Abstract: Bruton tyrosine kinase (BTK) links the B-cell antigen receptor (BCR) and Toll-like receptors with NF-κB. The role of BTK in primary central nervous system (CNS) lymphoma (PCNSL) is unknown. We performed a phase I clinical trial with ibrutinib, the first-in-class BTK inhibitor, for patients with relapsed or refractory CNS lymphoma. Clinical responses to ibrutinib occurred in 10 of 13 (77%) patients with PCNSL, including five complete responses. The only PCNSL with complete ibrutinib resistance harbored a mutation within the coiled-coil domain of CARD11, a known ibrutinib resistance mechanism. Incomplete tumor responses were associated with mutations in the B-cell antigen receptor–associated protein CD79B. CD79B-mutant PCNSLs showed enrichment of mammalian target of rapamycin (mTOR)-related gene sets and increased staining with PI3K/mTOR activation markers. Inhibition of the PI3K isoforms p110α/p110δ or mTOR synergized with ibrutinib to induce cell death in CD79B-mutant PCNSL cells. Significance: Ibrutinib has substantial activity in patients with relapsed or refractory B-cell lymphoma of the CNS. Response rates in PCNSL were considerably higher than reported for diffuse large B-cell lymphoma outside the CNS, suggesting a divergent molecular pathogenesis. Combined inhibition of BTK and PI3K/mTOR may augment the ibrutinib response in CD79B-mutant human PCNSLs. Cancer Discov; 7(9); 1018–29. ©2017 AACR. See related commentary by Lakshmanan and Byrd, p. 940. This article is highlighted in the In This Issue feature, p. 920

Abstract: We conducted a phase-2 study in newly diagnosed PCNSL utilizing R-MPV and HDC with ASCT. Excellent disease control and OS (2-year PFS: 79%) were observed, with an acceptable toxicity profile and minimal neurotoxicity.

Abstract: BACKGROUND: Treatment may be safely deferred in asymptomatic patients with advanced stage, low tumor burden follicular lymphoma (FL) until onset of symptoms or organ failure without compromising overall survival (OS). A randomized trial comparing immediate rituximab vs. observation in this setting reported a Time to New Treatment benefit without a corresponding OS benefit (Ardeshna et al, Lancet Oncol 2014). This is a comparison of Time to 1st Treatment (TT1T, observation arm) vs. Time to 2nd Treatment (TT2T, rituximab arm) and thus biased to immediate intervention. TT2T might be a less biased primary endpoint for trials evaluating immediate intervention vs. observation. Time to Treatment n (TT(n)T) is a function of cumulative time spent from diagnosis in periods of observation, treatment, and remission, and TT(n)T approaches OS as n approaches the maximum number of therapies received, thus we also hypothesize that TT2T might be a surrogate for OS. We have therefore performed a comprehensive evaluation of standard endpoints (TT1T, OS, and EFS12), described TT2T as a novel endpoint for trials evaluating intervention vs. observation in asymptomatic patients with advanced stage, low tumor burden FL, and aimed to determine if TT2T is a reliable surrogate for OS. METHODS: We identified 246 consecutive patients at our institution, diagnosed from 1998 to 2007 with advanced stage, low tumor burden follicular lymphoma grade 1-3A, for whom physician intention at diagnosis was observation. Median time to event was calculated using the Kaplan-Meier method for each event: TT1T, TT2T, and OS. Modified Kendall's tau was used to assess the correlation between TT1T, TT2T, and OS, accounting for censoring in these quantities. Tests of modified Kendall's tau against 0 (i.e. no correlation) were performed. EFS12 was defined as non-death event within 12 months of initiation of first treatment, and median OS for EFS12 analysis was calculated from end of first treatment. Of 69 patients who received chemoimmunotherapy as first therapy following initial observation, the log-rank test was used to compare survival distributions by EFS12. RESULTS: Of 246 patients with advanced stage, follicular lymphoma grade 1-3A for whom physician intention at diagnosis was observation, there was a slight female predominance (1.16:1), 34.6% were above age 60 with a median age of 56.1 years (range 25-88), and 11.8% (29/246) developed histologic transformation prior to 1st/2nd therapy, including 7.7% (19/246) prior to 1st treatment. At a median follow-up of 10.9 years: median TT1T was 43.5 months (3.5-217.4+, 179 events), median TT2T was 151.8 months (range 5.2-219.6+, 101 events), and median OS was not reached (range 5.2-219.6+, 48 events). The modified Kendall's tau measuring correlation between TT1T and OS was 0.012 (p = 0.537), and was 0.078 (p 〈 0.001) between TT2T and OS, suggesting that TT2T is strongly correlated with OS while TT1T is not. Failure to achieve EFS12 was observed in 10.3% (7/68) and associated with inferior OS (p=0.001). Of 7 patients who failed to achieve EFS12, 3 had histologic transformation. CONCLUSIONS: TT2T is a preferred primary endpoint for clinical trials evaluating intervention vs. observation. In patients with advanced stage, low tumor burden FL who are initially observed, the median time from diagnosis to 2nd treatment is 12.7 years. Future trials evaluating the role of immediate therapy in low tumor burden FL might restrict eligibility to high risk patients expected to have inferior TT2T. Efforts are ongoing to develop biomarkers (e.g. m7-FLIPI) that identify a population enriched with high risk patients. Our data also suggest that TT2T might be a better surrogate for OS than TT1T, and analyses are ongoing to validate this finding. Figure 1 Figure 1. Disclosures Hamlin: Molecular Templates: Research Funding; Seattle Genetics: Research Funding; Portola: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; Xencor: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Horwitz:Spectrum: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy; Huya: Consultancy; Infinity: Consultancy, Research Funding; Kyowa Hakka Kirin: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Celgene: Consultancy; ADCT Therapeutics: Research Funding. Palomba:Pharmacyclics: Consultancy. Moskowitz:Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding. Noy:Pharmacyclics, LLC, an AbbVie Company: Other: travel, accommodations, expenses, Research Funding. Kumar:Celgene: Research Funding; Pharmacyclics: Research Funding; Adaptive Biotechnologies: Research Funding; Seattle Genetics: Research Funding; Celgene: Honoraria, Other: Scientific Advisory Board. Zelenetz:Amgen: Consultancy; Takeda Pharma: Consultancy; Novartis: Consultancy; Nanostring Tech: Consultancy; Portola Pharmaceuticals: Consultancy; Adaptive Biotechnology: Consultancy; Bristol Myers: Research Funding; Boehringer Ingelheim: Other: DMC Membership; Janssen: Consultancy, Research Funding; Hospira: Consultancy; Celgene: Consultancy; Gilead: Consultancy, Research Funding; GSK: Consultancy, Research Funding; Genentech/Roche: Consultancy, Research Funding.

Abstract: Background: Prognosis of follicular lymphoma (FL) has long been defined by the FLIPI score (Solal-Céligny et al., 2004) which is a 5 factor risk model consisting of age, stage, lactate dehydrogenase, hemoglobin and number of nodal areas. The FLIPI model has been validated at diagnosis in both the pre- and post-Rituximab eras. However, many patients are initially observed and have prolonged lead time from diagnosis to first treatment. In this study, we investigated whether FLIPI risk group at diagnosis changed by the time of initial treatment, and whether change of FLIPI risk group impacted treated outcome. Patients and Methods: All adult (≥18 yo) patients with de novo follicular lymphoma (FL) treated at our center between 1998 and 2007 were evaluated. Study excluded patients with ≤2 follow up visits, known divergent of composite histology at diagnosis, and active concurrent malignancies. FLIPI was scored at diagnosis and at initiation of first treatment. For patients with missing FLIPI data, FLIPI category was scored if the omission did not alter the FLIPI category. Stable FLIPI risk group was defined as FLIPI score being low or intermediate at diagnosis and at initiation of first treatment (Low-Low, Int-Int). Progressed FLIPI risk group was defined by the population which changed categories from low or intermediate at diagnosis to a higher category at initiation of treatment (Low-Int, Low-High, Int-High). FLIPI scores were available for 570 patients at both diagnosis and initial treatment. Overall survival (OS) and progression free survival (PFS) were evaluated by Kaplan-Meier method and compared by log-rank tests. Time of diagnosis was used as time origin for OS analyses. When OS analyses involved FLIPI score at the first treatment, time of the first treatment was used as the entry time to adjust the risk sets to account for the fact that FLIPI at first treatment is unknown before the onset of the first treatment. Chi-squared tests and Fisher's exact tests were used to compare categorical variables by FLIPI score change status. Progression free survival before and after 24 months (PFS24) of initial therapy were calculated. Results: For 898 FL patients, median follow up was 9.2 years (range 0.23 - 16.84), median OS not reached. Based on FLIPI at diagnosis, the 5 year OS is 97.2% for low risk, 93.0% for int risk, and 80.2% for high risk, 10 yr OS is 90.9% for low risk, 77.7% for int risk, and 67.6% for high risk. Of 570 patients with FLIPI at diagnosis and first treatment, median time to first treatment was 0.18 years (range 0-12.5) for patients with stable FLIPI (N=280) and 2.70 years (range 0.01-13.33) for patients with progressed FLIPI (N=83). For patients observed ≥ 6 and 12 months, the median time to first treatment was 1.21 years (N=47, range 0.51-12.5) and 2.49 years (N=29, range 1.0-12.5) for patients with stable FLIPI and 3.77 years (N=62, range 0.54-13.3) and 3.92 years (N=57, range 1.13-13.3) for patients with progressed FLIPI, respectively. Progressed FLIPI was observed in 14.6% (83/570) of patients. The incidence of progressed FLIPI was 51.4% (57/111) in patients observed ≥1 year before initiating therapy. Parameters contributing to progressed FLIPI compared to stable FLIPI were decreased hemoglobin (29% versus 6%), increased nodal areas affected (43% versus 2%) and higher LDH (37% versus 5%). Patients with stable FLIPI had longer PFS at 12 and 24 months, 88.6% versus 73.8% (P=0.006) and 79.3% versus 66.1% (P= 0.031) (Figure 1). Analysis of patients initially observed ≥ 6 or 12 months demonstrated that progressed FLIPI negatively affected OS and PFS (Figure 2, observed ≥ 12 month data not shown). Median PFS for patients observed ≥ 6 months was 8.36 years for stable FLIPI, 3.14 years for progressed FLIPI. At observation of ≥ 12 months, median PFS was 6.25 and 3.22 years for stable and progressed FLIPI, respectively. Increased FLIPI was associated with increased risk of transformation throughout the disease course (25% vs 16%, P=0.039). Conclusion: Progressed FLIPI between diagnosis and first line treatment is associated with a reduced PFS, and increased incidence of histologic transformation. In patients who are initially observed, a progressed FLIPI reduces OS and PFS. The effect on PFS may be related to treatment bias and ongoing analysis is underway. Progressed FLIPI potentially identifies a population with heightened risk of transformation. Disclosures Hamlin: Seattle Genetics: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Portola: Research Funding; Novartis: Research Funding; Molecular Templates: Research Funding; Xencor: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Horwitz:Seattle Genetics: Consultancy, Research Funding; Celgene: Consultancy; Huya: Consultancy; Infinity: Consultancy, Research Funding; Kyowa Hakka Kirin: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; ADCT Therapeutics: Research Funding; Spectrum: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy. Kumar:Celgene: Honoraria, Other: Scientific Advisory Board; Pharmacyclics: Research Funding; Seattle Genetics: Research Funding; Adaptive Biotechnologies: Research Funding; Celgene: Research Funding. Moskowitz:Bristol Myers Squibb: Honoraria; Merck: Honoraria; Seattle Genetics: Honoraria, Research Funding. Moskowitz:Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding. Palomba:Pharmacyclics: Consultancy. Zelenetz:Gilead Sciences: Research Funding.

Abstract: Background: Several retrospective series have characterized the genomic landscape in many lymphoma subtypes. However, as these studies used different sequencing methods, depth of coverage, and specimen source, the incidence of alterations in many lymphoma subtypes remain unknown. Even when common genomic alterations were identified within a lymphoma subtype, the incidence and spectrum of the alterations varied. In this study, we prospectively examined the incidence of genomic alterations across different lymphoma subtypes using the Foundation One Heme (FOH) assay. Methods: FOH testing was offered to patients in routine clinical practice. Formalin-fixed paraffin-embedded (FFPE) tissue, bone marrow aspirate or peripheral blood were examined using the FOH targeted sequencing assay. Hybridization capture from 405 cancer related genes and 31 genes commonly rearranged in cancer was applied to ≥ 50ng of DNA extracted from 49 tumor specimens and sequenced to high, uniform coverage. Genomic alterations, which include: base substitutions, small insertions and deletions (indels), rearrangements, and copy number alterations, were determined. Results: Specimens from 48 non-consecutive patients with lymphoma (5 new diagnoses, 42 relapsed) were prospectively examined. Represented subtypes include DLBCL (44%), FL (17%), CLL (10%), MCL (10%), MZL (8%), T cell lymphoma (4%), and Hodgkin lymphoma (2%). Median age of diagnosis was 48.1 years (range 29.5-80.6) with a male predominance (69%). The majority (75%) had advanced stage disease at diagnosis, with a median of 3 lines of therapy (range 1-12, n=44). Forty-nine specimens, (1 patient with 2 specimens) were collected from FFPE (70%), peripheral blood (22%) or bone marrow aspirate (8%). Reports resulted after a median 28 days (range 10-48 days) from the time specimens were shipped to Foundation Medicine. Across 48 patients, 90 distinct alterations were detected with a median of 5 alterations/patient (range 0-11). Genomic alterations were more commonly observed in relapsed aggressive lymphoma compared to relapsed indolent lymphoma (median 6.4 vs 4 alterations/patient, p 〈 0.05) or in newly diagnosed patients. The most common alteration was various IgH translocations (46%) and alterations in cyclin dependent kinases (CDK) genes (CDKN2A, CDKN2B and CDKN2C) (31%). Alterations of p53 (23%) and MLL2 (21%) were also frequently observed. Several rare alterations not previously described in primary lymphomas were identified, including alterations in ATRX, CDH1, MSH6, pyruvate carboxylase, and thrombospondin receptor (CD36). Alterations associated with approved agents or clinical trials were found in 89% of patients and were more frequent in relapsed aggressive B-cell NHL (median 2/patient) versus relapsed indolent B-cell NHL (median 1/patient, p 〈 0.02). Commonly identified actionable alterations included CDK alterations in DLBCL, MCL and CLL, and alterations in the PI3K oncogenic pathway in DLBCL, FL and MZL. Conclusion: Application of a comprehensive next generation genomic sequencing assay provides an opportunity to both describe the spectrum and compare the incidence of genetic alterations across different lymphoma subtypes. Preliminary data suggest the vast majority of patients have one or more genomic alterations linked to approved agents or clinical trials. Data collection is ongoing. While the true incidence of each genomic alteration is not defined, the dataset provides the frequency of genomic alterations in a clinically relevant population. Moreover, these data will facilitate design of clinical trials by providing the opportunity to select patients based on shared genomic alterations rather than lymphoma subtype. Table 1.Clinical characteristics, N=48Age at diagnosis57.1 (29.5-80.6)N (% of patients)Sex Male Female33 (68.7%)16 (33.3%)Subtype DLBCL21 (43.8%)FL8 (16.7%)CLL5 (10.4%)MCL5 (10.4%)MZL4 (8.3%)T cell lymphoma2 (4.2%)Hodgkin lymphoma1 (2.1%)Other3 (6.3%)Stage at Diagnosis I/II III/IV Not recorded10 (20.8%)36 (75.0%)2 (4.2%)Biopsy sent At diagnosis At relapse6 (12.5%)42 (87.5%)Response to First line Therapy Near CR or CR PR SD PD Unknown22 (45.8%)9 (18.8%)5 (10.4%)3 (8.3%)8 (16.7%)Genomic Alterations with clinical value Potentially Prognostic Potentially Actionable Alterations previously not well described37 (77.0%)43 (89.6%)7 (14.6%) Figure 1 Figure 1. Disclosures Moskowitz: Seattle Genetics, Inc.: Consultancy, Research Funding; Genentech: Research Funding; Merck: Research Funding. Horwitz:Celgene: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Infinity: Research Funding; Kiowa]Kirin: Research Funding; Seattle Genetics: Consultancy, Research Funding; Spectrum: Research Funding; Amgen: Consultancy; Bristol] Myers Squibb,: Consultancy; Jannsen: Consultancy. Hamlin:Gilead, Spectrum, Seattle Genetics, Genentech: Consultancy; Spectrum, GSK, Jansen and Jansen/Pharmacyclics, Portola, Seattle Genetics: Research Funding. Matasar:Genentech: Consultancy; Spectrum: Consultancy. Miller:Foundation Medicine: Employment. Stephens:Foundation Medicine: Employment, Equity Ownership. He:Foundation Medicine: Employment. Younes:Novartis: Research Funding; J & J: Research Funding; Curis: Research Funding; Bayer; Bristol Meyer Squibb; Celgene; Incyte; Janssen R & D; Sanofi; Seattle Genetics; Takeda Millenium: Honoraria.

Abstract: Ibrutinib plus R-ICE was safe, tolerable, and was not prohibitive to mobilizing hematopoietic stem cells for autologous transplantation. A favorable early signal in all evaluable rel/ref non-GC DLBCL achieving a complete metabolic remission was observed.

Abstract: Background: Lymphoma is a clinically and molecularly heterogenous disease. Next generation sequencing of primary lymphoma samples has identified common recurring genomic alterations (GAs). The distribution and frequency of recurring GAs across lymphoma subtypes remains unknown because prior studies vary in sequencing methods, depth of coverage, and specimen source. In this study, we benchmark the distribution of GAs across different lymphoma subtypes by prospectively analyzing lymphoma cases and performing comprehensive DNA/RNA targeted sequencing of genes commonly found in hematologic malignancies using the Foundation One Heme (F1H) clinical assay. Methods: After obtaining proper consent, archived specimens from 183 samples [formalin fixed paraffin embedded (FFPE) N=141, peripheral blood N=28, BM aspirate N=14] distributed across lymphoma subtypes (including 62 DLBCL, 38 T cell lymphoma, 32 FL, 17 CLL, 13 MCL) were sequenced to high, uniform coverage averaging 〉 600x for DNA, 〉 20 million pairs for RNA. GAs were determined, including base substitutions, small insertions and deletions, rearrangements, and copy number alterations. Significant non-synonymous variants were identified as mutations from the COSMIC database, amplifications of established oncogenes, or homozygous deletions and/or clear loss-of-function mutations of known tumor suppressors. Fisher's exact test with Monte Carlo estimation corrected by false discovery rate was used for associations. Results: Samples from prospectively consented patients were banked for a median of 30 days prior to genomic analysis, range 1 day to 6.5 yr. Sequencing data was reported a median of 16 days from sample date receipt. GAs were identified in 95% of samples, with a median of 4 GAs/sample. The most common GAs were TP53 (29%), MLL2 (27%), BCL2 (25%), CDKN2A/B (17%) and CREBBP (14%). Alterations of chromatic modifiers (80%), BCR/NFkB components (51%), and cell cycle pathway (44%) were most common. In our group of unpaired follicular lymphoma samples (N=7 treatment naïve, N=25 treatment exposed), the number of GAs increased with treatment exposure. We found similar gene and biological signatures regardless of prior therapy; however differences emerge in genes of potential clinical relevance. Sequencing profiles augmented or altered the pathologic diagnosis in 11 of 183 (6%) of the cases. Importantly we were able to classify the GAs as actionable, potentially actionable and variants of unclear significance to better define the clinical relevance of targeted genomic sequencing. Conclusions: Integration of comprehensive next generation targeted genomic sequencing and clinical analysis in lymphoma provides an opportunity to describe the spectrum and incidence of GAs across different lymphoma subtypes and provide guidance on application of genomic profiling. This work serves to benchmark GAs across all lymphoma subtypes in a clinically relevant population and enables design of basket trials selecting patients based on shared genomic and biologic similarity instead of lymphoma subtype. To our knowledge, this is the largest repository of clinically annotated genomic sequencing in lymphoma. Table 1. Total Specimens N = 183 Median Age at Diagnosis 57 Range 21 - 84 Median Age at Biopsy 61 Range 21 - 91 Sex • Male • Female 113 70 62% 38% Biospecimen source • Paraffin embedded • Peripheral blood • Marrow aspirate 141 28 14 77% 15% 8% Patient consent • Prospective consent • Retrospective consent 145 38 79% 21% Prospectively consented patients (N=145) Median Days to Result Median Age of Sample 16 30 days 8 - 81 1 day - 6.5 yr Disclosures Palomba: Janssen: Consultancy. Gerecitano:Genentech: Consultancy, Other: Advisory Board; AbbVie: Consultancy, Other: Advisory Board. Matasar:Spectrum: Consultancy; Genentech: Consultancy. Straus:Millenium Pharmaceuticals: Research Funding. He:Foundation Medicine, Inc.: Employment, Equity Ownership. Balasubramanian:Foundation Medicine: Employment, Equity Ownership. Stephens:Foundation Medicine, Inc.: Employment, Equity Ownership. Miller:Foundation Medicine: Employment. Levine:Loxo Oncology: Membership on an entity's Board of Directors or advisory committees; CTI BioPharma: Membership on an entity's Board of Directors or advisory committees; Foundation Medicine: Consultancy. Younes:Celgene: Honoraria; Johnson and Johnson: Research Funding; Novartis: Research Funding; Bayer: Honoraria; Bristol Meyer Squibb: Honoraria; Sanofi-Aventis: Honoraria; Seattle Genetics: Honoraria, Research Funding; Curis: Research Funding; Janssen: Honoraria; Takeda Millenium: Honoraria; Incyte: Honoraria.

Abstract: Introduction In their lifetime, patients with follicular lymphoma frequently require multiple treatments, which have improved their survival over the past few decades. The expected treatment outcome based on lines of treatment in the post-Rituximab era is currently unknown. We analyzed the progression free survival and event free survival by line of treatment to aid estimating clinical endpoints when designing future clinical trials for multiply relapsed patients. Patients and Methods Adults (≥18 years) with de novo follicular lymphoma (FL) treated at our center between 1998 and 2007 were eligible (N=1134). 236 patients with ≤2 visits, mixed histology at initial diagnosis, and active concurrent malignancy were excluded. Of the remaining 898 patients, 105 were observed and did not require treatment during the timeframe of this dataset, and 2 had incomplete data, therefore 791 patients were eligible for response, progression and event free survival (PFS and EFS) analysis (Figure 1). Response was documented by investigators based on clinical or radiographic assessment. Complete response was based on radiographic assessment. PFS was defined as start of treatment to progression of disease or death. Patients with inadequate response to treatment, change of treatment, or stable disease without subsequent documented relapse were censored in the PFS analysis. Events for EFS were defined as progression, change of treatment, and death. PFS and EFS of sequential lines of treatment were evaluated by Kaplan-Meier method and compared across lines using log-rank test with adjustment for within-patient correlation. PFS and EFS were compared by other clinical variables using regular log-rank tests. Results Median age of diagnosis was 57.3 years with 1:1 male to female ratio. Median overall survival was not reached with median follow up of 9 years (N=898, range 0.2 - 16.8 years, Figure 1A). Median time to first treatment for the entire group was 2.3 months (range 0 - 13.3 years). In first line treatment of the 791 patients, 51% (N=406) received Rituximab with chemotherapy (R-Chemo), 13% (N=101) received chemotherapy only (Chemo), 19% (N=150) received Rituximab monotherapy (R-Mono), and 17% (N=129) received other treatments including radiation and surgery. For second line treatment, 405 patients were treated with about 37% receiving R-Chemo and 34% receiving R-Mono. As line of treatment increased, the percentage of patients with radiographically assessed complete response diminished from 71% at first line treatment to 25% by fifth line treatment (Figure 1B). Median PFS for first, second and third line treatment are 4.8, 1.6, and 1 year, respectively (Figure 2A). Median EFS for first, second and third line treatment are 3.8, 1.1, 0.8 year, respectively (Figure 2B). For subsequent lines of treatment, both median PFS and EFS were 〈 1 year. Conclusion Follicular lymphoma is an indolent disease often requiring multiple lines of treatment. However, PFS and EFS for multiple lines of treatment in FL has not been described in the post-Rituximab era. The work has benchmarked the median response by line of treatment. After third line treatment, the PFS was ≤1 year. This analysis serves to aide comparison of different therapies for future drug approval in relapsed FL. Disclosures Hamlin: Xencor: Membership on an entity's Board of Directors or advisory committees; Portola: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Molecular Templates: Research Funding; Novartis: Research Funding; Seattle Genetics: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees. Horwitz:Spectrum: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy; Huya: Consultancy; Infinity: Consultancy, Research Funding; Kyowa Hakka Kirin: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Celgene: Consultancy; ADCT Therapeutics: Research Funding. Kumar:Celgene: Honoraria, Other: Scientific Advisory Board; Celgene: Research Funding; Adaptive Biotechnologies: Research Funding; Seattle Genetics: Research Funding; Pharmacyclics: Research Funding. Moskowitz:Merck: Honoraria; Seattle Genetics: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria. Moskowitz:Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding. Palomba:Pharmacyclics: Consultancy. Zelenetz:Gilead Sciences: Research Funding.