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Background The importance of the immune system in modulating the trajectory of lymphoma outcomes has been increasingly recognized. We recently showed that CD4+ cells are associated with clinical outcomes in a prospective cohort of almost 500 patients with follicular lymphoma (FL). Specifically, we showed that the absence of CD4+ cells inside follicles was independently associated with increased risk of early clinical failure. These data suggest that the composition, as well as the spatial distribution of immune cells within the tumor microenvironment (TME), play an important role in FL. To further define the architecture of the TME in FL we analyzed a FL tumor section using the Co-Detection by Indexing (CODEX) multiplex immunofluorescence system. Methods An 8-micron section from a formalin-fixed paraffin-embedded block containing a lymph node specimen from a patient with FL was stained with a cocktail of 15 CODEX antibodies. Five regions of interest (ROIs) were imaged using a 20X air objective. Images underwent single-cell segmentation using a Unet neural network, trained on manually segmented cells (Fig 1A). Cell type assignment was done after scaling marker expression and clustering using Phenograph. Each ROI was manually masked to indicate areas inside follicles (IF) and outside follicles (OF). Relative and absolute frequencies of cell types were calculated for each region. Cellular contacts were measured as number and types of cell-cell contacts within two cellular diameters. To identify proximity communities, we clustered cells based on number and type of neighboring masks using Phenograph. The number of cell types and cellular communities were calculated inside and outside follicles after adjustment for total IF and OF areas. The significance of cell contact was measured using a random permutation test. Results We identified 13 unique cell subsets (11 immune, 1 endothelial, 1 unclassified) in the TME of our FL section (Fig. 1A). The unique phenotype of each subset was confirmed using a dimensionality reduction tool (t-SNE). The global composition of the TME varied minimally across ROIs and consisted primarily of B cells, T cells, and macrophages subsets - in decreasing order of frequency. Higher spatial heterogeneity across ROIs was observed in the frequency of T cell subsets in comparison to B cells subsets. Inspecting the spatial distribution of T cell subsets (Fig. 1B), we observed that cytotoxic T cells were primarily located in OF areas, whereas CD4+ T cells were found in both IF and OF areas. Notably, the majority of CD4+ T cells inside the follicles expressed CD45RO (memory phenotype), while most of the CD4+ T cells outside the follicles did not. Statistical analysis of the spatial distribution of CD4+ memory T cell subsets confirmed a significant increase in their frequency inside follicles compared to outside (20.4% vs 11.2%, p < 0.001; Fig. 1D). Cell-cell contact analysis (Fig 1C) showed increased homotypic contact for all cell types. We also found a higher frequency of heterotypic contact between Ki-67+CD4+ memory T cells and Ki-67+ B cells. Pairwise analysis showed these findings were statistically significant, indicating these cells are organized in niches rather than randomly distributed across image. Analysis of cellular communities (Fig. 1C) identified 13 niches, named according to the most frequent type of cell-cell contact. All CD4+ memory T cell subsets were found to belong to the same neighborhood (CD4 Memory community). Analysis of the spatial distribution of this community confirmed that these niches were more frequently located inside follicles rather than outside (26.3±4% vs 0.004%, p < 0.001, Fig. 1D). Conclusions Analysis of the TME using CODEX provides insights on the complex composition and unique architecture of this FL case. Cells were organized in a pattern characterized by (1) high degree of homotypic contact and (2) increased heterotypic interaction between activated B cells and activated CD4+ memory T cells. Spatial analysis of both individual cell subsets and cellular neighborhoods demonstrate a statistically significant increase in CD4+ memory T cells inside malignant follicles. This emerging knowledge about the specific immune-architecture of FL adds mechanistic details to our initial observation around the prognostic value of the TME in this disease. These data support future studies using modulation of the TME as a therapeutic target in FL. Figure 1 Disclosures Galkin: BostonGene: Current Employment, Patents & Royalties. Svekolkin:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Postovalova:BostonGene: Current Employment, Current equity holder in private company. Bagaev:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Ovcharov:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Varlamova:BostonGene: Current Employment, Current equity holder in private company, Patents & Royalties. Novak:Celgene/BMS: Research Funding. Witzig:AbbVie: Consultancy; MorphSys: Consultancy; Incyte: Consultancy; Acerta: Research Funding; Karyopharm Therapeutics: Research Funding; Immune Design: Research Funding; Spectrum: Consultancy; Celgene: Consultancy, Research Funding. Nowakowski:Nanostrings: Research Funding; Seattle Genetics: Consultancy; Curis: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other; Kymera: Consultancy; Denovo: Consultancy; Kite: Consultancy; Celgene/BMS: Consultancy, Research Funding; Roche: Consultancy, Research Funding; MorphoSys: Consultancy, Research Funding. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding. Ansell:Trillium: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol Myers Squibb: Research Funding; AI Therapeutics: Research Funding; ADC Therapeutics: Research Funding.

Abstract Background Factors associated with chronic immune stimulation such as transplantation, autoimmune disorders and chronic infections have been linked to the development of lymphoma, while atopic conditions have been associated with a lower risk of lymphoma. Vaccinations, in part due to their ability to induce immune responses, have been hypothesized to play a role in lymphoma etiology, but there are few studies with mixed results and limited data on lymphoma subtypes. Methods We used a clinic-based study of 2461 newly diagnosed lymphoma cases and 2253 frequency-matched controls enrolled from 2002-2015. Participants self-reported lymphoma risk factors and history of vaccinations for hepatitis A, hepatitis B, chicken pox, yellow fever and influenza. Pathology was centrally reviewed, and included 644 chronic lymphocytic leukemia, 528 follicular (FL), 414 diffuse large B-cell (DLBCL), 170 marginal zone, 127 mantle cell, 119 T-cell, 181 Hodgkin, and 278 other lymphoma subtypes. We used polytomous logistic regression to estimate odds ratio (OR) and 95% confidence intervals (CI) of vaccinations with lymphoma risk overall and for subtypes, adjusting for age, sex, socioeconomic status, body mass, alcohol use, smoking history, recreational sun exposure, and family history of hematological malignancies. Results The median age at diagnosis for lymphoma cases was 64 years (range: 18-93) and 58% were male; the median age at enrollment for controls was 62 years (range: 18-91) and 53% were male. The most common vaccinations among controls were influenza (90%) followed by hepatitis B (41%), hepatitis A (30%), chicken pox (20%), and yellow fever (11%). Vaccination for influenza was inversely associated with lymphoma risk overall (OR=0.75, CI:0.61-0.93, P=0.01), with an inverse trend for increasing number of vaccinations (P=0.0001). In subtype analyses, Influenza vaccination was inversely associated with risk of FL (OR=0.59, CI:0.43-0.80, P=0.001), DLBCL (OR=0.64, CI:0.44-0.92, P=0.02) and other lymphoma subtypes (OR=0.66, CI:0.43-1.00, P=0.05). Vaccination for hepatitis A was inversely associated with lymphoma risk (OR=0.79, CI:0.65-0.96, P=0.02), with no significant subtype-specific associations. No evidence of association with vaccination for hepatitis B (OR=0.95, CI:0.79-1.14) and chicken pox (OR=0.83, CI:0.68-1.02) for lymphoma risk overall or for any subtypes. Although no evidence of an association with vaccination for yellow fever (OR=0.81, CI:0.62-1.06) for lymphoma risk, it was inversely associated with DLBCL risk (OR=0.42, CI:0.22-0.80). Conclusion Vaccination for influenza and hepatitis A were inversely associated with overall lymphoma risk. DLBCL was associated with vaccination for influenza and yellow fever. FL was associated with vaccination for influenza. Understanding the underlying mechanisms for a putative protective effect of certain vaccines could provide new clues to the etiology and prevention of lymphoma. Citation Format: Geffen Kleinstern, Dennis P. Robinson, Carrie A. Thompson, Melissa C. Larson, Cristine Allmer, Grzegorz S. Nowakowski, Timothy G. Call, Stephen M. Ansell, Andrew L. Feldman, Neil E. Kay, Thomas M. Habermann, Susan L. Slager, James R. Cerhan. Vaccination history and risk of lymphoma and its major subtypes [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1054.

8556 Background: In the original PARMA trial it was demonstrated that salvage chemotherapy with DHAP followed by autologous bone marrow transplant resulted in increased overall survival over salvage chemotherapy with DHAP alone in patients with aggressive lymphomas. The current study was designed to assess safety and feasibility of ROAD as a salvage chemotherapy regimen which could be administered as an inpatient or outpatient. Methods: Patients received immunochemotherapy on the following schedule: rituximab 375 mg/m2 weekly × 4, oxaliplatin 130 mg/m2 on day 2, Ara C 2000mg/m2 x 2 doses on day 2 and dexamethasone 40 mg on days 2–5, with OAD repeated at 3 week intervals (up to 6 cycles). Patients were considered for autologous stem cell transplantation after 2 cycles if eligible. Eligible histologies included diffuse large B cell lymphoma, mantle cell lymphoma and transformed lymphoma in first relapse. Results: 50 patients were accrued from Aug 2006 through Jul 2008: 5 patients were deemed ineligible after central pathology review. Baseline characteristics of eligible patients included median age 69 (range 23 - 77), 53% were male, 53% had advanced stage at relapse, LDH was elevated in 58% and all patients had an ECOG PS of 2 or less. Patients received a median of 2 cycles of therapy (range 1–6) with 39/45 receiving treatment in cycle 2, with 12 patients continuing beyond 2 cycles. 31 patients experienced grade III/IV hematologic toxicity and 22 patients had grade III/IV non-hematologic toxicity, primarily febrile neutropenia. One patient developed grade III nephrotoxicity due to disease progression. Twenty patients received their treatments exclusively as outpatients. 26 responses were seen in the 45 eligible patients (58%, 95% CI: 44–74%), with 20 responding patients proceeding to autologous SCT. Conclusions: ROAD is a safe and effective salvage chemotherapy regimen for relapsed aggressive lymphoma, including as a preparatory regimen prior to stem cell transplant. It appears to have similar response rates to R-DHAP in a similar patient population, but without the potential nephrotoxicity (data from prior published study from NCCTG). ROAD can be safely administered as an inpatient or outpatient. No significant financial relationships to disclose.

Abstract Purpose: We sought to improve upon frontline bendamustine/rituximab (BR) induction therapy followed by rituximab maintenance in untreated high-risk follicular lymphoma (FL). Patients and Methods: Patients were randomized to BR induction followed by 2-year rituximab maintenance (BR-R), BR with bortezomib and rituximab maintenance (BVR-R), or BR followed by lenalidomide (1 year) with rituximab maintenance (BR-LR). Dual primary objectives were complete remission (CR) rate and 1-year disease-free survival (DFS); 289 patients enrolled (NCT01216683). Results: For induction, 92%, 87%, and 86% of patients randomized to BR-R, BVR-R, or BR-LR received six cycles, respectively. CR rate with BR versus BVR induction was 62% versus 75%, respectively (P = 0.04). One-year DFS rates with BR-R versus BR-LR were 85% versus 67%, respectively (P = 0.0009). This was due to an imbalance in CR rates post-BR induction and discontinuation due to adverse events (AEs). The most common grade 3–4 AEs for BVR versus BR were neutropenia and sensory neuropathy (12% vs <1%); 83% of the latter occurred with intravenous bortezomib. The most common grade 3–4 AEs related to LR versus rituximab maintenance were neutropenia 66% versus 21%, respectively (P < 0.0001), and febrile neutropenia 10% versus 2%, respectively (P = 0.05). The overall treatment-related mortality was 1.4%. With 5-year median follow-up, 3-year PFS rates for BR-R, BVR-R, and BR-LR were 77%, 82%, and 76%, respectively (P = 0.36) with OS rates of 87%, 90%, and 84%, respectively (P = 0.79). For prognostication, CR rate and POD-24 were associated with survival. Conclusions: Altogether, neither bortezomib added to BR induction nor lenalidomide added to rituximab maintenance immediately post-BR induction is recommended in untreated FL.

e20068 Background: FL grade 3B (FL3B) is an aggressive subtype of FL with a distinct morphologic, cytogenetic and immunohistochemical profile that is associated with higher mortality compared to other subtypes of FL. FL3B is a rare disease, and data regarding its prognostication beyond grading is lacking. Recent data suggests that spleen and extranodal (EN) involvement on PET/CT predict early clinical failure in FL grades 1-3A[1]. We aimed to determine the incidence of spleen and EN involvement on PET/CT in FL3B, and whether these can predict EFS. Methods: Patients with untreated FL3B diagnosed between 2003-2016, with available pre-treatment PET/CT, were identified using the Mayo Clinic Lymphoma Database and the University of Iowa/Mayo Clinic Lymphoma SPORE database. 27 patients were included in this analysis. All but two patients received treatment with immunochemotherapy. Associations with outcomes were assessed using EFS, defined as disease progression, relapse, transformation, or death. Results: 11/27 (40.7%) of patients had EN involvement on PET/CT. The most common EN site was bone, in 8/27 (29.5%) of patients. Soft tissue involvement was present in 4/27 (14.8%) of patients. Liver, brain, and endometrial involvement were each noted once. 11/27 (40.7%) of patients had spleen involvement on PET/CT. Presence of bone involvement as detected on PET/CT was associated with lower EFS (p = 0.02). EN involvement was associated with a trend toward a lower EFS but statistical significance was not reached likely secondary to low numbers in this cohort. Results in the table are compared to results obtained from our analysis in patients with FL grade 1-3A[1]. Conclusions: Bone involvement on pre-treatment PET/CT in FL3B was associated with early clinical failure in this small cohort of 27 patients. EN involvement at diagnosis may also be associated with poorer outcomes. These findings are similar to our analysis of a large (n = 613) cohort of patients with FL grade 1-3A. These findings may aid in the prognostication of patients with newly diagnosed FL3B, to guide therapy in select higher risk patients. [Table: see text]