Kay, Neil E.

Abstract Background: Smudge cells are ruptured CLL cells seen on blood smears of CLL patients. For over a century, smudge cells were thought to represent an artifact of slide preparation. We recently showed that smudge cell formation was inversely proportional to leukemic B cell vimentin content. Vimentin is a cytoskeletal protein critical for lymphocyte rigidity and migration; high vimentin content is related to poor prognosis in CLL. Concordantly, in an initial small cohort of patients from a single institution, we found that patients with a low (<30%) percentage of smudge cells on a blood smear have a shorter time to treatment (Mayo Clin Proc.2007;82:449–53). In the current study, we evaluated the impact of smudge cell percentage on prognosis of patients with CLL seen at member institutions of the CLL Research Consortium (CRC). Methods: Archived blood smears from untreated patients with CLL were evaluated for smudge levels. All blood smears were prepared manually in a standard fashion from blood obtained by CRC Tissue Core and stained with WrightGiemsa stain. Smudge cells were defined as broken cells with no intact cytoplasm and a disrupted nuclear membrane. A total of 200 lymphocytes and smudge cells were counted on each slide and the results were expressed as the percent smudge cells. The association between the percentage of smudge cells, prognostic factors (IgVH status, CD38, ZAP-70 and FISH) and time to initial therapy (TTT) was examined. Results: We calculated smudge cell percentage on blood smears obtained prior to treatment for 337 CLL patients. The median smudge cell percentage was 32 (range 2–95%). The percentage of smudge cells was lower in CD38 positive patients (mean 33% vs. 38% in CD38 negative patients, p=0.04). No difference in smudge cell percentage was observed based on IgVH gene mutation status or Zap70 expression. Smudge cell percentage as a continuous variable was associated with prolonged TTT, exponential coefficient 0.98, p=0.04. Using our previously published cutoff of 30% to stratify patients in low and high risk categories, the estimated median time to first therapy of patients with smudge cell percentage ≤30% (n=178) was 7.8 years versus not reached in patients in patients with > 30% (n=159) of smudge cells, p=0.0036, (Figure 1). Ten years from diagnosis, 62% of patients with ≤30% of smudge cells versus 39% of patients with >30% of smudge cells required therapy. In multivariate analysis, the low percentage of smudge cells (≤30%) was an independent predictor of the shortened time to treatment (HR 1.86, 95%CI 1.09–3.16, p=0.02). Conclusion: This multicenter study confirms our initial finding that the percentage of smudge cells on a blood smear is an independent predictor of clinical outcome in patients with CLL. The estimation of smudge cell percentage on routine blood smear provides a simple and inexpensive prognostic test available to nearly all patients with a diagnosis of CLL worldwide. It also allows reanalysis and risk stratification of previously completed trials provided that blood smears have been archived. Further studies of the role of the cytoskeleton in CLL biology are warranted and ongoing in our laboratory. Figure Figure

Abstract While cellular communication and interactive signaling typically relies on multiple mechanisms including secretion of various growth factors, cytokines, bioactive lipids, and adhesion molecules, we have recently focused on cell-to-cell communication that involves circular membrane vesicles designated as microvesicles (MVs). These are normal constituents of blood plasma released by leukocytes, endothelium, platelets and erythrocytes and are generated by cell activation and growth. In normal serum, the order of MV abundance is platelet-derived (80%), endothelial (10%) and leukocyte-derived (10%) but MV can also be released by malignant cells. The size varies from 0.1–1.0 μm and, MVs express antigens characteristic of the cell of origin, carry other membrane and cytoplasmic constituents and exhibit negatively charged phospholipids (phosphatidylserine) detectable by Annexin V binding. To begin to characterize MV and their potential for communication in CLL, we isolated and characterized MVs from the plasma of chronic lymphocytic leukemia B-cell (CLL B) patients (Rai 0-IV). After isolation from platelet-free plasma, MVs were characterized by flow cytometry for forward and side scatter using 1μm fluorescent beads and stained with Annexin V. Our results suggest that MVs are heterogeneous in size with the majority of MVs within 1μm. Transmission electron microscopy confirmed the size heterogeneity of MVs and exhibited the morphology of the membrane-bound vesicles after phosphotungstic acid staining onto parlodium-coated 300 mesh copper grids. Flow cytometric analysis further demonstrated the presence of CD61 (platelet/megakaryocyte marker), CD19, CD5, CD52, and CD20 on the surface of MV, albeit in differential amounts depending on the stage of the disease and the total leukocyte count. For example, in Rai stage IV (n= 5), we found lesser numbers of MV carrying platelet-derived marker CD61 and more CD19 (41–79%), and CD5 compared to normal MV; 1–5% MV from healthy controls expressed CD19 while Rai stage 4 patients MV expressed CD19 from 41–79%. These results suggest that a significant number of MVs are generated from the leukemic B-lymphocytes in more advanced Rai stage. However, we also found that patients with a higher blood lymphocyte count but lower Rai-stage (Rai I/II) contain moderate levels of CD19-bearing MVs (13–43%). Importantly, presence of MVs carrying CD52/CD20 in the blood of CLL patients may undermine the therapeutic effectiveness of alemtuzumab and rituximab. To this end, we observed that MVs could be incorporated into the CLL B cells as evident from the expression of the platelet antigen CD61 on CLL B cell surfaces after co-culture of CD61-bearing MVs with CLL B cells. Global proteomic analysis of MVs isolated from an advanced stage (Rai IV) CLL B patient detected the presence of about 700 proteins that normally reside in the nucleus, cytoplasm or membrane. In summary, we have isolated and characterized plasma MV from CLL B patients and found them to be more likely generated from CLL B cells in relation to disease stage or total lymphocyte count. These MVs contain a multitude of proteins and are able to integrate into bystander CLL B cells. We also found that these MVs carry a large set of proteins, which could potentially not only modulate cell-cell communication but also interrupt monoclonal antibody directed therapy. Further studies are underway to dissect their roles in CLL B malignancy.

Abstract Background: Historically, CLL patients with cytopenia were thought to have a poor prognosis and cytopenia is a key feature of CLL clinical staging systems. The implications of cytopenia in CLL could have changed because of improved diagnostic accuracy, increased recognition of early stage disease, and better treatments. Newer data suggest that the etiology of cytopenia determines its prognostic importance in CLL. Patients with cytopenia caused by autoimmune disease (AID) are less likely to have the poor prognosis associated with patients with bone marrow (BM) failure. To determine the prognostic significance of cytopenia in patients with CLL, we performed an observational study at Mayo Clinic Rochester (MCR). Methods: We studied all patients with CLL seen in the Division of Hematology at MCR from 1 January 1995 to 31 December 2004 (n = 1,750). Cytopenia (hemoglobin < 10 g/dL or platelet count < 100 × 09/L) was considered due to BM failure in patients with extensive BM involvement by CLL (< 20% residual myeloid tissue on BM biopsy) or reticulocytopenia without other causes persisting > 3 months after CLL therapy. Cytopenia was attributed to AID in patients with autoimmune hemolytic anemia (AIHA), immune thrombocytopenia (ITP), pure red blood cell aplasia (PRCA), or autoimmune granulocytopenia (AIG). Results: Median age at diagnosis of CLL was 63.7 years (69% male). Cytopenia occured in 423 (24.2%) patients. In 303 patients, cytopenia was due to CLL (228 BM failure and 75 AID). In 120 patients cytopenia was due to CLL related factors (splenomegaly, n = 11; possible AID, n = 18; treatment of CLL, n = 16) or non CLL causes (other malignancy, n = 12; iron deficiency, n = 11; anemia of chronic disease, n = 10; renal failure, n = 6; drugs effect, n = 4; surgical blood loss n = 4). In 28 (6.6%) patients the cause of cytopenia was not definitively determined. Of the patients with BM failure, 97 (43%) had cytopenia at CLL diagnosis (70% male, median age 63.3 years [range 32–95]), The AID patients the median age of CLL diagnosis was 66.7 years (range 30–85) with 79% male. AID diagnoses were AIHA (n = 41), ITP (n= 35), PRCA (n=8), and AIG (n=3); 9 patients had > 1 AID. Survival from diagnosis of cytopenia was significantly better for patients with AID (median 9.1 years) than BM failure (median 4.4 years, p < 0.001). AID patients had a longer survival from diagnosis of CLL (median 12.4 years) versus the rest of the CLL population (median 9.5 years, p = 0.020) but patients with BM failure at diagnosis had a worse prognosis (median 6.2 years, p < 0.001). Conclusion: We show that the etiology of cytopenia in CLL patients determines its prognostic importance. Anemia and thrombocytopenia caused by BM failure, but not AID, are associated with a significantly worse prognosis. These data show the importance of accurate determination of the etiology of cytopenia in all patients with CLL. Cytopenia in patients with AID is not a marker of advanced stage disease; these patients often need different management compared to those with BM failure. Cytopenia due to AID versus BM failure can be difficult to distinguish and a BM study should be done in all patients considered for treatment. Patients with cytopenia due to AID cannot be meaningfully classified by current clinical staging systems. We believe that efforts to review the NCI-WG 96 criteria are timely and should consider the etiology of cytopenia in CLL patients.

Abstract Introduction The natural history of patients (pts) with CLL varies considerably. Some pts may have asymptomatic, indolent disease, while others may require therapy soon after diagnosis. Clinical staging systems cannot identify early-stage pts at risk for inferior survival. Genetic and molecular markers can provide additional information regarding prognosis and response prediction, however their utilization is limited in routine practice (Mato, ASCO 2015) and results can be conflicting. There is a need to identify characteristics of early-stage CLL pts at highest risk of early progression and/or death. Such characteristics, if readily available and reproducible, may identify such pts as candidates for early-intervention studies; particularly in the era of kinase inhibitor therapy. The Connect CLL registry is the largest prospective study describing real-world management of a diverse cohort of 1494 CLL pts. In this analysis, we evaluate key factors that are associated with early CLL-associated mortality in clinical practice. Methods Connect CLL is a multicenter, observational cohort study aimed at understanding patterns of CLL management without a study-specific intervention. Eligible pts were adults with a clinical diagnosis of CLL, enrolled between 2010-2014 at 179 community (n=1311), 17 academic (n=155), and 3 government (n=28) sites within ≤ 2 months of initiating either a first line of therapy (LOT1), or a second-line or subsequent LOT (LOT≥2). The goal of this analysis was to assess potential predictors of death occurring within 18 months following initiation of frontline therapy (LOT1). Because CLL usually presents as an indolent disease associated with a prolonged clinical course, we chose to define early mortality as any death occurring ≤ 18 months following enrollment. Univariate logistic regression was performed against potential predictor variables including several clinical characteristics and comorbid conditions, race, treatment (Tx) site, insurance type, geographic region, presence of prior malignancies, genetic prognostic factors (FISH and cytogenetics) at enrollment, cell surface markers (Zap70, CD38), reasons for Tx initiation and Tx choice for LOT1 (BR or FCR). IgVH mutation status and genetic mutations (P53, Notch1, etc.) were not included as these tests were not readily performed in community practice. Predictors that were found to be significant at the 0.15 significance level were included in the multivariable logistic regression using a stepwise variable selection process, to identify factors associated with early mortality. Results 1344 pts completed 18 months of follow-up (n=1111) or died (n=233) within the first 18 months of study enrollment. Of these, 801 pts were enrolled in LOT1 (median time from diagnosis to LOT1 was 1.3 yrs; IQR, 0.1-3.7 yrs). 82 of 801 pts (10.2%) died within 18 months of LOT1 initiation; 41% of pts with available clinical information who died, were defined as early-stage (Rai stage 0-1). Of 26 potential predictors evaluated, 12 were associated with early mortality among LOT1 pts at the 0.15 significance level in univariate analyses including site, race, age>75, CD-38, del(17p), ECOG PS, CCI group, RAI stage, creatinine clearance, insurance status, reasons for Tx initiation, anemia and lymphocytosis. In multivariable logistic regression analyses we identified 4 independent predictors of mortality within 18 months of LOT1 initiation (Table): pt age, CD38 expression, baseline decreased hemoglobin (as a reason for Tx initiation), and race. Conclusions In CLL pts with Rai stage 0-1, we have identified 4 factors which are associated with increased risk of death within 18 months of initiation of frontline therapy. Interestingly, neither choice of FCR vs BR chemoimmunotherapy nor the presence of del(17p)/del(11q) were predictors of early mortality. Using these results, we are currently designing a model to predict early mortality in early-stage pts. Once validated, these results may provide a framework for trials targeting the "early stage, symptomatic" CLL pts for novel interventions. Table. Multivariable Analysis: Predictors of Early Mortality Odds ratio estimate 95% CI P -value LOT1, n=781 Age ≥75 years, yes vs no 2.2 1.4-3.5 0.0012 CD38 expression, positive vs negative/not specified 1.8 1.1-2.9 0.0182 Anemia as reason for treatment, yes vs no 2.1 1.3-3.4 0.0040 Race, other vs Caucasian 1.9 1.0-3.8 0.0501 Disclosures Farber: Gilead: Speakers Bureau; Genentech: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Pharmacyclics: Honoraria, Speakers Bureau. Mato:TG Therapeutics: Research Funding; Genentech: Consultancy; AbbVie: Consultancy, Research Funding; Pronai Pharmaceuticals: Research Funding; Gilead: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Celgene Corporation: Consultancy, Research Funding; Janssen: Consultancy. Nabhan:Celgene Corporation: Honoraria, Research Funding. Kipps:Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor. Flowers:Spectrum: Research Funding; Pharmacyclics: Research Funding; Infinity Pharmaceuticals: Research Funding; OptumRx: Consultancy; Gilead Sciences: Research Funding; Spectrum: Research Funding; Genentech: Research Funding; Onyx Pharmaceuticals: Research Funding; Acerta: Research Funding; OptumRx: Consultancy; Gilead Sciences: Research Funding; AbbVie: Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Consultancy; Onyx Pharmaceuticals: Research Funding; Genentech: Research Funding; Millennium/Takeda: Research Funding; Celegene: Other: Unpaid consultant, Research Funding; Janssen: Research Funding; Infinity Pharmaceuticals: Research Funding; Acerta: Research Funding; AbbVie: Research Funding; Seattle Genetics: Consultancy; Celegene: Other: Unpaid consultant, Research Funding; Janssen: Research Funding; Millennium/Takeda: Research Funding. Kay:Pharmacyclics: Research Funding; Hospira: Research Funding; Genentech: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharma: Research Funding; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding. Lamanna:Genentech-Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Grinblatt:Celgene Corporation: Consultancy, Honoraria, Speakers Bureau. Kozloff:Celgene: Consultancy, Speakers Bureau; Genentech: Consultancy, Speakers Bureau; Roche: Consultancy, Speakers Bureau; AbbVie: Consultancy. Sullivan:Celgene Corporation: Employment, Equity Ownership. Flick:Celgene Corporation: Employment, Equity Ownership. Kiselev:Celgene Corporation: Consultancy. Bhushan:Celgene Corporation: Employment, Equity Ownership. Swern:Celgene Corporation: Employment, Equity Ownership. Sharman:TG Therapeutics, Inc.: Research Funding; Celgene Corporation: Consultancy, Research Funding; Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Research Funding; Calistoga: Honoraria; Roche: Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding.

Abstract Introduction: Ibrutinib (Imbruvica®), an oral, first-in-class covalent BTK inhibitor, is a new treatment option approved by FDA for chronic lymphocytic leukemia (CLL) patients (pts) with ≥1 prior therapy. We previously reported results from the phase III trial, in which ibrutinib (ibr) significantly improved progression-free and overall survival vs ofatumumab (ofa) in pts with relapsed/refractory CLL or small lymphocytic lymphoma (SLL) (Byrd et al. NEJM, 2014). Here, we report measures of patient well-being, including hematologic, immunologic, and quality of-life parameters, at interim analysis (IA). Methods: Pts with CLL/SLL after ≥1 prior therapy were randomized 1:1 to ibr 420 mg/day until progression or unacceptable toxicity, or to ofa for up to 24 weeks. At IA, secondary efficacy endpoints of hematologic improvement (sustained improvement ≥56 days without transfusions or growth factors) and FACiT-Fatigue (FACiT-F) outcomes were analyzed, along with exploratory endpoints assessing disease-related symptoms (DRS), serum immunoglobulin, patient-reported outcomes (PROs) by EORTC QLQ-C30, and medical resource utilization (MRU). Results: Of 391 enrolled pts (ibr n=195; ofa n=196), 63% had cytopenia(s) at baseline: 45% had anemia (hemoglobin ≤11 g/dL), 35% thrombocytopenia (platelets ≤100×109/L), and 20% neutropenia (absolute neutrophil counts [ANC] ≤1.5×109/L). On the ibr arm, 69% of pts with baseline cytopenias experienced sustained improvement in blood counts compared to 43% on ofa (P<0.0001, table). There was no decrement in serum immunoglobulins (IgA, IgG, IgM) during follow-up. IgA levels increased on the ibrutinib arm only (mean change from baseline: 41% at week 24). Immune cells CD4+ and CD8+ T-cell and NK-cell levels remained relatively stable during treatment. Mean change in FACiT-F score from baseline are shown in the figure for ibr and ofa arms. At week 24, clinically meaningful (≥3 points) improvement in FACiT-F occurred in more pts on ibr than ofa (59% vs 46%, P=0.06); clinically meaningful deterioration was reported by 14% vs 24% (P=0.08), respectively. A larger proportion of ibr vs ofa pts showed clinically meaningful improvement on EORTC-QLQ-C30 global health scores (46% vs 40%). Clinically meaningful improvement (≥10 points) from baseline to week 24 in ibr vs ofa pts was observed for fatigue (median 11 vs 0). A 50% reduction in lymph node based on IRC-assessed CT was observed in 93% (177/190 evaluable) of ibr pts compared with 17% (29/174 evaluable) of ofa pts (P< 0.0001). Splenic response based on IRC-assessed CT was reported for 85% (138/163 evaluable) of ibr pts compared with 54% (82/151 evaluable) of ofa pts. Baseline DRS were comparable between groups; however, improvement by at least 1 grade (G) post-baseline was observed in ibr relative to ofa pts for weight loss (100% vs 93%), fatigue (88% vs 72%), night sweats (95% vs 86%), and anorexia (100% vs 64%), respectively. Cumulative MRU was comparable for growth factors and transfusions, with ibr pts having longer median treatment duration: 8.6 months for ibr vs 5.3 for ofa. Hospitalizations in the first 30 days occurred in 2% ibr vs 15% ofa pts. After adjusting for treatment exposure duration, diarrhea, grade 1-2 bleeding events (e.g petechiae), and atrial fibrillation were among those noted to be more frequent on the ibrutinib arm while events such as fatigue, infusion reaction, and peripheral sensory neuropathy were seen more commonly with ofa. Major hemorrhage events were uncommon, observed in 2 patients on the ibr arm vs 3 on ofa arm without adjusting for exposure time. Exposure-adjusted analysis showed no difference in any-grade infection and a 43% relative reduction for grade 3 or higher infections for ibr. Conclusions: Ibr compared to ofa when administered to previously treated CLL/SLL pts led to improvements in hematologic function and disease burden. A survival benefit with ibr, together with sustained improvements in hematologic endpoints and PRO suggest that ibr enhances quality of life while prolonging survival. Table. Sustained hematologic improvement Parameter, n (%) ITT population Pts with cytopenias at baseline Ibr n=195 Ofa n=196 P value Ibr n=195 Ofa n=196 P value Platelets 60 (31) 19 (10) <0.0001 53/74 (72) 14/64 (22) <0.0001 ANC 52 (27) 19 (10) <0.0001 26/41 (63) 12/38 (32) 0.0047 Hemoglobin 42 (22) 32 (16) 0.1883 42/89 (47) 32/86 (37) 0.1815 Figure. Improvement in FACiT-F by treatment arm. Figure. Improvement in FACiT-F by treatment arm. Disclosures Barrientos: Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding. Brown:Sanofi, Onyx, Vertex, Novartis, Boehringer, GSK, Roche/Genentech, Emergent, Morphosys, Celgene, Janssen, Pharmacyclics, Gilead: Consultancy. Kay:Genetech: Research Funding; Pharmacyclics: Research Funding; Hospira: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees. Coutre:Janssen, Pharmacyclics: Honoraria, Research Funding. Tam:Pharmacyclics and Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Mulligan:Roche, Abbvie: Consultancy, Honoraria. Jaeger:Janssen Cilag: Honoraria. Devereux:Pharmacyclics, Janssen: Consultancy, Honoraria. Robak:Janssen: Consultancy, Research Funding. Schuh:Roche, Gilead, GSK, NAPP, Celgene: Honoraria. Bloor:GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Dearden:Roche, GSK, Gilead, Janssen, Napp: Honoraria. Jones:Pharmacyclics: Consultancy, Research Funding. Kierschniak:Pharmacyclics, GmbH: Employment. Eckert:Pharmacyclics: Employment. Suzuki:Pharmacyclics: Employment. Hsu:Pharmacyclics: Employment. James:Pharmacyclics: Employment. Byrd:Pharmacyclics: Research Funding. Hillmen:Pharmacyclics, Janssen, Gilead, Roche: Honoraria, Research Funding.

Abstract Introduction: CLL is the most prevalent leukemia in the United States (≥120,000 cases) with approximately 5000 deaths per year. The dominant cause of mortality in CLL patients is serious infection. Indeed, about 80% of CLL patients will sustain infectious complications at some point during their disease course and infection risk increases with length of the disease. Steady-state hematopoiesis in BM is required to sustain a peripheral repertoire of blood cells and maintain immune competence. There have been few studies evaluating the hematopoietic capacity of CLL BM and how it may relate to immune competence. Thus, the goal of this study was to determine the status of BM hematopoiesis in untreated and treated CLL patients. Methods and findings: The hematopoietic stem (HSC) and progenitor cell pool (HSPC) in human BM is defined by expression of CD34 and lack of surface markers (Lin-) expressed on their mature progeny. Frequencies of Lin- CD34+ progenitors in BM between age matched healthy subjects (HS) (n=22) and untreated CLL patients (n=10) were compared. We note that the Lin+ cocktail used included an antibody to CD19, eliminating dilution of CD34+ HSPC frequency due to variation in leukemic B cell infiltration. CD34+ HSPCs were significantly reduced in untreated CLL patients (6.33±3.01% vs. 2.04±2.33% in HS vs. CLL, p=0.0004). Next we evaluated total CFU responding cells within the residual CD34+ cells to determine if they were functionally compromised. Numbers of total CFU-responsive CD34+ progenitors (CFU-GM, CFU-E, and CFU-GEMM) were reduced when assayed from purified CLL patient CD34+ cells compared to HS. Thus, while HSPC are present in CLL patient BM, they are functionally compromised even after removal from the tumor microenvironment. To determine if reductions in CFUs were accompanied by decreased myeloid and erythroid lineage differentiated progeny, we evaluated frequencies and absolute numbers of CD14+ monocytes and CD71+ erythroid progenitors by flow cytometry and found both were severely reduced in CLL patient BM. To determine if the reductions in myeloid/erythroid lineage cells was due to deficiencies in their precursor HSPCs, we evaluated frequencies and absolute numbers of HSC, multipotent progenitors (MPP), and common myeloid progenitors (CMP). Proportions, but not absolute numbers, of HSC, MPP, and CMP were significantly reduced in CLL patient BM. Frequencies of CD14+ monocytes and CD71+ erythroid precursors were also significantly reduced in patients with low BM tumor burden (designated as 20-40% BM involvement), suggesting that the hematopoietic dysfunction is not solely due to tumor burden. Comparative analysis of frequencies of CD14+ monocytes in BM to frequencies of monocytes in peripheral blood revealed a strong association, suggesting that for some immune cell types the blood immune repertoire may be reflective of BM dysfunction. In addition to BM evaluation of untreated CLL patients, we also studied a cohort of post-therapy patients (n=23). Not surprisingly, we found considerable heterogeneity in the extent of BM hematopoietic reconstitution. Nevertheless, we observed robust BM hematopoiesis post therapy in a subset of treated patients (n=9 of 23). Summary: Our findings reveal BM hematopoietic dysfunction (HD) in CLL not solely due to the degree of tumor burden. Importantly, the BM HD is reversible by effective therapies. The HD is manifested by reduced numbers and function of HSPCs and production of their mature progeny. Of significance is the severe reduction in monocytic and granulocytic cells found in CLL BM. This is an important finding as these two innate cell types provide critical first responder protection against invading pathogens. Our study also uncovered that levels of blood monocytes can mirror their diminished production in BM. Future studies will focus on determining the mechanism(s) that reduce the ability of CLL BM to sustain immune cell production in addition to determining if restoration of hematopoiesis is a necessary outcome for more effective therapies. Disclosures Ding: Merck: Research Funding. Kay:Pharmacyclics: Research Funding; Tolero Pharmaceuticals: Research Funding; Acerta: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Morpho-Sys: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees.

Abstract Background Although hypogammaglobulinemia is a well-recognized complication in patients with chronic lymphocytic leukemia (CLL), its prevalence at the time of CLL diagnosis and association with novel prognostic markers and clinical outcomes are not well understood. Methods All patients seen at Mayo Clinic between 1/1995 - 4/2013 with newly diagnosed CLL (<12 months diagnosis) and who had baseline assessment of serum immunoglobulin G (IgG) were included in this analysis. Baseline demographic and clinical characteristics as well as serum IgG levels measured by either immunoassay or serum protein electrophoresis analysis were recorded. Based on the normal range for IgG at our laboratory, patients with serum IgG<757 mg/dL were classified as having hypogammaglobulinemia. Patients with IgG<757 were also further stratified by terciles (lower tercile: IgG<585 mg/dL; middle tercile: IgG 585-687 mg/dL, upper tercile: IgG 688-756 mg/dL). The relationship between hypogammaglobulinemia at diagnosis and prognostic parameters including immunoglobulin heavy chain (IGHV) gene mutation status, genetic abnormalities detected by fluorescence in-situ hybridization (FISH), and ZAP-70, CD38 and CD49d expression was assessed. Associations of hypogammaglobulinemia with time to first treatment (TTT) and overall survival (OS) was also evaluated. Results Of 1485 patients who met the eligibility criteria, 382 (26%) had hypogammaglobulinemia (median IgG=624 mg/dL) at the time of CLL diagnosis while the remaining 1103 (74%) had normal serum IgG levels (median IgG=1040 mg/dL). Baseline demographic and clinical characteristics of patients with and without hypogammaglobulinemia are shown in Table 1. When patients with hypogammaglobulinemia (IgG<757 mg/dL) were further stratified into terciles, patients in the lower tercile (n=127) were more likely to have advanced Rai stage (III-IV) at diagnosis (15% vs. 6% vs. 4%, p=0.008), be CD49d positive (56% vs. 43% vs. 32%, p=0.01), and have trisomy 12 on FISH testing (29% vs. 24% vs. 9%, p=0.005) compared to patients in the middle (n=127) and upper (n=128) terciles. After median follow-up of 4.2 years, 479 (32%) patients had received treatment for CLL, and 328 (22%) patients had died. The median TTT for patients with hypogammaglobulinemia was 3.8 years compared to 7.4 years for patients with a normal IgG (p-value<0.001). Among patients with hypogammaglobulinemia, the median TTT for patients in the lower, middle, and upper terciles were 1.7, 2.9, and 6.3 years respectively (p-value<0.001, Figure 1). On multivariable analysis that included age, gender, Rai stage, IGHV mutation status, FISH risk category and hypogammaglobulinemia, the following were independently associated with a shorter TTT: advanced (III-IV) Rai stage (hazard ratio [HR] =15.3, p<0.0001); intermediate (I-II) Rai stage (HR=3.0, p<0.0001); unmutated IGHV (HR=2.6, p=<0.0001); and hypogammaglobulinemia (HR=1.5, p=0.02). Conclusion In this large cohort study, approximately one-quarter of CLL patients had a low serum IgG level at the time of diagnosis. High-risk features, including advanced Rai stage and expression of CD49d, were associated with greater risk of hypogammaglobulinemia at the time of diagnosis. Patients with hypogammaglobulinemia at diagnosis had shorter TTT, a finding that persisted after adjusting for other prognostic factors. Evaluation of acquired hypogammaglobulinemia during the course of follow-up among patients who initially had normal IgG levels is ongoing. Disclosures: Shanafelt: Genentech: Research Funding; Glaxo-Smith-Kline: Research Funding; Cephalon: Research Funding; Hospira: Research Funding; Celgene: Research Funding; Polyphenon E International: Research Funding.

Abstract In chronic lymphocytic leukemia (CLL), it is recognized that germinal center experience by the cell-of-origin has an influence on the malignant phenotype and impacts clinical behavior. Measurement of the mutational status of the IGHV locus is a commonly used approach that subgroups patients according to this natural history. Other biomarkers correlating with these subgroups, such as ZAP70 expression and ZAP70 DNA methylation, are also used. Recently, we and others have found vast differences in global DNA methylation profiles among CLL cases that classifies distinct subgroups related to their natural history. Here we systematically evaluate various markers of natural history of the cell-of-origin for their ability to discriminate clinical outcomes. IGHV mutational status and ZAP70 expression are currently the most widely used prognostic markers of germinal center experience. These markers are generally concordant, with IGHV-unmutated associating with ZAP70 positivity. To compare their relative prognostic impact, we selected CLL cases from a large sample cohort collected as a prospective study maintained by the CLL Research Consortium that were discordant (IGHV-mutated and ZAP70(+) or IGHV-unmutated and ZAP70(-); n=192). We found a significant difference in time-to-first-treatment (TTFT; P=0.002) and overall survival (OS; P=0.032) between discordant groups, with curves separating according to IGHV as opposed to ZAP70 (Fig.1A). DNA methylation-based classification of CLL according to their natural history has not been compared to IGHV status. This classification strategy subgroups the majority of cases into low-programmed CLL (LP-CLL) or high-programmed (HP-CLL) subgroups that generally correlate with IGHV-unmutated/ZAP70(+) and IGHV-mutated/ZAP70(-), respectively, along with a minority of cases in an intermediate (IP-CLL) subgroup. We used our previously-described DNA methylation assay, based on MassARRAY interrogating 7 genomic loci including ZAP70, to group the 192 samples with discordant IGHV/ZAP70 results with 327 samples analyzed previously from the same cohort. DNA methylation (LP-CLL vs. HP-CLL) outperformed IGHV classification (unmutated vs. mutated) in terms of separating TTFT curves (n=432; LP-CLL vs. HP-CLL median difference=4.8 years, unmutated vs. mutated IGHV median difference=2.9 years) and OS curves (n=491; LP-CLL vs. HP-CLL median difference=12.9 years, unmutated vs. mutated IGHV median difference=6.8 years). To evaluate whether DNA methylation subgroups provide additional prognostic information to IGHV, we compared TTFT and OS within IGHV subtypes. We found that the ability of DNA methylation subgrouping to separate OS curves was maintained in the IGHV-unmutated subtype (P<0.001; Fig.1B) and TTFT in both IGHV-unmutated and mutated subtypes (P<0.001 and P=0.016, respectively). Conversely, IGHV subtypes did not significantly separate outcomes within DNA methylation subgroups (P>0.5 for all). Further investigation of the features of DNA methylation subgroups as defined revealed a strong bias in the frequency of several recurrent adverse prognostic somatic mutations. In particular 17p deletions and EGR2, SF3B1 and XPO1 mutations occurred frequently within the LP-CLL subgroup. We next explored whether the presence of each mutation correlated with clinical outcome within its corresponding DNA methylation subgroup, and found heterogenous results. EGR2 mutations separated TTFT in the LP-CLL subgroup (P=0.0009), but 17p, XPO1 and SF3B1 did not (P>0.3). This suggests that the cell-of-origin should be taken into account to accurately assess the clinical impact of somatic mutations. In summary, we demonstrate that among discordant cases for IGHV/ZAP70, IGHV appears to be a stronger prognostic factor for both TTFT and OS. When then evaluating the relative importance of DNA methylation subgrouping and IGHV status on TTFT and OS, we find that DNA methylation subgrouping is the more powerful prognostic factor. Among the markers of the cell-of-origin, DNA methylation is a strong tool for risk-stratifying patients and should be considered in development of risk prediction models. Figure 1. A) Kaplan-Meier analysis of TTFT of IGHV-mutated and ZAP70(+) versus IGHV-unmutated and ZAP70(-) (P=0.002, median difference=4.4 years). B) Kaplan-Meier analysis of OS in patients with unmutated IGHV separated by DNA methylation subgroup (P<0.001). Figure 1. A) Kaplan-Meier analysis of TTFT of IGHV-mutated and ZAP70(+) versus IGHV-unmutated and ZAP70(-) (P=0.002, median difference=4.4 years). B) Kaplan-Meier analysis of OS in patients with unmutated IGHV separated by DNA methylation subgroup (P<0.001). Disclosures Wierda: Acerta: Research Funding; Novartis: Research Funding; Gilead: Research Funding; Genentech: Research Funding; Abbvie: Research Funding. Brown:Infinity: Consultancy; Janssen: Consultancy; Gilead Sciences: Consultancy; Roche/Genentech: Consultancy; Celgene: Consultancy; Sun BioPharma: Consultancy; Pfizer: Consultancy; Abbvie: Consultancy. Kipps:Roche: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Gilead: Consultancy, Honoraria, Speakers Bureau; Pharmacyclics, LLC, an AbbVie Company: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding.

Abstract Introduction: Results of several large clinical trials have demonstrated inferior outcomes when CLL patients (pts) with del(17p), or to a lesser extent del(11q), are treated with chemoimmunotherapy. Despite recent advances in targeted therapies, management of unfavorable-risk CLL pts remains challenging. The Connect CLL registry is the largest prospective study describing real-world management of a diverse cohort of CLL pts. Here we describe the management of genetically unfavorable-risk CLL pts enrolled in the Connect CLL Registry, and test associations between del(17p)/del(11q) mutations and treatment choice, timing of therapy, and outcomes. Methods: Connect CLL is a longitudinal, multicenter, observational cohort study of 1,494 CLL pts enrolled between 2010-2014 at 179 community (n=1,311), 17 academic (n=155), and 3 government (n=28) sites within ≤ 2 months of initiating any line of therapy (LOT). For this study, pts were categorized into 3 risk-groups based on FISH or cytogenetic results at enrollment: unfavorable risk [either del(17p)/del(11q) positive]; favorable risk [absence of del(17p)/del(11q)]; and unknown risk (testing not performed). Analyses were stratified by LOT at enrollment (LOT1 vs LOT≥2). The risk of an EFS defining event was compared across risk-groups stratified by LOT, including only pts who had been followed for ≥ 2 years (yr) or those who had an EFS defining event (death, progression/relapse, transformation) within 2 yr, using multivariable (MV) logistic regression. Logistic regression analyses of 18 potential predictors were performed, and significant predictors (0.10 significance level) were then included in a MV logistic regression model to identify factors associated with inferior 2 yr EFS. Results: Of 1,494 pts enrolled, 225 had unfavorable risk [del(17p), n = 94; del(11q), n = 131], 621 favorable risk, and 648 unknown risk. For pts enrolled at LOT1 (n = 889), 141 had unfavorable risk, 425 favorable risk, and 323 unknown risk. Baseline characteristics for unfavorable-risk pts in LOT1 included: median age 69 yr (62% age ≥ 65 yr); 91% White; 53% Rai stage ≥ 2; 86% community sites; 0.9 yr median time from dx to LOT1; 8% family history CLL. With the exception of age, unfavorable-risk pts treated at LOT1 with FCR (median age 63) and BR (median age 74) had similar demographic characteristics. Median time from dx to LOT1 was 1.0, 1.3, and 2.0 yr for unfavorable risk, favorable, and unknown-risk pts, respectively (P < 0.001 for comparison of the 3 risk-subgroups). Reasons for initiating treatment in unfavorable-risk pts were lymphadenopathy (42%), bone marrow failure (36%), and lymphocytosis (33%) (similar across the 3 risk-subgroups). The three most common therapies for unfavorable-risk pts in LOT1 were FCR (36%), BR (21%), and FR (6%). Favorable-risk (FCR 26%, BR 24%, and R 10%) and unknown-risk pts (FCR 22%, BR 18%, and R 17%) were treated similarly in LOT1. Median time from dx to LOT≥2 was 3.5 yr in unfavorable-risk pts (vs 4.1 yr in favorable and 4.6 yr in unknown risk pts; P = 0.04 for comparison of the 3 risk-groups). For unfavorable-risk pts in LOT≥2, BR (26%), R (11%), and FCR (10%) were most commonly prescribed. At any LOT, only 10% of unfavorable-risk pts participated in a clinical trial and 4% underwent allogeneic SCT. Overall, 33% (LOT1) and 68% (LOT≥2) of pts experienced an EFS defining event within 2 yrs. Pts with unfavorable risk (vs favorable risk) had significantly worse outcomes, with a higher-risk of death/progression/relapse/transformation within 2 yr (LOT1: 42% vs 29%, respectively, P = 0.008; and LOT≥2: 80% vs 61%, P = 0.004). Unfavorable-risk pts treated with either FCR or BR at LOT1 had similar risk of an EFS defining event (odds ratio [OR] 0.9, CI 0.6-1.5). Results from MV analyses of LOT1 pts identified unfavorable risk (OR 1.9; 95% CI 1.1-3.1; P = 0.0168) and age ≥ 75 years (OR 2.6; 95% CI 1.5-4.3; P = 0.007) as independent predictors of inferior EFS at 2 yr. Conclusions: Although similar treatment approaches were used among the 3 risk-subgroups, pts with unfavorable-risk CLL had inferior outcomes at LOT1 and LOT≥2. These results, from a real-world setting, validate the findings for unfavorable risk pts from large clinical trials. These data underscore the importance of performing genetic risk stratification on all CLL pts, and support consideration of clinical trials and/or B cell receptor targeted agents for unfavorable risk CLL pts when treatment is considered. Disclosures Mato: Janssen: Consultancy; AbbVie: Consultancy, Research Funding; Genentech: Consultancy; Pronai Pharmaceuticals: Research Funding; Celgene Corporation: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Gilead: Consultancy, Research Funding; TG Therapeutics: Research Funding. Nabhan:Celgene Corporation: Honoraria, Research Funding. Flowers:Celegene: Other: Unpaid consultant, Research Funding; Celegene: Other: Unpaid consultant, Research Funding; Spectrum: Research Funding; Infinity Pharmaceuticals: Research Funding; OptumRx: Consultancy; Onyx Pharmaceuticals: Research Funding; Janssen: Research Funding; AbbVie: Research Funding; Seattle Genetics: Consultancy; Onyx Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding; Gilead Sciences: Research Funding; Genentech: Research Funding; Acerta: Research Funding; Genentech: Research Funding; Janssen: Research Funding; Millennium/Takeda: Research Funding; Infinity Pharmaceuticals: Research Funding; Spectrum: Research Funding; Millennium/Takeda: Research Funding; Pharmacyclics: Research Funding; OptumRx: Consultancy; Gilead Sciences: Research Funding; AbbVie: Research Funding; Seattle Genetics: Consultancy; Acerta: Research Funding. Kay:Pharmacyclics: Research Funding; Genentech: Research Funding; Tolero Pharma: Research Funding; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Hospira: Research Funding. Kipps:Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor; Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor. Grinblatt:Celgene Corporation: Consultancy, Honoraria, Speakers Bureau. Lamanna:Genentech-Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Kozloff:Genentech: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Roche: Consultancy, Speakers Bureau; AbbVie: Consultancy. Sullivan:Celgene Corporation: Employment, Equity Ownership. Flick:Celgene Corporation: Employment, Equity Ownership. Kiselev:Celgene Corporation: Consultancy. Bhushan:Celgene Corporation: Employment, Equity Ownership. Swern:Celgene Corporation: Employment, Equity Ownership. Sharman:Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Calistoga: Honoraria; Roche: Research Funding; TG Therapeutics, Inc.: Research Funding; Celgene Corporation: Consultancy, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Janssen: Research Funding.

Abstract Introduction Approximately 2-8% chronic lymphocytic leukemia (CLL) patients develop diffuse large B-cell lymphoma (DLBCL, so-called Richter syndrome [RS]) over long-term follow-up. The outcomes of patients with RS are variable and poorly understood. Methods CLL patients seen at Mayo Clinic from January 1995 to April 2013 who developed biopsy-proven DLBCL during follow-up were included in this analysis. Clinical characteristics, therapy and overall survival (OS) of all patients with RS were analyzed. Results One hundred and twenty patients with biopsy-proven RS were identified in the Mayo Clinic database. The median age at diagnosis of RS was 67 years (range, 29-88 years), 87 (73%) were male, and 83 (69%) had received prior CLL therapy. The median duration between diagnosis of CLL and development of RS was 3.8 years (range, 0-34.5 years). Stereotyped B-cell receptors were found in 9/30 (30%) RS patients compared to 219/1294 (17%) non-RS patients (OR=2.1, p=0.07). IGHV4-39 gene usage was present in 2/26 (8%) RS patients compared to 57/1354 (4%) non-RS patients (p=0.3). Of the 30 RS biopsy samples in which Epstein Barr virus (EBV) in-situ hybridization studies were performed, EBV was detected in 7 (23%) patients. After a median follow-up of 5.2 years, 86 (72%) patients have died. Causes of death were as follows: progressive DLBCL (n=46, 53%), progressive CLL (n=2, 2%), infection (n=8, 9%), unknown (n=20, 23%) and other (n=10, 12%). The median OS of the entire cohort was 0.9 years (95% CI, 0.5-1.3 years). Tsimberidou and colleagues proposed a prognosis score (RS score) based on the following variables at the time of RS diagnosis: Eastern Co-operative Group performance status of 2-4, lactate dehydrogenase >1.5 x normal, platelets<100 x 109/L, tumour size >5 cm and >1 prior therapy for CLL. Each parameter was assigned one point, and patients were then assigned to one of four risk groups based on their calculated RS score: 0 or 1, low risk; 2, low-intermediate risk; 3, high-intermediate risk; 4 or 5, high risk. The OS according to the RS score for our group of patients is shown in Figure 1. Median survival in the low, intermediate-1, intermediate-2 and high-risk groups were 2.4 years, 0.7 years, 0.3 years and 0.2 years, respectively (p<0.001). Fifteen (12%) patients received cyclophosphamide, doxorubicin, vincristine and prednisone (CHOP) as initial therapy for RS, and 68 (57%) received rituximab in addition to CHOP (R-CHOP). There was no difference in survival among patients who received CHOP compared to R-CHOP (median, 1.8 years. vs. 1.2 years, p=0.5). Twenty-four patients (20%) received non-CHOP-based chemotherapy, and treatment was unknown in 4 (3%) patients. Nine patients (7%) died before definitive therapy could be instituted. Thirteen (11%) patients were able to proceed to stem cell transplantation (SCT): 10 (8%) autologous SCT, 2 (2%) allogeneic SCT and 1 (1%) autologous SCT followed by an allogeneic SCT. Although RS patients who underwent SCT were younger compared to those who did not undergo SCT (median, 59 years. vs. 69 years, p=0.001), no differences in prior CLL therapy or receipt of R-CHOP therapy for DLBCL was noted between the two groups. The median survival of patients who proceeded to SCT was superior compared to those who did not (5.2 years vs. 0.7 years; p=0.005). Conclusion Stereotyped B-cell receptors but not VH4-39 had a suggested evidence of an increased risk of RS in our cohort. Although 90% RS patients received intensive chemotherapy, only 11% patients were able to proceed to SCT. Median survival of RS patients remains dismal at 1 year, and newer therapies are needed to improve outcomes. Disclosures: Shanafelt: Genentech: Research Funding; Glaxo-Smith-Kline: Research Funding; Cephalon: Research Funding; Hospira: Research Funding; Celgene: Research Funding; Polyphenon E International: Research Funding.