Ansell, Stephen M.

Background: Two-year follow-up from ZUMA-1 trial for axicabtagene ciloleucel (axi-cel) CD19 chimeric antigen receptor T-cell (CART) in aggressive non-Hodgkin lymphoma (NHL) demonstrated that patients (pts) achieving complete remission (CR) as their best response have the longest progression free survival (PFS), while PFS remained poor for others. Majority of the best response are achieved by month 3 post-infusion. Moreover, a subset of pts who do not achieve CR by month 1 may still achieve CR while others will progress within months. Having a clinically available test to predict for durable response can assist clinicians in selecting pts who can be observed for continued response vs. those who may need intervention earlier. Peak CAR-T expansion has been correlated with best clinical response to axi-cel. However there is no clinically available test to quantify CART cells post treatment. Given the prolonged lymphotoxic effect of the lymphodepletion (LD) chemotherapy administered before CART infusion, we hypothesize that the peak expansion of absolute lymphocyte count (ALC, ALCpeak) after infusion likely corresponds to CART expansion. We examined for correlation between ALCpeak and clinical response at month 3 post-infusion for pts who received axi-cel. Methods: Data was collected from pts who received axi-cel between June 2016 and March 2019 at Mayo Clinic Rochester (NCT02348216, NCT03153462, and standard of care). All infused pts were included in the intention to treat analysis for response and event-free survival (EFS). Lugano 2014 criteria were used for clinical response. EFS was defined as the date of infusion until progression or death due to any cause and evaluated using Kaplan Meier curves with log-rank test. Comparison between subgroups was investigated using Fisher's exact test and Wilcoxon test for categorical and continuous variables, respectively. Statistical analysis performed using JMP Pro 14.1. Results: Of the thirty-six NHL pts treated with axi-cel, the median age was 56 yrs (range 26-65); 78% (28) were male; 44% (16) had DLBCL; the median number of prior therapies was 3 (2-6), 47% (17) had stem cell transplant. Nineteen (53%) pts received bridging therapy after leukapheresis. All pts received fludarabine and cyclophosphamide for LD chemotherapy and achieved ALC nadir by the day of CART infusion (median 0.03 x 10^9/L, range 0.01-0.11). As CART expansion were found to peak within the first two weeks in ZUMA-1 trial, we examined ALC trend over 15 days post infusion and found that ALCpeak generally happened within the same timeframe (median ALCpeak day: 9, range 6-15). At 3 months post infusion, 33.3% (12/36) of pts achieved CR, 8.3% (3/36) pts were in partial remission (PR). No correlation was found between CR response and clinical characteristics: age >60 years, stage III/IV, B symptoms, elevated LDH, IPI score 3-4, number of previous treatments, use of bridging therapy, peak CRP and ferritin. However, the ALCpeak was significantly different between CR and non-CR pts (median, range: 1.09, 0.35-2.55; 0.67, 0.15-1.03; p=0.04). Using receiver operator curve (ROC)-derived area under the curve (AUC) estimates, ALCpeak 1.08 x 10^9/L was identified as the best threshold to discriminate patients at different likelihood to achieve CR at month 3. Pts achieving ALCpeak ≥ 1.08 showed a strong increased likelihood of achieving CR at month 3 (OR 2.8; 95% CI, 1.12-6.99; P=0.02). There was no statistical difference between the ALCpeak high and low groups in terms of use of bridging therapy, occurrence of any grade or higher grade cytokine release syndrome or neurotoxicity, or the use of tocilizumab or steroid. Interestingly, for pts who had changes in clinical response from month 1 to month 3, all 3 pts who converted to CR by month 3 had ALCpeak≥1.08, while the 13 of the 15 pts who had progressed by month 3 had ALCpeak<1.08. In addition, EFS was significantly different between pts who had ALCpeak above and below 1.08 (6 months EFS rate 75% vs. 25%, respectively, Figure 1). Conclusions: We found that the ALC expansion occurred in the first 15 days post axi-cel infusion, consistent with the known time frame for CART expansion. Higher ALCpeak level in this timeframe correlated with higher likelihood of achieving CR, and is associated with conversion to CR. This study is limited by the small sample size and limited follow-up, but the results are promising for further prospective investigation in a larger cohort of patients. Disclosures Paludo: Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding; Celgene: Research Funding; Celgene: Research Funding. Ansell:Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding. Bennani:Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Adicet Bio: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Kite Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Seattle Genetics: Other: Advisory board; Adicet Bio: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Other: Advisory board; Purdue Pharma: Other: Advisory board. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Karyopharm: Research Funding; Rigel: Consultancy. Kapoor:Celgene: Honoraria; Janssen: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding. Kenderian:Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding. Kumar:Takeda: Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.

BackgroundPrior studies in oncology have shown that a higher annual facility patient volume is associated with reduced mortality. Because classic Hodgkin lymphoma is uncommon but highly curable, this study used the National Cancer Database (2003‐2014) to analyze whether such a relationship exists for this disease.MethodsThe facilities were classified by quartiles, and random intercepts were used to account for clustering of patients within facilities. A Cox regression model was used to determine the volume‐outcome relationship.ResultsThere were 47,633 patients with classic Hodgkin lymphoma treated at 1310 facilities. The first quartile (Q1), which included 58.4% of the facilities, treated 3 or fewer patients per year, whereas the fourth quartile (Q4), which included 5.9% of the facilities, treated more than 9 patients per year. Compared with the patients treated at Q4 facilities, those treated at lower quartile facilities had a higher risk of death (hazard ratio for the third quartile [HR], 1.19; 95% confidence interval [CI], 1.1‐1.29; HR for the second quartile, 1.28; 95% CI, 1.19‐1.38; HR for Q1, 1.29; 95% CI, 1.2‐1.39) after adjustments for all other factors (P < .0001). Compared with facilities treating 10 patients per year, facilities treating 40 patients per year had approximately 27% lower overall mortality rates.ConclusionsPatients with classic Hodgkin lymphoma treated at high‐volume centers had lower overall mortality than those treated at lower volume centers. Because this is a highly curable malignancy, such differences may suggest a benefit from referral to higher volume facilities or the emulation of their care models.

Abstract Summary: T-cell transfer into lymphodepleted recipients results not only in homeostatic activation of the infused cells but also in T-cell inhibition due to upregulation of immune checkpoint receptors including PD-1 and CTLA4, thereby mitigating T-cell efficacy. Dual checkpoint blockade of PD-1 and CTLA4 in conjunction with lymphodepletion—an “immunotransplant”—uncouples the T-cell inhibition from activation and amplifies the T-cell antitumor immune response. See related article by Marshall et al., p. 1520.

Abstract Effector CD8+ T cells play a crucial role in anti-tumor immunity. Two major subsets of effector CD8+ T cells have been identified based on expression of KLRG1 and CD127: KLRG1+CD127- short-lived effector cells (SLECs) and KLRG1-CD127+ memory precursor effector cells (MPECs). In B-cell non-Hodgkin lymphoma (NHL), the frequency and function of SLECs and MPECs are unknown. Furthermore, the underlying mechanism by which these two CD8+ subsets were regulated and differentiate in B-cell NHL remains poorly understood. The goal of the present study is therefore to phenotypically and functionally characterize SLECs and MPECs in B-cell NHL. Using patient biopsy specimens, we observed that the median percentage of SLECs was greater than MPECs and was 39.9% (range: 22.7%~ 54.7%) and 18% (range: 7.66%~31.6%), respectively. In controls, the median percentage of SLECs was lower than that of MPECs and was 13.71% (range: 5.26%~29.2%) and 51.63% (range: 22.5%~70.1%) in PBMC and 12.14% (range: 4.01%~26%) and 51.62% (range: 29.2%~70.3%) in tonsil, respectively. Using mass cytometry (CyTOF), we observed that SLECs have higher expression levels of TIGIT and PD-1 and lower expression of CCR7, CD26 and CD27 when compared to MPECs. SLECs were functionally superior to MPECs as the numbers of cytokine (IFN-γ and TNF-α) - and granule (granzyme B and perforin)-producing cells were higher in SLECs than MPECs. However, SLECs had a lower proliferative capacity and a higher apoptosis rate when compared to MPECs. We observed that a reciprocal differentiation pathway exists between SLECs and MPECs. Activation and cytokine stimulation (IL-2 and IL-15) promoted the development of SLECs and decreased the number of MPECs. This effect was reversed when cells were treated with neutralizing antibodies to block IL-2 or IL-15 signaling. We also found that these two subsets had a distinct transcription factor profile as SLECs had higher expression of Eomes and T-bet, and lower expression of Tcf-1than MPECs. IL-2 and IL-15 enhanced the expression of T-bet and decreased the expression of Tcf-1. Taken together, our results show that SLECs are more prevalent than MPECs in B-cell NHL when compared to normal control tissue. These two effector cell subsets have distinct phenotypical and function profiles and their development is controlled by cytokines that may be dysregulated in lymphoma. Despite the fact that SLECs produce more granzyme B and IFN-γ, they are less proliferative and more susceptible to apoptosis. This may compromise an effective anti-tumor immune response in B-cell NHL. Disclosures Ansell: Celldex: Research Funding; Takeda: Research Funding; Merck & Co: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Pfizer: Research Funding; Seattle Genetics: Research Funding.

Abstract Background: Waldenström macroglobulinemia (WM) is an indolent B-cell lymphoma with a heterogeneous disease course. For nearly a decade, the International Prognostic Scoring system (IPSS), requiring 5 variables (platelet count, hemoglobin, age, Beta 2 microglobulin and immunoglobulin M size) has been used to prognosticate patients with active WM. In this study, we attempt to propose a simplified prognostic model for patients with active/symptomatic WM. Methods: All patients with active WM diagnosed between 01/01/1996 and 12/31/2017 and evaluated consecutively at Mayo Clinic, Rochester were included in the study after Institutional Review Board approval. Active WM was defined as ≥10% marrow infiltration with lymphoplasmacytic cells plus monoclonal IgM of any size requiring systemic therapy. The follow up and overall survival (OS) were calculated from the time of active WM until date of last follow up or death. Baseline parameters at active disease were used to assess prognostic factors for OS using a univariate followed by a multivariate (MV) Cox regression analysis. Independent variables on the MV analysis were given a score proportional to their risk ratios (RR). All time-to-event analyses were performed using the Kaplan-Meier method and the survival curves were compared using log-rank test. Discriminatory ability of the IPSS and the currently proposed prognostic system was assessed using Harrell's concordance index wherein a higher c-statistic is associated with a better discriminatory ability. Results: We identified 889 patients with active WM. The median follow up was 8.2 years (95% CI: 7.5-9 years). The baseline characteristics of the patients are shown in Table 1. At the time of diagnosis of WM, 16% of patients had previously documented MGUS and 16% patients had smoldering (asymptomatic) WM. The course of WM was complicated by systemic amyloidosis in 8% (n=69), transformation to high-grade lymphoma in 4% (n=38), symptomatic hyperviscosity in 13% (n=118), myelodysplastic syndrome in 2% (n=17) and Bing-Neel syndrome in 1.4% (n=12) of patients. Of the patients tested, cryoglobulinemia was present in 17% (n=48), cold agglutinin disease in 34% (n=43) and Coombs positive hemolytic anemia in 9% (n=34) patients. The median OS was 10.6 years (95% CI: 9.7-11.4 years). The factors affecting OS are shown in Table 2. While the patients' MYD88L265P mutation status was not found to be prognostic for OS, age >65 years [RR 1.8 (95% CI: 1.2-2.8); p=0.01], LDH > upper limit of normal [RR 2.5 (95% CI: 1.3-4.6); p=0.003] and serum albumin <3.5 g/dL [RR 1.6 (95% CI: 1.1-2.5); p=0.02] were independently prognostic. Owing to comparable RRs, each of these were assigned a score of 1 point and a prognostic model with a minimum score of 0 and maximum score of 3 was constructed. A score of 0 was considered as low risk WM and 1 as intermediate risk WM. The patients with scores of 2 and 3 were analyzed together to form the high risk cohort due to comparable OS for these two groups. The patient outcomes based on this prognostic model are depicted in Figure 1. Using the new prognostic model (n-=341), the median OS for the low risk group (n=71, 21%) was 14.6 years (95% CI: 9 years- not reached) compared to 11 years (95% CI: 8.1-14.7 years) for intermediate risk (n=140, 41% ) and 7.2 years (95 % CI: 5.4-10 years) for the high risk group (n=130, 38%), p<0.0001. The data for the IPSS-WM were available in 319 patients in the entire cohort. The OS for low risk IPSS (n=56) was 14.6 years (95% CI: 12.1 years-NR), 15.6 years (95% CI: 8.3-18.5 years) for intermediate risk IPSS (n=131) and 9.1 years (95% CI: 6.8-11.2 yeas) for the high risk IPSS group (n=132; p=0.009). Among the 220 patients having data for IPSS-WM as well as our proposed model, the current three variable model held its prognostic significance (p=0.0004). The Harrell's c-index was 0.647 (95% CI 0.592-0.702) for our prognostic model and 0.58 (95%CI: 0.521-0.638) for IPSS-WM. Common frontline treatment comprised of rituximab monotherapy (n=277, 33%), rituximab with alkylator or purine analog combination (n=255, 30.5%) and other therapies, including alkylators/purine analog monotherapy, ibrutinib, proteasome inhibitors, etc., in 37% patients. Conclusion: A simpler, clinically useful, risk stratification model based on age, serum albumin and serum LDH with a potentially higher discriminatory value than IPSS-WM may be used to prognosticate patients with WM. This model requires external validation. Disclosures Ansell: Pfizer: Research Funding; Affimed: Research Funding; Celldex: Research Funding; Bristol-Myers Squibb: Research Funding; Takeda: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Merck & Co: Research Funding; Regeneron: Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Gertz:Abbvie: Consultancy; Prothena: Honoraria; Medscape: Consultancy; annexon: Consultancy; Amgen: Consultancy; Alnylam: Honoraria; Teva: Consultancy; janssen: Consultancy; Physicians Education Resource: Consultancy; Ionis: Honoraria; spectrum: Consultancy, Honoraria; celgene: Consultancy; Research to Practice: Consultancy; Apellis: Consultancy. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Lacy:Celgene: Research Funding. Dingli:Millennium Takeda: Research Funding; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Millennium Takeda: Research Funding. Kumar:Takeda: Membership on an entity's Board of Directors or advisory committees; Merck: 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, Research Funding; Janssen: 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, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Roche: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kapoor:Takeda: Research Funding; Celgene: Research Funding.

Abstract Introduction Waldenstrom macroglobulinemia (WM) is a rare disease accounting for only 1-2% of all hematologic malignancies and with an overall annual, age-adjusted incidence of approximately 3.5 to 5.5 cases per million-person years. With approximately 13,000 active hematologist/oncologists in the US, most of who are in the community oncology setting, it's estimated that a hematologist/oncologist will only diagnose a WM case approximately every 8 years. Therefore, the clinical experience of a general hematologist/oncologist in the management of WM is likely very limited compared to more prevalent malignances. Previous studies in the setting of rare cancers suggest a correlation between higher volume of care and improved outcomes. Therefore, we explored the volume-outcome relationship in WM using the National Cancer Data Base (NCDB). Methods Patient-level data from the NCDB, a nationwide, facility-based, database covering approximately 70% of all newly diagnosed cancer cases in the US, was queried for all new WM cases diagnosed between 2004 and 2014. Only patients requiring treatment were included. Treatment facilities were divided into quartiles based on the average annual volume of newly diagnosed cases of WM seen. Cox regression was used to analyze the association between facility WM volume and survival, adjusted by demographics (sex, age, race), socioeconomic status (income, education, insurance type), geography (area of residence, treatment facility type, travel distance), comorbidity factors (Charlson-Deyo score), and year of diagnosis. Time-to-event analysis was calculated from frontline therapy initiation date using the Kaplan-Meier method and the log-rank test. Results A total of 3,732 patients with WM treated in 831 facilities were included. The median age at diagnosis was 70 years and 75% of the patients were treated within 20 miles from their residency zip code. Patient characteristics per treatment facility volume quartile are shown in table 1. The median annual facility volume was 1 new WM patient/year (range 0.1 to 21). The median follow-up from frontline treatment was 5 years. The unadjusted median OS by facility volume was: Q1: 6.5 years (95% CI: 5.7-7.4), Q2: 7 years (95% CI: 6.3-8.2), Q3: 8.2 years (95% CI: 7.1-8.9), and Q4: NR (95% CI: 8.5-NR), p<0.0001 (figure 1). The estimated 5-year OS by facility volume was: Q1: 56%, Q2: 61%, Q3: 64%, Q4: 71%, p<0.0001. Multivariate analysis including all variables showed in Table 1 demonstrated that facility volume was independently associated with all-cause mortality. Compared to patients treated at Q4 facilities, patients treated at lower-quartiles facilities had a higher incremental risk of death (Q3 hazard ratio [HR], 1.07 [95% CI: 0.88 to 1.29] p=0.46; Q2 HR, 1.34 [95% CI: 1.11 to 1.63] p=0.002; Q1 HR, 1.52 [95% CI: 1.23 to 1.88] p=<0.0001). Conclusion Our results suggest that a volume-outcome relationship exits in WM as patients treated initially at higher-volume facilities had a lower risk of mortality. Although differences in the underlying disease biology, referral patterns after initial therapy, or cumulative treating-physician experience could not be assessed, these potential biases would only underestimate the magnitude of the volume-outcome relationship reported. Disclosures Ansell: Celldex: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Pfizer: Research Funding; Affimed: Research Funding; Merck & Co: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding. Gertz:Medscape: Consultancy; janssen: Consultancy; Alnylam: Honoraria; Ionis: Honoraria; Physicians Education Resource: Consultancy; Prothena: Honoraria; Teva: Consultancy; Research to Practice: Consultancy; spectrum: Consultancy, Honoraria; celgene: Consultancy; Amgen: Consultancy; Abbvie: Consultancy; annexon: Consultancy; Apellis: Consultancy. Kapoor:Takeda: Research Funding; Celgene: Research Funding. Ailawadhi:Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Research Funding; Celgene: Consultancy; Takeda: Consultancy. Reeder:Affimed: Research Funding. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Lacy:Celgene: Research Funding. Kumar:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Introduction REGN1979 is an anti-CD20 x anti-CD3 bispecific IgG4 antibody (Ab) modified to reduce Fc binding. Engaging both targets results in CD20-specific, local T-cell activation and cytotoxicity, a mechanism of action distinct from standard anti-CD20 Abs. We report updated promising efficacy results of a Phase 1 trial of REGN1979 in patients (pts) with relapsed/refactory (R/R) B-NHL previously treated with anti-CD20 Abs. Methods The primary objectives of the study are to determine safety, tolerability, and occurrence of dose limiting toxicities (DLTs). Other objectives include assessment of preliminary antitumor activity, pharmacokinetics (PK), and pharmacodynamics. Eligible pts with R/R NHL must have received at least 1 prior CD20-directed therapy. Treatment consists of 12 weekly doses of REGN1979 followed by every 2 week dosing for 12 doses for a total of 36 weeks. Guidelines are provided for management of cytokine release syndrome (CRS) and include steroids and/or tocilizumab at investigator discretion. Results As of June 1, 2018, 54 pts with B-NHL were treated with REGN1979 monotherapy: DLBCL (pt number [n]=30), FL (n=16), MCL (n=5), MZL (n=2), and WM (n=1). The median number of prior regimens was 3 (range, 1-11); 41 pts were refractory to their last prior systemic therapy, 18 had bulky disease, and 6 had prior HSCT. Pts were treated with REGN1979 0.03-27 mg and received a median of 7 (range, 1-24) doses. Eight pts remain on treatment, 13 completed treatment, and 33 discontinued therapy prior to the planned 36 wks (majority [n=22] due to progressive disease [PD]). There have been no DLTs to date. The most common treatment-related treatment-emergent adverse events (TR-TEAEs) included infusion-related reactions (IRR) or CRS; 26 pts experienced CRS (Grade 1-2, n=23; Grade 3, n=3) with a median duration of CRS of 2 (range 1-15) days. Six pts received tocilizumab. The severity of CRS symptoms declined through optimized pre-medication even with REGN1979 dose escalation. Other common Grade ≥3 TR-TEAEs were lymphocytopenia/ decreased lymphocyte count (n=8); neutropenia/ decreased neutrophil count (n=7); and thrombocytopenia/ decreased platelet count, hypotension, hypophosphatemia, and anemia (each n=3). Seventeen pts experienced a nervous system event including headache, dizziness, paraesthesia, dysgeusia, and peripheral neuropathy with no Grade ≥3 events; no neurologic event required termination of study drug. Seven pts died on study: PD (n=5), gastric perforation (n=1), and cardiac arrest (n=1). TEAEs leading to premature discontinuation of REGN1979 were Grade 3 fatigue (n=1), Grade 3 hemolysis (n=1), and Grade 2 pyrexia/Grade 2 tachycardia (n=1). Among 27 pts treated with REGN1979 ≥5 mg (dose associated with tumor killing in pre-clinical data), the overall response rate (ORR) was 55.6% (5 complete response [CR] and 10 partial response [PR]; Table/Figure). Responses were seen in 7/7 FL Grade 1-3a pts (5 CR, 2 PR), 6/15 DLBCL pts (all PR), 2/2 MCL pts (all PR). At 18 mg and 27 mg of REGN1979, 4 of 4 pts with DLBCL had best response of PR. Post data cut-off, 1 pt with a DLBCL best response of PR converted to CR. PK and pharmacodynamic assessments suggest that for pts treated with REGN1979 5-18 mg, best exposures in the first 3 weeks appear to linearly increase with dose. In pts treated with up to REGN1979 18 mg, a maximum mean Ctrough of 1.6 mcg/mL was observed in the first 3 weeks of weekly dosing. Studies of peripheral blood biomarkers demonstrated depletion of peripheral B lymphocytes, transient margination of circulating T-cells, and elevated circulating cytokines following REGN1979 dosing. Increased peak cytokine levels (IL-6, IL-10, and TNF-alpha) were observed in pts with CRS. Immunohistological analysis of malignant lymph node tissue demonstrated a decrease of CD20 expression in responding pts; among the responders, subsequent relapse was associated with either maintenance of CD20 expression or further CD20 loss, suggesting antigen-dependent and independent disease escape mechanisms. Conclusions REGN1979 displays efficacy and an acceptable safety profile in pts with R/R B-NHL. Most TR-TEAEs were IRR/CRS and have been well managed with supportive care. No significant neurological toxicity has been observed. At doses of 5-27 mg of REGN1979, the preliminary ORR was 100% in pts with FL Grade 1-3a and 40.0% in pts with DLBCL. This promising efficacy warrants further clinical investigation. Disclosures Bannerji: Regeneron Pharmaceuticals, Inc.: Consultancy; AbbVie, Inc.: Consultancy. Arnason:Regeneron Pharmaceuticals, Inc.: Consultancy. Advani:Bayer Healthcare Pharmaceuticals: Other: Consultancy/Advisory Role; Janssen Pharmaceutical: Other: Institutional Research Support; Bristol Myers Squibb: Other: Consultancy/Advisory role and Institutional Research Support; Pharmacyclics: Other: Institutional Research Support; Takeda: Other: Consultancy/Advisory Role; Millenium: Other: Institutional Research Support; Gilead/Kite: Other: Consultancy/Advisory Role; Infinity: Other: Institutional Research Support; Merck: Other: Institutional Research Support; Forty Seven, Inc: Other: Institutional Research Support; Cell Medica: Other: Consultancy/Advisory Role; Agensys: Other: Institutional Research Support; Celgene: Other: Institutional Research Support; Seattle Genetics: Other: Consultancy/Advisory role, Institutional Research Support; Kura: Other: Institutional Research Support; Roche/Genentech: Other: Consultancy/Advisory Role, Institutional Research Support; Kyowa: Other: Consulting/Advisory Role; Regeneron Pharmaceuticals, Inc.: Other: Institutional Research Support; Autolus: Other: Consultancy/Advisory Role; AstraZeneca: Other: Consultancy/Advisory Role. Brown:Acerta / Astra-Zeneca: Membership on an entity's Board of Directors or advisory committees; Verastem: Consultancy, Research Funding; Pharmacyclics: Consultancy; Celgene: Consultancy; Genentech: Consultancy; TG Therapeutics: Consultancy; Morphosys: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Abbvie: Consultancy; Gilead: Consultancy, Research Funding; Sun Pharmaceutical Industries: Research Funding; Sunesis: Consultancy; Loxo: Consultancy; Beigene: Membership on an entity's Board of Directors or advisory committees; Invectys: Membership on an entity's Board of Directors or advisory committees; Roche/Genentech: Consultancy; Boehringer: Consultancy. Allan:Genentech: Membership on an entity's Board of Directors or advisory committees; Verastem: Membership on an entity's Board of Directors or advisory committees; Sunesis: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees; Acerta: Consultancy. Ansell:Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Merck & Co: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Celldex: Research Funding; Takeda: Research Funding; Pfizer: Research Funding. O'Brien:Kite Pharma: Research Funding; Aptose Biosciences Inc.: Consultancy; Pharmacyclics: Consultancy, Research Funding; GlaxoSmithKline: Consultancy; Astellas: Consultancy; Sunesis: Consultancy, Research Funding; Alexion: Consultancy; Amgen: Consultancy; TG Therapeutics: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Vaniam Group LLC: Consultancy; Regeneron: Research Funding; Janssen: Consultancy; Celgene: Consultancy; Abbvie: Consultancy; Acerta: Research Funding; Gilead: Consultancy, Research Funding. Chavez:Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Merck: Research Funding; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Speakers Bureau; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Humanigen: Consultancy. Lowy:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Charnas:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Sternberg:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Ambati:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Adriaens:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Ufkin:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Yan:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Li:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Navarro:Regeneron Pharmaceuticals, Inc.: Employment. Gasparini:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Jankovic:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Fiaschi:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Zhang:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Hamon:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Thurston:Regeneron Pharmaceuticals, Inc.: Employment, Equity Ownership. Topp:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Research Funding; F. Hoffmann-La Roche Ltd: Membership on an entity's Board of Directors or advisory committees, Research Funding; Boehringer Ingelheim: Research Funding; Regeneron Pharmaceuticals, Inc.: Honoraria, Research Funding.

Abstract Background: Checkpoint blockade therapies (CBT) have substantially improved outcomes for patients in a variety of cancers. However, they are associated with a unique spectrum of immune-related adverse events (AEs). Additionally, unlike standard chemotherapy, many patients (pts) remain on CBT for prolonged periods of time, thus immune-related symptomatic AEs may be chronic or low grade therefore important to capture long term tolerability when used as a single agent or in combination with chemotherapy. In this study, we applied the Toxicity over Time (ToxT) analytic approach (Thanarajasingam et al, Lancet Oncol 2016), which incorporates the dimension of time and includes chronic lower grade events, to the first 6 cohorts (A-F) of a Phase 1/2 ECOG-ACRIN sponsored study of the combinations of Brentuximab Vedotin (BV) and the CBT therapies ipilimumab (Ipi) and nivolumab (Nivo) in pts with relapsed or refractory Hodgkin lymphoma (R/R HL). Methods: Pts with confirmed R/R HL were treated with BV 1.8mg/kg + Ipi 1or 3 mg/kg (n=23); or Nivo 3mg/kg + BV: 1.2 or 1.8 mg/kg (n=19). BV was administered every 21 days for 16 cycles; Ipi every 21 days x 4 and then every 3 months for one year and Nivo every 21 days for up to 2 years. Seven symptomatic (subjective) AEs were selected: fatigue, peripheral sensory neuropathy (PSN), nausea/vomiting (NV), rash/skin (RS), diarrhea, ocular-all types, and hair loss. Treatment-related AEs of any grade were investigated by conventional maximum grade toxicity analysis (ToxC) and ToxT methods up to 12 cycles. Using ToxT, mean AE grades over cycles were analyzed for time trend with repeated measures models, time to grade 2 or higher AE (gr2+) was analyzed with time-to-event analysis; AE profile over the entire course of the study was summarized by area under the curve (AUC) analyses. Comparisons were performed between treatment groups: BV/Ipi(A-C arms) and BV/Nivo (D-F arms). Results: 9/23 (BV/Ipi) and 6/19 (BV/Nivo) pts completed 10 cycles. For BV/Ipi vs. BV/nivo, ToxC provides overall incidence rates (any grade): fatigue 52% vs 26% (p=0.09); PSN 61% vs 53%; NV 70% vs 53% ; RS 65% vs. 37% (p=0.07); diarrhea 57% vs. 21% (p=0.02); ocular 17% vs. 21% ; and hair loss 17% vs. 0% (p=0.06), respectively. Gr3 AE occurred in 1 pt (2.4%) each for PSN, NV, diarrhea, and 6 pts (14.3%) for RS, and were similar between BV/ipi and BV/nivo. AUC from ToxT which captures chronic lower grade AEs suggested for BV/Ipi: diarrhea (p=0.02) and NV (p=0.03) are significantly more substantial over time with a trend seen for fatigue (p=0.07), RS (p=0.07) and hair loss (p=0.07) . Additionally, ToxT captures the trajectory of AEs, demonstrated a rising incidence and worsening grade of PSN (BV-related) on BV/Ipi (c1: 9% gr1, c2: 21% gr1 5% gr2, c5: 11% gr1 and c10: 22% gr2 [p=0.005], Fig 1a). In contrast there was a slow but significant decreasing incidence of NV on both combinations; for BV/Nivo (c1:52% gr1, c5: 26% gr1 and c10: 22% gr1) and BV/Ipi (c1: 47% gr1 ,c5: 0% and c10 1% gr1) with p=0.006 (Fig 1b). RS and diarrhea appear early on treatment and are not cumulative (Fig1c and 1d). There is no significant difference in the time to gr 2+ toxicities in any of the 7 AE. Combining all 7 AEs and using the maximum grade as a pilot measure of overall AE burden , ToxC indicates no difference in any grade (100% vs 100%) but a significantly higher gr 3+ incidence (35% vs. 11%) for BV/Ipi. Additionally, ToxT further elucidates that BV/Ipi is associated with significantly higher overall AE over time (Fig 2a, p=0.02) and compared to BV/Nivo a significantly higher risk of developing gr 2+ toxicity ( 57% vs 16% gr2 + event by day 50) (HR=0.41, p=0.02, Fig 2b). Conclusions: The CBT therapies Ipi and Nivo, in combination with BV, are overall both well tolerated over time, although BV/Ipi has a higher overall AE burden. Neither regimen has significant cumulative immune toxicity. Results of this analysis should be interpreted in the context of limited number of pts in both cohorts. A larger scale examination of this analysis is planned to incorporate both phase 1 and the ongoing phase 2 components of E4412. Compared with conventional tox analysis, ToxT delineated important additional and clinically relevant depictions of AEs over time and adds a more comprehensive assessment of the tolerability of chronically administered immune therapies for lymphoma. Disclosures Hong: Merck: Consultancy. Ansell:Regeneron: Research Funding; Merck & Co: Research Funding; Takeda: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Pfizer: Research Funding; Celldex: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding. Cohen:Bristol-Myers Squibb: Research Funding; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Janssen: Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioInvent: Consultancy; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Research Funding; BioInvent: Consultancy; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Research Funding. Advani:Kura: Research Funding; Janssen: Research Funding; Bayer: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Autolus: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Cell Medica: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Kyowa: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Millenium: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Celgene: Research Funding; Agensys: Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Infinity: Research Funding; Forty Seven Inc.: Research Funding; Celgene: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Regeneron: Research Funding; Gilead/Kite: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Merck, Takeda, Celgene, Seattle Genetics, Bayer: Research Funding. Svoboda:Pharmacyclics: Consultancy, Research Funding; Merck: Research Funding; KITE: Consultancy; TG Therapeutics: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Regeneron: Research Funding; Seattle Genetics: Consultancy, Research Funding; Kyowa: Consultancy. Karmali:AstraZeneca: Speakers Bureau; Gilead: Speakers Bureau. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Dueck:Bayer: Employment; Phytogine: Employment; Pfizer: Honoraria. Kahl:Genentech: Consultancy; Acerta: Consultancy; AstraZeneca: Consultancy; Abbvie: Consultancy; Juno: Consultancy; Celgene: Consultancy; Seattle Genetics: Consultancy; ADC Therapeutics: Consultancy; CTI: Consultancy; Gilead: Consultancy. Diefenbach:Merck: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Acerta: Research Funding; Millenium/Takeda: Research Funding; Genentech: Consultancy; Denovo: Research Funding; Incyte: Research Funding; Seattle Genetics: Consultancy, Research Funding; Trillium: Research Funding.

Abstract T cell Ig and ITIM domain (TIGIT) is an immune checkpoint molecule that is expressed on a variety of cell types including NK cells, effector and memory T cells, and Treg cells. Upon ligation with CD155, TIGIT delivers an inhibitory signal and negatively regulates anti-tumor responses. While important in normal T-cell biology, the pathological significance of TIGIT expression and function in the tumor microenvironment of the patients with follicular lymphoma (FL) is largely unknown. The present study sought to phenotypically and functionally characterize TIGIT+ T cell subsets in FL. While its expression is not detected on resting T cells in peripheral blood, we found that TIGIT is highly expressed on intratumoral T cells from FL. Treatment with cytokines such as IL-4 and TGF-β downregulated TIGIT expression on T cells. We found that TIGIT is predominantly expressed on effector memory T cells (TEM) with an activation/exhausted phenotype, and TIGIT+ T cells have higher expression levels of CD69 and PD-1 when compared to TIGIT- T cells. Functionally, TIGIT+ T cells displayed reduced capacity of cell proliferation and cytokine production (IFN-γ and IL-2). Using mass cytometry (CyTOF), we observed that TIGIT is abundantly expressed on some intratumoral Treg (CD4+CD25+Foxp3+) cells, while other Treg cells lack TIGIT expression in FL, forming two subsets of Treg cells: CD4+CD25+TIGIT+ and CD4+CD25+TIGIT-. These two subsets are phenotypically distinct in that CD25+TIGIT+ cells exhibited increased expression of activation/costimulatory markers such as CD69, CD27 and CD28 compared to CD25+TIGIT-, suggesting an activated Treg subset of CD25+TIGIT+ cells. This CD25+TIGIT+ subset had increased suppressive function and could more effectively inhibit activation and proliferation of CD8+ T cells than CD25+TIGIT- cells. Furthermore, we found that lymphoma B cells promoted the development of TIGIT-expressing T cells as TGF-β-mediated downregulation of TIGIT on T cells was inhibited when CD19+ lymphoma cells were present. Using a cohort of 31 FL patients, we found that intratumoral TIGIT-expressing T cells were associated with a favorable prognosis. Patients with TIGIT+ T cell numbers greater than 50% had better overall survival than patients with TIGIT+ T cell numbers less than 50%. Taken together, our results reveal a role of TIGIT in defining Treg cell subsets with different immune function and TIGIT expression may be useful in predicting patient outcome in FL. Disclosures Ansell: Takeda: Research Funding; Bristol-Myers Squibb: Research Funding; Pfizer: Research Funding; Seattle Genetics: Research Funding; Celldex: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Merck & Co: Research Funding.

Abstract Introduction: Outcomes of multidisciplinary and molecular tumor boards have been reported. Lymphoma specific tumor board outcomes have not been reported in the molecular era. In addition, the utility of multi-site, interactive tumor boards using videoconference technology are not widely reported. We prospectively followed the outcomes of a multidisciplinary multi-site lymphoma tumor board in the molecular era and during a change in the revision of the World Health Organization Classification in first published in 2016. Methods: The Mayo Clinic Lymphoma Tumor Board is a component of the international Mayo Clinic Care Network (MCCN). The format includes the clinical case presentation, presentation of radiology and hematopathology findings by the appropriate specialist, proposed treatment options, review of the literature pertinent to the case, and discussion followed by recommendations. Requirement for presentation includes having a diagnosis of lymphoma with pathology reviewed at Mayo Clinic, Rochester, MN (MCR). Pathology and radiology material, when relevant to the case, are required to be reviewed at MCR and presented by MCR pathologists/radiologists. Patients must be presented prospectively, and have active clinical issues or questions to be addressed. Four cases are presented per 60-minute meeting. 309 consecutive highly selected cases with a diagnosis of lymphoma were presented at the Mayo Clinic Lymphoma Tumor Board from 2014 to 2018. The pathology material was independently reviewed by the presenting hematopathologists and radiology material by the presenting radiologist. Participants are office based and included multiple members of the health care team which also incudes pharmacists, clinical research associates affiliated with lymphoma research, and physicians in training. Recommendations were prospectively tracked for changes in radiology interpretation, pathologic diagnosis, and treatment approaches. Actual follow-up of all patients after the meeting was not allowed in the MCCN. Participation in the meeting can be either via in-room attendance at MCR, video conference at a participating MCCN site, or via non-participatory live-stream online. Results: 309 cases were presented were presented from 2014-2018. 258 cases were from MCR, and 51 were not physically seen at MCR. 16 cases were presented at a subsequent meeting for further recommendations in the course of their disease after the initial presentation. 54% of patients presented had changes in some aspect of their care as a result of the meeting. Changes in radiologic interpretation occurred in 5 (1.6%) patients. The pathologic diagnosis changed in 27 (8.7%). Additional testing was recommended in 44 (14%). Clinical management changes were recommended in 90 (29%) cases. These included alterations in treatment approach in 43 (14%), change from undecided to pursuit of treatment 10 (3%), change from undecided regarding treatment approach to further diagnostic testing 4 (1.3%), change from observation to treatment 9 (3%), change from treatment to observation 4 (1.3%), and treatment to further tests in 2 (0.6%) Site in room average attendance (internal/external) was 16.8/8.6. Non-participatory live-stream attendance was not possible to track. In an annual electronic evaluation of this activity, 93% of the responders reported an improvement in knowledge and competence, and 100% recommended no changes to the format of the conference. Enhancements over time have included Continuous Medical Education credit, an in room microscope, and real-time radiology images. Selected cases will now be on line on an international web site. Conclusion: In this highly selected group of lymphoma cases from multiple sites over a 4-year period, 54% of the (167/309) case presentations resulted in changes to some aspect of care as a direct result of this tumor board. A multidisciplinary lymphoma tumor board approach was of value, efficacious, and meaningfully impacted lymphoma patients while substantially enhancing interdisciplinary interactions. Disclosures Ansell: Celldex: Research Funding; Seattle Genetics: Research Funding; Takeda: Research Funding; Bristol-Myers Squibb: Research Funding; Pfizer: Research Funding; Merck & Co: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Affimed: Research Funding.