Ruppert, Amy S.

Abstract Background : Effective therapy for classical hairy cell leukemia (c-HCL) refractory to purine nucleoside analog (PNA) treatment is limited, and there are no accepted treatment standards for variant hairy cell leukemia (v-HCL). Ibrutinib, an oral small molecule inhibitor of Bruton tyrosine kinase (BTK), has shown single-agent efficacy and acceptable tolerability in patients with various B-cell malignancies, including chronic lymphocytic leukemia, mantle cell lymphoma, and Waldenstrom's. While BTK is expressed in HCL cells, the clinical activity of ibrutinib in this disease has not been previously assessed. We conducted a single-arm, multi-center phase 2 study (NCI #9268) of single-agent ibrutinib to characterize the overall response rate (complete + partial response) and safety of single-agent ibrutinib treatment for HCL. Methods : Patients with c-HCL (unfit for or relapsed after PNA) and v-HCL (relapsed or treatment-naïve) were eligible. Enrolled patients required treatment, had ECOG ≤ 2, no active infection, and preserved end-organ function. Patients received continuous once daily ibrutinib in 28-day cycles. Using a Simon 2-stage design, the first 13 patients were treated at 420 mg daily, and a second cohort of 13 patients was accrued at the 840 mg dose-level. Ultimately, the pre-specified number of objective responses was reached at the 420 mg dose-level, and accrual to the second stage of the design continues at that dose. Response, including bone marrow biopsy with immunohistochemistry for minimal residual disease (MRD), was assessed after 8 and 12 cycles. Patients experiencing clinical benefit may continue ibrutinib until unacceptable toxicity or progressive disease. Results: As of 15 May 2016, 28 patients had been enrolled and were evaluable for response: 420 mg/day (n=15) and 840 mg/day (n=13). Enrolled patients (1 treatment-naïve v-HCL, 10 relapsed v-HCL, 17 relapsed c-HCL) included 22 male and 6 female patients with median age 65 years (range: 43-78). Relapsed patients received median 4 prior therapies (range: 1-11); all had prior PNA, 81% had prior rituximab, and 3 c-HCL patients had prior vemurafenib. Response data are summarized by dose and histology in the table. To date, the ORR is 46% [4 CR (all c-HCL) and 9 PR (6 c-HCL)], with objective responses more commonly observed in patients with c-HCL. Eight additional patients (29%) with stable disease have experienced clinical benefit (resolution of symptoms, improvement in peripheral blood cell counts) not meeting criteria for PR, most commonly attributable to persistent thrombocytopenia, and continue on treatment. At median follow-up of 22 months, 20 patients (71%) remain on treatment, 3 patients (1 v-HCL, 2 c-HCL) have progressed, 2 patients (c-HCL) with severe neutropenia at baseline (c-HCL) had early deaths from pneumonia, 1 (c-HCL) discontinued during cycle 8 for failure to resolve baseline neutropenia, and 2 other patients (v-HCL) have discontinued for adverse events. Estimated 24-month progression-free survival (PFS) was 79% (95% CI: 57-91%) and the median PFS has not been reached. Redistribution lymphocytosis was observed in patients with circulating disease at baseline. Soluble interleukin-2 receptor (sIL2R) level was increased at baseline in all c-HCL patients for whom data were available and correlated with response. In general, toxicity did not differ by dose level or disease histology. The most frequent (>10%) grade ≥3 adverse events (AEs) were lymphopenia (21%), neutropenia (18%), lung infection (18%), thrombocytopenia (14%), hypophosphatemia (11%), and hypertension (11%). Common grade 1/2 non-hematologic toxicities included myalgia (57%), diarrhea (54%), fatigue (50%), nausea/vomiting (46%), bruising (46%), and rash (46%); grade 1/2 atrial fibrillation (no grade ≥3) was observed in 5 patients. Grade ≥3 infection was observed in 25%, but no grade ≥3 bleeding AEs were reported. Conclusions: Ibrutinib can induce remission in both c-HCL and v-HCL patients, including heavily pre-treated patients, but complete remissions have only been observed in c-HCL to date. The drug is generally well-tolerated during long-term administration, and durable clinical benefit is observed in the majority of treated patients even when objective response criteria are not met. Table 1. Table 1. Figure 1. Figure 1. Disclosures Jones: Pharmacyclics, LLC, an AbbVie Company: 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. Lozanski:Stemline Therapeutics Inc.: Research Funding; Beckman Coulter: Research Funding; Genentech: Research Funding; Boehringer Ingelheim: Research Funding.

Background The phase 3 trial A041202 solidified the Bruton's Tyrosine Kinase (BTK) inhibitor ibrutinib as a standard of care for older patients with previously untreated CLL by showing superior progression-free survival (PFS) as compared with bendamustine plus rituximab. While ibrutinib is highly effective in previously untreated CLL, there do remain disadvantages to this therapy, specifically the low rate of complete response (CR) and therefore the need for continuous administration, which increases cost and toxicity. In older patients especially, toxicities with ibrutinib are common; 17% of patients had atrial fibrillation and 29% had grade 3 or higher hypertension on the A041202 study. Thus, strategies to decrease the exposure time to ibrutinib are of interest. Venetoclax is an inhibitor of BCL2 that has shown efficacy as a single agent and in combination with monoclonal antibodies, specifically the anti-CD20 monoclonal antibody obinutuzumab for patients with previously untreated CLL. One significant advantage to venetoclax is the ability to produce CRs and minimal residual disease negative (MRD-) responses. In this study, we compare ibrutinib plus obinutuzumab (IO) to ibrutinib plus venetoclax plus obinutuzumab (IVO) with a response-dependent discontinuation. While other studies have been designed with the goal of discontinuation of ibrutinib through combinations with venetoclax, no other study has been presented using a response-dependent discontinuation strategy. Study Design and Methods A041702 is a randomized phase 3 study led by the Alliance for Clinical Trials in Oncology that is currently enrolling through the NCI National Clinical Trials Network (NCTN). CLL patients age 70 years or older who are previously untreated and in need of therapy are eligible. Previous treatment of autoimmune complications with steroids or rituximab is allowed. Patients must have intermediate- or high-risk Rai stage, ECOG performance status 0-2, ANC ≥ 1000/mm3 unless due to marrow involvement, and platelets ≥ 30,000/mm3. CrCl must be ≥ 40 mL/min and AST/ALT ≤ 2.5x upper limit of normal. Patients with hepatitis B must have undetectable viral load, and patients must not have an intercurrent illness that is expected to limit survival to < 5 years. Warfarin and strong inhibitors or inducers of CYP3A4/5 are not permitted. Patients are initially preregistered to the study and submit a peripheral blood sample for central FISH analysis of del(17p). Patients who are registered are randomized 1:1 to Arm 1 (IO) or Arm 2 (IVO), and are stratified by Rai stage and presence of del(17p). IO consists of I daily starting cycle 1 day 1, and O dosed as standard starting cycle 1 day 1 and continuing to cycle 6 day 1. IVO consists of IO as in Arm 1, with V starting cycle 3 day 1 with standard 5-week ramp-up and continuing until cycle 14 day 28. At the end of 14 cycles, patients in both arms undergo response evaluation with central peripheral blood and bone marrow MRD testing. Patients on IO then continue I indefinitely. Patients on IVO who are in a bone marrow MRD- CR discontinue all therapy, and those who are not continue I indefinitely. The primary objective of the study is to compare PFS between IO and IVO using the strategy of response-dependent discontinuation. There is 90% power to detect a hazard ratio for PFS of 0.55 (corresponding to 5-year PFS rates of 70% and 82.187% for IO and IVO, respectively), at a one-sided significance level of 0.025 by a log-rank test. This design requires 128 events and 431 total evaluable patients assuming uniform accrual over the course of 3 years and minimum follow-up of 5 years. The study includes two interim analyses for superiority when 50% and 75% of the expected number of events have been observed and three interim analyses for futility when 25%, 50%, and 75% of the expected number of events have been observed. Conclusions A041702 is an ongoing phase 3 clinical trial using a novel response-dependent discontinuation method. Results of this study have the potential to change the standard of care for older patients with previously untreated CLL. The study is expected to accrue for 3 years beginning January 2019, and we welcome participation from sites throughout the NCTN. Support: U10CA180821, U10CA180882, UG1CA189823, U24CA196171; U10CA180820 (ECOG-ACRIN); https://acknowledgments.alliancefound.org; ClinicalTrials.gov Identifier: NCT03737981 Disclosures Woyach: Janssen: Consultancy, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; AbbVie: Research Funding; Karyopharm: Research Funding; Loxo: Research Funding; Morphosys: Research Funding; Verastem: Research Funding. Lozanski:Beckman Coulter: Research Funding; Boehringer Ingelheim: Research Funding; Stemline Therapeutics Inc.: Research Funding; Genentec: Research Funding. Ding:Merck: Research Funding; DTRM Biopharma: Research Funding. Hill:Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria; Celegene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Amgen: Research Funding; TG therapeutics: Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Research Funding; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Stone:Argenx, Celgene, Takeda Oncology: Other: Data and Safety Monitoring Board/Committee: ; Novartis, Agios, Arog: Research Funding; AbbVie, Actinium, Agios, Argenx, Arog, Astellas, AstraZeneca, Biolinerx, Celgene, Cornerstone Biopharma, Fujifilm, Jazz Pharmaceuticals, Amgen, Ono, Orsenix, Otsuka, Merck, Novartis, Pfizer, Sumitomo, Trovagene: Consultancy. Byrd:Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Ohio State University: Patents & Royalties: OSU-2S; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Acerta: Research Funding; Novartis: Other: Travel Expenses, Speakers Bureau; BeiGene: Research Funding; Ohio State University: Patents & Royalties: OSU-2S; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; Genentech: Research Funding; BeiGene: Research Funding; Genentech: Research Funding; Acerta: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau.

Background: NGS of myeloid mutations is an integral part of AML clinical decision-making. There is currently no information regarding concordance between NGS panels in AML using samples from the same patient across various platforms in different diagnostic laboratories. To study this important question, we analyzed NGS of myeloid mutations in diagnostic samples from The Beat AML Master Trial (BAMT) for newly diagnosed older AML patients, and compared variant calls made between institutional laboratories enrolling the study subject with those made by Foundation Medicine (FM), the central laboratory used for treatment assignment in this precision medicine trial. Methods: We identified newly diagnosed AML patient samples (peripheral blood (PB) and/or bone marrow (BM)) from 2 lead institutions in the BAMT(Ohio State, OSU and Oregon Health and Sciences University, OHSU) that were analyzed by both the institutional and by FM from Nov 15, 2016 to Apr 15, 2019. Samples sent to both laboratories >3 days apart were excluded. Samples were analyzed at the institutional laboratories using their respective NGS mutational panels and by FM using the FoundationOne®Heme(FMH) NGS panel which utilizes capture based sequencing. The OSU NGS assay utilizes sequencing on Illumina MiSeq. The OHSU NGS assay employs semiconductor-based sequencing (Ion Torrent PGM platform). The variant allele frequency (VAF) sensitivity for detection for all 3 laboratories range from 1-2%. We evaluated the ability to identify mutations in 8 genes : FLT3, IDH1/ 2, NPM1, TET2, DNMT3A, WT1 and TP53 used in treatment assignment in theBAMT. A detection cutoff of 2% was used to define the presence or absence of a mutation. Overall, agreement was defined as the number of times the local and central laboratories made the same call divided by the total number of patients. Sensitivity was defined as the number of present calls made locally divided by the number of present calls made centrally, and specificity as the number of absent calls made locally divided by the number of absent calls made centrally. The overall kappa statistic, controlling for institution, provided another measure of agreement between local and central calls, where a value of 1 indicates perfect agreement. Results: 194 patient samples were identified using methods above and analyzed locally at the screening institution (125 at OSU, 69 at OHSU) and centrally at FM. Type of tissue analyzed for variants between local site and FM were 59 PB, 129 BM, and 6 with BM/PB mismatch. Overall agreement in presence/absence calls between local and central results for each of the 8 genes was over 95% (Table 1). There was perfect agreement for NPM1. The sensitivity was above 94% for all genes except TP53 (88.6%) and WT1 (63.6%). Failure to detect a mutation locally was primarily due to reporting of all TP53 variants, including variants of unknown significance (VUS) (5) by FM as agreed upon in the study protocol, detection at low levels below local site sensitivity cutoff (1), detection of variants in a portion of gene not covered at the local site(1)and possible artifact (1). For the WT1 gene, discordance in 5 samples included VUS (3) reported by FM ,a variant detected in a portion of the gene not covered at the local site(1).and difference in leukemic tissue analyzed with mutation not detected by the central laboratory on a PB sample, and present at the institutional lab on a BM sample; affecting the overall agreement and specificity but not sensitivity. Specificity was at least 98% for each of the 8 genes. Finally, most discrepancies in reported mutations in FLT3 (n=2), IDH1 (n=1), IDH2 (n=2), DNMT3A (n=4) and TET2 (n=5) were due to reporting of VUS in one laboratory and not by another. Conclusion: Detection of pathogenic myeloid mutations using orthogonal assays showed a high degree of concordance for genes used in therapeutic assignment on the BAMT.The small number of discordant results, in TP53 and WT1, were attributed to the reporting of VUS. This study illustrates the importance of quality control and standardization as NGS continues to be widely utilized in AML for clinical decision making, with a variety of platforms across multiple laboratories. Our next steps involve evaluating the differences in VAFs reported between local and central laboratories when a given mutation is identified, as well as the potential reasons for observed differences and clinical implications of known pathogenic mutations vs putative VUS. Disclosures Borate: Daiichi Sankyo: Consultancy; AbbVie: Consultancy; Novartis: Consultancy; Takeda: Consultancy; Pfizer: Consultancy. Vergilio:Foundation Medicine: Employment; Roche Holding AG: Equity Ownership. Stein:Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo, Inc.: Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astellas Pharma US, Inc: Membership on an entity's Board of Directors or advisory committees; Bioline: Membership on an entity's Board of Directors or advisory committees; Genentech: Membership on an entity's Board of Directors or advisory committees; PTC Therapeutics: Membership on an entity's Board of Directors or advisory committees; Syros: Membership on an entity's Board of Directors or advisory committees. Patel:France Foundation: Honoraria; Dava Oncology: Honoraria; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Baer:Astellas: Research Funding; Abbvie: Research Funding; AI Therapeutics: Research Funding; Forma: Research Funding; Incyte: Research Funding; Kite: Research Funding; Takeda: Research Funding. Stock:Daiichi: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Agios: Membership on an entity's Board of Directors or advisory committees; Research to Practice: Honoraria; UpToDate: Honoraria; Kite, a Gilead Company: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees. Schiller:Amgen: Other, Research Funding; Astellas: Research Funding; Biomed Valley Discoveries: Research Funding; Bristol Myer Squibb: Research Funding; Celgene: Research Funding, Speakers Bureau; Constellation Pharmaceutical: Research Funding; Daiichi Sankyo: Research Funding; Eli Lilly and Company: Research Funding; FujiFilm: Research Funding; Genzyme: Research Funding; Gilead: Research Funding; Incyte: Research Funding; J&J: Research Funding; Jazz Pharmaceuticals: Honoraria, Research Funding; Karyopharm: Research Funding; Novartis: Research Funding; Onconova: Research Funding; Pfizer Pharmaceuticals: Equity Ownership, Research Funding; Sangamo Therapeutics: Research Funding; Agios: Research Funding, Speakers Bureau. Blum:AmerisourceBergen: Consultancy; Boehringer Ingelheim: Research Funding; Celgene: Research Funding; Astellas,: Research Funding; Xencor: Research Funding; Forma: Research Funding. Kovacsovics:Pfizer: Research Funding; Jazz: Consultancy; Novartis: Research Funding; Abbvie: Research Funding; Amgen: Consultancy, Research Funding. Foran:Agios: Honoraria, Research Funding. Druker:Pfizer: Research Funding; OHSU (licensing fees): Patents & Royalties: #2573, Constructs and cell lines harboring various mutations in TNK2 and PTPN11, licensing fees ; Cepheid: Consultancy, Honoraria; Aileron Therapeutics: #2573, Constructs and cell lines harboring various mutations in TNK2 and PTPN11, licensing fees , Membership on an entity's Board of Directors or advisory committees; ALLCRON: Membership on an entity's Board of Directors or advisory committees; Amgen: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Aptose Biosciences: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Beta Cat: Membership on an entity's Board of Directors or advisory committees, Other: Stock options; GRAIL: Equity Ownership, Other: former member of Scientific Advisory Board; Patient True Talk: Consultancy; The RUNX1 Research Program: Membership on an entity's Board of Directors or advisory committees; Vivid Biosciences: Membership on an entity's Board of Directors or advisory committees, Other: Stock options; Beat AML LLC: Other: Service on joint steering committee; CureOne: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Gilead Sciences: Other: former member of Scientific Advisory Board; ICON: Other: Scientific Founder of Molecular MD, which was acquired by ICON in Feb. 2019; Monojul: Other: former consultant; Novartis: Other: PI or co-investigator on clinical trial(s) funded via contract with OHSU., Patents & Royalties: Patent 6958335, Treatment of Gastrointestinal Stromal Tumors, exclusively licensed to Novartis, Research Funding; Bristol-Myers Squibb: Other: PI or co-investigator on clinical trial(s) funded via contract with OHSU., Research Funding; Pfizer: Other: PI or co-investigator on clinical trial(s) funded via contract with OHSU., Research Funding; Merck & Co: Patents & Royalties: Dana-Farber Cancer Institute license #2063, Monoclonal antiphosphotyrosine antibody 4G10, exclusive commercial license to Merck & Co; Dana-Farber Cancer Institute (antibody royalty): Patents & Royalties: #2524, antibody royalty; Burroughs Wellcome Fund: Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Patents & Royalties, Research Funding. Byrd:Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Acerta: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Ohio State University: Patents & Royalties: OSU-2S. Levine:C4 Therapeutics: Membership on an entity's Board of Directors or advisory committees; Isoplexis: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Loxo: Membership on an entity's Board of Directors or advisory committees; Qiagen: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria; Prelude Therapeutics: Research Funding; Novartis: Consultancy; Gilead: Consultancy; Lilly: Honoraria; Imago Biosciences: Membership on an entity's Board of Directors or advisory committees. Mims:Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Astellas Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; PTC Therapeutics: Membership on an entity's Board of Directors or advisory committees; Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees.

With the launch of the National Cancer Institute’s Precision Medicine Initiative in 2015, there has been a shift to trial designs that tailor health care solutions to individual patients by using a screening platform and by moving away from the one-trial/one-biomarker-at-a-time approach. To make precision medicine a reality, it is critical to identify and validate potential biomarkers to help select patients who will truly benefit from a targeted therapy. In this article, we discuss five trial designs: enrichment, umbrella, basket, subgroup, and window of opportunity. For each trial design, we describe the design characteristics, use ongoing or completed trials as case studies, provide any recent advances to the trial design, and discuss advantages and disadvantages of each design.

Abstract Introduction: The most effective initial therapy for older adults with CLL has not yet been established due to the lack of comparison of chemoimmunotherapy (CIT) and targeted therapy with the Bruton's Tyrosine Kinase (BTK) inhibitor ibrutinib. CIT has been the gold standard since studies showing that addition of CD20 antibody to chemotherapy prolongs survival. Bendamustine plus rituximab (BR) is one standard, more aggressive CIT regimen for patients (pts) age 65 or older. While ibrutinib has been FDA approved for untreated CLL since 2016, it has only been compared to chlorambucil, which is relatively ineffective, and never before to aggressive CIT. Additionally, the benefit of the addition of rituximab to ibrutinib in this setting has not been prospectively studied in a phase 3 trial. As part of a randomized phase 3 trial, the Alliance sought to answer these important clinical questions. Pts and Methods: Alliance A041202 is a multicenter NCI National Clinical Trials Network phase 3 study comparing BR (Arm 1) with ibrutinib (Arm 2) and the combination of ibrutinib plus rituximab (Arm 3) to determine whether ibrutinib-containing regimens are superior to CIT in terms of PFS. Additionally, this study sought to determine if adding rituximab to ibrutinib would prolong PFS over ibrutinib alone. At time of progression, pts on Arm 1 could cross over to Arm 2. Eligible pts were those age ≥ 65 years with previously untreated, symptomatic CLL. Pts had a CrCl ≥ 40 mL/min, bilirubin ≤ 1.5 x ULN, and no significant life-limiting intercurrent illness or need for warfarin treatment. Pts were stratified based upon Rai stage, Zap-70 methylation performed centrally, and del(17)(p13.1) or del(11)(q22.3) by local interphase cytogenetics and were randomized 1:1:1 to each arm. With 166 pts per arm, the trial was powered to detect an improvement in 2-year PFS from 61% in Arm 1 to 75% in Arms 2 or 3 (HR=0.586) using two one-sided log-rank tests with type I error rate of 2.5% and 90% power. The Alliance Data and Safety Monitoring Board approved the data release after meeting the protocol-defined efficacy threshold at a planned interim analysis with a one-sided critical value of 0.001538. These data were locked July 2, 2018; updated results will be presented at the meeting. Results: Between 12/9/2013 and 5/16/2016, 547 pts were registered and randomized (Arms 1: 183, 2: 182, and 3: 182). Median age was 71 years and 67% of pts were men. High-risk Rai stage (stage III/IV) was seen in 54%, unmethylated Zap-70 in 53%, and del(17p) or del(11q) by local FISH in 28%. Local vs centralized FISH was performed for del(11q) and del(17p) with agreement between local and central results in 94% (Kappa=0.80) and 97% (Kappa=0.76) of pts, respectively. 525 (96%) pts were eligible and included in the primary PFS analysis (Arms 1: 176, 2: 178, and 3: 171). With median follow-up of 32 months (mo), median PFS was 41 mo in Arm 1 and has not been reached in Arms 2 or 3 (HR comparing Arm 2 to 1 is 0.40 with one-sided p&lt;0.0001; HR comparing Arm 3 to 1 is 0.41 with one-sided p&lt;0.0001; HR comparing Arm 3 to 2 is 1.01 with one-sided p=0.48). 2-year PFS estimates were 74%, 87% in 2, and 88% in Arms 1, 2, and 3 respectively. At this time, there are no significant differences in overall survival (OS) among arms (p=0.87), median OS has not been reached for any arm, and 2-year OS estimates were 95%, 90%, and 94% in Arms 1, 2, and 3, respectively. Adverse events (AEs) were compared among arms using Fisher's exact tests. Grade 3+ treatment-emergent AEs were seen in 428 of 537 evaluable pts with 61%, 41%, and 38% of pts experiencing Grade 3+ heme AEs (p&lt;0.0001) and 60%, 72%, and 71% of pts experiencing Grade 3+ non-heme AEs (p=0.03) in Arms 1, 2, and 3 respectively. Grade 5 AEs were seen in 5 (2.8%), 14 (7.8%), and 14 (7.7%) pts (p=0.07). Unexplained or unwitnessed death over the entire observation period was seen in 2 (1.1%), 7 (3.9%), and 4 (2.2%) pts (p=0.24) in Arms 1, 2, and 3 respectively. Conclusions: This international phase 3 trial demonstrates that ibrutinib produces superior PFS to standard CIT in older pts with CLL and justifies it as a standard of care treatment for pts age 65 and older. The addition of rituximab does not prolong PFS with ibrutinib. While ibrutinib represents a major therapeutic advance, toxicities and also cost justify future efforts to reduce the need for long-term continuous treatment. Support: K23CA178183, R01CA183444, U10CA180821, U10CA180882, U24CA196171, Clinicaltrials.gov identifier: NCT01886872 Figure. Figure. Disclosures Ding: Merck: Research Funding. Bartlett:Astra Zeneca: Research Funding; ImaginAB: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Bristol-Meyers Squibb: Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Affimed: Research Funding; Janssen: Research Funding; Novartis: Research Funding; Merck & Co: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, 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; Celgene: Research Funding; Immune Design: Research Funding; Forty Seven: Research Funding; Novartis: Research Funding; Millennium: Research Funding. Brander:BeiGene: Other: Institutional research funding for non investigator initiated clinical trial, Research Funding; TG Therapeutics: Consultancy, Honoraria, Other: Institutional research funding for non investigator initiated clinical trial, Research Funding; Genentech: Consultancy, Honoraria, Other: Institutional research funding for non investigator initiated clinical trial, Research Funding; Novartis: Consultancy, Other: DSMB; AbbVie: Consultancy, Honoraria, Other: Institutional research funding for non investigator initiated clinical trial, Research Funding; Pharmacyclics, an AbbVie Company: Consultancy, Honoraria, Research Funding; Teva: Consultancy, Honoraria; Acerta: Other: Institutional research funding for non investigator initiated clinical trial, Research Funding; DTRM: Other: Institutional research funding for non investigator initiated clinical trial, Research Funding. Barr:AbbVie, Gilead: Consultancy. Parikh:Gilead: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding. Coutre:Celgene: Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Pharmacyclics LLC, an AbbVie Company: Honoraria, Research Funding; Gilead: Research Funding; Beigene: Consultancy; AbbVie: Consultancy, Research Funding. Lozanski:Novartis: Research Funding; BI: Research Funding; Genentech: Research Funding; Stem Line: Research Funding; Coulter: Research Funding; Beckman: Research Funding. Larson:Ariad/Takeda: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding. Erba:Amgen: Research Funding; Juno: Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; MacroGenics: Consultancy; Juno: Research Funding; Janssen: Research Funding; Seattle Genetics: Consultancy, Research Funding; Janssen: Research Funding; Juno: Research Funding; Agios: Consultancy, Speakers Bureau; MacroGenics: Consultancy; Incyte: Consultancy, Speakers Bureau; Seattle Genetics: Consultancy, Research Funding; Takeda/Millenium: Research Funding; Novartis: Consultancy, Speakers Bureau; Takeda/Millenium: Research Funding; Incyte: Consultancy, Speakers Bureau; MacroGenics: Consultancy; Celgene: Consultancy, Speakers Bureau; Janssen: Research Funding; Novartis: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Astellas: Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; MacroGenics: Consultancy; Daiichi Sankyo: Consultancy, Research Funding; Pfizer: Consultancy, Other: grant; Astellas: Research Funding; Juno: Research Funding; Janssen: Research Funding; Novartis: Consultancy, Speakers Bureau; Amgen: Research Funding; Agios: Consultancy, Speakers Bureau; Astellas: Research Funding; Agios: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Amgen: Research Funding; Pfizer: Consultancy, Other: grant; Pfizer: Consultancy, Other: grant; Astellas: Research Funding; Amgen: Research Funding; Agios: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Jazz: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Jazz: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Pfizer: Consultancy, Other: grant; Jazz: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Jazz: Consultancy, Speakers Bureau; Seattle Genetics: Consultancy, Research Funding; Celgene: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Takeda/Millenium: Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Celgene: Consultancy, Speakers Bureau; Takeda/Millenium: Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee. Owen:Janssen: Honoraria, Research Funding; Celgene: Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Research Funding; F. Hoffmann-La Roche Ltd: Honoraria, Research Funding; AbbVie: Research Funding; Merck: Honoraria; Teva: Honoraria. Abramson:Bayer: Consultancy; Novartis: Consultancy; Merck: Consultancy; Karyopharm: Consultancy; Seattle Genetics: Consultancy; Verastem: Consultancy; Humanigen: Consultancy; Juno Therapeutics: Consultancy; Gilead: Consultancy; Celgene: Consultancy; Amgen: Consultancy.

Abstract Introduction: Aggressive chemo-immunotherapy followed by peripheral blood stem cell autografting (ASCT) in CALGB (Alliance) 59909 achieved a median progression-free survival (PFS) in MCL of 5 years (Damon et al JCO, 2009), but late recurrences occurred. Using the CALGB 59909 treatment backbone, we evaluated tolerability and efficacy of adding post-transplant bortezomib consolidation (BC) or maintenance (BM)in a randomized phase II trial. Interim results of CALGB (Alliance) 50403 were previously presented (ASH 2015) demonstrating 5 yr PFS 70% and 69% for the BM and BC arms respectively. We now report final 8 year follow up results from this trial and compare outcomes to CALGB 59909, which differed from CALGB 50403 only by the absence of post-transplant bortezomib. Methods: The primary endpoint was PFS measured from randomization for each treatment arm. Induction therapy was with 2-3 cycles of augmented R-CHOP (2000 mg/m2 cyclophosphamide) and methotrexate (300 mg/m2) followed by high-dose cytarabine/etoposide/rituximab(R)/filgrastim (EAR) stem cell mobilization and cyclophosphamide/carmustine/etoposide (CBV) ASCT. After 2 doses of post-transplant R, patients were randomized to BC (1.3 mg/ m2 IV days 1, 4, 8, 11 of a 3-week cycle for 4 cycles) or BM (1.6 mg/m2 IV weekly x4 every 8 weeks for 18 months) beginning at approximately day 90. Minimal residual disease (MRD) was analyzed using patient-specific PCR probes for the bcl-1 / IgH junction or the IgH CDR3 region. Results: 151 patients were enrolled from 10/2006 - 6/2010 at 14 sites; 147 who received treatment are included in this analysis. Median age was 59 years (29-69); stage II (2.7%), III (11.6%), IV (85.0%); MIPI low (52.4%), intermediate (30.6%), high (17.0%); blastoid histology (12.9%); bone marrow involvement (81.0%); Ki67 was evaluated in 86 and was >30% in 17.4% of patients. 118 (80%) underwent ASCT and 102 (68%) were randomized. Most withdrawals (45) were for progression (10) or adverse events (AEs) (19) including 4 treatment-related deaths. Fifty-two patients were randomized to BM and 50 to BC. Following randomization, 34 (65%) completed BM and 33 (66%) completed BC. Withdrawal for AEs occurred in 14 (28%) of BC and 7 (13%) of BM patients (p = 0.09), most for cytopenias or peripheral neuropathy. With a median follow-up 7.8 years from randomization (8.3 from registration), the median PFS from randomization for the BM arm was not reached and was 8.9 years (95% CI 7.2 to not reached) for the BC arm. Both arms had median PFS significantly greater than the null hypothesis setting median PFS to 4 years (p < 0.001; 1-sided test of exponential parameter)The 8-year PFS estimates in the BM and BC arms were 77% (95% CI 66-90%) and 58% (95% CI 44-76%), respectively. Among all 147 patients treated on CALGB 50403, 8-year PFS from time of registration was 43.6% (35.6-53.3%). PFS from registration was not significantly extended in CALGB 50403 compared with CALGB 59909 (log rank p=0.24), but using a landmark analysis from time of transplant, PFS was significantly extended in CALGB 50403 (log rank p=0.005)(fig 1). Baseline patient characteristics in the two studies were not significantly different. In CALGB 50403, 8-year PFS from registration by MIPI was 52.0% (95% CI 41.1-66.0%) in MIPI low risk, 37.5% (95% CI 25.3-55.4%) in intermediate risk, and 28.2% (95% CI 13.7-57.9%) in high-risk. Bone marrow MRD results were collected for 42 patients post-induction therapy; 8-year PFS estimates were 80.2% (95% CI 62.2-100%) (n=17) and 43.2% (95% CI 27.3-68.2%) (n=25) for MRD-negative and MRD-positive patients, respectively (p=0.009). Conclusions: Induction chemotherapy followed by ASCT and either BC or BM was efficacious and tolerable, although BC was associated with more withdrawals for toxicity. PFS was not significantly different between BC and BM. The comparison between studies 50403 and 59909 with long-term follow up continues to suggest a PFS benefit from the addition of BC or BM among patients undergoing transplant. This did not translate into a PFS benefit from time of study enrollment possibly due to the higher pre-transplant dropout rate in 50403. MRD-negativity following induction chemo-immunotherapy is highly associated with improved PFS and the role of ASCT in post-induction MRD-negative patients is currently under investigation in a randomized clinical trial. Support: U10CA180821, U10CA180882, U24CA196171; ClinicalTrials.gov Identifier: NCT00310037 Disclosures Kaplan: Bayer Pharmaceuticals: Consultancy. Maurer:Celgene: Research Funding; Morphosys: Research Funding; Nanostring: Research Funding. Stock:Jazz Pharmaceuticals: Consultancy. Bartlett:Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: 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. Blum:Acerta: Consultancy; Astra-Zeneca: Consultancy. LaCasce:Seattle Genetics: Consultancy, Honoraria; Humanigen: Consultancy, Honoraria; Research to Practice: Speakers Bureau; Bristol-Myers Squibb: Other: Data safety and monitoring board. Leonard:AstraZeneca: Consultancy; Juno: Consultancy; BMS: Consultancy; ADC Therapeutics: Consultancy; Gilead: Consultancy; Biotest: Consultancy; Karyopharm: Consultancy; Novartis: Consultancy; MEI Pharma: Consultancy; Celgene: Consultancy; United Therapeutics: Consultancy; Sutro: Consultancy; Genentech/Roche: Consultancy; Pfizer: Consultancy; Bayer: Consultancy. Cheson:AbbVie, Roche/Genentech, Pharmacyclics, Acerta, TG Therapeutics: Consultancy.

Abstract PURPOSE Urgency to initiate therapy has to be weighed against the time required for screening and consenting to enroll a patient onto a clinical trial. Exclusion of patients with rapidly progressive or symptomatic disease may lead to selection of patients with less aggressive disease. We recently identified that a short diagnosis to treatment interval (DTI) is associated with adverse clinical factors and inferior outcome in patients with diffuse large B-cell lymphoma (DLBCL) (Maurer et al, JCO 2018); shorter time to treatment was also found to be associated with outcome in other aggressive lymphomas, including mantle cell lymphoma (MCL), in the National Cancer Database (Olszewski et al, BJH 2018). Here we assess the association of DTI with clinical variables and outcome in MCL from an observational cohort with validation in patients enrolled on an NCTN clinical trial. PATIENTS AND METHODS Newly diagnosed patients with MCL were prospectively enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE Molecular Epidemiology Resource (MER), now a subcohort of the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study. Patients initially managed with observation were excluded. DTI was defined as the time in days from date of first lymphoma-containing biopsy to the initiation of therapy. Associations of DTI with clinical factors and outcome were examined using a 14 day split based on the previous MER study of DTI in DLBCL. Odds ratios (OR) and Cox model hazard ratios (HR) are reported. Outcome was assessed using event-free survival (EFS) where events were defined as progression/relapse, initiation of new anti-lymphoma therapy, or death due to any cause. A validation cohort was assembled from patients enrolled in CALGB (Alliance) clinical trial 50403. Protocol therapy was high dose chemotherapy with autologous hematopoietic stem cell transplantation (ASCT) consolidation and post-ASCT rituximab followed by bortezomib as either consolidation or maintenance. DTI was defined as time from diagnosis to study registration and outcome was assessed using progression-free survival (PFS) as defined on the clinical trial. RESULTS 271 patients with MCL enrolled in the MER from 2002-2015 and initiated treatment within 100 days of diagnosis. Median age at diagnosis was 64 years (range 36-76), 211 (78%) were male, and 92% were stage III-IV; MIPI was Low (41%), Intermediate (36%) and High (23%). Induction therapy was R-CHOP based (50%), B-R based (16%), HyperCVAD based (8%), 2-CDA based (11%), and other (15%). Median EFS of the cohort was 41 months (95% CI: 34-46). Median DTI was 26 days (IQR: 14-38) and 28% enrolled within 14 days of diagnosis, exhibiting a longer DTI than DLBCL patients enrolled in the MER during the same time period. Short DTI (0-14 days) was associated with adverse clinical factors including ECOG PS 2-4 (OR=5.74, 95% CI: 2.51-13.1, p<0.0001), elevated LDH (OR=2.30 95% CI: 1.25-4.22, p=0.0072), and higher MIPI score (OR=1.48, 95% CI: 1.04-2.07, p=0.025) but was not significantly associated with age, sex, B-symptoms, or stage (all p>0.30). Short DTI was also associated with inferior EFS (HR=1.78, 95% CI: 1.27-2.49, p=0.0008) which remained significant after adjusting for MIPI score (HR=1.72, 95% CI: 1.23-2.41, p=0.0016). In the validation cohort, 144 patients enrolled on 50403 within 100 days of diagnosis from 2006-2010. Median age at diagnosis was 59 years (range 29-69), 77% were male, and 97% were stage III-IV; MIPI was Low (51%), Intermediate (31%) and High (17%). Median PFS of the cohort was 84 months (95% CI: 50-109). Median DTI was 35 days (IQR: 22-46) and 11% enrolled within 14 days of diagnosis. Short DTI (0-14 days) was associated with PS (OR=9.00, 95% CI: 1.18-69.0, p=0.034) and) higher MIPI score (OR=2.09, 95% CI: 1.08-4.04, p=0.029) but not elevated LDH (OR=1.27, 95% CI: 0.43-3.74, p=0.66). Short DTI was associated with inferior PFS (HR=2.21, 95% CI:1.19-4.09, p=0.011) which remained clinically significant after adjusting for MIPI score (HR=1.85, 95% CI: 0.98-3.47, p=0.056). CONCLUSION A short diagnosis-to-treatment interval is strongly associated with adverse clinical factors and poor outcome in newly diagnosed MCL in the MER. Clinical trials are encouraged to facilitate enrollment of patients with short DTI to avoid potential selection bias. Support: U01 CA195568, P50 CA097274, U10CA180821, U10CA180882; ClinicalTrials.gov Identifier: NCT00310037 (CALGB 50403) Figure. Figure. Disclosures Maurer: Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Research Funding. Kaplan:Bayer Pharmaceuticals: Consultancy. Cohen:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Pharmacyclics: 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; Bristol-Myers Squibb: Research Funding; AbbVie: 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; Millennium: 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; BioInvent: Consultancy; Takeda: Research Funding. Martin:Gilead: Consultancy; Kite: Consultancy; Seattle Genetics: Consultancy; AstraZeneca: Consultancy; Janssen: Consultancy; Bayer: Consultancy. Kahl:Abbvie: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy; Acerta: Consultancy; Juno: Consultancy; Celgene: Consultancy; Genentech: Consultancy; Seattle Genetics: Consultancy; CTI: Consultancy; ADC Therapeutics: Consultancy. Bartlett:ImaginAB: Research Funding; Bristol-Meyers Squibb: Research Funding; Novartis: Research Funding; Immune Design: Research Funding; Janssen: Research Funding; Merck & Co: Research Funding; Forty Seven: Research Funding; Novartis: Research Funding; Pharmacyclics: Research Funding; Affimed: Research Funding; Astra Zeneca: Research Funding; Pharmacyclics: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Millennium: Research Funding; Genentech: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cerhan:Celgene: Research Funding; Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding. Leonard:Karyopharm: Consultancy; Biotest: Consultancy; Bayer: Consultancy; Pfizer: Consultancy; ADC Therapeutics: Consultancy; Novartis: Consultancy; AstraZeneca: Consultancy; Juno: Consultancy; BMS: Consultancy; Sutro: Consultancy; MEI Pharma: Consultancy; Genentech/Roche: Consultancy; Celgene: Consultancy; Gilead: Consultancy; United Therapeutics: Consultancy.

Abstract In chronic lymphocytic leukemia (CLL), it is recognized that germinal center experience by the cell-of-origin has an influence on the malignant phenotype and impacts clinical behavior. Measurement of the mutational status of the IGHV locus is a commonly used approach that subgroups patients according to this natural history. Other biomarkers correlating with these subgroups, such as ZAP70 expression and ZAP70 DNA methylation, are also used. Recently, we and others have found vast differences in global DNA methylation profiles among CLL cases that classifies distinct subgroups related to their natural history. Here we systematically evaluate various markers of natural history of the cell-of-origin for their ability to discriminate clinical outcomes. IGHV mutational status and ZAP70 expression are currently the most widely used prognostic markers of germinal center experience. These markers are generally concordant, with IGHV-unmutated associating with ZAP70 positivity. To compare their relative prognostic impact, we selected CLL cases from a large sample cohort collected as a prospective study maintained by the CLL Research Consortium that were discordant (IGHV-mutated and ZAP70(+) or IGHV-unmutated and ZAP70(-); n=192). We found a significant difference in time-to-first-treatment (TTFT; P=0.002) and overall survival (OS; P=0.032) between discordant groups, with curves separating according to IGHV as opposed to ZAP70 (Fig.1A). DNA methylation-based classification of CLL according to their natural history has not been compared to IGHV status. This classification strategy subgroups the majority of cases into low-programmed CLL (LP-CLL) or high-programmed (HP-CLL) subgroups that generally correlate with IGHV-unmutated/ZAP70(+) and IGHV-mutated/ZAP70(-), respectively, along with a minority of cases in an intermediate (IP-CLL) subgroup. We used our previously-described DNA methylation assay, based on MassARRAY interrogating 7 genomic loci including ZAP70, to group the 192 samples with discordant IGHV/ZAP70 results with 327 samples analyzed previously from the same cohort. DNA methylation (LP-CLL vs. HP-CLL) outperformed IGHV classification (unmutated vs. mutated) in terms of separating TTFT curves (n=432; LP-CLL vs. HP-CLL median difference=4.8 years, unmutated vs. mutated IGHV median difference=2.9 years) and OS curves (n=491; LP-CLL vs. HP-CLL median difference=12.9 years, unmutated vs. mutated IGHV median difference=6.8 years). To evaluate whether DNA methylation subgroups provide additional prognostic information to IGHV, we compared TTFT and OS within IGHV subtypes. We found that the ability of DNA methylation subgrouping to separate OS curves was maintained in the IGHV-unmutated subtype (P<0.001; Fig.1B) and TTFT in both IGHV-unmutated and mutated subtypes (P<0.001 and P=0.016, respectively). Conversely, IGHV subtypes did not significantly separate outcomes within DNA methylation subgroups (P>0.5 for all). Further investigation of the features of DNA methylation subgroups as defined revealed a strong bias in the frequency of several recurrent adverse prognostic somatic mutations. In particular 17p deletions and EGR2, SF3B1 and XPO1 mutations occurred frequently within the LP-CLL subgroup. We next explored whether the presence of each mutation correlated with clinical outcome within its corresponding DNA methylation subgroup, and found heterogenous results. EGR2 mutations separated TTFT in the LP-CLL subgroup (P=0.0009), but 17p, XPO1 and SF3B1 did not (P>0.3). This suggests that the cell-of-origin should be taken into account to accurately assess the clinical impact of somatic mutations. In summary, we demonstrate that among discordant cases for IGHV/ZAP70, IGHV appears to be a stronger prognostic factor for both TTFT and OS. When then evaluating the relative importance of DNA methylation subgrouping and IGHV status on TTFT and OS, we find that DNA methylation subgrouping is the more powerful prognostic factor. Among the markers of the cell-of-origin, DNA methylation is a strong tool for risk-stratifying patients and should be considered in development of risk prediction models. Figure 1. A) Kaplan-Meier analysis of TTFT of IGHV-mutated and ZAP70(+) versus IGHV-unmutated and ZAP70(-) (P=0.002, median difference=4.4 years). B) Kaplan-Meier analysis of OS in patients with unmutated IGHV separated by DNA methylation subgroup (P<0.001). Figure 1. A) Kaplan-Meier analysis of TTFT of IGHV-mutated and ZAP70(+) versus IGHV-unmutated and ZAP70(-) (P=0.002, median difference=4.4 years). B) Kaplan-Meier analysis of OS in patients with unmutated IGHV separated by DNA methylation subgroup (P<0.001). Disclosures Wierda: Acerta: Research Funding; Novartis: Research Funding; Gilead: Research Funding; Genentech: Research Funding; Abbvie: Research Funding. Brown:Infinity: Consultancy; Janssen: Consultancy; Gilead Sciences: Consultancy; Roche/Genentech: Consultancy; Celgene: Consultancy; Sun BioPharma: Consultancy; Pfizer: Consultancy; Abbvie: Consultancy. Kipps:Roche: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Gilead: Consultancy, Honoraria, Speakers Bureau; Pharmacyclics, LLC, an AbbVie Company: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding.

Abstract Abstract 3865 ZAP-70 expression is a prognostic marker differentiating chronic lymphocytic leukemia (CLL) patients with indolent disease from those rapidly progressing after diagnosis and requiring treatment. We previously demonstrated in four independent clinical cohorts that DNA methylation at a single CpG dinucleotide in the ZAP-70 promoter region impacts on ZAP-70 transcriptional regulation and is prognostic in CLL (Claus et al. J Clin Oncol. 2012;30(20):2483–91). Here, we confirm and extend our previous findings by investigating the significance of ZAP-70 methylation relative to established prognostic biomarkers in CLL: IGHV mutation status or expression of ZAP-70 protein or CD38. DNA methylation analysis of the ZAP-70 core promoter region was conducted in mononuclear cells of 295 untreated CLL patients, previously reported by the CRC (Rassenti et al. Blood 2008;112:1923–30) using MALDI-TOF mass spectrometry (MassARRAY, Sequenom). The 295 patients had a median age of 55 years (range 26–82), 69% were male, and 46% were Rai stage 0, 47% stage I/II, and 7% stage III/IV at diagnosis. ZAP-70 protein and CD38 expression were measured by four-color flow cytometry and IGHV mutational status was assessed, as previously described. By hierarchical clustering, the previously identified single CpG dinucleotide (“CpG unit 1”, position +223 relative to the transcription start) separated patients with high methylation levels across the entire region from those with lower methylation levels at this specific site. With a median follow-up of 3.9 years in 50 patients who had not started treatment and 5.6 years among those still alive (n=196), patients with lower methylation levels at CpG unit 1 had shortened time to first treatment (TTT) and overall survival (OS) (both p<0.0001), confirming the prognostic relevance of this site. In our previous study, an optimal cut-off for CpG unit 1 methylation across four data sets was between 10% and 20%. In this cohort, the optimal cut-off across the two endpoints was between 15% and 25%. A natural gap in CpG unit 1 methylation levels occurred between 20% and 25%, adding potential biological significance, as lower values may represent patient cell samples in which both alleles are unmethylated. Applying a 20% cut-off, TTT and OS were significantly different for those with lower and higher methylation levels (both p<0.0001). The 5-year TTT estimates were 22% (95 % CI: 0.16–0.28) and 64% (95% CI: 0.52–0.74), respectively, for patients with low versus high methylation levels; 5-year OS estimates were 80% (95% CI: 0.73–0.85) and 90% (95% CI: 0.81–0.95). Low ZAP-70 methylation was significantly associated with CLL-cell expression of ZAP-70, CD38, or unmutated IGHV status (each p<0.0001). In a model of TTT, expression of ZAP-70 modified the strong effect of ZAP-70 methylation. In patients with CLL cells lacking ZAP-70 expression, high methylation was protective (hazard ratio [HR]=0.37, 95% CI: 0.23–0.58). In contrast, methylation had no significant effect in ZAP-70+ CLL (HR=1.47, 95% CI: 0.81–2.68); TTT was short regardless of methylation levels (Figure 1). IGHV mutation status and expression of CD38 did not provide significant additional prognostic information. The effect modification described for TTT was not observed for OS (p=0.57). Here, ZAP-70 methylation was the strongest risk factor (hazard ratio=0.32, 95% CI: 0.19–0.54; p<0.0001), and expression of ZAP-70, CD38 or unmutated IGHV did not significantly improve the ability to explain differences in OS. Hence, the prognostic value of ZAP-70 CpG unit 1 methylation was confirmed in a large patient cohort with extensive follow-up. We defined a clinically applicable threshold for ZAP-70 methylation assessment and determined its relative value to current prognostic markers in CLL. ZAP-70 methylation predicted longer TTT among patients with CLL cells lacking ZAP-70 expression, but not among those with ZAP-70+ CLL cells, although this could reflect sampling bias due to the small number of patients (n=16) in our cohort with both high methylation and expression of ZAP-70. Lastly, methylation was the strongest risk factor for OS, and neither IGHV mutation status nor expression of ZAP-70 or CD38 significantly improved the ability to predict prognosis. In conclusion, ZAP-70 DNA methylation represents a clinically valuable biomarker for predicting TTT and OS in previously untreated patients with CLL. Disclosures: Gribben: Gilead: Honoraria; Mundipharma: Honoraria; GSK: Honoraria; Pharmacyclics: Honoraria; Roche: Honoraria; Celgene: Honoraria. Kay:Celgene: Research Funding.

AbstractAlterations in global DNA methylation patterns are a major hallmark of cancer and represent attractive biomarkers for personalized risk stratification. Chronic lymphocytic leukemia (CLL) risk stratification studies typically focus on time to first treatment (TTFT), time to progression (TTP) after treatment, and overall survival (OS). Whereas TTFT risk stratification remains similar over time, TTP and OS have changed dramatically with the introduction of targeted therapies, such as the Bruton tyrosine kinase inhibitor ibrutinib. We have shown that genome-wide DNA methylation patterns in CLL are strongly associated with phenotypic differentiation and patient outcomes. Here, we developed a novel assay, termed methylation-iPLEX (Me-iPLEX), for high-throughput quantification of targeted panels of single cytosine guanine dinucleotides from multiple independent loci. Me-iPLEX was used to classify CLL samples into 1 of 3 known epigenetic subtypes (epitypes). We examined the impact of epitype in 1286 CLL patients from 4 independent cohorts representing a comprehensive view of CLL disease course and therapies. We found that epitype significantly predicted TTFT and OS among newly diagnosed CLL patients. Additionally, epitype predicted TTP and OS with 2 common CLL therapies: chemoimmunotherapy and ibrutinib. Epitype retained significance after stratifying by biologically related biomarkers, immunoglobulin heavy chain mutational status, and ZAP70 expression, as well as other common prognostic markers. Furthermore, among several biological traits enriched between epitypes, we found highly biased immunogenetic features, including IGLV3-21 usage in the poorly characterized intermediate-programmed CLL epitype. In summary, Me-iPLEX is an elegant method to assess epigenetic signatures, including robust classification of CLL epitypes that independently stratify patient risk at diagnosis and time of treatment.