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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: Multiple Myeloma (MM) patients have a substantially reduced Health related Quality of Life (HQOL) at diagnosis (dx) due to disease related symptoms like bone pain (58%) and fatigue (32%). HQOL monitoring is becoming increasingly important, owing to improved survival and the impact of treatment-related toxicity. As a result HQOL assessments are increasingly being used in clinical trials, but the literature regarding the relationship between HQOL and outcomes in MM is sparse. We used the Mayo Clinic “Hematology Patient Reported Symptom Screen” (HPRSS) to assess the impact of HQOL on outcomes in newly dx patients with MM. Methods:We retrospectively reviewed charts of 453 patients with newly dx MM seen at Mayo Clinic, Rochester from 2009 to 2014. All patients who visit Mayo clinic hematology clinic complete a 3-point questionnaire (HPRSS) on pain, fatigue and quality of life (QOL) (scored on a scale of 0-10; with 0 being the least fatigue or pain and 10 being the best QOL). Pain, fatigue and QOL scores documented at the time of dx and at 6 months were collected. JMP version 10 was used for the data analysis. Results: The median age at diagnosis was 67 years (range, 33-95); 60% were male. The estimated median OS for the cohort was 21 m (95% CI19, 23); 387 (85%) of the patients were alive at last follow up and the median OS for the population was not reached. The median (IQR) scores for pain, fatigue and QOL were 4 (2, 6), 3 (1, 5), and 7 (5, 9), respectively. First, we examined the relationship between each of the scores (dichotomized at the median) and the baseline characteristics. Higher fatigue scores were associated with lower Hb and serum albumin and higher beta 2 microglobulin, LDH and marrow plasmacytosis. Higher pain scores were seen in female patients, and associated with higher B2M, serum calcium and lytic bone lesions. Lower QOL scores were associated with lower absolute lymphocyte count and serum albumin levels. Next, we examined the relationship between the scores and the OS from diagnosis. The overall survival was inferior for patients with higher pain scores, fatigue scores and lower QOL scores (Figure). In a multivariable analysis, fatigue scores were most strongly associated with survival outcome. Patients with adverse scores in two or more of pain, fatigue and QOL had significantly inferior outcomes (Figure). In univariate analysis, age, B2M, LDH, FISH high risk and the presence of two or more adverse scores were all significantly associated with poorer OS. In a multivariable analysis, age, LDH and the presence >=2 adverse scores were all associated with shorter OS. Of the 453 patients included in the study, 222 patients had pain, fatigue and QOL scores at 6 month from diagnosis. At 6 months, the median (IQR) scores for pain, fatigue and QOL were 2 (1, 5), 4 (2, 5), and 7 (5, 9), respectively; suggesting improved pain, worsened fatigue and static QOL scores. Improvement in the scores by at least one point was seen in 50%, 49% and 38% for the fatigue, pain and QOL scores. While the pain and fatigue scores at 6 months correlated inversely with OS, improvements in the scores in any of the three were not associated with any improved outcomes. Conclusion: A simple, patient reported scoring system for pain, fatigue, and overall perceived QOL at the time of diagnosis is a powerful predictor of survival outcomes in patients with newly diagnosed MM and should be considered routinely in clinical practice. The results of these patient reported measures can be utilized to develop risk-adapted trials in patients with MM. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Abstract Introduction: Monoclonal B cell lymphocytosis (MBL) is an asymptomatic expansion of clonal CD19+/CD5+ B cells with less than 5x109/L cells in the peripheral blood and without other manifestations of chronic lymphocytic leukemia (CLL). Approximately 1% of MBL evolves to CLL requiring therapy per year; thus it is critical to develop more precise tools to identify which MBL will progress to CLL and require treatment. Patients and Methods: In this study, we performed targeted deep sequencing (TDS) on 49 high-count MBL individuals (median B-cell count 3.7x109/L; range 0.8-4.9x109/L) and explored the mutation status of 20 driver genes recurrently mutated in CLL. We analyzed the clonal evolution in 45 of these 49 MBLs by screening 2-4 sequential samples (average time between samples 56 months, range 10-119 months). At last follow-up, 19 cases (39%) had progressed to Rai>0, and 10 cases (20%) required treatment. Tumor and germ line DNAs were isolated from sorted CD5+/CD19+ and CD5-/CD19- cell populations, respectively. Overall, 154 samples from 49 MBL cases (105 tumor and 49 germ line) were screened using semiconductor sequencing technology. The latter genetic information was integrated with relevant clinical and biological parameters, and we evaluated the effect of driver mutations and clonal expansion on time to CLL progression and time to treatment (TTT). Results and Discussion: Our cohort consisted in 17 women and 32 men, with a median age of 66 years (range: 44-80). Five cases presented secondary diseases, including melanoma, lung and bladder cancer. Clinical and biological parameters were collected, including IGHV mutation status (mutated 66%, unmutated 34%), ZAP70 and CD49 expression (25% each). At presentation, 46% of cases had del(13q), 27% trisomy 12, 6% del(11q), and 4% del(17p). Overall, we found somatic non-synonymous mutations in 23 of 49 MBLs (47%) at the initial time point including 22% of cases with more than one mutated driver gene. The average depth of coverage was 730x, thus allowing the identification of small subclonal mutations. Recurrent mutations were found in most of the drivers: CHD2, DDX3X (8% of cases), FBXW7, NOTCH1, SF3B1 (6% each), ATM, BCOR, BIRC3, BRAF, KRAS, MED12, MYD88 and ZMYM3 (4% each). Furthermore, ITPKB, POT1, SAMHD1 and XPO1 were mutated in only one case, whereas no mutations were found in HIST1H1E, RIPK1 and TP53. In 4 individuals, we found two mutations in the same gene (BRAF, DDX3X, KRAS and SAMHD1). Genes that are known to be associated with disease progression in CLL were either mutated with significantly lower incidence (NOTCH1, SF3B1) or not mutated (TP53). Mutations were detected on average 45 months (range 9-73) prior to progression to CLL Rai>0 indicating the early origin of most driver gene mutations in the MBL/CLL continuum. The presence of driver mutations in MBL was associated with shorter TTT (median TTT: present: 96 months vs. not present: not reached, HR: 5.52, 95% CI: 1.2-26.2, P =0.015). Next, we looked at clonal expansion of driver mutations over time (defined as >2-fold change in the allelic frequency of driver mutations between time points). Of 20 MBLs with mutations at baseline who had sequential samples available, 10 cases showed clonal expansion. Seven out of 10 MBLs who required therapy showed clonal expansion, which was detected on average 15 months (range 6-30 month) prior to treatment. Finally, the detection of clonal expansion was significantly associated with reduced TTT (median TTT: clonal expansion: 21 months vs. no clonal expansion: 84 months, HR: 7.79, 95% CI: 1.94-31.3, P <0.001). Conclusion: We have confirmed the existence of recurrent mutations in most CLL putative driver genes at the premalignant MBL stage many years before progression to CLL. Furthermore, the early identification of driver mutations and its clonal expansion predicts a shorter TTT. Of note, clonal evolution under selective pressure has recently been linked to the onset of CLL progression after therapy. In this study, we characterized the clonal dynamics in the pre-malignant stages of the disease and underlined its impact on clinical outcome. Despite the relatively small size of the cohort, these findings suggest that the sequential monitoring of MBL individuals with a simple and reliable technique, such as TDS, will be at least of prognostic use and thus its incorporation in the disease stratification and clinical management should be further tested. Disclosures Fonseca: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Applied Biosciences: Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Millennium: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Binding Site: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Onyx/Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Bayer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding. Kay:Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Tolero Pharma: Research Funding; Genentech: Research Funding; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding; Hospira: Research Funding.

Abstract Introduction. CLL primarily affects elderly individuals who frequently have comorbid health conditions. It is typically assumed non-CLL-related etiologies will be the ultimate cause of death for most CLL patients, particularly those with comorbid conditions at diagnosis. Methods. Between 9/2002 and 11/2014, 1174 patients with newly diagnosed CLL were enrolled in a prospective cohort study evaluating the natural history of CLL. Comorbidities were prospectively recorded at the time of diagnosis. Comorbidities arising during the course of disease were not considered for this analysis. Standardized longitudinal follow-up was performed in all patients every 6 months for the first 3 years after diagnosis and annually thereafter through 04/2015. Internal and external medical records, death certificates, and information from next of kin were centrally reviewed to determine cause of death, using a standardized protocol. Categorical and continuous variables were evaluated using the c2 or Fisher exact tests and the Mann-Whitney test, as appropriate. Results. Baseline characteristics at time of CLL diagnosis are shown in the Table. Over 80% of patients had 2 or more comorbidities at diagnosis (median 3, range 0-11). After a median follow up of 5 years, 224 (19%) patients have died. The cause of death could be accurately determined in 183 (82%) of these patients. The cause of death was due to CLL in 135 (74%), including 84 (46%) CLL progressions, 14 (8%) infections, and 37 (20%) other cancers. Death was due to non-CLL-related causes (such as congestive heart failure, stroke or chronic obstructive pulmonary disease) in the remaining 48 (26%) patients. On univariable analysis, age and number of comorbid health conditions were not related to whether or not the cause of death was related/unrelated to CLL. The only specific co-morbid condition at diagnosis that predicted for non-CLL related death was stroke (8% vs 1%, p=0.04). Unmutated IGHV was the only prognostic factor thatpredicted greater likelihood of CLL-related death (70% vs 50%, p=0.03). Conclusions. The majority of patients with CLL have multiple comorbidities at time of diagnosis. Despite this fact, CLL progression and/or CLL-related complications are the primary cause of death. The number and type of comorbidities at diagnosis have minimal relationship to whether or not the ultimate cause of death was CLL-related. In contrast, the CLL-specific characteristic IGHV status (but interestingly not FISH defects) correlates with cause of death. Collectively, these findings illustrate the need for more effective CLL therapy, particularly treatments that can be tolerated by patients with comorbid health conditions. It is hoped the signaling inhibitors may help address this unmet need. Table. Number (%), median [range] N=1174 Age (years) 63 [23-89] Males Females 791 (67) 383 (33) Creatinine-Clearance > (mL/min) 86 [10-252] B2M (mg/dL) 2.3 [1.1-13.2] Rai stage 0 I-II III-IV 604 (52) 512 (38) 54 (10) CD49d positive negative 277 (30) 638 (70) CD38 positive negative 332 (30) 780 (70) ZAP70 positive negative 380 (37) 650 (63) IGHV unmutated mutated 394 (44) 506 (56) FISH del13q negative +12 del11q del17p 395 (40) 175 (18) 276 (28) 90 (9) 50 (5) Comorbid health conditions Other cancers 237 (20) Stroke 38 (3) Cardiac disease 326 (28) Hypertension 472 (40) Respiratory 210 (18) Endocrinologic 165 (14) Diabetes 118 (10) Hyperlipidemia 485 (41) Rheumatologic 489 (42) Gastrointestinal 384 (33) Genitourinary 412 (35) Psychiatric 197 (17) DVT/PE 33 (3) Substance abuse 58 (5) Sexually transmitted disease 35 (3) Obesity 376 (32) # of Comorbidities 0 1 2 3 4 > 4 66 (6) 148 (13) 203 (17) 220 (19) 206 (17) 331 (28) Disclosures Kay: Hospira: Research Funding; Genentech: 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; Pharmacyclics: Research Funding; Tolero Pharma: Research Funding. Cerhan:Kite Pharma: 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

Monoclonal B cell lymphocytosis (MBL) has been shown to be the precursor condition that precedes overt diagnosis of chronic lymphocytic leukemia (CLL). Whereas CLL is classified with greater than or equal to 5 × 109/L B lymphocytes in the peripheral blood, MBL is a clonal expansion of B-cells below this threshold. MBL can be further divided into high- or low-count based on whether the B-cell count is above or below 0.5 × 109/L. Approximately 10% of the population over 40 is estimated to have MBL, increasing to >50% over the age of 90. While low-count MBL is unlikely to progress, 1-2% of high-count (HC) MBL individuals progress to CLL requiring therapy per year. It is debatable if all patients with detectable MBL should be classified as an entity requiring monitoring by a hematologist, especially for low-count MBL. In addition, the diagnosis of leukemia is distressing to patients; therefore, it is important to identify HC MBL patients that are more likely to progress to disease requiring treatment and thus should be monitored more closely. As the majority of MBL cases phenotypically resemble CLL, established prognostic markers including recurrent chromosomal aberrations, beta-2 microglobulin levels, and the mutational status of the Immunoglobulin heavy-chain variable region locus (IGHV) have been shown to predict time to treatment (TTT) and overall survival (OS) in a large retrospective study of MBL1. CLL patients can also be divided into three distinct epigenetic subtypes that reflect progressive DNA methylation changes that occurs during B cell development. These 'epitypes' termed low-programmed (LP), intermediate-programmed (IP), and high-programmed (HP) independently predict clinical outcomes irrespective of disease stage and treatment2. LP-CLL patients follow a generally unfavorable clinical course compared to the more indolent HP-CLL patients, while IP CLL patients display an intermediate outcome. Here we sought to determine if epitype forecasts progression to CLL and eventual clinical outcome for individuals with MBL. We analyzed 66 individuals diagnosed with HC MBL at the Mayo Clinic with a median follow-up of 6.3 years. Developmental epitype was determined using our novel Methylation-iPLEX technique that interrogates 34 CpGs and assigns epitype using a random forest model2. Seventy-seven percent of the MBL cases were assigned to one of the three epitypes: 42.4% HP, 19.7% IP, and 15.2% LP. The residual 23% remained unclassified due to ambiguous (low confidence) epigenetic patterns or insufficient purity (Figure 1A). The overall proportion of HP and IP epitypes in MBL were significantly greater than proportions observed in CLL cohorts (P<0.01). Epitypes remained stable over time as 20/21 cases for which we obtained a high-confidence epitype classification at multiple time points remained unchanged. Epitype significantly predicted MBL individuals progressing to treatment (P=0.001) with LP individuals progressing in a median of 5.6 years (P=0.049 and P=0.0002 versus IP and HP, respectively); median was not reached in HP or IP (Figure 1B). Epitype also predicted overall survival (OS) in MBL (P=0.04), with LP individuals having a significantly shorter OS (median of 11 years versus not reached in IP and HP; P=0.056 and P=0.048 versus IP and HP, respectively). In this study we evaluated a cohort of 66 HC MBL cases and determined that classification using developmental DNA methylation epitypes can be employed in HC MBL to aid in risk stratification. HC MBL patients classified as LP are more likely to progress to requiring treatment and have a significantly reduced OS. The epigenetic classification may help clinicians decide how closely and frequently a HC MBL individual needs to be monitored. Figure 1: (A) Breakdown of the epigenetic subtype assigned to 66 HC MBL samples. (B) Kaplan-Meier analysis of time to treatment and (C) overall survival of MBL patients separated by epitype. 1. Parikh, S. A. et al. Outcomes of a large cohort of individuals with clinically ascertained high-count monoclonal B-cell lymphocytosis. Haematologica103, e237-e240 (2018). 2. Giacopelli, B. et al. Developmental subtypes assessed by DNA methylation-iPLEX forecast the natural history of chronic lymphocytic leukemia. Blood blood.2019000490 (2019). doi:10.1182/blood.2019000490 Disclosures Byrd: Ohio State University: Patents & Royalties: OSU-2S; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; Genentech: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding. Shanafelt:Patent: Patents & Royalties: US14/292,075 on green tea extract epigallocatechin gallate in combination with chemotherapy for chronic lymphocytic leukemia; Merck: Research Funding; Polyphenon E International: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding; Hospira: Research Funding; Glaxo-SmithKline: Research Funding; Abbvie: Research Funding; Cephalon: Research Funding; Celgene: Research Funding. Parikh:Genentech: Honoraria; Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding; Ascentage Pharma: Research Funding. Kay:Agios: Other: DSMB; MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board.

Abstract Introduction: Several prognostic models for overall survival (OS) in chronic lymphocytic leukemia (CLL) have been developed, but none were derived for patients (pts) with relapsed or refractory (R/R) CLL treated in the era of novel agents. We used a comprehensive approach to derive and validate a novel risk model for OS in 2,475 pts with R/R CLL who received therapy in randomized phase 3 trials evaluating ibrutinib (IBR), idelalisib (IDELA), and venetoclax (VEN) vs control arms, or the Mayo Clinic CLL Database (MCCD). Methods: In collaboration with Janssen, Gilead, Pharmacyclics, and Genentech/Roche, the analysis included 2,475 pts from 6 multicenter randomized phase 3 trials or the MCCD. Trials included were: IBR plus bendamustine-rituximab (BR) vs placebo plus BR (HELIOS: NCT01611090), IBR vs ofatumumab (RESONATE: NCT01578707), IDELA plus BR vs placebo plus BR (Study 115: NCT01569295); IDELA plus rituximab vs placebo plus rituximab (Study 116: NCT01539512); IDELA plus ofatumumab vs ofatumumab (Study 119: NCT01659021); VEN plus rituximab vs BR (MURANO: NCT02005471). All pts had R/R CLL and required treatment by iwCLL criteria. The model-building dataset (n=969) included pts from HELIOS and RESONATE, and was randomly assigned to the IBR/chemoimmunotherapy (CIT) training dataset (n=727) and IBR/CIT internal-validation dataset(n=242). Three independent external validation datasets included IDELA/CIT (n=897), VEN/CIT (n=389), and MCCD (n=220). We applied univariate and multivariate analyses (MVA) to 28 candidate clinical/laboratory and genetic prognostic factors to derive the risk model in the training dataset. The primary endpoint was OS. We assessed the need for separate models for targeted agents by interactions with treatment in univariate analyses. We proceeded to develop a single model for all pts with R/R CLL, as only one candidate factor (del(13q), interaction p value <0.1) demonstrated a marginal differential effect. We evaluated cutoffs for dichotomized covariates and for definition of risk groups after the final factors were selected. We fit a Cox regression on the training and internal/external validation datasets using the risk categories as the covariate to test the difference among the groups, and calculated the C-statistic as a measure of discrimination. Results: Of 11 selected factors with a significant univariate effect on OS (p<0.1), 6 were independently prognostic in the MVA of OS (p<0.05): Baseline β2-microglobubulin (B2M), lactate dehydrogenase (LDH), hemoglobin (HGB), IGHV mutational status, number of prior therapies, and time from initiation of last therapy. We excluded number of prior therapies from the model, reasoning that its optimal cutoff might change with advances in CLL therapies. IGHV did not remain significant (p=0.0592) in MVA of 5 remaining prognostic factors. Notably, del(17p) was not independently prognostic for OS. The final risk model consisted of 4 prognostic factors: B2M ≥5 mg/L, LDH elevated, HGB <110 mg/L for women or <120 mg/L for men, and time from initiation of last therapy <24 months. Because hazard ratios for each factor were similar (range, 0.55-0.68) with overlapping confidence intervals, 1 point was assigned to each factor. The resulting score separated pts into low (score 0-1), intermediate (score 2-3), and high risk (score 4) groups. Our risk model was prognostic for OS in the IBR/CIT training dataset (C-statistic 0.74 [95% CI 0.60-0.85]; log-rank p<0.0001) and was validated in the IBR/CIT internal validation (C-statistic 0.79 [95% CI 0.56-0.97]; log-rank p<0.0001), as well as in all 3 external validations: IDELA/CIT dataset (CS=0.71, 95% CI 0.59-0.81; log-rank p<0.001); VEN/CIT dataset (CS=0.76, 95% CI 0.66-0.85; log-rank p=0.01); MCCD (CS=0.61, 95% CI 0.56-0.66; log-rank p<0.001). Conclusions: We present the first validated risk model for OS in R/R CLL in the era of targeted therapies. Our model consists of 4 readily available factors (B2M ≥5 mg/L, LDH elevated, HGB <110 mg/L for women or <120 mg/L for men, and time from initiation of last therapy <24 months), identifies 3 prognostic groups with significantly different OS, and has been validated for pts treated with all FDA approved targeted therapies: IBR, IDELA, and VEN. This identifies a well-defined cohort of pts with R/R disease with an unmet clinical need who are suitable for prospective trials targeting these pts. An exploratory analysis regarding prediction of MRD is ongoing. Figure. Figure. Disclosures Darif: Jannsen: Employment. Londhe:Jannsen: Employment. Xing:Gilead Sciences, Inc.: Employment. Mun:Genentech: Employment, Equity Ownership. Kay:Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees. Shanafelt:Mayo Clinic: Patents & Royalties: Physician Well-being Index, Medical Student Well-being Index, Well-being index; GlaxoSmithKline: Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Janssen: Research Funding; Abbvie: Research Funding; Celgene: Research Funding. Furman:Loxo Oncology: Consultancy; Pharmacyclics LLC, an AbbVie Company: Consultancy; Sunesis: Consultancy; TG Therapeutics: Consultancy; Verastem: Consultancy; Gilead: Consultancy; Incyte: Consultancy, Other: DSMB; Acerta: Consultancy, Research Funding; Genentech: Consultancy; Janssen: Consultancy; AbbVie: Consultancy. Hillmen:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Pharmacyclics: Research Funding; Alexion Pharmaceuticals, Inc: Consultancy, Honoraria; Novartis: Research Funding; Gilead Sciences, Inc.: Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees. Sharman:Acerta: Consultancy, Research Funding; Pharmacyclics, an AbbVie Company: Consultancy, Research Funding. Seymour:AbbVie: Consultancy, Honoraria, Research Funding; Celgene: Consultancy; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding. Jones:Celgene: Employment, Equity Ownership. Ferrante:Jannsen: Employment. Dreiling:Gilead: Employment. Mobasher:F. Hoffmann-La Roche Ltd: Other: Ownership interests non-PLC; Genentech Inc: Employment. Stark:Genentech: Employment. Reddy:Actinium Pharmaceuticals: Employment, Equity Ownership; Pharmacyclics: Employment. Howes:Janssen: Employment. James:Pharmacyclics: Employment. Bhargava:Gilead: Employment. Zelenetz:Novartis/Sandoz: Consultancy; Abbvie: Research Funding; Celgene: Consultancy; Amgen: Consultancy; Gilead: Consultancy, Research Funding; AstraZeneca: Consultancy; Genentech/Roche: Consultancy, Research Funding.

Abstract The targeted therapy ibrutinib inhibits B cell receptor signaling (BTK inhibitor) and has yielded high response rates and durable remissions in patients with chronic lymphocytic leukemia (CLL). However, it is widely believed that the addition of immune therapies to targeted drugs will be required to activate anti-tumor immunity and work towards curative therapy. Identifying effective combinations of targeted drugs and/or standard chemotherapy with immunotherapy is a priority research area and particularly relevant for CLL, as patients' T cells have been shown to exhibit profound tolerance/exhaustion and notably, no activity was reported in a recent trial of anti-PD-1 immunotherapy for relapsed disease. Ibrutinib has shown beneficial immunomodulatory activity in CLL by inhibiting IL-2-inducible T cell kinase (ITK) as well BTK that is associated with increased effector CD4+and CD8+ T cell numbers and decreased expression of inhibitory checkpoint receptors such as PD-1 on patient T cells. Here we have performed comparative immune bioassays from a randomized phase III trial comparing ibrutinib-based therapy to traditional FCR chemoimmunotherapy to assess the effects of treatments on anti-tumor T cell function. Viable peripheral blood mononuclear cell samples were collected serially (baseline, 6 months and 12 months) from CLL patients on the randomized phase III E1912 trial of ibrutinib and rituximab versus FCR for previously untreated disease to allow longitudinal batched immune analysis. Cytotoxicity assays revealed that highly purified CD3+ T cells from the FCR treated patients at 6 and 12-month time-points did not change their activated killing function against autologous baseline CD19+ CLL tumor B cells (acting as target antigen-presenting cells pulsed with superantigen, sAg) compared to pre-treatment/baseline exhausted T cells (n=22). In contrast, patients treated with ibrutinib-based therapy had a significant increase in activated anti-tumor T cell killing function (P<.01, n=22) at both 6-month (66% increase) and 12-month (89% increase) time-points. Flow cytometric analysis of circulating immune subsets revealed that the percentage of PD-1 and PD-L1 positive cells among CD8+ and CD4+ T cells (particularly effector compartments) were reduced with ibrutinib-based therapy, whereas only a partial reduction was detected following FCR treatment. However, patients' T cells from both treatment arms responded normally to T cell receptor engagement by upregulating these checkpoint molecules. This led us to explore ex vivo treatment of highly purified CD3+ T cells and CD19+ CLL B cells from both treatment arms with anti-PD-L1 or anti-PD-1 immunotherapy prior to cytotoxicity assays. Our functional data revealed that the T cells from both FCR time-points (6 and 12-months) were not sensitive to either anti-PD-L1 (n=14) or anti-PD-1 (n=14) treatment. In contrast, ibrutinib-based treatment sensitized anti-tumor T function (23% increase in killing) following anti-PD-L1 treatment (n=14) at the 6-month time-point only (P<.01) but not with anti-PD-1. To investigate the mechanism underlying these effector function differences, we compared the ability of highly purified CD3+ T cells from each treatment arm (n=45) time-point to form F-actin immunological synapses with baseline autologous CLL tumor B cells. Quantitative confocal image analysis revealed that ibrutinib-based therapy significantly (P<.01) enhanced polarization of F-actin, tyrosine-phosphorylated proteins and granzyme B at immune synapses with tumor cells at both 6 and 12-month time-points, whereas FCR treated patient T cells failed to mobilize these lytic synapse molecules. Importantly, our assays have revealed that T cells from both FCR treatment time-points formed "non-polarized" immune synapses with tumor cells, in keeping with cytotoxic dysfunction and insensitivity to additional checkpoint immunotherapy. In contrast, our functional correlative bioassays have revealed that ibrutinib-based therapy can reactivate exhausted cytolytic T cell function and suggest to us, a potential therapeutic window for anti-PD-L1 immunotherapy at the earlier 6-month time-point. We believe this data supports the concept of incorporating functional bioassays to immune-monitoring assays associated to clinical trials that should aid knowledge-led design of future combination immunotherapy. Disclosures Kay: Janssen: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding. Shanafelt:Pharmacyclics: Research Funding; Genentech: Research Funding; GlaxoSmithKline: Research Funding; Jansen: Research Funding. Ramsay:Celgene Corporation: Research Funding; Roche Glycart AG: Research Funding; MedImmune: Research Funding.