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Background: Although diffuse large B cell lymphoma (DLBCL) can be cured using immuno-chemotherapy, 40% of patients experience relapse or refractory disease. Large-scale profiling studies have mainly focused on DLBCL at diagnosis, resolving different outcome groups based on gene expression (e.g. cell-of-origin (COO) or molecular high grade), MYC/BCL2 translocations (double-hit lymphoma) or gene mutations and copy number aberrations (Schmitz et al, NEJM 2018; Chapuy et al, NatureMedicine 2018). In comparison, longitudinal studies have been hindered by the limited availability of sequential biopsy samples. To date, the relapse-specific gene mutations identified are limited and inconsistent across studies. In our study, we have focussed attention on the changes in gene expression profile (GEP) accompanying DLBCL relapse. Methods: We retrospectively collected archival paired diagnostic/relapse formalin fixed paraffin embedded tumor biopsies from 38 de novo DLBCL patients collected from multiple UK sites treated with rituximab-based immuno-chemotherapy, where partial or complete remission was reported following treatment. COO classification was performed by the Lymph2Cx assay on NanoString to distinguish activated B-cell-like (ABC) and germinal center B-cell-like (GCB) subtypes. The Ion AmpliSeq™ Transcriptome Human Gene Expression Kit was used to measure the expression levels of > 20,000 genes on the paired samples. Results: COO remained stable from diagnosis to relapse in 17 ABC-ABC pairs, 11 GCB-GCB pairs and 4 unclassified (UNC)-UNC pairs. Frank COO switching was observed in 6 cases (1 ABC-GCB, 2 ABC-UNC, 2 GCB-UNC, 1 UNC-ABC). Pairs with stable COO were taken forward for further analysis. Gene expression analysis using the limma R package identified 163 and 136 genes as differentially expressed (DE) (p 1) between the diagnostic and relapse biopsies in ABC and GCB tumors respectively, with only a one gene overlap. Gene Set Enrichment Analysis further suggested that ABC and GCB relapses are mediated via different mechanisms, with tumor growth and proliferation signatures enriched in ABC relapses, whilst adaptive immunity-related signatures accompanied GCB relapses. Next, we aimed to utilise our relapse-specific genes to identify outcome predictors at diagnosis using publicly available GEP datasets. In order to increase our discovery power and accuracy, a larger set of DE genes from the paired differential analysis (796 genes in ABC pairs and 387 from GCB pairs) were selected (p The prognostic significance of this 30-gene discriminator was successfully validated using a linear predictor in two independent GEP datasets: 1) a population-based cohort (Lenz et al, NEJM 2008) with 93 R-CHOP-treated ABC cases identifying 47 low and 46 high-risk cases (HR=1.92, p=0.046, C-index=0.77; Fig1.C) and 2) a clinical trial dataset (REMoDL-B, Davies et al, Lancet Oncol 2019) with 255 ABC cases identifying 110 low and 145 high-risk ABC cases (HR=1.95, p=0.0051, C-index=0.70; Fig1.D). Conclusions: Here we describe a 30-gene discriminator in ABC-DLBCL, derived from genes differentially expressed between diagnosis and relapse, that allowed the definition of clinically distinct high and low risk subgroups in ABC-DLBCLs at diagnosis. The clinical translation of such a tool may be useful to guide therapy for this unfavourable subgroup of ABC-DLBCLs. Validation of this signature is currently underway in additional datasets and further study is required to understand the contribution of these genes in DLBCL pathology. Disclosures Korfi: Roche: Consultancy. Burton:Celgene: Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees. Rule:TG Therapeutics: Consultancy, Honoraria; Napp: Consultancy; Kite: Consultancy; Pharmacyclics: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Astra-Zeneca: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Crosbie:Janssen: Honoraria. Scott:Celgene: Consultancy; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding; Roche/Genentech: Research Funding. Rimsza:NanoSting: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution]. Davies:Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding; Bayer: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Research Funding; Karyopharma: Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Research Funding; Acerta Pharma: Honoraria, Research Funding; ADCT Therapeutics: Honoraria, Research Funding; BioInvent: Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; MorphoSys AG: Honoraria, Membership on an entity's Board of Directors or advisory committees. Gribben:Abbvie: Consultancy, Honoraria, Research Funding; Acerta/Astra Zeneca: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Okosun:Gilead Sciences: Honoraria, Research Funding. Johnson:Epizyme: Honoraria, Research Funding; Novartis: Honoraria; Kite: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Boehringer Ingelheim: Honoraria; Takeda: Honoraria; Genmab: Honoraria; Celgene: Honoraria; Incyte: Honoraria. Fitzgibbon:Epizyme: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Speakers Bureau.

Although long considered as a disease of failed apoptosis, it is now clear that chronic lymphocytic leukemia (CLL) cells undergo extensive cell division in vivo, especially in progressive disease. Signaling via the B-cell receptor is thought to activate proliferation and survival pathways in CLL cells and also has been linked to poor outcome. Here, we have analyzed the expression of the proto-oncoprotein MYC, an essential positive regulator of the cell cycle, after stimulation of surface IgM (sIgM). MYC expression was rapidly increased after sIgM stimulation in a subset of CLL samples. The ability of sIgM stimulation to increase MYC expression was correlated with sIgM-induced intracellular calcium fluxes. MYC induction was partially dependent on the MEK/ERK signaling pathway, and MYC and phosphorylated ERK1/2 were both expressed within proliferation centers in vivo. Although stimulation of sIgD also resulted in ERK1/2 phosphorylation, responses were relatively short lived compared with sIgM and were associated with significantly reduced MYC induction, suggesting that the kinetics of ERK1/2 activation is a critical determinant of MYC induction. Our results suggest that ERK1/2-dependent induction of MYC is likely to play an important role in antigen-induced CLL cell proliferation.

The anti-CD20 mAb rituximab is central to the treatment of B-cell malignancies, but resistance remains a significant problem. We recently reported that resistance could be explained, in part, by internalization of rituximab (type I anti-CD20) from the surface of certain B-cell malignancies, thus limiting engagement of natural effectors and increasing mAb consumption. Internalization of rituximab was most evident in chronic lymphocytic leukemia (CLL) and mantle cell lymphoma (MCL), but the extent of internalization was heterogeneous within each disease. Here, we show that the inhibitory FcγRIIb on target B cells promotes this process and is largely responsible for the observed heterogeneity across a range of B-cell malignancies. Internalization correlated strongly with FcγRIIb expression on normal and malignant B cells, and resulted in reduced macrophage phagocytosis of mAb-coated targets. Furthermore, transfection of FcγRIIb into FcγRIIb negative Ramos cells increased internalization of rituximab in a dose-dependent manner. Target-cell FcγRIIb promoted rituximab internalization in a cis fashion and was independent of FcγRIIb on neighboring cells. It became phosphorylated and internalized along with CD20:anti-CD20 complexes before lysosomal degradation. In MCL patients, high FcγRIIb expression predicted less durable responses after rituximab-containing regimens. Therefore, target-cell FcγRIIb provides a potential biomarker of response to type I anti-CD20 mAb.

Primary central nervous system (CNS) lymphoma is an aggressive B-cell tumor that is defined clinically by the absence of systemic disease. We have used immunoglobulin variable (V)–gene analysis to identify tumor cells at the CNS site in 12 cases and to probe the involvement of peripheral tissues in 3 patients. Clonal tracking revealed tumor cells in the bone marrow and/or blood for 3 of 3 cases, with evidence for increased V-gene mutational activity at peripheral sites. In 2 of 3 cases, intraclonal variant analysis revealed identity with the brain biopsy but detected additional variants unique to extracerebral sites. These findings suggest that peripheral tumor cells can undergo separate development locally with no reentry into the brain. Primary CNS lymphoma appears to have both CNS-specific and systemic components with limited interchange. The more malignant behavior of tumor cells in the CNS suggests either a local environmental influence or a less malignant phenotype of the peripheral clone.

Abstract 2747 Background: Single-agent immunotherapy with rituximab is a viable treatment option for low risk FL, with limited toxicity and a long duration of response in some patient subsets. We have previously shown that high expression of FcγRIIB promotes rituximab internalisation on various B cell targets, including FL (Blood 2011 118:2530–2540), something not seen with type II anti-CD20 antibodies. The SAKK 35/98 trial examined rituximab monotherapy in FL and now has long-term follow-up data of almost 10 years (JCO 2010 28:4480–4484). We analysed diagnostic tumour samples from this trial to determine the relationship of FcγRIIB expression to responses and clinical outcomes after rituximab treatment in FL. Methods: 202 patients (pts) with newly diagnosed or relapsed FL received induction treatment with rituximab 375 mg/m2 weekly for 4 weeks. Pts with stable or responding disease at week 12 were randomized into 2 groups: no further treatment or prolonged treatment with single infusions of rituximab 375 mg/m2 at weeks 12, 20, 28 and 36. Archived tissue samples from 135 evaluable pts were stained using an anti-human FcγRIIB antibody (clone EP888Y, Abcam) at a dilution of 1:3000 on a Dako autostainer. The samples were pretreated with the Dako EnVisionFLEX target retrieval solution high pH and detection using the Dako AS-Link 48 with Dako EnVision flex plus detection kit. Positive samples were graded into negative/low intensity staining (n=120) versus medium/high (n=13) by an expert lymphoma histopathologist blinded to the clinical outcomes. Data from 2 slides and response at week 12 data for 4 pts were unavailable (1 of whom also has missing slide data), resulting in 130 pts available for analysis. Failure-free survival (FFS) was defined as time from registration until failure to achieve complete/partial response at week 12, progression, relapse, a second cancer or death from any cause. Objective response rate (ORR) was associated with intensity staining levels using Fisher's exact test. All time-to-event endpoints were evaluated using the Kaplan-Meier method; groups were compared using the log-rank test. The hazard ratio (HR) was assessed using Cox proportional hazards models. Results: Registered and randomised pts had very similar baseline characteristics; previously untreated pts had slightly more favourable characteristics but were balanced between the 2 treatment arms. Pts expressing medium/high levels of FcγRIIB were less likely to respond to rituximab by week 12 (ORR 58.1% vs 23.1%, Fisher's exact test, p=0. 02), a finding independent of prior therapy. For FFS, there was a statistically significant difference (p=0.001; HR=0.42; 95% confidence interval (C.I.): 0.23–0.77) between the negative/low staining group (median: 21.4 months; 95% C.I.: 7.0–34.2) and the medium/high staining group (median: 7.0 months; 95% C.I.: Not calculable). The interaction between staining levels and randomised treatment groups for FFS was not statistically significant. There was a non-significant trend towards better overall survival in the low/negative group (median: 140.0 vs 50.0 months; p=0.15; HR=0.57; 95% C.I.: 0.27–1.23); however the event rate was lower (36.8% vs 61.5%). Conclusion: Elevated FcγRIIB expression level is associated with poor response to rituximab in pts with FL. This group may show better results with non-internalising type II antibodies, a hypothesis for validation in future prospective clinical trials. Disclosures: Ghielmini: Roche: Honoraria, Speakers Bureau. Johnson:Roche: Honoraria.