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Abstract Background Survival rates for older pts with advanced HL (aged ≥60 yrs) were historically poor with doxorubicin, bleomycin, vinblastine and dacarbazine (ABVD). Reasons may include decreased tolerance of therapy, increased toxicity (particularly with bleomycin), comorbidities, and disease biology. The pivotal phase 3 ECHELON-1 study demonstrated superior 2-yr modified progression-free survival (mPFS) with frontline brentuximab vedotin + doxorubicin, vinblastine and dacarbazine (A+AVD) vs ABVD in pts with stage III/IV cHL (Connors JM et al, NEJM 2018). The study allowed entry of older pts, with no upper age limit. Alternative dosing schedules of the A+AVD regimen have been studied (e.g., sequential brentuximab vedotin before and after AVD; NCT01476410, Evens AM et al, J Clin Oncol 2018). We report efficacy and safety results from ECHELON-1 for older pts with cHL and compare these with those for pts aged <60 yrs. Methods mPFS per independent review facility (IRF) for pts ≥60 years was a prespecified subgroup analysis of ECHELON-1. Additional exploratory safety and efficacy analyses were also assessed and compared with younger pts (<60 yrs). The study was not powered for age-based subgroup analyses; p-values are descriptive without multiplicity adjustment. Results 14% (186/1334) of pts in the intent-to-treat (ITT) population were aged ≥60 yrs (A+AVD, n=84; ABVD, n=102) and included in the sub analyses. Median age (range) of older pts was: A+AVD, 68.0 yrs (60-82); ABVD, 66.0 yrs (60-83). Baseline pt and disease characteristics in older pts were similar in both arms. ECOG PS scores were 0 (36% vs 36%), 1 (52% vs 54%), and 2 (12% vs 10%) in A+AVD and ABVD arms, respectively. Pts received a median of 6 cycles with mean relative dose intensities for each drug (%) in older pts of: A+AVD, 92.3, 96.6, 93.3, and 97.9; ABVD, 97.3, 88.7, 93.3, and 95.9. With median follow-up of ~25 months, 2-yr mPFS per IRF was similar in both arms for older ITT pts (A+AVD 70.3% [95% CI: 58.4, 79.4] vs ABVD 71.4% [95% CI: 60.5, 79.8]; HR=1.00 [95% CI: 0.58, 1.72]; p=0.993). An exploratory analysis of standard PFS per investigator (INV) showed HR=0.85 ([95% CI: 0.49, 1.48]; p=0.576) (Table 1). For older pts with stage IV cHL (A+AVD n=51; ABVD n=67), there was an increase in 2-yr PFS per INV with A+AVD vs ABVD (74.0% [95% CI: 59.5, 84.0] vs 59.9% [95% CI: 45.6, 71.5]; HR, 0.66 [95% CI: 0.34, 1.26]; p=0.20); mPFS per IRF improvement with A+AVD in older stage IV pts was lower (HR=0.80; [95% CI: 0.42, 1.53]). In younger stage III/IV pts (<60 yrs) 2-yr mPFS per IRF and PFS per INV were also higher compared with older pts in both arms (Table 1). 66 of 83 older A+AVD pts required ≥1 dose modification of brentuximab vedotin, reasons were: dose reduction (n=27), dose held (n=4), dose delayed (n=51), brentuximab vedotin discontinued (n=17). In older pts, grade (G) 3/4 AEs occurred in 88% of A+AVD pts vs 80% ABVD pts; for younger pts, rates were 82% (A+AVD) vs 63% (ABVD) (Table 2). In older pts there were 3 (4%) on-study deaths in the A+AVD arm (1 each: hemophagocytosis, neutropenic sepsis, and myocardial infarction) and 5 (5%) with ABVD (all pulmonary-related). In pts <60 yrs, there were 6 on-study deaths (1%) with A+AVD vs 8 (1%) with ABVD. G3 neutropenia in older pts was (70%) A+AVD pts vs (59%) ABVD pts, and febrile neutropenia (FN) in 31 (37%) vs 17 (17%) pts. In older pts who had G-CSF primary prophylaxis (PP) neutropenia was seen in 4/10 (40%) A+AVD pts vs 1/9 (11%) ABVD pts (on-study FN in 3 [30%] vs 2 [22%] pts). In older pts, treatment-emergent peripheral neuropathy (PN) was reported in 54 (65%) of A+AVD pts vs 42 (43%) of ABVD pts (G≥3 in 15 [18%] vs 3 [3%] pts), respectively. In pts <60 yrs PN was reported in 388 (67%) A+AVD pts vs 244 (43%) ABVD pts (G≥3 in 55 [9%] vs 8 [1%] pts), respectively. In older pts at last follow-up, 65% (35/54) of A+AVD pts and 60% (25/42) of ABVD pts had complete resolution (A+AVD, 39%; ABVD, 38%) or improvement (A+AVD, 26%; ABVD, 21%) of PN events. 2% older A+AVD pts had pulmonary AEs (both G1/2 pulmonary infiltration) vs 13% older ABVD pts. Conclusions For older ECHELON-1 pts, mPFS and PFS were similar in both arms. In the larger subgroup of younger pts, mPFS and PFS were improved vs older pts. As expected, incidence of treatment-emergent AEs was higher in older pts, with regimen-specific AEs seen, including fatal pulmonary events in ABVD pts. The high incidence of FN in older A+AVD pts points to the need for G-CSF PP. Disclosures Evens: Acerta: Consultancy; Pharmacyclics International DMC: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Affimed: Consultancy; Janssen: Consultancy; Abbvie: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bayer: Consultancy; Tesaro: Research Funding; Novartis: Consultancy. Connors:Merck: Research Funding; Amgen: Research Funding; Takeda: Research Funding; Roche Canada: Research Funding; NanoString Technologies: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Seattle Genetics: Honoraria, Research Funding; Janssen: Research Funding; F Hoffmann-La Roche: Research Funding; Bayer Healthcare: Research Funding; Cephalon: Research Funding; Bristol Myers-Squibb: Research Funding; Lilly: Research Funding; Genentech: Research Funding. Younes:Sanofi: Honoraria; Merck: Honoraria; Astra Zeneca: Research Funding; Celgene: Honoraria; Incyte: Honoraria; Seattle Genetics: Honoraria; Bayer: Honoraria; Novartis: Research Funding; Curis: Research Funding; J&J: Research Funding; Genentech: Research Funding; Takeda: Honoraria; Roche: Honoraria, Research Funding; Abbvie: Honoraria; Janssen: Honoraria, Research Funding; Pharmacyclics: Research Funding; BMS: Honoraria, Research Funding. Ansell:Merck & Co: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Celldex: Research Funding; Bristol-Myers Squibb: Research Funding. Radford:Takeda: Consultancy, Research Funding, Speakers Bureau; GlaxoSmithKline: Equity Ownership; AstraZeneca: Equity Ownership; Seattle Genetics: Consultancy, Speakers Bureau; ADC Therapeutics: Consultancy, Research Funding; Novartis: Consultancy, Speakers Bureau; Pfizer: Research Funding; Celgene: Research Funding; BMS: Consultancy, Speakers Bureau. Feldman:Seattle Genetics: Research Funding, Speakers Bureau; Janssen: Speakers Bureau; Pharmacyclics: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Celgene: Speakers Bureau; Portola: Research Funding; KITE: Speakers Bureau. Tuscano:Takeda: Research Funding; Genentech: Consultancy, Research Funding; Amgen: Honoraria, Speakers Bureau; Seattle Genetics: Honoraria, Speakers Bureau; Celgene: Honoraria, Research Funding, Speakers Bureau; Pharmacyclics: Research Funding. Oki:Seattle Genetics: Research Funding; Takeda Millenium: Honoraria, Research Funding; Jazz Pharmaceuticals: Employment. Grigg:Roche: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Pocock:Kent & Canterbury Hospital: Employment. Dlugosz-Danecka:Roche: Consultancy; Servier: Consultancy. Fenton:Seattle Genetics, Inc.: Employment, Equity Ownership. Engley:Seattle Genetics: Employment. Liu:Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Miao:Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Jolin:Takeda Pharmaceuticals International Co.: Employment. Gautam:Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Gallamini:Takeda: Consultancy, Speakers Bureau.

Abstract Background: The pivotal phase 3 ECHELON-1 study demonstrated superior efficacy of brentuximab vedotin plus doxorubicin, vinblastine and dacarbazine (A+AVD) versus doxorubicin, bleomycin, vinblastine and dacarbazine (ABVD) in patients with previously untreated advanced stage classical Hodgkin lymphoma (cHL) with a 2-year modified progression-free survival (mPFS) of 82.1% in the A+AVD group versus 77.2% in the ABVD group (Hazard Ratio=0.77; 95% confidence interval [CI] 0.60, 0.98; p=0.04). PN is a known toxicity associated with anti-mitotic agents, including vinblastine and the MMAE component of brentuximab vedotin. In the ECHELON-1 study, the incidence of any-grade PN events was 67% (442 of 662 patients) and 43% (286 of 659 patients) in the A+AVD and ABVD arms, respectively; the incidence of grade ≥3 PN was 11% and 2%, respectively. At the time of the initial analysis, 67% of A+AVD-treated patients had either resolution (43%) or improvement (24%) of PN events. A total of the 92% of ongoing PN events were grade 1 (64%) or grade 2 (29%). Here, we report rates of PN resolution and improvement in patients participating in the ECHELON-1 study after long-term follow-up. Methods: Patients with Stage III or IV cHL were randomized 1:1 to receive up to six cycles of A+AVD (n=664) or ABVD (n=670). Pre-existing PN was an exclusion factor at study entry. Peripheral neuropathy was determined on the basis of a standardized MedDRA query; patients who developed PN were monitored throughout the study and those with ongoing PN at end of treatment were followed for resolution or improvement during the post-treatment follow-up period; follow-up visits were scheduled for every 12 weeks ±1 week until 36 months, then every 6 months until study closure. PN resolution was defined as completely resolved and improvement was defined as improved by ≥1 grade from worst grade as of the latest assessment. Results: At the time of the primary analysis, 51% (226/442) and 61% (174/286) of patients in the A+AVD and ABVD arms, respectively, had resolution or improvement of PN events at EOT. Upon continued follow-up (~10 additional months) for approximately 30 months (range 0-78.5) after end of treatment, 76% (335/442) of patients with PN in the A+AVD arm had either complete resolution (59%, 260/442) or improvement (17%, 75/442) of their PN events compared with 82% (234/286) with either resolution (72%) or improvement (10%) in the ABVD arm. In the A+AVD arm, 90% of ongoing PN cases (n=182) were grade 1/2; grade 1=58% (n=106), grade 2=32% (n=58). Residual grade 3 PN was reported in 9% (n=17) of patients (1 patient with grade 4 PN died before resolution). In the ABVD arm, residual PN (n=81) was grade 1 (65%; n=53), grade 2 (30%; n=24), and grade 3 (5%; n=4). For the subset of patients with PN that had not resolved by end of treatment, the median time to resolution of all PN events from AE start date was 28 weeks for A+AVD and 14 weeks for ABVD, the median time to improvement of PN was 39 weeks for A+AVD and 18.5 weeks for ABVD. Conclusions: After approximately 2.5 years of continued follow-up, PN continues to resolve and improve for patients who were treated with A+AVD or ABVD in the ECHELON-1 study. In both study arms, the majority of ongoing PN cases are grade 1 or grade 2. Further follow-up is ongoing. Disclosures Radford: Celgene: Research Funding; ADC Therapeutics: Consultancy, Research Funding; Seattle Genetics: Consultancy, Speakers Bureau; GlaxoSmithKline: Equity Ownership; Takeda: Consultancy, Research Funding, Speakers Bureau; Pfizer: Research Funding; BMS: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; AstraZeneca: Equity Ownership. Connors:Takeda: Research Funding; Seattle Genetics: Honoraria, Research Funding; Roche Canada: Research Funding; Genentech: Research Funding; Cephalon: Research Funding; Bristol Myers-Squibb: Research Funding; Janssen: Research Funding; Bayer Healthcare: Research Funding; NanoString Technologies: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Merck: Research Funding; F Hoffmann-La Roche: Research Funding; Amgen: Research Funding; Lilly: Research Funding. Younes:Astra Zeneca: Research Funding; J&J: Research Funding; Curis: Research Funding; BMS: Honoraria, Research Funding; Bayer: Honoraria; Takeda: Honoraria; Sanofi: Honoraria; Roche: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Merck: Honoraria; Seattle Genetics: Honoraria; Celgene: Honoraria; Incyte: Honoraria; Abbvie: Honoraria; Novartis: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding. Gallamini:Takeda: Consultancy, Speakers Bureau. Ansell:Affimed: Research Funding; Merck & Co: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Bristol-Myers Squibb: Research Funding; Celldex: Research Funding; Seattle Genetics: Research Funding. Gopal:Aptevo: Consultancy; Janssen: Consultancy, Research Funding; Merck: Research Funding; Gilead: Consultancy, Research Funding; Brim: Consultancy; Spectrum: Research Funding; Takeda: Research Funding; BMS: Research Funding; Pfizer: Research Funding; Seattle Genetics: Consultancy, Research Funding; Incyte: Consultancy; Teva: Research Funding; Asana: Consultancy. Flinn:Trillium: Research Funding; Calithera: Research Funding; Forma: Research Funding; Portola: Research Funding; Verastem: Research Funding; Janssen: Research Funding; Infinity: Research Funding; Genentech: Research Funding; Forty Seven: Research Funding; Constellation: Research Funding; Merck: Research Funding; Curis: Research Funding; Takeda: Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Research Funding; Incyte: Research Funding; ArQule: Research Funding; Verastem: Consultancy, Research Funding; Celgene: Research Funding; Agios: Research Funding; Novartis: Research Funding; Gilead: Research Funding; Pfizer: Research Funding; TG Therapeutics: Research Funding; Kite: Research Funding; BeiGene: Research Funding. Pettengell:CTI: Honoraria; Pfizer: Honoraria; Roche: Honoraria; Servier: Honoraria; Takeda: Honoraria. Dlugosz-Danecka:Servier: Consultancy; Roche: Consultancy. Engley:Seattle Genetics: Employment. Fenton:Seattle Genetics, Inc.: Employment, Equity Ownership. Liu:Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Purevjal:Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Miao:Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Gautam:Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Kuruvilla:Janssen: Consultancy, Honoraria, Research Funding; Princess Margaret Cancer Foundation: Research Funding; BMS: Consultancy, Honoraria; Abbvie: Consultancy; Karyopharm: Honoraria; Celgene: Honoraria; Seattle Genetics: Consultancy, Honoraria; Lundbeck: Honoraria; Merck: Consultancy, Honoraria; Amgen: Honoraria; Roche: Consultancy, Honoraria, Research Funding; Gilead: Consultancy, Honoraria; Leukemia and Lymphoma Society Canada: Research Funding.

Abstract Background: The phase 3 ECHELON-1 study assessed frontline brentuximab vedotin administered with doxorubicin, vinblastine, and dacarbazine (A+AVD) vs doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) in patients (pts) with advanced cHL (NCT01712490). The primary endpoint of ECHELON-1, modified PFS (mPFS) per independent review facility (IRF), is defined as (1) progressive disease, (2) death, or (3) subsequent anticancer therapy (chemotherapy [chemo] and/or radiotherapy [RT]) following detection of a non-complete response (non-CR = Deauville score 3-5) at end of frontline therapy. A+AVD was superior to ABVD (hazard ratio [HR]=0.77; p=0.035) with 2-year mPFS rates of 82.1% and 77.2%; as previously reported. In pts with newly diagnosed cHL, the aim of frontline therapy is curative. Pts who do not achieve a satisfactory response to frontline therapy may initiate subsequent anticancer therapy prior to response criteria-defined progression. The measurement of traditional PFS becomes confounded, as pts may effectively be rescued from criteria-defined progression by subsequent treatment, resulting in an overestimation of PFS with frontline therapy (Connors et al. Haematologica 2016;101[s5]:22-3[P007]). To further evaluate modified and traditional PFS in the ECHELON-1 study, two sensitivity analyses were conducted. Methods: 1334 pts with Stage III (36%) or IV (64%) cHL were randomized 1:1 to receive A+AVD (n=664) or ABVD (n=670) on days 1 and 15, for up to six 28-day cycles. In addition to mPFS per IRF, mPFS per investigator (INV) was collected. A sensitivity analysis (mPFS-chemo) was performed in which RT following a non-CR at the completion of frontline therapy was not counted as an event: in this case, mPFS-chemo was defined as (1) progression, (2) death, or (3) receipt of additional anticancer chemo excluding RT for pts who are not in CR after completion of frontline therapy. A second sensitivity analysis of traditional PFS (PFS-traditional), defined as (1) progression or (2) death, was also performed. All analyses were performed per INV as, per protocol, IRF follow up of pts was not conducted after the initiation of subsequent therapy. Results: At 2 years, the rates of mPFS per INV (95% CI) for A+AVD vs ABVD were 81.0% (77.6-83.9%) vs 74.4% (70.7-77.7%), respectively; HR=0.72 (95% CI: 0.573, 0.914; p=0.006). Concordance between IRF and INV mPFS assessments was high among all pts in both arms, at 91%. A total of 123 mPFS events per INV were observed among pts treated with A+AVD, including 73 pts with PD, 15 deaths, and 35 who received additional anticancer therapy following evidence of non-CR at the end of frontline therapy, vs 164 per INV mPFS events among pts treated with ABVD, of which 103 were PD, 22 were deaths, and 39 were additional anticancer therapy following evidence of non-CR at the end of frontline therapy. Of the 35 (A+AVD) and 39 (ABVD) additional anticancer therapy events, chemo/RT following evidence of non-CR at the end of frontline therapy accounted for 11/24 and 17/22 of these events, respectively. For mPFS-chemo, a larger benefit in favor of A+AVD vs ABVD, with a HR=0.687 (95% CI: 0.534, 0.885; p=0.003), was observed. The 2-year mPFS-chemo (95% CI) was estimated as 84.0% (80.9-86.7%) for pts treated with A+AVD vs 77.3% (73.7-80.4%) for pts treated with ABVD. A total of 103 events were observed among pts in the A+AVD arm, including 78 pts with PD, 15 deaths, and 10 who received additional chemo following evidence of a non-CR at the end of frontline therapy, vs 145 events among pts treated with ABVD, of which 106 were PD, 22 were deaths, and 17 were additional chemo following evidence of non-CR at the end of frontline therapy. For PFS-traditional, an advantage in favor of A+AVD vs ABVD was also observed: HR=0.70 (95% CI: 0.54-0.91; p=0.006). The 2-year PFS estimate (95% CI) was 84.2% (81.1-86.9%) for A+AVD vs 78.0% (74.4-81.1%) for ABVD. In total, there were 101 PFS events in the A+AVD arm, including 86 pts with PD and 15 deaths; vs 140 PFS events in the ABVD arm, including 118 pts with PD and 22 deaths. Conclusions: Consistent with the primary outcome of ECHELON-1, a benefit in favor of A+AVD vs ABVD was observed independent of the inclusion of additional anticancer RT or chemo as survival events, in addition to progression or death. A traditional PFS assessment including only progression or death events demonstrated that A+AVD resulted in a 30% reduction in the risk of progression or death compared to ABVD. Figure. Figure. Disclosures Connors: Lilly: Research Funding; Bayer Healthcare: Research Funding; Janssen: Research Funding; Bristol Myers-Squibb: Research Funding; Merck: Research Funding; NanoString Technologies: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Seattle Genetics: Honoraria, Research Funding; Roche Canada: Research Funding; Amgen: Research Funding; Genentech: Research Funding; F Hoffmann-La Roche: Research Funding; Cephalon: Research Funding; Takeda: Research Funding. Younes:J&J: Research Funding; Celgene: Honoraria; BMS: Honoraria, Research Funding; Sanofi: Honoraria; Abbvie: Honoraria; Curis: Research Funding; Genentech: Research Funding; Merck: Honoraria; Bayer: Honoraria; Pharmacyclics: Research Funding; Janssen: Honoraria, Research Funding; Novartis: Research Funding; Incyte: Honoraria; Seattle Genetics: Honoraria; Roche: Honoraria, Research Funding; Astra Zeneca: Research Funding; Takeda: Honoraria. Gallamini:Takeda: Consultancy, Speakers Bureau. Ansell:Pfizer: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Takeda: Research Funding; Merck & Co: Research Funding; Celldex: Research Funding; Seattle Genetics: Research Funding. Kim:J&J: Research Funding; Kyowa-Kirin: Research Funding; Mundipharma: Research Funding; Celltrion: Honoraria, Research Funding; Novartis: Research Funding; Takeda: Research Funding; Roche: Honoraria, Research Funding; Eisai: Honoraria, Research Funding; Celgene: Research Funding; Merck: Research Funding. Advani:Janssen: Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Cell Medica: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Forty Seven Inc.: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Kura: Research Funding; Kyowa: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Merck: Research Funding; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Celgene: Research Funding; Autolus: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Millenium: Research Funding; Agensys: Research Funding; Infinity: Research Funding; Regeneron: Research Funding; Celgene: Research Funding; Gilead/Kite: 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; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board. Bartlett:KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; ImaginAB: Research Funding; Celgene: Research Funding; Pharmacyclics: Research Funding; Pharmacyclics: Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees; Millennium: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Meyers Squibb: Research Funding; Immune Design: Research Funding; Astra Zeneca: Research Funding; Forty Seven: Research Funding; Affimed: Research Funding; Genentech: Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Merck & Co: Research Funding; Janssen: Research Funding. Straus:Onco Tracker: Consultancy; Roch China: Speakers Bureau; Memorial Sloan Kettering Cancer Center: Employment; JUNO: Consultancy; Medical Crossfire: Speakers Bureau; DAVA Oncology: Consultancy, Honoraria; Bayer: Consultancy; InPractice Elselvier: Consultancy; Millenium (Takeda): Consultancy, Research Funding; Seattle Genetics: Consultancy. Sureda:BMS: Consultancy, Honoraria; Sanofi: Honoraria; Roche: Honoraria; Takeda: Consultancy, Honoraria, Speakers Bureau; Merck: Consultancy, Honoraria. Hutchings:Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche/Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Dlugosz-Danecka:Servier: Consultancy; Roche: Consultancy. Engley:Seattle Genetics: Employment. Fenton:Seattle Genetics, Inc.: Employment, Equity Ownership. Liu:Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Miao:Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Jolin:Takeda Pharmaceuticals International Co.: Employment. Gautam:Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Radford:Novartis: Consultancy, Speakers Bureau; Celgene: Research Funding; Pfizer: Research Funding; GlaxoSmithKline: Equity Ownership; Takeda: Consultancy, Research Funding, Speakers Bureau; AstraZeneca: Equity Ownership; Seattle Genetics: Consultancy, Speakers Bureau; BMS: Consultancy, Speakers Bureau; ADC Therapeutics: Consultancy, Research Funding.

Abstract Background: Blinatumomab is an investigational bispecific T-cell engager (BiTE®) antibody construct designed to direct cytotoxic T cells to CD19-expressing B cells. In a study in minimal residual disease (MRD)-positive ALL, 80% of pts achieved MRD-negative status after receiving one treatment cycle of blinatumomab (Topp MS, et al. J Clin Oncol. 2011;29:2493-8). For pts with newly diagnosed ALL, persistence of MRD after first-line treatment predicts disease recurrence. However, only limited data are available about the relationship between MRD and outcome in adult pts with r/r ALL. Therefore, the aim of this secondary analysis was to evaluate MRD responses and their relationships to other efficacy indices in adult pts with r/r ALL receiving blinatumomab in this phase 2 study. Methods: Eligibility criteria included adult pts ≥18 years, with Philadelphia chromosome negative B-cell r/r ALL who were primary refractory or refractory to first salvage, had their first relapse within 12 months of first remission or allogeneic hematologic stem cell transplantation (HSCT), or received second or later salvage. Blinatumomab was dosed via continuous IV infusion at 28 μg/d (cycle 1 only: 9 μg/d on days 1-7, 28 μg/d on days 8-28) for up to five cycles (one cycle: 4 weeks on, 2 weeks off). The primary endpoint was complete remission (CR: ≤5% blasts with platelets >100,000/µL, absolute neutrophil count >1000/µL) or CR with partial hematologic recovery (CRh*: platelets >50,000/µL, absolute neutrophil count >500/µL) within the first two treatment cycles. MRD in bone marrow was assessed at a central laboratory using allele-specific real-time quantitative PCR. Two MRD-based exploratory endpoints were analyzed: MRD response (no PCR amplification at a minimum sensitivity of 10-4 or <10-4 leukemic cells by PCR) and complete MRD response (no PCR amplification at a minimum sensitivity of 10-4) within the first two treatment cycles. Results: Of 189 treated pts (median [range] age = 39 [18–79] years), 81 (43%) pts had a CR (n = 63, 33%) or a CRh* (n = 18, 10%) during the first two treatment cycles. In the subgroup of pts with a CR/CRh* and evaluable MRD data (n = 73), 60 (82%) pts had an MRD response. Of those, 51 (70%) pts had a complete MRD response. The majority of those who achieved a CR/CRh* also achieved a complete MRD response regardless of the number of prior lines of salvage therapy (Table 1). Of all treated pts, 64 (34%) pts had prior HSCT. In pts who achieved CR/CRh*, the rate of MRD response was 81% in pts without and 85% in pts with prior HSCT. In pts who achieved CR/CRh*, the median (95% CI) duration of overall survival was 11.4 (8.5, not estimable) months for those with a MRD response and 6.7 (2.0, not estimable) months for those with no MRD response. The median (95% CI) duration of relapse-free survival was 6.9 (5.5, 10.1) months in patients with a MRD response and 2.3 (1.2, not estimable) months in patients with no MRD response. The HSCT realization rate did not differ significantly between pts with CR/CRh* and a MRD response and those with CR/CRh* and no MRD response (31% and 43%, respectively). Seventeen pts classified as nonresponders per protocol had ≤5% blasts and no evidence of disease, but recovery of peripheral counts did not meet criteria for CRh*. Ten of these 17 pts had evaluable MRD assessments; 50% (5/10) had MRD response and 20% (2/10) had complete MRD response. The clinical significance of this finding remains open. Grade ≥3 adverse events regardless of causality and occurring in >10% of all treated pts during treatment until 30 days after treatment were febrile neutropenia (25%), neutropenia (16%), and anemia (14%). Grade 3 cytokine release syndrome (CRS) was reported in three (1.6%) patients. Three (1.6%) patients had grade 4 neurologic events, all resolved. Twenty-one (11%) patients had grade 3 neurologic events, 17 were resolved, with 4 events unresolved at death or unknown. Conclusion: In this largest study to date of adult pts with r/r ALL with PCR-based central assessment of MRD, pts who achieved CR/CRh* during single-agent treatment with blinatumomab had high MRD response rates. The exploratory analyses suggested that within pts with a CR/CRh*, those who did not achieve MRD responses tended to have shorter durations of overall and relapse-free survival. These results are consistent with prior reports highlighting the importance of achieving an MRD response in first-line therapy. Disclosures Goekbuget: Amgen Inc.: Consultancy, Honoraria, Research Funding. Off Label Use: This presentation will discuss the off-label use of blinatumomab, as this agent is not approved for use by the FDA, EMA or any other regulatory authorities. Kantarjian:Amgen Inc.: Research Funding. Brüggemann:Amgen Inc.: Consultancy, Research Funding. Stein:Amgen Inc.: Membership on an entity's Board of Directors or advisory committees. Bargou:Amgen Inc.: Consultancy, Honoraria. Dombret:Amgen Inc.: Research Funding. Heffner:Amgen Inc.: Honoraria, Research Funding; Biotest: Research Funding; Dana Farber CI: Research Funding; Genentech: Research Funding; Gilead: Research Funding; Idera: Research Funding; Janssen: Research Funding; Pfizer: Research Funding; Pharmacyclics: Honoraria, Research Funding; Onyx: Research Funding; Spectrum: Research Funding; Talon Therapeutics: Research Funding. Rigal-Huguet:Amgen, Inc.: Consultancy; Ariad: Consultancy; BMS: Consultancy; Novartis: Consultancy; Pfizer: Consultancy. Litzow:Amgen Inc.: Honoraria, Research Funding. Zugmaier:Amgen Reseach (Munich) GmbH: Employment; Amgen Inc.: Equity Ownership. Jia:Amgen Inc.: Employment, Equity Ownership. Maniar:Amgen Inc.: Employment, Equity Ownership. Huber:Amgen Research (Munich) GmbH: Employment; Amgen Inc.: Equity Ownership. Nagorsen:Amgen Inc.: Employment, Equity Ownership, Related to blinatumomab Patents & Royalties. Topp:Amgen Inc.: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction: Novel substances such as the next generation IMiD pomalidomide or the recently approved next generation proteasome inhibitor carfilzomib (Cfz) have considerably expanded our treatment options in MM, both of them influencing multiple myeloma (MM) interaction with bone marrow stroma cells (BMSCs), that provides an interesting target for anti MM therapy. More compounds directed at this disease critical crosstalk are currently under investigation, however the development of novel drugs remains inefficient, displayed by a substantial drop out rate of the 376 preclinical single agents tested since 1961 (Rongvaux, Annu Rev Immunol. 2013; Schüler, Expert Opin Biol Ther. 2013; Kortüm, CLML 2014). Our focus in the projected presented here was to develop a novel bone-derived in vitro 3D co-culture model specifically adapted to mimic the BM niche to more closely study the role of bone and BM bystander cells and to perform more reliable ex vivo compound screening in MM. Methods: Previous 2D models were compared to a novel 3D co-culture model (agarose matrix interlayer, 100 microwells/cm², 1.5mm in depth, permeable for oxygen+cytokines, but not for BMSCs utilizing U266, RPMI-8226, OPM-2 and primary BM patient (pt) cells, with and without HS-5 vs. M210B4 stroma support (Fig. A + Fig. B.a. for pt characteristics). Analyses covered Trypan Blue, Annexin/PI, MTT, FACS, cell cycle analyses and H2B-mCherry/cytochrome c-GFP assays (Udi, Br J Hematol. 2013). In a next step, primary bone-derived stroma cells were acquired from bones of C57BL/6 J mice. Bones were flushed, digested and FACS sorted in order to acquire single BM and bone bystander cell subtypes (MSPCs [mesenchymal stem and progenitor cells], endothelial cells, osteoblasts, PAS [PDFGRalphaSca1] and CaRs [CXCL12-abundant reticular cells]) which were then compared to HS-5 and M210B4 with regard to growth support, cytokine secretion and protection from anti-MM substances. Results: MMCLs and pt specimens were cultured at different concentrations (10 vs. 100 cells per microwell) with and without M210B4 demonstrating a growth advantage with vs. without M210B4 (Fig. B.b). Liquid overlay technique allowed cluster formation of pt specimens leading to more reliable propagation of pt material for up to 20d of culture. Apoptotic changes were assessed by confocal microscopy of RPMI8226 co-expressing fluorescently labelled histone 2B-mCherry (red) and cytochrome c-GFP (green) as indicators of late and early apoptosis. Comparing BMSCLs with regard to their MM growth support capacities, human HS-5 proved even more beneficent than M210B4 stroma (Fig. B.b). Phenotypic analyses of pt specimens showed decreased CXCR4 expression with vs. without BMSCs suggesting a dynamic regulation of homing molecules. The model was then used as an ex-vivo platform allowing both cytotoxicity and cell cycle analyses for the combination of bortezomib (Btz) vs. Cfz with ARRY-520 (kinesin spindle protein inhibitor). Btz (10nM) and Cfz (20nM) proved significantly cytotoxic compared to the control (U266 and pt specimens, respectively) after 48h of single agent treatment Fig.B.c). Compared to Btz (10nM, B10) and Cfz (20nM, C20) as single agents, the additional combination with ARRY-520 showed stronger additive cytotoxicity for Btz (A5+B10, median: 37.5% vs. 13.1%) than for Cfz (A5+C20, 38.6% vs. 34.1%). To note, the model could also be utilized for more profound analyses as depicted for G2/M cell cycle studies in Fig.B.d. 5nM ARRY-520 (A5) led to significant accumulation of OPM-2 cells in G2/M arrest after 48h of treatment confirming prior analyses (Hernández-Garcia Blood Suppl 4710,2014; Fig. B.d). Co-culture studies with different subsets of BM and bone-derived bystander cells are currently ongoing and will be presented at the meeting (Fig. B.e). Conclusions: More complex, 3D bone-derived high-throughput in vitro models are urgently needed to better predict the potency of preclinically tested agents and to better estimate the likelihood of their later clinical adoption into phase I-II trials. With this work, we provide an innovative model which reflects the BM microenvironment as a crucial predictor for in-vivo sensitivity as shown for ARRY-5200. This ex-vivo approach helps to better incorporate MM growth support by bone and BM-derived bystander cells and thus depicts a valid tool to better characterize the role of the BM niche in myeloma. Figure 1. Figure 1. Disclosures Engelhardt: Deutsch Krebshilfe: Other: grant. Wäsch:German Cancer Aid: Research Funding; Comprehensiv Cancer Center Freiburg: Research Funding; Janssen-Cilag: Research Funding; MSD: Research Funding.

Abstract Introduction: Customized gene panel sequencing is an attractive approach to genomic tumor characterization in clinical care. Based on published MM exome data we developed a MM Mutation Panel (M3 P) that includes the most commonly mutated genes, actionable drug targets, genes targeted by current standard of care (SOC) therapies and which allows tracking of clonal evolution, copy number and sample purity. Methods and Material: M3 P (v3.0) covers 88 genes (1327 amplicons, 181kb). MM samples from 504 patients (pts) have been analyzed (corresponding germline in 81%) through collaborations between Mayo Clinic and Hospital-12-de-Octubre (Madrid, Spain), the DSMM and GMMG (Würzburg, Ulm, Freiburg and Heidelberg, Germany) and the HOVON trial groups (Rotterdam, The Netherlands). The investigated cohort includes 410 untreated pts (81%), which includes a high risk cohort of 72 pts with del17p, 25 paired samples with later follow up from the same cohort, and 94 relapsed patients, of which 50 were relapsed and refractory. Results: Overall coverage per mutation averaged >500x depth. We identified 945 variants (1.9 per pt) and in 83% of the pts a mutation was found. Clonal heterogeneity was assessed with mutations ranging from 3%-100% variant reads suggesting the presence of a significant number of subclones (e.g. 21% of mutations were in < 10% of reads). The mutation incidence was compared with and closely resembles the most recent MM comprehensive genomic data from the MMRF CoMMpass study: We compare here all pts sequenced by M3 P, untreated pts sequenced by M3 P and CoMMpass: KRAS (24%/23%/24%), NRAS (20%/20%/18%), DIS3 (13%/14%/10%), BRAF (9%/7%/6%), FAM46C (6%/6%/8%) and TRAF3 (6%/6%/7%). TP53 mutation incidence, however, was significantly increased in our cohort (14%/12%/4.2%), a difference explained by the inclusion of del17p (untreated) and relapsed refractory MM in panel sequenced pts, cohorts with elevated incidences of TP53 mutations (32% / 26% respectively). Potentially actionable targets include BRAF mutationsin 43 patients (9%), with druggable p.V600E in 19 or 5%, 8 pts (2%) with FGFR3 (p.R248C and p.G375C one patient each), p.R132 mutation in 4 out of 5 IDH1 (1%) and p.R172K IDH2 mutation in 1 of 3 (1%) pts. Mutations in the MAPK pathway (NRAS, KRAS, BRAF) were detected in 59% of pts, ranging from 36% untreated MM to 72% in refractory MM. Similarly, the CRBN/CUL4B/IKZF1/IKZF3/IRF4 pathway, important for IMiD function, harbored a significant enrichment of mutations in advanced disease (6% untreated vs 17% relapsed), including CRBN mutations (0.5% vs 7%). Nine of 17 IRF4 mutations were located at the p.K123R hotspot, with minor difference between early or late disease (1% vs 3%). Notably, in 8 of 9 pts with CRBN mutation and clinical information, all were unresponsive to IMiD therapy, supporting association of these mutations with resistance to IMiDs. Conversely, M3 P genes related to other SOC therapies, including NR3C1 (targeted by steroids) and 5 proteasome subunit genes (proteasome inhibitors), were rarely mutated across the cohorts not exceeding 1% mutation incidence for each gene. Significant differences in DIS3 and FAM46C mutation incidences were observed across cohorts: DIS3 mutations are more common in untreated pts with a 1.7 fold increased predominance (14% untreated and 8% treated). FAM46C has an expected incidence of 8% but was rarely mutated in untreated del17p high risk disease with only one of 100 patients harboring both mutations. The significance of this finding needs to be determined but implies a possible overlap in function. Finally we assessed impact on survival of the mutation variants identified in 142 untreated Mayo patients and found STAT3 mutations negatively impacting PFS (p=0.034) and OS (p=0.001). This gene is rarely mutated in MM (2% of the total cohort) thus the sample size was small and this finding needs further validation. Conclusion: We here describe 504 MM patients sequenced using the M3 P gene panel, which identified mutations in >80% of investigated patients, overlaps well with published whole exome sequence data and provides clinically relevant information. New findings were the high frequency of minor clones, the relative lack of overlap of del17 and FAM46C mutation, a higher frequency of DIS3 mutation at diagnosis compared to relapse, the prognostic significance of STAT3 mutation and the frequent presence of CRBN pathway mutation in drug resistant relapsed patients. Disclosures Sonneveld: Janssen-Cilag, Celgene, Onyx, Karyopharm: Honoraria, Research Funding; novartis: Honoraria. Mai:Janssen-Cilag: Other: Travel Grant; Onyx: Other: Travel Grant; Mundipharma: Other: Travel Grant; Celgene: Other: Travel Grant. Goldschmidt:Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Onyx: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Millenium: Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Chugai: Honoraria, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Knop:Celgene Corporation: Consultancy. Kull:Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees. Martinez-Lopez:Novartis: Honoraria, Research Funding; Bristol-Meyer Squibb: Honoraria; Celgene: Honoraria; Janssen: Honoraria. Einsele:Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau; Amgen/Onyx: Consultancy, Honoraria, Speakers Bureau. Raab:Novartis: Research Funding. Stewart:Oncospire Inc.: Equity Ownership; Celgene: Consultancy; Novartis: Consultancy; BMS: Membership on an entity's Board of Directors or advisory committees.

Abstract Abstract 1567 Fusions of the tyrosine kinase domain of JAK2 with multiple partners occur in leukemia/lymphoma where they are believed to promote JAK2-oligomerization and autonomous signalling although the underlying mechanisms remain unclear. Affected entities are candidates for therapy with JAK2 signalling inhibitors. Among 200 peripheral T-cell lymphomas surveyed, we identified only two with JAK2 amplification and none with JAK2 translocations, confirming their rarity in T-cell neoplasias. Here we describe the genomic, transcriptional and signalling characteristics of PCM1-JAK2 formed by t(8;9)(p22;p24) in cell lines established at indolent and aggressive phases of a cutaneous T-cell lymphoma. To investigate signalling, PCM1-JAK2 was subjected to lentiviral knockdown which inhibited 7 genes most upregulated in t(8;9) cells, notably SOCS2/3. SOCS3, but not SOCS2, was also upregulated in a chronic eosinophilic leukemia bearing PCM1-JAK2. Conversely, expression of GATA3, a key T-cell developmental gene silenced in aggressive phase cells, was partially restored by PCM1-JAK2 knockdown. Activation of the tumor suppressor SOCS3 by PCM1-JAK2 may follow structural alteration of JAK2 affecting the ternary complex it forms with SOCS3 and receptor proteins. Treatment with JAK2 inhibitor (TG101348) to which MAC-1/2A/2B cells were conspicuously sensitive mimicked knockdown results, highlighting JAK2 as the active moiety. PCM1-JAK2 signalling required pSTAT5 as reported for JAK2V617F or ETV6/TEL-JAK2, thus extending the paradigm of STAT5 activation by JAK2 alterations in hematopoietic malignancies. MAC-1/2A/2B are the first JAK2– translocation cell line models. Our data support further investigation of SOCS2/3 as signalling effectors, prognostic indicators and potential therapeutic targets in cancers with JAK2 rearrangements. Disclosures: No relevant conflicts of interest to declare.

Abstract Introduction: In the past decade, substantial progress has been made in the understanding of multiple myeloma (MM) cell biology and its interaction with the bone marrow microenvironment (BMM). Binding of MM cells to BM stroma cells (BMSCs) alters the expression of SDF-1α and its receptor CXCR4, leading to the secretion of anti-apoptotic cytokines, promoting tumor growth, drug resistance and migration. MM cancer stem cells migrate to endosteal BM niches, where they escape therapies in a quiescent state causing relapse in the course of the disease. The development of novel agents that aim to target the MM and BMM interaction includes drugs as promising as 2nd and 3rdgeneration IMIDs or proteasome inhibitors. Despite these profound advances, the failure rate of preclinically proven cytotoxic single substances is sizeable, as preclinical models often lack the biological, genetic, etiological and immunological properties of the disease (Schüler, Expert. Opin. Biol. Ther. 2013; Kortüm. CLML 2014; Rongvaux. Annu Rev Immunol 2013). Methods & Results: We have previously demonstrated that BM interaction and homing to niches, mediated by the adhesion molecules CXCR4, CD49d and CD44, protect MM cell lines (MMCL) and primary plasma cells (PC) from the cytotoxic effect of anti-MM agents, such as bortezomib (Bor), vorinostat (Vor) and pomalidomide (Pom). Our in vitro and in vivo observed cytotoxic effects from Bor, Vor and Pom confirmed their potent cytotoxicity, whereas cocultivation with M2-10B4 substantially reduced apoptosis and induced tumor protective effects. Additional treatment with the CXCR4 inhibitor AMD3100 blocked CXCR4 in coculture, but left CD49d, CD44 and CD11a widely unchanged. Toxic or therapeutic effects from AMD3100 monotherapy were excluded for the doses used. Comparison of the CXCR4 antibody (ab)-clones 12G5, 44717 and 4G10 revealed that AMD3100 treatment of U266 cells reduced CXCR4 expression with use of 12G5 and 44717, whereas binding of both FITC- and PE-coupled 4G10 was not influenced, making the latter the most reliable for CXCR4 analysis. Use of image cytometry (IC) allowed accurate visualization of co-localisation of CXCR4 expression both on the cell surface and within the cytoplasm of MM cells. IC correlated with flow cytometry-determined CXCR4 expression and allowed the detailed assessment of treatment studies with and without anti-MM agents and AMD3100. Of note, AMD3100 resensitized MM cells to Bor, Vor and Pom (Waldschmidt. Blood 2012:2450), whereas carfilzomib (Cfz) reduced CXCR4 expression in MMCL and could not be antagonized by stroma coculture. Cfz sensitivity was not increased by adding AMD3100 (Simon. Blood 2013:3851). These preclinical studies need additional adaptation to the clinical setting in order to surpass prior drug failure rates, and there is a need to develop more broadly available and better predictive preclinical systems. Therefore, we are currently assessing a 3D co-culture MM model composed of agarose matrix interlayers, based on a novel liquid overlay technique. This model has been specifically adapted to MM cell and BM component interactions as described (Udi. BJH 2013; Zlei. Exp Hematol 2007; Schüler. EOBT 2013). MM cells are cultivated in conical microwells of a non-adherent agarose matrix after BMSCs were plated on the bottom of each plate, allowing the diffusion of soluble cytokines but no direct contact between BMSC and MMCL. Therein, we are presently testing novel anti-MM substances in comparison to our standard-coculture system. Conclusion: Targeting microenvironmental mediators, like SDF-1α and CXCR4, is a promising approach to expand the choice of antimyeloma agents and amplify the effects of established antimyeloma drugs, as previously shown by us and others for the combination of AMD3100 and Bor or Pom. However, as our knowledge on MM and its BMM has dramatically increased a great effort has been made in the preclinical testing of promising new anti-MM agents, and more complex high-throughput in vitro models are urgently needed to better predict the potency of these substances in order to reduce dropouts in clinical trials. We hereby provide a novel approach which better reflects the spatial growth of human MM samples in BMSC coculture, and more closely mimics the growth and proliferation of human MM clones in vivo. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Follicular lymphoma (FL) is the second most common nodal lymphoma worldwide and remains incurable for most patients (pts). FL is recognized to be a highly heterogeneous disease and a subset of pts experience remarkable poor outcome. In a recent study, 19-26% of pts receiving first-line R-CHOP experienced progression of disease (POD) within 24 months after diagnosis and had a 5-year (yr) overall survival (OS) of only 34-50%, as compared to a 5-yr OS of 90-94% for pts without POD within 24 months (Casulo et al., J Clin Oncol 2015). Consequently, event-free survival at 12 (EFS12) and 24 months (EFS24) have been suggested as novel surrogate endpoints for poor overall survival in clinical trials and useful for patient counseling (Maurer et al., ASH 2014). We have previously shown that a clinicogenetic risk model (m7-FLIPI) that includes the mutation status of seven genes (EZH2, ARID1A, MEF2B, EP300, FOXO1, CREBBP, and CARD11), the FL International Prognostic Index (FLIPI), and the Eastern Cooperative Oncology Group (ECOG) performance status, improves risk stratification for failure-free survival (FFS) and OS in pts with FL receiving first-line immunochemotherapy (Pastore et al., Lancet Oncology 2015). An online tool is available at: http://www.glsg.de/m7-flipi. It would be advantageous to determine prognosis prior to front-line therapy rather than after POD. Thus, we aimed to investigate the predictive utility of the m7-FLIPI for early POD. Patients and Methods: Clinical and mutation data were available from two independent cohorts: 151 pts who received R-CHOP and IFN maintenance as part of a randomized trial of the German Low-Grade Lymphoma Study Group (GLSG), and 107 pts from a population-based registry of the British Columbia Cancer Agency (BCCA) who received R-CVP. Among the latter, 93 (87%) received R-maintenance by intention to treat. All pts had symptomatic, advanced stage or bulky disease considered ineligible for curative radiotherapy, and a biopsy specimen obtained </=12 months prior to the initiation of first-line therapy. POD was defined as progression, relapse, or death due to any cause. POD12 and POD24 were defined based on POD status at 12 and 24 months after therapy initiation, respectively. Logistic regression analysis was performed to assess if m7-FLIPI was predictive of early POD using the statistical software R (version 3.1.2). Results: In the GLSG cohort, median age was 57 yrs (range 27-77), 51% had high-risk FLIPI, and 5-yr failure-free survival (FFS) and OS rates were 66% and 83%, respectively (median follow-up for OS 7.7 yrs). In the BCCA cohort, median age was higher (62 yrs, 37-83), but high-risk FLIPI was similarly frequent (50%); 5-yr FFS and OS rates were 58% and 74%, respectively (median follow-up for OS 6.7 yrs). A total of 43 GLSG (28%) and 24 BCCA pts (22%) were classified as high-risk by m7-FLIPI, with a 5-yr OS of 65% and 42%, respectively. In the GLSG cohort, 8 (5%) and 29 pts (19%) had POD within 12 and 24 months, respectively, 4 and 10 pts were censored before POD12 and POD24 (table). High-risk m7-FLIPI pts were significantly more likely to experience early POD with an Odds Ratio (OR) of 20.80 (95% confidence interval (CI) 3.53-395.96; p=0.0052) for POD12 and 6.33 (95% CI 2.67-15.69; p<0.0001) for POD24. Likewise, in the BCCA cohort, 16 (15%) and 28 pts (26%) experienced POD12 and POD24, respectively (table). The OR for high-risk m7-FLIPI pts was 4.69 (95% CI 1.52-14.65; p=0.0068) for POD12, and 5.36 (95% CI 2.03-14.60; p=0.0008) for POD24. In the GLSG and BCCA cohorts, the m7-FLIPI had a sensitivity of 88% and 50%, a specificity of 75% and 82%, a positive predictive value (PPV) of 16 and 33%, and a negative predictive value (NPV) of 96% and 90% to predict POD12. For POD24, sensitivity was 62% and 46%, specificity 79% and 86%, PPV 42% and 54%, and NPV 82% and 82%, respectively. Conclusion: We conclude that patients classified as high-risk m7-FLIPI are highly enriched among those with early progression of disease. However, approximately one-half of patients with progression by 24 months after therapy initiation are classified as low-risk m7-FLIPI. Thus, further efforts are needed to refine the m7-FLIPI and thereby capture additional cases that may benefit from innovative first-line approaches. Table. Population m7-FLIPI N POD12 POD24 GLSG Total 151 8/147* 29/141* High-risk 43 7 18 Low-risk 108 1 11 BCCA Total 107 16/107 28/107 High-risk 24 8 13 Low-risk 83 8 15 *Pts censored were removed Disclosures Ansell: Bristol-Myers Squibb: Research Funding; Celldex: Research Funding.