Citations

Abstract To study the impact of dose modification and temporary interruption of ibrutinib in routine clinical practice, we conducted a retrospective study of consecutive CLL patients treated with ibrutinib outside the context of a clinical trial at Mayo Clinic, (Rochester, MN) from 11/2013 to 12/2017. Of 209 patients, 131 (74%) had unmutated IGHV , 38 (20%) had TP53 disruption, and 47 (22%) were previously untreated. A total of 87/209 (42%) patients started reduced dose ibrutinib (<420 mg daily; n = 43, physician preference; n = 33, concomitant medications; and n = 11, other). During 281 person‐years of treatment, 91/209 patients had temporary dose interruption (54%, nonhematologic toxicity; 29%, surgical procedures; 10%, hematologic toxicity; and 7%, other). After a median follow‐up of 24 months, the estimated median event‐free survival (EFS) was 36 months, and median overall survival (OS) was not reached. On multivariable analyses, temporary ibrutinib interruption (hazard ratio [HR]: 2.37, P = .006) and TP53 disruption at ibrutinib initiation (HR: 1.81, P = .048) were associated with shorter EFS, whereas only TP53 disruption (HR: 2.38, P = .015) was associated with shorter OS. Initial ibrutinib dose and dose modification during therapy did not appear to impact EFS or OS. These findings illustrate the challenges associated with continuous oral therapy with ibrutinib in patients with CLL.

7526 Background: Stem cell transplant (SCT) was considered to be beneficial in CLL patients with Richter transformation (RT). We report a single center experience of SCT for RT. Methods: CLL patients with biopsy-confirmed RT to DLBCL who underwent SCT were identified from Mayo Clinic CLL database, and clinical information was abstracted by chart review. Survival analysis was done with the Kaplan-Meier method. Results: Twenty-four of 204 RT patients underwent SCT, 20 autologous and 4 allogeneic. The median lines of prior CLL therapy was 1 (range 0-4). Only 4 patients were exposed to ibrutinib prior to RT. The median age at RT diagnosis was 62 (range 41-73). Five of 17 (29%) patients had bulky disease (≥ 5 cm), 12 of 20 (60%) had elevated LDH, and 6 of 15 (40%) had TP53 disruption (del(17p) or TP53 mutation). The median lines of RT therapy prior to SCT was 2 (range 1-4); treatments included R-CHOP-like alone (n = 7), platinum-based alone (n = 1), both R-CHOP-like and platinum-based (n = 11), novel agents (n = 2), and high dose MTX-based (n = 3). Response prior to SCT was CR in 12 (50%) and PR in 12 (50%) patients. The median time from RT diagnosis to SCT was 6.8 months (range 3.3-42.3). After a median follow-up of 52.7 months after SCT, there were 10 RT relapses, 4 CLL progression, and 11 deaths (7 RT, 1 CLL and 3 unrelated). The median progression-free survival (PFS) was 28.5 months (95% CI 8.3-NA; 1-year PFS 61.8%, 2-year PFS 50.5%). The median post-SCT survival was 56.3 months (95% CI 30.6-76.6; 2-year survival 82.0%, 4-year survival 65.6%). Elevated LDH was associated with worse PFS (median 8.9 months vs NA, P= 0.014) and a trend of worse post-SCT survival (53.7 vs 67.4 months, P= 0.153). Other factors including age, prior CLL treatment (untreated vs treated), bulky disease, response prior to SCT, and TP53 disruption were not associated with PFS or post-SCT survival. Among the 4 allogeneic SCT patients, 1 had RT relapse 10.5 months after SCT and was treated with venetoclax, ibrutinib and obinutuzumab and remained alive at last follow-up (12.9 months after SCT). All 3 other patients remained in remission and alive at last follow up (15.6, 16.1 and 108.5 months after SCT, respectively). Conclusions: SCT may benefit select RT patients. The role of SCT in the novel agent era needs further study.

7525 Background: New prognostic markers in chronic lymphocytic leukemia (CLL) are in demand. Different groups have developed models which combine multiple prognostic markers into a single index to classify CLL patients (pts). The CLL-International Prognostic Index (CLL-IPI) combines five parameters: age, clinical stage, TP53 status, IGHV mutational status, and serum β2 microglobulin levels. B-cell maturation antigen (BCMA) is a cell membrane receptor expressed exclusively on late stage B-cells and plasma cells with elevated serum (s) levels found in B-cell malignancies, such as multiple myeloma (MM). In MM, sBCMA levels can be used to monitor disease status and predict overall survival (OS). To further evaluate this biomarker in other hematologic malignancies, we studied it in CLL. Methods: Untreated (UNTX) CLL pts seen and consented at Mayo Clinic were identified. sBCMA levels were measured on stored sera of 331 UNTX CLL pts using an ELISA-based assay with a polyclonal anti-BCMA antibody from R&D Systems (Minneapolis, MN). The Mann-Whitney analysis was used to assess differences between CLL pts and healthy controls. The relationships between sBCMA and both time to first treatment (TFT) and OS were also assessed using Cox Regression models with an optimal sBCMA cutoff of 40.9 ng/mL. Results: The median age of pts was 61 years, and 71% were male. The distribution of CLL-IPI risk groups was as follows: 135 (41%) Low; 114 (34%) Intermediate; 67 (20%) High; 15 (5%) Very High. The median level of sBCMA in CLL pts (48.6 ng/mL) was higher (P <0.0001) than those of healthy controls (n = 104; 36.03 ng/mL). In CLL pts, sBCMA is significant in univariable analyses of TFT (HR 2.9 (95%CI, 2.0-4.2); P < 0.0001) and OS (HR 2.5 (95%CI, 1.5-4.0); P < 0.0003), and remains significant when adjusting for sex and CLL-IPI factors (HR 2.3 (95%CI, 1.6-3.3), P < 0.0001; HR 1.9 (95%CI 1.1-3.1), P = 0.01, respectively). Conclusions: sBCMA is elevated in CLL pts compared to healthy controls. After adjusting for CLL-IPI and sex, sBCMA levels provided independent prognostic value in predicting TFT and OS in this cohort. Measuring sBCMA with a readily accessible ELISA-based test, provides incremental value over the current CLL-IPI model in predicting prognosis of CLL.

7522 Background: Ibrutinib therapy is associated with an increased risk (~15%) of AF. An accurate risk assessment model for the development of AF in pts starting ibrutinib is not established, and outcomes after AF are not well described. Methods: An IRB approved retrospective review of CLL pts treated with ibrutinib at Mayo Clinic between Oct 2012 and Nov 2018 was conducted. Results: 299 pts were identified with a total of 565 years of ibrutinib exposure (Table). After a median follow-up of 24 months (range 0–70 months), 51 pts developed treatment-emergent AF (13 [25%] CTCAE 3 or higher). Our study assessed 3 clinical prediction models, the Framingham (Schanbel:Lancet 2009), Italian (Visentin:Blood 2018;132:3118), and Shanafelt (Shanafelt:Leuk Lymp; 2017) risk scores. Based on a lower Akaike information criteria, the Italian score was best able to predict risk of treatment emergent AF (2-year risk of AF with score 0 6%; 1-2 8%; 3-4 26%; 5+ 47%). Thirty (61%) pts were treated with medical therapy for AF (27 rate control; 2 rhythm control; 1 both). 16 (31%) pts underwent interventional therapy (3 AV node ablation; 11 cardioversion; and 2 pacemaker). Twelve (23%) pts temporarily held ibrutinib and resumed their original dose, 22 (43%) pts continued reduced dose ibrutinib and 11 (22%) continued their initial ibrutinib dose. Six (12%) pts permanently discontinued ibrutinib. Of 51 pts with treatment-emergent AF, 41 (80%) had a CHA2DS2-VASc score of ≥2 (41% received anticoagulation alone; 12% received antiplatelet therapy alone; 10% received both). No pt developed a thrombotic stroke after treatment-emergent AF. Two major bleeds, (1 GI and 1 intracranial) occurred, one in a pt on concomitant antiplatelet and anticoagulation therapy, and one in a pt receiving neither. The development of AF was associated with shorter event-free survival (HR 2.5, 95%CI 1.5-4.2, p<.001) and shorter overall survival (HR 3.5, 95%CI 2.0-6.3, p<.001). Conclusions: The Italian score was the best predictor of AF development in this cohort of ibrutinib treated pts. Although the vast majority of pts who develop AF after ibrutinib are able to continue therapy, the occurrence of AF appears to be associated with shorter EFS and OS. [Table: see text]

7086 Background: The HRQOL of patients (pts) with chronic lymphocytic leukemia (CLL) has not been adequately delineated across patient, disease and treatment characteristics. We evaluated HRQOL of CLL pts undergoing treatment in the United States (US) by age, gender and line of therapy. Methods: Data were collected in Connect CLL, a prospective observational US registry. Physicians provided data on demographics, clinical characteristics and line of therapy at enrollment. HRQOL was self-reported by pts at enrollment using the Functional Assessment of Cancer Therapy-Leukemia, an instrument that yields a leukemia-specific total HRQOL score (FACT-Leu) and a cancer-specific total HRQOL score (FACT-G). Mean total scores were analyzed by line of therapy, age and gender. Statistical significance was ascertained by ANOVA using SAS 9.2. Multivariate analyses were conducted to assess the relative association of line of therapy, age and gender with HRQOL. Results: Among 1,252 pts enrolled from 161 geographically diverse centers (90% community, 8% academic, 2% veterans/military), pts were predominantly male (63%), white (89%) with mean age 69 yrs. Pts were categorized by line of therapy at enrollment: First 61%, Second 18%, Third 11%, Higher 9%; and by age group: <65 33%, 65-74 35%, 75+ 32%. Univariate analyses suggested that the total FACT-Leu score was significantly better in men than women (P=0.004); in pts aged 65-74 vs younger or older pts (P=0.033); and in pts initiating first-line treatment vs pts receiving subsequent treatments (P=0.0002). Similar results were found with the FACT-G score except that gender differences were not statistically significant. Multivariate analysis confirmed that line of therapy (P=0.007), gender (P<0.0001), and age group (P=0.039) were each associated with significant differences in the FACT-Leu total score. Conclusions: Results from the Connect CLL Registry indicate that HRQOL is better among pts initiating first-line therapy compared to pts initiating subsequent treatments, and that this remains true when age and gender are considered. Future analyses should determine how HRQOL may change over time relative to treatment and treatment response.

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.