Gandhi, Anita K.

Background Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive non-Hodgkin lymphoma subtype with a 5-year survival of ~64%. While DLBCL is treated using immunochemotherapy (IC) with curative intent, 20%-40% of patients do not reach remission or relapse post IC. Clonal somatic mutations have been associated with aging, hematologic malignancies (predominately myeloid), and reduced OS in the general population. The objective of this study was to evaluate the association of clonal somatic mutations with event-free survival (EFS) and overall survival (OS). Methods We studied newly diagnosed DLBCL cases treated with IC who were enrolled in the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). Clinical and treatment data were abstracted from medical records and all patients were systematically followed for disease outcomes. Pre-treatment DNA was extracted from matched peripheral blood and paraffin-embedded tumor tissue, and whole exome sequencing was conducted at 100x coverage. From the peripheral blood, allele counts from GVCF files produced by HaplotypeCaller in GATK were extracted for 42 genes commonly associated with clonal hematopoiesis (e.g. DNMT3A, TET2, and ASXL1). Mutations were deemed clonal somatic if the population minor allele frequency was <0.5% in ExAC and had a variant allele fraction (VAF) that deviated from 0.5 using a binomial distribution test at p<0.001. Furthermore, mutations had to have a minimum alternate read count of at least 5 reads, a VAF greater than or equal to 10%, and met at least one of the following criteria: CAVA impact of "HIGH"; pathogenic/likely pathogenic per ClinVar; or reported in COSMIC at least 10 times. EFS was defined as time from diagnosis to disease progression, relapse, retreatment, or death due to any cause. The association of clonal somatic mutations with prognosis was estimated using Kaplan-Meier curves, and hazard ratios (HR) and 95% confidence intervals (CI) from Cox regression. Associations were adjusted for age at diagnosis, sex, and the International Prognostic Index (IPI). Results The study consisted of 261 DLBCL patients treated with IC. The median age at diagnosis was 65 years (range 20-90) and 56% were male. With a median follow-up time of 5.1 years (range 0.1-15.0), there were 100 events and 80 deaths. A total of 17 (6.5%) patients had clonal somatic mutations, and16 patients were over the age of 60. A total of 8 (of 42) genes had clonal somatic mutations, with SF3B1, ASXL1, and TET2, being the most frequent (4 individuals per gene). VAFs ranged from 0.10 to 0.28 and none of the patients had multiple mutations. Additionally, the clonal somatic variants found in the peripheral blood were abscent in the tumor sample. Of the 17 patients with clonal somatic mutations, 12 had an event while 88 patients without a mutation had an event. In a univariate analysis, clonal somatic mutations were associated with inferior EFS (HR=2.55, 95% CI 1.39-4.68, p=0.002; Figure 1A). After adjusting for age, sex, and IPI, clonal somatic mutations remained associated with inferior EFS (HR=2.02, 95% CI 1.09-3.74, p=0.026). Clonal somatic mutations were also associated with inferior OS in the univariate analysis (HR=2.06, 95% CI 0.99-4.29, p=0.053), which attenuated after multivariate adjustment (HR=1.59, 95% CI: 0.76-3.34, p=0.22, Figure 1B). Although based on small numbers, mutations in SF3B1 were associated with inferior EFS (HR=3.25, 95% CI 1.16-9.12, p=0.025), but did not reach significance for OS (HR=2.56, 95% CI 0.78-8.38, p=0.120). Conclusions In this novel study of newly diagnosed DLBCL patients, clonal somatic mutations were identified in 6.5% of patients and were associated with inferior outcomes. Additional research is required at deeper sequencing to validate these findings and integration with tumor genomics is required to understand the prognosis of DLBCL patients with smaller clonal populations. Disclosures Shah: Dren Bio: Consultancy. Maurer:Celgene / BMS: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Martin:Celgene: Consultancy; Karyopharm: Consultancy, Research Funding; Morphosys: Consultancy; Regeneron: Consultancy; Incyte: Consultancy; Kite: Consultancy; Cellectar: Consultancy; Bayer: Consultancy; Beigene: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy; Janssen: Consultancy; Teneobio: Consultancy. Witzig:AbbVie: Consultancy; Incyte: Consultancy; Acerta: Research Funding; Karyopharm Therapeutics: Research Funding; Immune Design: Research Funding; Spectrum: Consultancy; Celgene: Consultancy, Research Funding; MorphSys: Consultancy. Nowakowski:NanoString: Research Funding; Seattle Genetics: Consultancy; Curis: Consultancy; Kymera: Consultancy; Kite: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees; MorphoSys: Consultancy, Research Funding; Celgene/BMS: Consultancy, Research Funding. Novak:Celgene/BMS: Research Funding. Cerhan:NanoString: Research Funding; BMS/Celgene: Research Funding.

AbstractCancer treatment has been transformed by checkpoint blockade therapies, with the highest anti-tumor activity of anti-programmed death 1 (PD-1) antibody therapy seen in Hodgkin lymphoma. Disappointingly, response rates have been low in the non-Hodgkin lymphomas, with no activity seen in relapsed/refractory chronic lymphocytic leukemia (CLL) with PD-1 blockade. Thus, identifying more powerful combination therapy is required for these patients. Here, we preclinically demonstrate enhanced anti-CLL activity following combinational therapy with anti-PD-1 or anti-PD-1 ligand (PD-L1) and avadomide, a cereblon E3 ligase modulator (CELMoD). Avadomide induced type I and II interferon (IFN) signaling in patient T cells, triggering a feedforward cascade of reinvigorated T-cell responses. Immune modeling assays demonstrated that avadomide stimulated T-cell activation, chemokine expression, motility and lytic synapses with CLL cells, as well as IFN-inducible feedback inhibition through upregulation of PD-L1. Patient-derived xenograft tumors treated with avadomide were converted to CD8+ T cell-inflamed tumor microenvironments that responded to anti-PD-L1/PD-1-based combination therapy. Notably, clinical analyses showed increased PD-L1 expression on T cells, as well as intratumoral expression of chemokine signaling genes in B-cell malignancy patients receiving avadomide-based therapy. These data illustrate the importance of overcoming a low inflammatory T-cell state to successfully sensitize CLL to checkpoint blockade-based combination therapy.

Background: DLBCL has traditionally been classified by cell of origin (COO) subcategories based on tumor gene expression profiles which include Activated B-Cell (ABC) and Germinal Center B-Cell (GCB). Recently, using tumor samples from patients treated with RCHOP, new classification models have focused on DNA alterations. However, a comprehensive integrative approach using a large transcriptomic data set across both newly diagnosed (nd) and relapsed/refractory (r/r) DLBCL is yet to be accomplished. A robust clustering of this type will allow for identification of biologically driven DLBCL patient subgroups and may predict patient outcome and inform treatment approaches. Methods: RNAseq was performed on a total of 882 DLBCL tumor FFPE biopsies from 2 ndDLBCL cohorts (cohort 1 and 2) and 2 r/r DLBCL cohorts (cohorts 3 and 4). Cohort 1 (N=267) was commercially sourced and served as the discovery cohort. Cohort 2 (N=340) was from the Mayo/Iowa Lymphoma SPORE Molecular Epidemiology Resource (MER) and served as the replication cohort. Cohort 3 (N=189) was from the CC-122-ST-001 and CC-122-DLBCL-001 clinical trials (NCT01421524 and NCT02031419), and cohort 4 (N=86) was from r/r patients from the MER. Clustering input consisted of gene expression data, gene set variation analysis (GSVA) scores computed from the hallmark gene sets of MSigDB gene sets, as well as immune cell abundance estimates from a DLBCL-specific deconvolution method. An integrative clustering method iClusterPlus was applied to the input data to identify patient subgroups. A multinomial generalized linear model classifier was trained on the discovery dataset and applied to cohorts 2, 3, and 4 to assess patterns of gene expression and clinical features among the subgroups. Results: Integrative clustering identified 8 subgroups of ndDLBCL patients (DLBCL1-8; D1-D8) in cohort 1. Classifiers trained on cohort 1 were applied to cohort 2 and the same 8 clusters were identified. Among RCHOP treated patients in cohort 2, subgroups D4 (p<0.01) and D8 (p<0.0001) had significantly worse survival outcomes than the rest of the population. D4 comprised 21% of the MER ndDLBCL replication cohort (cohort 2) with a median event-free survival (mEFS) of 38.2 months and a median overall survival (mOS) of 80.3 months. D8 comprised 5% of the cohort with a mEFS of 7.5 months and a mOS of 12.1 months. The remaining 6 subgroups were standard risk, with mEFS ranging from 82.1 months to not reached, and none reaching mOS. The subgroups were not uniquely defined by previously known molecular classification methods such as COO or double hit signature (DHITsig), nor by clinical risk factors such as age or international prognostic index (IPI). Within D4, 92% of patients were ABC, representing a high risk subset of ABC patients. The mEFS in D4 ABCs was 38.2 months, while mEFS of non-D4 ABCs was not reached (p<0.005). Transcriptomic analysis revealed a lower abundance of immune infiltration. D4 was associated with high IPI, with 49% of D4 having IPI>2, compared to 33% of non-D4 with IPI>2 (p<0.05). D8 represented a high-risk subset which was 73% GCB. The mEFS of D8 GCBs was 5.4 months, while mEFS of non-D8 GCBs was not reached (p<0.0001). Transcriptomic analysis revealed low expression of immune response and cytokine signaling pathways, consistent with the low abundance of immune cells in D8. This subgroup consisted of 63% DHITsig positive patients. Although only 20% of all DHITsig positive patients were in D8, these D8 DHITsig patients showed significantly worse survival than non-D8 DHITsig patients (mEFS 11.3 months vs. not reached, p<0.0001). In the r/r DLBCL setting, D1-D8 were all present, with an increased prevalence of D4 and D8 in Cohort 3 (30% and 17%, respectively) and Cohort 4 (30% and 14%) compared to the newly diagnosed setting. Mutational data for these cohorts has been collected and is being interpreted in the context of the discovered subgroups. Conclusion: A novel integrative clustering of transformed gene expression data revealed 8 biologically homogeneous groups, two of which had inferior outcomes when treated with RCHOP therapy. Furthermore, these two subgroups were more prevalent in r/r DLBCL. This classification allows for the transcriptomic identification of high-risk patients underserved by RCHOP therapy. *Ortiz, Wenzl and Stokes contributed equally **Gandhi and Novak contributed equally Disclosures Ortiz: Celgene Corporation: Employment, Equity Ownership. Stokes:Celgene Corporation: Employment, Equity Ownership. Huang:Celgene Corporation: Employment, Equity Ownership. Maurer:Celgene: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Towfic:Celgene Corporation: Employment, Equity Ownership. Hagner:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Ratushny:Celgene Corporation: Employment, Equity Ownership. McConnell:Celgene Corporation: Employment, Equity Ownership. Danziger:Celgene Corporation: Employment, Equity Ownership. Stong:Celgene Corporation: Employment, Equity Ownership. Lata:Celgene Corporation: Employment, Equity Ownership. Kamalakaran:Celgene Corporation: Employment, Equity Ownership. Mavrommatis:Celgene Corporation: Employment, Equity Ownership. Trotter:Celgene Corporation: Employment, Equity Ownership. Czuczman:Celgene Corporation: Employment, Equity Ownership. Ansell:Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding. Cerhan:NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding. Nowakowski:Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding. Gandhi:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Novak:Celgene Coorperation: Research Funding.

Background: Diffuse large B cell lymphoma (DLBCL) is the most common aggressive lymphoid malignancy in adults. Though standard immunochemotherapy regimens can result in clinical remission and cure in a majority of patients, approximately 30% of patients are primary refractory or eventually relapse, and their prognosis is very poor. Recent progress by large scale genomic and transcriptomic profiling of DLBCL patients has resulted in a deep understanding of disease drivers in newly diagnosed DLBCL (ndDLBCL). However, previous genomic studies of relapsed and/or refractory DLBCL (rrDLBCL) are limited by small sample sizes and much less is known about the genomic landscape or the changes in clonal populations that occur within a patient undergoing R-CHOP therapy. Analysis of a large cohort of rrDLBCL is needed to uncover the importance of known drivers, define clonal shifts that occur in relapsing patients, and discover novel mutations that impact resistance to therapy. Methods: DNA sequencing (whole exome or genome sequencing) was performed on tumor and matching germline samples from two rrDLBCL patient cohorts (N=143). The first rrDLBCL cohort consisted of 68 formalin fixed paraffin embedded (FFPE) tumor samples with matched germline obtained from the Mayo/Iowa Lymphoma SPORE Molecular Epidemiology Resource (MER); including 18 diagnostic/relapse paired samples. The second cohort consisted of 75 FFPE samples from 2 rrDLBCL clinical trials CC-122-ST-001 and CC-122-DLBCL-001 (NCT01421524 and NCT02031419). In addition, a ndDLBCL cohort (n=364) consisting of MER front line samples were also analyzed. CNV and SV calling was performed with Sclust and Manta, respectively. Mutational drivers were identified with cDriver. Cosmic mutational signatures were calculated for all samples. Results: For comparison of overall mutation rates between the ndDLBCL and rrDLBCL we analyzed the frequency of mutations in known driver genes [n=211, Chapuy et al, 2018; Schmitz et al, 2018; Reddy et al 2017]. Of these, the top 5 most mutated genes found in the relapse cohort were KMT2D (34.3%), IGLL5 (25.9%), CREBBP (22.4%), TP53 (21.0%), and HIST1H1E (19.6%) all of which were previously reported as mutated genes in rrDLBCL [Morin et al. 2016; Park et al. 2016;Greenawalt et al. 2017]. None of these frequencies changed significantly from the MER ndDLBCL cohort. However, frequencies of 2 genes NCOR1 and ACTB were increased significantly from 3.3% to 13.3% (p= 5.85 x 10-05) and 0.5% to 6.3% (p=2.56 x 10-04), respectively, in the rrDLBCL cohorts. Analysis of the previously reported driver mutations in 18 paired samples revealed a significant increase in the mean variant allele frequency (VAF) from diagnosis to relapse of mutations in BCL2 and BIRC6 from 18.5% to 28.8%(p=0.016) and 4.3% to 13.7%(p=0.011), respectively. In our analysis of novel drivers in rrDLBCL cohorts, 59 significant driver mutations (FDR 0.1) were identified, 23 were novel driver mutations while the remaining 36 have been previously reported as drivers of newly diagnosed DLBCL. These include novel mutations in genes such as IL4R (8.8%), CDK5R1 (6.7%), LAPTM5 (3.7%) and others whose function in lymphoma are unknown. In a secondary analysis, we performed mutational signature analysis for rrDLBCL and identified groups of patients with COSMIC mutational signatures that are associated with aging, defects in homologous end joining resulting in large insertions/deletions, and with defective mismatch repair often found in microsatellite unstable tumors. Together with the high prevalence of TP53 mutations, these results indicate genetic instability as a hallmark of relapse/refractory DLBCL. Analysis of CNV and SV will also be reported. Conclusion: Here we report to our knowledge the largest genomic dataset in relapsed and /or refractory DLBCL using tumor biopsies. Previously identified mutated genes in rrDLBCL were confirmed and novel drivers identified. Paired samples analysis reveals clonal shifts which occur during treatment and at time of relapse. Whether the novel driver mutations appeared as a function of selection of a rare clone over the course of therapy or a therapy induced mutation will be the focus of ongoing work. Novel variants including SNV, CNV and SV can potentially lead to new insights and deepen our understanding of the mechanisms of resistance in DLBCL. * Wenzl, Ortiz and Stong contributed equally **Novak and Gandhi contributed equally Disclosures Ortiz: Celgene Corporation: Employment, Equity Ownership. Stong:Celgene Corporation: Employment, Equity Ownership. Huang:Celgene Corporation: Employment, Equity Ownership. Maurer:Morphosys: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Nanostring: Research Funding. Towfic:Celgene Corporation: Employment, Equity Ownership. Hagner:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Nikbakht:Celgene Corporation: Employment, Equity Ownership. Stokes:Celgene Corporation: Employment, Equity Ownership. Lata:Celgene Corporation: Employment, Equity Ownership. Kamalakaran:Celgene Corporation: Employment, Equity Ownership. Mavrommatis:Celgene Corporation: Employment, Equity Ownership. Trotter:Celgene Corporation: Employment, Equity Ownership. Czuczman:Celgene Corporation: Employment, Equity Ownership. Ansell:Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding. Cerhan:Celgene: Research Funding; NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees. Nowakowski:Bayer: Consultancy, Research Funding; Curis: Research Funding; Celgene: Consultancy, Research Funding; MorphoSys: Consultancy, Research Funding; Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding. Novak:Celgene Coorperation: Research Funding. Gandhi:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties.

Diffuse large B-cell lymphoma is a heterogeneous disease, commonly described by cell-of-origin (COO) molecular subtypes. We sought to identify novel patient subgroups through an unsupervised analysis of a large public dataset of gene expression profiles from newly diagnosed de novo DLBCL patients, yielding two biologically distinct subgroups characterized by differences in the tumor microenvironment. Pathway analysis and immune deconvolution algorithms identified higher B-cell content and a strong proliferative signal in subgroup A and enriched T-cell, macrophage, and immune/inflammatory signals in subgroup B, reflecting similar biology to published DLBCL stratification research. A gene expression classifier, featuring 26 gene expression scores, was derived from the public dataset to discriminate subgroup A (classifier-negative, immune-low) and subgroup B (classifier-positive, immune-high) patients. Subsequent application to an independent series of diagnostic biopsies and replicated the subgroups with immune cell composition confirmed via immunohistochemistry. Avadomide, a CRL4CRBN E3 ubiquitin ligase modulator, demonstrated clinical activity in relapsed/refractory DLBCL patients, independent of COO subtypes. Given the immunomodulatory activity of avadomide and need for a patient selection strategy, we applied the gene expression classifier to pretreatment biopsies from relapsed/refractory DLBCL patients receiving avadomide (NCT01421524). Classifier-positive patients demonstrated an enrichment in response rate and progression-free survival of 44% and 6.2 months versus 19% and 1.6 months for classifier-negative patients (HR=0.49 [0.280, 0.86]; P=.0096). The classifier was not prognostic for R-CHOP or salvage immunochemotherapy. The classifier described here discriminates DLBCL tumors based on tumor and non-tumor composition and has potential utility to enrich for clinical response to immunomodulatory agents including avadomide.

Introduction: New Diffuse Large B-cell (DLBCL) treatments remain a clinical need despite the success of rituximab combined with CHOP chemotherapy (RCHOP), which results in durable responses in 60-70% of patients. Those refractory to, or who relapse following, first-line therapy have a very poor outcome, with only 20% surviving beyond 5 years. Rationally-targeted frontline strategies are needed, especially for those with high-risk disease. Significant advances have been made in the genomic classification of DLBCL, but none have impacted the design of phase III trials for untreated DLBCL patients. Building on new genetic profiling studies to personalize clinical treatment, an NCI initiative, could allow clinicians to add targeted therapies to the RCHOP backbone based on individual tumor signatures. The phase II ECOG-ACRIN1412 trial, which compared RCHOP combined with lenalidomide (R2CHOP) versus RCHOP showed significantly superior event free survival (EFS) and overall survival benefits for those treated with R2CHOP. Herein, we report the profile of a high-risk ABC/non-GCB subset of DLBCL driven by genomic alterations in inflammatory genes that are susceptible to front-line R2CHOP, but continue to experience poor outcome with RCHOP alone. Methods: We studied a total of 196 DLBCL patients. 47 were treated with R2CHOP from an investigator-initiated, open-label, single-arm phase II study (NCT00670358). 149 were newly diagnosed DLBCL cases treated with RCHOP, or R-immunochemotherapy (herein called RCHOP), and followed prospectively through the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic SPORE that served as a contemporary cohort. Patients from each treatment group were divided based on their event free survival at 24 months (EFS24). DNA alterations within these populations were identified through whole exome sequencing (WES). Variants were analyzed for their presence in EFS24 achievement or failure groups in both RCHOP and R2CHOP. Both tumor and germline sequencing was performed for 47/47 R2CHOP cases and 49/149 RCHOP cases. Gene expression data from the PanCan panel of 730 B-cell-related genes was analyzed to determine gene expression profiles characteristic of the high-risk/R2CHOP-profile on 59 available non-GCB DLBCL cases (45 RCHOP; 14 R2CHOP). A two-sided comparative marker analysis T statistic test was applied to assess what genes displayed differential expression based on achieving EFS24 in both R2CHOP and RCHOP populations. Positive values represented associations with achieving EFS24 and negative values were associated with cases of EFS24 failure. Results: Three genes were enriched in the RCHOP cases that failed EFS24 but achieved EFS24 with R2CHOP among non-GCB patients: PIM1, SPEN, and MYD88 (L265P), herein referred to as Responder Alterations. In R2CHOP cases, patients with a Responder Alteration had a better overall EFS (P = 0.051) compared to wild type patients. In contrast, RCHOP treated patients with a Responder Alteration in their tumor had a significantly worse overall EFS (P = 0.0004) compared to patients without a mutation. Together, PIM1, SPEN, or MYD88 (L265P) mutations were present in 38.0% (30/79) of all non-GCB cases. Collective R2CHOP and RCHOP EFS24 differential gene expression T values were significantly different for 18 previously-defined signatures. The R2CHOP cases that achieved EFS24 were enriched for genes involved in cell cycle, JAK-STAT, cytokine signaling, and NF-κB pathways based on these signatures and ontology analyses. Lastly, cases with WES and PanCan data were analyzed together to observe differential gene expression patterns between cases with and without signature mutations. These data suggest that R2CHOP disrupts tumors reliant on IRF4, NF-κB, and STAT transcription factors, leading to a loss of proliferative feedback systems. Conclusions: Our combined analysis of DNA and RNA across R2CHOP and RCHOP treatment cohorts identifies a high-risk non-GCB phenotype that encompasses approximately 38% of non-GCB patients, is capable of sustaining JAK-STAT and NF-κB signaling, and is sensitive to R2CHOP. Our study lays the groundwork for a precision therapy approach in DLBCL in which DNA or RNA profiles can be used to identify patients early in treatment who may not benefit from the current standard of care, RCHOP, and who would benefit from the addition of lenalidomide or other targeted agents. Disclosures Gandhi: Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Ansell:LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding. Cerhan:Celgene: Research Funding; NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees. Nowakowski:Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding; NanoString: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees. Novak:Celgene Coorperation: Research Funding.

Abstract Introduction:The prognosis is poor for patients with follicular lymphoma (FL) who experience early relapse within 2 years of initial diagnosis and for those who are double refractory to both rituximab and chemotherapy (Casulo et al. J Clin Oncol 2015). Avadomide, a cereblon-modulating agent that promotes degradation of the hematopoietic transcription factors Aiolos and Ikaros, is being examined in this setting. Avadomide demonstrated promising clinical activity in combination with obinutuzumab or rituximab in relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) and FL (Michot et al. Blood 2017; Ribrag et al. Blood 2017). Herein, we report FL subgroup analyses for the avadomide plus rituximab combination (Arm D) of the CC-122 DLBCL-001 study in both lenalidomide-naïve and treated patients. Methods: CC-122-DLBCL-001 (NCT02031419) is aphase Ib dose escalation/expansion study of avadomide, CC-223, and CC-292 given orally as doublets, and as triplets in combination with rituximab, as well as avadomide plus rituximab doublets, in patients with R/R DLBCL or FL after ≥1 prior line of therapy. In the dose expansion phase of the study, patients received avadomide once daily (QD) for 5 days/week (5/7 d), with a fixed dose of intravenous rituximab 375 mg/m2/cycle (28-day cycle). The study endpoints were safety, tolerability, pharmacokinetics, preliminary efficacy (overall response rate [ORR] and complete response [CR]), and blood pharmacodynamic markers of avadomide. Results: As of May 1, 2018, 37 patients with FL were enrolled in the Arm D expansion group, including 29 in cohort 1 (no prior lenalidomide) and 8 in cohort 2 (≥2 cycles of prior lenalidomide). Baseline patient characteristics were similar between the two cohorts. In the total FL population, the median age was 61 years (range, 41-81 years), 54% were male, and 46% had an Eastern Cooperative Oncology Group performance status of 1. The median number of prior systemic anticancer regimens was 3 (range, 1-8). At disease diagnosis, three patients (8%) had bulky disease (≥7 cm in single dimension) and 7 (19%) had high Follicular Lymphoma International Prognostic Index scores. Twenty-three patients (62%) were refractory to rituximab and 11 (30%) were double-refractory to rituximab and an alkylating agent. As of the data cutoff, 27 patients (71%) were ongoing and no evaluable patients had experienced a dose-limiting toxicity. The most common (≥10%) any-grade adverse events (AEs) were neutropenia (46%) and anemia (24%). Grade 3/4 AEs occurring in >1 patient were neutropenia (32%); fatigue, dizziness, and anemia (8% each); febrile neutropenia and diarrhea (5% each). Six patients (16%) experienced serious AEs related to study drugs. One patient died during the study (sepsis considered possibly related to study treatment). Avadomide dose reduction occurred in 7 (19%) patients. Among all FL patients, the ORR was 65% with 8 patients (22%) achieving a CR. Response rates appeared to be independent of prior lenalidomide treatment, with an ORR of 62% (CR=14%) in cohort 1 and an ORR of 75% (CR=50%) in cohort 2. The median follow up for progression-free survival (PFS) was 6.3 months and 49% of patients had <6 months of PFS follow up. In the total FL population, 6-month and 12-month PFS rates were 83 (95% CI, 64-93) and 66 (37-84), respectively. Conclusions: Avadomide combined with rituximab was well tolerated. AEs were generally consistent with the known safety profile of avadomide and toxicities associated with rituximab. Moreover, this combination showed promising efficacy in patients with R/R FL independent of prior treatment with lenalidomide. These findings support the role of avadomide plus an anti-CD20 antibody as a novel chemotherapy-free treatment for this difficult to treat patient population. Disclosures Nastoupil: TG Therappeutics: Research Funding; Karus: Research Funding; Novartis: Honoraria; Merck: Honoraria, Research Funding; Juno: Honoraria; Celgene: Honoraria, Research Funding; Gilead: Honoraria; Janssen: Research Funding; Spectrum: Honoraria; Genentech: Honoraria, Research Funding. Ribrag:Amgen: Research Funding; Roche: Honoraria, Other: travel; epizyme: Consultancy, Honoraria; MSD: Honoraria; Infinity: Consultancy, Honoraria; NanoString Technologies: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Other: travel; Servier: Consultancy, Honoraria; pharmamar: Other: travel; Gilead: Consultancy, Honoraria; Incyte Corporation: Consultancy; argenX: Research Funding. Chavez:Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Humanigen: Consultancy; Merck: Research Funding; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Speakers Bureau. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Andorsky:AstraZeneca: Consultancy; Genentech: Consultancy; Celgene: Research Funding; CTI BioPharma: Consultancy, Research Funding. Corradini:Janssen: Honoraria, Other: Lecturer; Amgen: Honoraria, Other: Advisory Board & Lecturer; Gilead: Honoraria, Other: Advisory Board & Lecturer; Celgene: Honoraria, Other: Advisory Board & Lecturer; Roche: Honoraria, Other: Advisory Board & Lecturer; Takeda: Honoraria, Other: Advisory Board & Lecturer; Sanofi: Honoraria, Other: Advisory Board & Lecturer; Novartis: Honoraria, Other: Advisory Board & Lecturer; Abbvie: Honoraria, Other: Advisory Board & Lecturer; Sandoz: Other: Advisory Board. Flinn:ArQule: Research Funding; Agios: Research Funding; TG Therapeutics: Research Funding; Calithera: Research Funding; BeiGene: Research Funding; Verastem: Consultancy, Research Funding; Janssen: Research Funding; Curis: Research Funding; Pharmacyclics: Research Funding; Incyte: Research Funding; Trillium: Research Funding; Forty Seven: Research Funding; Kite: Research Funding; Pfizer: Research Funding; Verastem: Research Funding; Novartis: Research Funding; Genentech: Research Funding; Merck: Research Funding; Portola: Research Funding; Takeda: Research Funding; Seattle Genetics: Research Funding; Constellation: Research Funding; Forma: Research Funding; Celgene: Research Funding; Gilead: Research Funding; Infinity: Research Funding. Sangha:Merck: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; Lilly: Honoraria, Membership on an entity's Board of Directors or advisory committees; Lundbeck: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche/Genentech: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; BI: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees. Uttamsingh:Celgene Corporation: Employment, Equity Ownership. Hagner:Celgene Corporation: Employment, Equity Ownership. Gandhi:Celgene Corporation: Employment, Equity Ownership. Chen:Celgene Corporation: Employment, Equity Ownership. Hege:Mersana: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; SITC: Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Employment, Equity Ownership, Patents & Royalties: multiple; Arcus Biosicences: Membership on an entity's Board of Directors or advisory committees. Pourdehnad:Celgene Corporation: Employment, Equity Ownership. Kuruvilla:Celgene: Honoraria; Roche: Consultancy, Honoraria, Research Funding; Gilead: Consultancy, Honoraria; Lundbeck: Honoraria; BMS: Consultancy, Honoraria; Abbvie: Consultancy; Merck: Consultancy, Honoraria; Amgen: Honoraria; Seattle Genetics: Consultancy, Honoraria; Karyopharm: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Princess Margaret Cancer Foundation: Research Funding; Leukemia and Lymphoma Society Canada: Research Funding.

Abstract Background: We previously reported that Lenalidomide combined with R-CHOP (R2CHOP) has significant activity in non-GCB (non-germinal center B-cell) subtype of DLBCL as defined by immunohistochemistry (IHC) using Hans algorithm (J Clin Oncol. 2015 Jan 20;33(3):251-7). However, defining non-GCB subtype of DLBCL by IHC as opposed to the "gold standard" gene expression profiling (GEP) is subject to technical limitations and its prognostic value has not reproduced in some recently published studies. In addition, recent reports questioned prognostic value of GEP in prospective clinical trials as opposed to initial reports from retrospective case series. To address these concerns, we assessed outcomes by cell of origin (COO) as determined via GEP using NanoString Lymphoma Subtyping Test (LST) on formalin-fixed paraffin-embedded (FFPE) tissue on patients enrolled in a phase 2 study of R2CHOP and an independent comparison cohort of patients treated with RCHOP alone. Methods: Eligible patients for R2CHOP phase 2 study MC078E were adults with newly diagnosed, untreated, stages II-IV CD20 positive DLBCL. Patients received oral lenalidomide 25 mg days 1-10 with standard dose R-CHOP every 21 days for 6 cycles. All patients received pegfilgrastim on day 2 of each cycle and aspirin prophylaxis. DLBCL molecular subtype was determined by GEP using NanoString LST, a multiplexed digital gene expression assay performed on the nCounter® Dx Analysis System and reported as GCB vs ABC vs unclassified. A comparison cohort of RCHOP treated DLBCL patients was generated from the prospectively enrolled Mayo Clinic component of the Lymphoma SPORE Molecular Epidemiology Resource (MER). MER patients meeting the same inclusion criteria as MC078E with available tissue were selected based via matching on age, stage, and IPI to the MC078E patients. Event-free survival was defined as time from diagnosis (MER) or study registration (MC078E) to progression, re-treatment, or death. EFS24 was defined as being event-free at 24 months. Associations between COO and outcome were assessed via log-rank tests due to censoring for EFS24. Results: 50 MC078E R2CHOP patients enrolled between 2008 and 2013,124 matched MER RCHOP patients diagnosed between 2003 and 2012 were assessed for COO. Median follow up in 70 patients still alive was 7.9 years (1.9-13.0) in RCHOP treated patients and 4.4 years (1.9-5.5) for 24 in R2CHOP treated patients still alive. Median age was 65 years (range 35-89) in RCHOP treated patients and 69 years (22-87) in R2CHOP patients (p=0.485). 53 RCHOP treated patients (43%) and 31 R2CHOP treated patients (62%) had intermediate-high or high IPI (p=0.021). COO was GCB, ABC, and unclassified DLBCL subtype in 80, 31 and 13 patients in the 124 RCHOP cohort and 33, 13 and 4 patients in the R2CHOP treated patients, respectively (see table). EFS24 was inferior for ABC (48%) compared to GCB DLBCL 71% in MER RCHOP treated patients (p=0.013). In contrast, in R2CHOP treated pts, EFS24 was not different between ABC vs GCB DLBCL 69% vs 67% (p= 0.674). Conclusion: Cell of origin classification of DLBCL determined by NanoString LST remains prognostic in a series of prospectively enrolled DLBCL patients treated with RCHOP. R2CHOP shows promising efficacy in ABC DLBCL as defined by NanoString LST, where the addition of lenalidomide to RCHOP appears to mitigate the negative impact of an ABC molecular subtype on the outcome. Table Table. Disclosures Nowakowski: Morphosys: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Research Funding. Maurer:Kite Pharma: Research Funding; Celgene: Research Funding. Storhoff:NanoString Technologies, Inc.: Employment, Other: Stock option. Dennis:NanoString Technologies, Inc.: Employment, Other: Stock option. Gandhi:Celgene Corporation: Employment, Equity Ownership. Thakurta:Celgene: Employment, Equity Ownership. Hagner:Celgene Corporation: Employment, Equity Ownership. Rimsza:NCI/NIH: Patents & Royalties: L.M. Rimsza is a co-inventor on a provisional patent, owned by the NCI of the NIH, using Nanostring technology for determining cell of origin in DLBCL..