRNAs were differentially expressed using the criteria listed above with 158 lncRNAs having a FC>10. Notable lncRNAs in this group included: LOC541472 (down in CLL and associated with the IL-6 gene), D63785 (up in CLL and associated with TBC1D3C, an oncoprotein), CTC-459I6.1 (up in CLL and associated with RASGRF2) and AC002480.5 (down in CLL and associated with STEAP1B, shown to be overexpressed in prostate cancer). We next evaluated T12 samples and identified 90 candidate lncRNAs that may discriminate between progressive and indolent T12 cases. Within this group were 11 lncRNAs with a FC > 10, 5 of which have no known associated gene. Of those associated with known genes, 3 were ultra-conserved region encoding lncRNAs down-regulated in progressive T12 patients (TTT ≤1 yr) and linked to hephaestin-like protein 1 precursor, pannexin-1, and tubulin beta-3 chain isoform 1. Of potential high relevance we found that the lncRNA LPP-AS1 was down-regulated in progressive T12 patients (TTT ≤1 yr) and known to be associated with the LIM-containing lipoma preferred partner (LPP) gene (p=0.028; FDR=0.03 and FC=18.3). Looking specifically at IGHV M progressive T12 patients (T12M≤1 yr) vs IGHV M indolent T12 patients (T12M>5 yrs), we again found the LPP-AS1 lncRNA was highly down-regulated in T12M≤1 (p=0.00046; FDR=0.006 and FC=34.5) but it was not found to be differentially expressed in the UM T12≤1 yr vs UM T12>5 yr comparison. The LPP gene has been shown to play a role in cell-cell adhesion, motility and signaling, and is often the fusion partner for the mixed lineage leukemia (MLL) gene in secondary acute leukemia. Furthermore, LLP may play a role in breast cancer cell invasion. LPP-AS1 may be participating in IGHV M T12 progression by affecting LPP and thus influencing migration through the lymph node microenvironment. CONCLUSION: While candidate lncRNAs in T12 CLL need to be validated, the LPP-AS1 lncRNA shows promise as a possible marker and potential treatment target for those patients with T12 and M IGHV that may progress rapidly. Further studies are needed to evaluate the impact of lncRNAs on clinical outcome of T12 CLL patients. Disclosures Shanafelt: Hospiria: Research Funding; Pharmacyclics/Jannsen: Research Funding; Cephalon: Research Funding; Celgene: Research Funding; glaxoSmithKline: Research Funding; Genetech: Research Funding; Polyphenon E Int'l: Research Funding. Kay:Celgene: Research Funding.

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 Background: Monoclonal B-cell lymphocytosis (MBL) is characterized by the presence of a circulating population of clonal B-cells where the total B-cell count is <5 × 109/L and criteria for the diagnosis of other lymphoproliferative disorders are not present. In most patients the immunophenotype is similar to that of chronic lymphocytic leukemia with co-expression of CD19 and CD5. The natural history of MBL is unclear. We used the Mayo Clinic hematopathology database to identify patients with MBL and abstracted clinical information on natural history and prognostic parameters from clinical and research records. Methods: After IRB review and approval, we reviewed the hematopathology records of 2292 patients seen at Mayo Clinic between August 1998 and May 2006 who had a clonal B-cell population on flow cytometry phenotypically consistent with CLL and fewer than <5 × 109/L B-cells. Clinical records were then reviewed to identify patients who fulfilled the criteria for MBL (no evidence of other lymphoproliferative disorders, no adenopathy on exam). Patient characteristics, prognostic parameters, and clinical outcomes were abstracted from the clinical and research records of these patients. Cox regression analysis was used to evaluate association between prognostic markers and time to treatment. Results: A total of 118 patients meeting the criteria for MBL were identified. Median age at the time of MBL diagnosis was 69.4 years (range 39.0 – 91.4). A slight male preponderance was observed (54% male). CD38 status was available for 106 (90%) patients of whom 20% were CD38 positive using the 30% threshold to classify CD38. Cytogenetic analysis by fluorescent in situ hybridization (FISH) was available in 58 (49%) patients. Using the hierarchical classification system of Dohner and colleagues, 26 (44.8%) were 13q-, 10 (17.2%) were trisomy 12, 2 (3.4%) were 11q-, 1 (1.7%) was 17p-, and 19 were (32.8%) no defect was detected. ZAP-70 status was available for 32 patients of whom 22% were ZAP-70+ positive. IgVH gene mutation status was only available for 15 (12.7%) patients of whom 40% were unmutated. Time from MBL diagnosis to treatment is shown in Figure 1. Survival free of treatment was 92.7% (95%CI: 86.8–99.1%) at 1 year, 90.9% (95%CI: 84.2–98.2%) at 2 years, and 87.5% (95% CI: 78.7–97.4%) at 5 years. While age (p=0.68) and gender (p=0.14) were not found to be associated with time to treatment (TTT), CD38 status showed a strong relationship with TTT (p<0.001, HR: 22.7, 95% CI: 3.4–239.6). Conclusion: The distribution of prognostic parameters (e.g. CD38, FISH) in patients with MBL appears similar to that of patients with early stage CLL. We observed a low rate of progression, with 5 year survival free of treatment greater than 87%. TTT among newly diagnosed MBL patients was associated with the CD38 status of clonal B-cells. Figure Figure

Antibody secreting plasma cells (PCs) play an important role in effective humoral immune responses. The low frequency of bone marrow PCs in humans makes it challenging to obtain sufficient numbers of PCs for biologic studies. Previous studies have employed in vitro model systems to generate cells that morphologically, phenotypically, and functionally resemble normal polyclonal PCs. Gene expression profiles of in vitro generated PCs (IVPCs) mirror their normal counterparts, however to date extensive immunoglobulin (Ig) repertoire analysis of IVPCs is lacking. Here, we used a modified 3-step protocol to generate IVPCs and used RNA-seq to explore the transcriptome with emphasis on the Ig repertoire of plasmablasts and PCs. Total B cells were isolated from 3 normal donors and cultured with various cytokines and the B cell activators CpG ODN and CD40L. RNA was obtained from freshly isolated B cells (Day 0; D0) as well as from Day 4 (D4) plasmablasts, and Day 10 (D10) IVPCs. Morphologically, D10 cells exhibited typical PC morphology, including an eccentric nucleus and perinuclear hof. RNA-seq was performed on total RNA from all 3 donors and time points using the Standard TRuSeq v2 library prep and with paired end sequencing on the Illumina HiSeq 4000 platform. Principle component analysis of gene expression data showed that D0, D4 and D10 cells could be clearly segregated across all 3 normal donors. Of importance, transcripts previously described as distinguishing B cells from PCs were found to be differentially expressed including overexpression of CXCR5, CD19, EBF, CD83, PAX5, IRF8 in D0 B cells and overexpression of IRF4, Blimp-1, XBP1, BCMA, SLAMF7, Syndecan-1, CD38 and CD27 in IVPCs, thus validating our in vitro model for generating PCs. Furthermore, expression of cell cycle related transcripts such as CKS1, CDK1, and CCDN2 followed the pattern of low expression in resting B cells, increased expression in plasmablasts, and decreased expression in IVPCs confirming the cells are actively cycling in a manner comparable to cells in vivo. D10 IVPCs also overexpressed transcripts known to be upregulated during the unfolded protein response. As expected from Ig secreting cells, D10 IVPCs had an over-representation of Ig transcripts. At D0, resting B cells had high levels of IgD and IgM heavy chain (HC) transcripts. At D10, IgM transcripts modestly increased with Log2 fold change (FC) = 3 and as expected, IgD levels decreased significantly (Log2 FC = -2.2). IgA and IgG isotype transcripts significantly increased at D10 (Log2 FC > 6.0) with the IgG4 subtype having the greatest Log2 FC at 8.4. Next we focused on the Ig repertoire of D0, D4, and D10 cells. By aligning to known germline Ig sequences in IMGT/V-Quest (www.imgt.org) and then assembling the paired ends of D0, D4 and D10 Ig transcripts, we were able to analyze the Ig repertoire. Since the Ig HC variable (V) region is encoded by V, diversity (D) and joining (J) segments, only fragments that could be confidently determined were considered. All but 3 IGHV transcripts (IGHV3-35, IGHV3-47 and IGHV7-8) and 2 IGHD transcripts (IGHD4-4 and IGHD5-5) were found and all IGHJ segments were represented across the differentiation spectrum. In D0 cells, the number of unique VDJ combinations ranged from 643 to 863 across all 3 normal samples and increased to a range of 2524 to 2867 in D10 IVPCs. When looking at the differential expression of each VDJ combination from D0 to D10, a pairwise t-test for relative frequency showed that there was no significant change greater than 1%, suggesting the repertoire diversity was not skewed, thus proving the conditions for stimulation were not targeting any one starting B cell. Our data also allowed us to track clonal expansions during differentiation as defined by the increasing frequency of sequences with identical nucleotide sequence in the V region and CDR3 (including D and J regions). Hence, a single sequence could be tracked from D0 to D10. Of interest, in a small sampling of the total available sequences, only those B cells with a mutated IGHV region, characteristic of a memory B cell, went on to expand in this system whereas B cells with an unmutated IGHV did not. Our analysis of the Ig repertoire of IVPCs suggests this system provides a functional model to study Ig repertoire along the B cell differentiation process and further delineate the conditions that may result in a clonal expansion, a hallmark of many hematologic malignancies including multiple myeloma. Disclosures No relevant conflicts of interest to declare.

Abstract Aberrant over production of monoclonal immunoglobulin is a classic feature of the plasma cell (PC) malignancy multiple myeloma (MM). At diagnosis and more frequently upon relapse, some MM patients present with increased production of monoclonal free light chain (FLC) without a corresponding increase in intact immunoglobulin. This phenomenon is commonly referred to as light chain escape (LCE). As previously described (Walters et al. 2018, Experimental Hematology, Vol 57 p42-49), we have established a monoclonal IgA kappa MM cell line, designated as MC-B11/14, from the bone marrow (BM) aspirate of a 46 year old man diagnosed with MM. This cell line is non-hyperdiploid and possesses an 11;14 chromosomal translocation. Given our long standing interest in immunoglobulin function and secretion, we used CRISPR technology to knock out IgA heavy chain production in an effort to create a model of LCE. Successful knockout (KO) of IgA expression was demonstrated by immunofluorescence, flow cytometry, and western blot. As expected, secretion of intact IgA was undetectable in the MC-B11/14IgA- cells. Notably, no significant difference in morphology, phenotypic markers, or growth patterns was observed between the MC-B11/14WT and MC-B11/14IgA- cells. Examination of drug sensitivity between the MC-B11/14WT and MC-B11/14IgA- cells revealed that the response to pomalidomide treatment was similar between the MC-B11/14WT and MC-B11/14IgA- cells; however, the MC-B11/14IgA- cells were found to be more resistant to treatment with bortezomib. Given that increased bortezomib resistance was the only significant difference detected between the MC-B11/14WT and MC-B11/14IgA- cell lines in our initial study, we decided to take a metabolomics approach to examine whether loss of IgA heavy chain expression may alter cellular metabolism. Metabolomics or the profiling of small molecules is a powerful tool to characterize the metabolome of cells/biological systems and has proven to be useful in identifying alterations that occur in malignancy. In this regard, we employed pathway-specific targeted LC-MS/MS protocols in order to examine over 330 metabolites in 35 metabolic pathways in MC-B11/14WT and MC-B11/14IgA- methanolmetabolite extracts using an Agilent 1290 UPLC-6490 QQQ-MS liquid chromatography mass-spectrometer. Of the 330 metabolites examined, 28 were found to be significantly more abundant in the MC-B11/14IgA- cells compared to MC-B11/14 WT cells while 79 were found to be significantly less abundant. In general, the majority of significant metabolic differences between the two cell lines were found to involve metabolites from various amino acid synthesis pathways. More specifically, the MC-B11/14 WT cell line was found to possess significantly more citraconic acid, anthranilic acid, and homovanillic acid. By contrast, further analysis revealed that the MC-B11/14IgA- cell line was found to possess an 11.5 fold increase of the metabolite 2-hydroxyglutarate (2-HG). 2-HG has previously been shown to act as a competitive antagonist of α-ketoglutarate (α-KG), which results in the inhibition of α-KG-dependent dioxygenases including the JmjC domain-containing histone demethylases (KDMs) and the ten-eleven translocation (TET) family of DNA hydroxylases. Notably, these proteins are known to play a role in histone and DNA demethylation, respectively. Taken together, these data suggest that MM cells that have undergone LCE may also possess an accumulation of 2-HG which could lead to altered patterns of histone and DNA methylation. Given that MM patients who relapse with LCE typically have a poorer prognosis, further investigation of metabolomics in light-chain only expressing cell lines and patients who have relapsed with LCE is warranted. Disclosures No relevant conflicts of interest to declare.

Abstract Intercellular communication between multiple myeloma (MM) cells and the normal bone marrow stroma leads to a modification of the bone marrow microenvironment, which favors tumor progression. New developments in extracellular vesicle (EV) research suggest that this diverse population of vesicles, released by cancer cells including MM cells, express transmembrane proteins and carry cargo that can modify recipient cells in myriad ways. In particular, tumor-derived EVs have been shown to create permissive microenvironments that lead to metastatic colonization by circulating tumor cells. As we have previously shown that MM EVs can enhance proliferation of recipient MM cells, we hypothesize that MM EVs can potentially play a much larger role in MM development and progression. In order to understand the scope of potential EV roles in MM, we executed a comprehensive proteomic analysis of the cargo of MM EVs. We isolated EVs from patient derived MM cell lines that represent the most common genetic variants of this tumor, and used in vitro generated plasma cells (IVPCs) as a reference population. In a first pass analysis, we selected proteins that were expressed ≥3 fold higher in MM EVs than in IVPC EVs, and this analysis identified 306 proteins. Of interest, included in the 306 differentially proteins were several involved in the regulation of cell adhesion such as members of the a disintegrin and metalloprotease domain (ADAM8, 9, 10, 13, 15 and 22) family, which are also associated with inhibition of cell proliferation. Moreover, CEACAM1, PTPRK, and CDH2, which are also linked to cellular adhesion, were also expressed at a higher level in MM EVs. Various proteins linked to myeloma cell biology were likewise found to be over-represented in MM EVs, and these include BCMA, ITGAV, ITGB5, IL6ST (gp130), CD276 (B7-H3), and CD28. As we are most interested in biologically relevant and actionable proteins present uniquely in MM derived EVs, we filtered from our data proteins that were also present in EVs from IVPCs. We further filtered out proteins known to be present in EVs from normal cells. This filtering strategy reduced the number of interesting candidates to 8, which included CD28, MET, TRKC, and ADAM15. Thus far, we have confirmed the presence of these 4 proteins in a panel of MM EVs, and we are currently in the process of validating additional candidate cargo proteins for their biological role in enhancing tumor cell proliferation and/or protection from apoptosis. In summary, EV proteomic analysis of cell lines representing MM genetic subtypes can lead to the identification of biologically relevant proteins transported systemically by EVs as well as suggest novel biomarkers that are easily detectable in plasma and may permit earlier recognition of disease progression in patients with MM. Disclosures No relevant conflicts of interest to declare.