Kay, Neil E.

7015 Background: Besides clinical staging, a number of biomarkers predicting OS in CLL have been identified. The multiplicity of markers, limited information on their independent value, and a lack of understanding of how to interpret discordant markers are major barriers to use in routine clinical practice. We developed an integrated prognostic index using the database of the German CLL Study Group (GCLLSG), which was subsequently validated in a cohort of untreated CLL patients (pts) from the Mayo Clinic. Methods: The analysis was based on a dataset collected between 1997 and 2006 in 3 GCLLSG phase III trials. The external validation was performed on a series of newly diagnosed CLL pts managed at Mayo Clinic. Results: The GCLLSG dataset (1,948 physically fit pts at early and advanced stage; median age: 60 yr (range 30-81); median observation time 63.4 mo) was used as a training dataset. 7 parameters were identified as independent predictors for OS: sex, age, ECOG status, del 17p, del 11q, IGHV mutation status, thymidine kinase and β2-microglobulin. By using a weighted grading a prognostic index was derived separating four different pts groups: low risk (score 0 - 2), intermediate risk (score 3-5), high risk (score 6-10) and very high risk (score 11-14) with significant different OS rates (95.2%, 86.9%, 67.7% and 18.7% OS after 5 yr for the low, intermediate, high and very high risk group respectively (p<0.001). This prognostic index was validated in a cohort of 676 newly diagnosed, untreated pts from the Mayo Clinic (median age 61.5 yr (range 32 - 89); median observation time 47.0 mo). The 4 risk groups were reproduced with 98.3%, 95.4%, 75.4% and 10.8% OS after 5 yr. The prognostic index predicts OS independent of Rai/Binet stage and provides accurate estimations regarding time to first treatment (TTF). C-statistic is 0.75. Conclusions: Using a multi-step process including external validation, we developed a comprehensive prognostic index combining clinical, serum, and molecular information into a single risk score for pts with untreated CLL. The prognostic index provides more accurate prediction of both TTF and OS. To our knowledge it is the first prognostic model in CLL to reach the C-statistic threshold (c > 0.70) necessary to have utility at the level of the individual.

TPS8619 Background: Chemoimmunotherapy (CIT) treatment approaches such as FCR have markedly improved outcomes for CLL pts when administered as initial or second-line therapy. Despite this progress, virtually all pts relapse and effective salvage regimens that induce durable remissions or can be administered safely to elderly pts or those with comorbidities are lacking. BTK, an essential mediator of B-cell receptor signaling, is a novel target in CLL. Ibrutinib, a first-in class inhibitor of BTK, promotes apoptosis and inhibits proliferation, migration and adhesion in CLL cells. Phase II data of ibrutinib monotherapy in RR CLL demonstrated an estimated PFS and OS of 75% and 83% respectively at 26 months (Byrd Abst #189 ASH 2012). These findings confirmed BTK as an important target in CLL and supported initiation of a pivotal phase III study in pts with RR CLL/SLL. Methods: PCYC-1112-CA is an ongoing international Phase 3 randomized controlled study of ibrutinib versus ofatumumab for treatment of pts with RR CLL/SLL. The study is enrolling 350 planned pts in 9 countries. Pts are randomized 1:1 to receive ibrutinib 420 mg orally once daily or ofatumumab per the package insert at 300 mg for the first dose, then 2000 mg for a total of 12 doses over 24 weeks. Pts are stratified based on del 17p and disease refractory to purine analogs. Key inclusion criteria include RR CLL/SLL with >= 1 prior line of therapy including pts who experienced a short remission duration to purine analog based CIT, pts who are older or have comorbidities, and pts with del 17p. Pts must have active disease meeting criterion for requiring therapy and measurable nodal disease by CT. Key exclusion criteria include Richter’s transformation, stem cell transplantation within 6 months, GVHD or immunosuppression, platelet count <30,000 cells/ul or use of warfarin The primary objective of the study is PFS evaluated by an IRC. Other outcomes include ORR, OS, hematologic improvement, and safety. An independent DMC is monitoring the study. Clinical trial information: NCT01744691.

6122 Background: Clinicians and investigators commonly use ECOG PS and clinician-reported patient (pt) fatigue as surrogates for HRQOL, a multi-faceted construct that comprehensively looks at the pt perspective on disease and well-being. Because limited data exist on the relationships between PS, fatigue, and HRQOL for CLL pts, we examined the associations between these measures, and 3 validated HRQOL instruments: the Functional Assessment of Cancer Therapy-Leukemia (FACT-Leu), EQ-5D, and Brief Fatigue Inventory (BFI). Methods: Data were collected in CONNECT CLL, a prospective US observational registry initiated in 2010. Patient demographics and clinical characteristics were provided by clinicians. Patient HRQOL was self-reported at enrollment using the FACT-Leu, EQ-5D, and BFI. Scores were analyzed by ECOG PS (0, 1, 2-4) and clinician-reported fatigue (yes, no). Differences in HRQOL scores were assessed by ANOVA. Results: HRQOL data were reported by 899 pts from 148 community, 10 academic, and 3 government centers. ECOG PS was available on 711 pts. Overall HRQOL, measured by mean FACT-Leu, FACT-G and EQ-5D Visual Analogue Scale (VAS), worsened with ECOG PS severity and was worse in pts with fatigue (all p<0.0001). All FACT-Leu domains except social/family were worse in pts with fatigue and those with higher ECOG PS. Mean EQ-5D pain/discomfort, mobility, self care and usual activities domain scores worsened in severity as ECOG worsened and for pts with fatigue (all p<0.011). BFI data indicated that global fatigue, fatigue severity and fatigue-related interference worsened by ECOG severity and were associated with clinician-reported fatigue (all p<0.0001). Conclusions: Initial CONNECT CLL results confirm that HRQOL worsens with worsening ECOG PS and was worse among pts with fatigue, especially in physical/functioning domains, pain/discomfort, and mobility. These results indicate that baseline ECOG PS and physician-rated fatigue are rapid assessments that predict robust measures of HRQOL. Future analyses are planned to examine how HRQOL, ECOG PS and fatigue change over time with changes in treatment and CLL disease status.

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

Cellular immunotherapy is a rapidly progressing field in multiple myeloma (MM). Multiple clinical trials have reported impressive efficacy of B cell maturation antigen (BCMA) directed chimeric antigen receptor cell therapy (BCMA CART) in MM. While trials demonstrated an overall response rate of 70-90% in patients with relapsed/refractory MM, the durable response rate is around 30%. Most patients lose their CART cells and the disease relapses within the first year, suggesting an inhibition by the MM tumor microenvironment (TME). Therefore strategies to overcome this inhibition would represent a major advance in CART cell therapy for MM. Cancer associated fibroblasts (CAFs) within the TME play a critical role in promoting tumor growth and in the generation of an immunosuppressive microenvironment. We hypothesized that CAFs from bone marrows of patients with MM (MM-CAFs) inhibit BCMA CART cells and contribute to their failure and that targeting both the malignant plasma cells and CAFs can overcome this resistance. To test this hypothesis, we isolated MM-CAFs and studied their interaction with BCMA CART cells generated from normal donors (41BB costimulated, lentivirally transduced). Our initial findings suggest that MM-CAFs inhibit BCMA CART cell antigen specific proliferation in the presence of the BCMA+ MM cell line OPM2, and this inhibition is predominantly mediated through the secretion of TGF-β (Fig A). MM-CAFs also promoted MM tumor growth in an MM-TME xenograft model established in the laboratory (Fig B). Here, immunocompromised NOD-SCID-γ-/- (NSG) mice were engrafted with 1x106 luciferase+ BCMA+ OPM2, in combination with either 1x106 CAFs or vehicle control intraveneously (IV). Subsequent tumor burden was monitored by bioluminescent imaging of these mice. The presence of CAFs in this model significantly accelerated MM progression (Fig B). Based on these findings, we aimed to develop CART cell therapy targeting both malignant MM cells and their CAFs and to determine whether this strategy can reverse MM-CAF induced CART cell inhibition. To identify targets for these CART cells, we first verified the expression of Fibroblast Associated Protein (FAP), an established CAF target, on MM-CAFs. Flow cytometric analysis of MM-CAFs showed significantly higher expression of FAP, compared to fibroblasts derived from normal bone marrow (Fig C). In addition, our screening flow cytometric analysis identified CS1 as another protein overexpressed by MM-CAFs (Fig C). We therefore designed and generated FAP CART cells (41BB costimulated, lentivirally transduced) and CS1 CART cells (CD28 costimulated, lentivirally transduced). We also generated dual CART cells for both BCMA-FAP CART cells and BCMA-CS1 CART cells. These dual CART cells were generated through the dual transduction of two lentiviral vectors during CART manufacturing. Next, we evaluated the impact of CAFs on effector functions of BCMA CART cells compared to dual targeting CART cells. When CART cells were stimulated with the BCMA+ MM cell line MM1S, in the presence of MM-CAFs, the antigen specific proliferation of BCMA CART cells, but not the dual targeting CART cells was significantly inhibited (Fig A). Similarly, in the presence of MM-CAFs, production of key effector cytokines by BCMA CART cells, but not the dual CART cells was reduced (Fig D). Finally, to verify the significance of our laboratory findings, we investigated the impact of CAFs on CART cell functions in vivo. First, using OPM2 xenografts, treatment with BCMA CART cells were able to completely eradicate MM (Fig E). However, to determine the effect of targeting CAFs, we used our MM-TME model. Here, NSG mice were engrafted with the luciferase+ MM cell line OPM2, along with MM-CAFs, as described in Fig 1B. Mice were then imaged for engraftment and randomized to treatment with 1) untransduced control T cells, 2) BCMA CART cells, 3) BCMA-FAP CART cells, or 4) BCMA-CS1 CART cells. A lower dose (1x106 IV) of CART cell was used to induce relapse post BCMA CART cells. Treatment with BCMA CART cells led to a transient antitumor activity in this MM-TME model (mice died within 2 weeks), while dual targeting CART cells resulted in durable remissions and long term survival of these mice (Fig F). In summary, we demonstrate for the first time that dual targeting both malignant plasma cells and the CAFs within the TME is a novel strategy to overcome resistance to CART cell therapy in multiple myeloma. Figure Disclosures Sakemura: Humanigen: Patents & Royalties. Cox:Humanigen: Patents & Royalties. Parikh:Janssen: Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; AstraZeneca: Honoraria, Research Funding. Kay:Celgene: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; MorphoSys: Other: Data Safety Monitoring Board; Agios: Other: DSMB. Kenderian:Lentigen: Research Funding; Kite/Gilead: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Tolero: Research Funding; Novartis: Patents & Royalties, Research Funding; Morphosys: Research Funding.

Background The CLL international prognostic index (CLL-IPI) is a validated staging system for newly diagnosed CLL patients that combines age, clinical stage, serum Beta-2 microglobulin, TP53, and IGHV mutation status into a single score and stratifies CLL patients into four prognostic risk groups with a c-statistic=0.72. Next-generation sequencing identified ~60 putative driver genes recurrently mutated in CLL, and genome-wide association studies (GWAS) identified 41 single nucleotide polymorphisms (SNPs) associated with CLL risk. We previously showed that a polygenic risk score (PRS) of the weighted average of the number of risk alleles among these 41 SNPs is associated with risk of both CLL and MBL. We and others have also shown that the tumor mutational load (TML), i.e., the total number of somatically mutated driver genes, is associated with time to first treatment (TTT). Herein, we examine whether TML and PRS add prognostic value beyond CLL-IPI for disease progression in a cohort of CLL and high-count MBLs. Methods We used the Mayo Clinic CLL resource to identify newly diagnosed (&lt;2 years) previously untreated CLL and high-count MBL patients based on the 2008 International Workshop CLL (IWCLL) criteria . We extracted DNA from CD5+/CD19+ clonal B-cells and sequenced the coding regions of 59 recurrently mutated CLL driver genes using a custom SureSelect panel and Illumina HiSeq 4000. The median coverage depth per sample was 2737X. Somatic mutations were called using MuTect2 in tumor-only mode. Germline variants were eliminated based on minor allele frequencies &gt;0.01%, and by those identified in 1000 Genomes Project, ExAC and/or ESP6500 databases, unless present in known mutation hotspots or COSMIC. After filtering high/moderate impact mutations, we calculated the TML. Peripheral blood DNA was genotyped on Illumina Omni Express array; after extensive quality control metrics, we calculated the germline PRS as the weighted average of the number of risk alleles among the CLL susceptibility SNPs. Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) to test for associations with TTT. We analyzed the low/intermediate risk groups and the high/very high risk groups in stratified analyses and tested for interactions between CLL-IPI and TML or PRS. Survival curves are displayed using the Kaplan-Meier method using P-values from the log-rank test; the PRS is displayed by tertile categories. Results Of 166 patients (120 CLL, 46 MBL), 67% were male and the median age at diagnosis was 62 years (range: 28-85). The median follow-up was 5.3 years, and 73 were treated for progressive disease as defined by the 2018 IWCLL criteria. Low risk CLL-IPI comprised 51%, intermediate risk 27%, high risk 18%, and very-high risk 4%. The most commonly somatically mutated genes were TP53 (8%), CHD2 (8%), BIRC3 (8%), SF3B1 (7%), and NOTCH1 (7%). We found that 42%, 32%, and 26% of patients had 0, 1, or 2+ genes with somatic mutations, respectively. The median PRS was 8.3 (range: 6.1-11.3) which is consistent with our prior PRS study on CLL/MBL and higher than 7.53 found in 7983 controls from our prior work. When we modeled TML, PRS, sex, CLL/MBL status and CLL-IPI together with the joint effects of CLL-IPI with TML and PRS, both interactions were significant in the model (P=0.008 for TML*CLL-IPI and P=0.014 for PRS*CLL-IPI), with c-statistic=0.81 (CI:0.77-0.85). When we stratified by CLL-IPI, TML was associated with shorter TTT in the low/intermediate risk (N=129, continuous HR=2.36 per TML category, CI: 1.61-3.47, P=1.3x10-5, Figure 1.A), but there was no evidence of an association in the high/very-high risk (N=37, continuous HR=1.12 per TML category, CI: 0.70-1. 78, P=0.64, Figure 1.B), after adjusting for PRS, sex, and CLL/MBL status. However, the PRS was associated with a shorter TTT in the high/very-high risk (continuous HR=1.77 per SD, CI: 1.00-3.12, P=0.048, Figure 1.D), with no evidence of an association in the low/intermediate risk (continuous HR=0.95 per SD, CI: 0.95-1.29, P=0.74, Figure 1.C), after adjusting for TML, sex, and CLL/MBL status. Conclusions In our study, TML was prognostic among the low/intermediate CLL-IPI risk groups while the PRS was prognostic among the high/very-high CLL-IPI risk groups. Sequencing CLL driver genes and genotyping relevant germline SNPs at time of diagnosis may provide incremental value over the CLL-IPI in predicting TTT among patients with CLL/MBL. Disclosures Parikh: MorphoSys: Research Funding; Genentech: Honoraria; AbbVie: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; Janssen: Research Funding; Ascentage Pharma: Research Funding; Acerta Pharma: Research Funding. Ding:Merck: Research Funding; DTRM Biopharma: Research Funding. Cerhan:Celgene: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding. Kay:MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Agios: Other: DSMB.

Treatment with CD19-directed chimeric antigen receptor T cell (CART19) therapy has resulted in unprecedented clinical outcomes and was FDA-approved in acute lymphoblastic leukemia and non-Hodgkin B-cell lymphoma. However, its success in chronic lymphocytic leukemia (CLL) has been modest to date. An increasing body of evidence indicates that impaired CART cell fitness is the predominant mechanism of the relative dysfunction in CLL. The immunosuppressive microenvironment in CLL is well known and in part may be related to the abundance of circulating extracellular vesicles (EVs) bearing immunomodulatory properties. We hypothesized that CLL-derived EVs contribute to CART cell dysfunction. In this study, we aimed to investigate the interaction between circulating EVs isolated from CLL patient plasma (designated as CLL-derived EVs) and CART19 cells. We enumerated and immunophenotyped circulating EVs from platelet free plasma in untreated patients with CLL. We determined their interaction with CART19 cells using second generation, 41BB co-stimulated, lentiviral transduced CART19 cells generated in the laboratory from normal donors (FMC63-41BBζ CART cells). Our findings indicate that CLL-derived EVs impair normal donor CART19 antigen-specific proliferation against the CD19+ mantle cell lymphoma cell line Jeko-1 (Figure 1A). Next, we characterized CLL-derived EVs using nanoscale flow cytometric analysis of surface proteins and compared to healthy controls. Although the total EV particle count was not different between CLL and healthy controls (Figure 1B), there were significantly higher PD-L1+ EVs in patients with CLL (Figure 1C). Based on these results, we sought to assess the physical interaction between CLL-derived EVs and CART cells from normal individuals. When CLL-derived EVs were co-cultured with CART19 and CLL B cells and imaged with super-resolution microscopy, EVs were localized at the T cell-tumor junction (Figure 1D). Furthermore, CLL-derived EVs are captured by T cells as indicated by a significant reduction in the absolute count of EVs when co-cultured with resting T cells (Figure 1E). Having demonstrated that 1) there is an excess of PD-L1+ EVs in patients with CLL (Figure 1C) and 2) CLL-derived EVs physically interact with CART cells (Figures 1D-E), we sought to establish their functional impact on CART19 cells. Here, CART19 cells were stimulated with irradiated CD19+ JeKo-1 cells at a 1:1 ratio in the presence of increasing concentrations of CLL-derived EVs. There was a significant upregulation of inhibitory receptors such as PD-1 and CTLA-4 on the T cells (Figure 1F). This is associated with a reduction in CART effector cytokines (i.e., TNFβ) at higher concentrations of EVs (Figure 1G), suggesting a state of exhaustion in activated CART19 cells in the presence of CLL-derived EVs. This was further supported by transcriptome interrogation of CART19 cells. Here, CART19 cells were stimulated via 24-hour co-culture with the irradiated CD19+ cell line JeKo-1, in the presence of CLL-derived EVs at ratios of 10:1 and 1:1 EV:CART19 and then isolated by magnetic sorting. RNA sequencing of these activated CART19 cells indicated a significant upregulation of AP-1 (FOS-JUN) and YY1 (Figures 1H), known critical pathways in inducing T cell exhaustion. Finally, to confirm the impact of CLL-derived EVs on CART19 functions in vivo, we used our xenograft model for relapsed mantle cell lymphoma. Here, immunocompromised NOD-SCID-ɣ-/- mice were engrafted with the CD19+ luciferase+ cell line JeKo-1 (1x106 cells I.V. via tail vein injection). Engraftment was confirmed through bioluminescent imaging and mice were randomized to treatment with 1) untreated, 2) CART19 cells, or 3) CART19 cells co-cultured ex vivo with CLL-derived EVs for six hours prior to injection. A single low dose of CAR19 (2.5x105) was injected, to induce relapse. Treatment with CART19 cells that were co-cultured ex vivo with CLL-derived EVs resulted in reduced anti-tumor activity compared to treatment with CART19 alone (Figure 1I). Our results indicate that CLL-derived EVs induce significant CART19 cell dysfunction in vitro and in vivo, through a direct interaction with CART cells resulting in a downstream alteration of their exhaustion pathways. These studies illuminate a novel way through which circulating and potentially systemic EVs can lead to CART cell dysfunction in CLL patients. Disclosures Cox: Humanigen: Patents & Royalties. Sakemura:Humanigen: Patents & Royalties. Parikh:Ascentage Pharma: Research Funding; Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Genentech: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding. Kay:Agios: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; MorphoSys: Other: Data Safety Monitoring Board. Kenderian:Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding.

Despite the success of chimeric antigen receptor T (CART) cell therapy, it is limited by 1) lower rates of durable responses related to inadequate CART cell expansion and trafficking to tumor sites and 2) development of life-threatening complication such as cytokine release syndrome (CRS). Development of a strategy to efficiently and robustly image and track CART cells in the clinic would allow the in vivo characterization of T cell expansion and trafficking to tumor sites as well as the development of strategies to potentially overcome these limitations. The sodium iodide symporter (NIS) is a characterized and sensitive reporter system that has been used for cell imaging in the clinic. We hypothesized that the incorporation of NIS into CART cells would be a sensitive and efficient way to assess CART cell expansion, trafficking, and toxicity. To test our hypothesis, we used two CART cell constructs that are characterized in preclinical models and studied extensively in the clinic: CART19 (41BB costimulated) and BCMA-CART cells (41BB costimulated). First, we generated NIS+CART19 and NIS+BCMA-CART cells through dual transduction of lentiviral vectors (Fig A) and revealed the exclusive 125I uptake by these NIS+CARTs and its inhibition by the NIS inhibitor KClO4in vitro (Fig B). We then analyzed T cell functions of NIS+CART cells. Here, NIS+CART19 or CART19 cells were cultured with the CD19+ acute lymphoblastic leukemia (ALL) cell line NALM6. There was no difference in CART cell cytotoxicity (Fig C), proliferation, or cytokine production (not shown) between NIS+CART19 and CART19. This indicates that the incorporation of NIS into CART cells does not impair their antitumor activity. Next, we evaluated the sensitivity of NIS+CART19 cell detection by TFB-PET in vivo; imaging was performed using an Inveon TFB-PET/CT scanner. Mice received 250 μCi 18F-TFB 45 minutes prior to image acquisition. NIS+CART cells were detectable with TFB-PET when cells were subcutaneously injected at a dose of 1.25x106 cells (Fig D). Having demonstrated that the incorporation of NIS in CART cells provides a sensitive way of their detection by TFB-PET and does not interfere with their effector functions, we tested its efficiency to assess CART cell trafficking in vivo, using multiple myeloma (MM) xenografts. Here, immunocompromised NOD-SCID-ɣ-/- (NSG) mice were engrafted with the BCMA+OPM2 MM cell line (1x106 IV). After engraftment, the tumor burden was assessed by bioluminescence imaging (BLI) and mice were randomized to receive 1) BCMA-CART or 2) NIS+BCMA-CART cells (5x106 IV). Mice were then serially imaged for 1) bioluminescence as a measure of disease burden, and 2) with TFB-PET to assess CART cell expansion and trafficking. As expected, BLI demonstrated that MM predominantly engrafts in bones (Fig E). TFB-PET confirmed trafficking of the NIS+BCMA-CART cells to the bones, corresponding to the areas involved by MM based on BLI (Fig E, right). Both BCMA-CART and NIS+BCMA-CART cells exhibited similarly potent antitumor activity in this model (not shown). Finally, we aimed to explore whether TFB-PET can detect CART massive expansion in vivo and predict the development of CRS. Here, we used an established CRS model in our laboratory. NSG mice were engrafted with patient derived relapsed ALL blasts (5x106 IV). Engraftment was confirmed by peripheral blood sampling. When the leukemic burden is &gt;10 CD19+ cell/µl, mice were treated with either high dose NIS+CART19 cells (5x106 IV) or PBS control. One week after NIS+CART19 cell treatment, mice developed muscle weakness, hunched bodies, and weight loss (Fig F), which correlate with an extreme elevation of cytokines (Sterner et al. Blood 2018). TFB-PET revealed a significant uptake in the bone marrow, spleen, liver, and lungs (Fig G) of the diseased mice but not control mice. Mice were then euthanized, and tissues were harvested. Flow cytometric analysis confirmed an extensive infiltration of CART cells in the liver and spleen. This demonstrates the ability of TFB-PET to detect NIS+CART cell expansion in vivo, correlating with the development of CRS. In summary, our results robustly show that the incorporation of NIS into CART cells provides a sensitive, clinically applicable platform to image CART cells using TFB-PET and to assess their expansion, trafficking to tumor sites, and the development of CRS. These studies illuminate a novel way to noninvasively assess CART cell functions in vivo. Figure Disclosures Sakemura: Humanigen: Patents & Royalties. Suksanpaisan:Imanis: Employment. Cox:Humanigen: Patents & Royalties. Parikh: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; Genentech: Honoraria. Kay:Agios: Other: DSMB; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; MorphoSys: Other: Data Safety Monitoring Board. Peng:Imanis: Equity Ownership. Russell:Imanis: Equity Ownership. Kenderian:Kite/Gilead: Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Novartis: Patents & Royalties, Research Funding.

Overview: B-Chronic lymphocytic leukemia (CLL) is a relatively common B-cell malignancy that has a very heterogeneous clinical course, despite carrying the designation of “chronic,” which is a gross oversimplification. Being able to give some estimate of the rates of disease progression and overall survival (OS) at first diagnosis is, therefore, important in CLL. The ability to accurately predict response to therapy, as well as subsequent duration of response to therapy, is required given the variability of current therapies to induce and sustain treatment responses. The holy grail of prognostics would be to state with accuracy which therapy or types of therapy are best for a given patient. Although there is no complete answer to prognostic counseling, there is a continued development of markers specific to the CLL B cell and/or to its environment, as well as of testing of prognostic models. These models use both traditional and novel prognostic markers that can aid in the dissection of outcome for early-stage CLL in terms of progression risk and time to therapy. This has resulted in significant enhancement of our ability to guide and predict outcome for our patients with CLL.