Gandhi, Maher K.

Abstract A short diagnosis-to-treatment interval independently predicts inferior outcomes in follicular lymphoma. Using international discovery and validation cohorts, we demonstrate its prognostic value beyond established prognostic indices, with implications for risk stratification, clinical trial design, and interpretation.

Abstract Background Primary CNS lymphoma (PCNSL) is a rare, aggressive diffuse large B-cell lymphoma confined to the CNS, with poor outcomes. Virally associated PCNSL, including AIDS-related PCNSL (AR-PCNSL) and CNS post-transplant lymphoproliferative disorder (CNS-PTLD) accounts for ~10% of cases and is strongly linked to EBV infection and poor prognosis. In our prior Blood (Gandhi et al. 2021) study, targeted sequencing showed that EBV⁺ PCNSL lacks canonical MYD88, CD79B, and PIM1 mutations and retains intact HLA class I/II, suggesting distinct immunobiology. However, questions remain regarding the immune microenvironment, broad mutational landscape, and intratumoral heterogeneity. Here, we present the first large-scale comprehensive integrated analysis of virally associated PCNSL to define subtype-specific vulnerabilities and therapeutic implications. Methods FFPE brain biopsies from 72 PCNSL patients (40 EBV- de novo PCNSL, 32 EBV+ PCNSL including 18 AR-PCNSL and 14 CNS-PTLD) were analyzed. Immune gene expression was profiled using the NanoString PanCancer Immune Panel. Whole exome sequencing (WES) defined recurrent driver mutations, tumor mutational burden (TMB), and LymphGen classification (excluding A53 subtype). Single nuclei RNA sequencing (snRNA-seq) using the 10x Genomics Chromium Flex platform characterized cellular heterogeneity. Results WES demonstrated a marked reduction in canonical mutations (MYD88L265P, CD79B, PIM1, CARD11) in CNS-PTLD (0%) and AR-PCNSL (29%) vs. de novo PCNSL (87.5%; p<0.0001). AR-PCNSL had a distinct mutational signature when compared with CNS-PTLD and de novo PCNSL. NOTCH1/2 mutations were significantly enriched in AR-PCNSL (71%) vs. CNS-PTLD (9%) and de novo PCNSL (33%) (p<0.01). NLRC5 mutations were present in 64% of AR-PCNSL cases, higher than the 25% observed in de novo PCNSL and were absent in CNS-PTLD. TMB was significantly elevated in AR-PCNSL (mean 26.27 mutations/Mb) vs. de novo PCNSL (17.22) and CNS-PTLD (11.01; p=0.0018) underscoring pronounced genomic instability and suggesting HIV may exert a mutagenic influence beyond immunosuppression. EBV driven subtypes lacked MCD features and were more often classified as ST2 or unassigned. Despite NOTCH2 mutations, AR-PCNSL cases were not classified under the BN2 subtype, further highlighting limitations in current molecular classification systems to accurately stratify virally associated PCNSL. Immune transcriptomic profiling revealed further distinctions within EBV+ PCNSL. CNS-PTLD showed increased expression of genes related to antigen presentation (p<0.0001), cytotoxicity (p=0.0019), and T cell function (p<0.0001), suggesting retained immune responsiveness. AR-PCNSL exhibited significant suppression of HLA class I/II genes (p=0.0027 and p<0.0001 respectively), despite intact genomic loci, implicating post-transcriptional or epigenetic silencing. Immune cell composition revealed reduced macrophage infiltration and suppressed CD4 expression in AR-PCNSL. CNS-PTLD showed higher expression of checkpoint molecules LAG3, TIM3, and CTLA4, consistent with T cell exhaustion. snRNA-seq profiling of AR-PCNSL identified distinct malignant and non-malignant cell populations, including a reduced CD4⁺ compartment and altered microglial/macrophage populations and cell states compared to de novo PCNSL, corroborating bulk transcriptomic data, amongst other ongoing analysis. Conclusion This study represents the largest and most comprehensive immunogenomic investigation of virally associated PCNSL. AR-PCNSL and CNS-PTLD lack canonical PCNSL driver mutations and instead harbor distinct mutational signatures, including NOTCH pathway alterations in AR-PCNSL. These findings underscore divergent pathogenic mechanisms and support tailored therapies. AR-PCNSL is marked by high TMB, suppressed antigen presentation, and reduced CD4⁺ infiltration, indicating profound immune dysfunction. CNS-PTLD retains immune functionality but shows checkpoint upregulation and T cell exhaustion. Despite both being EBV-driven and CNS-restricted, they display distinct molecular and immunological programs, suggesting context specific EBV mechanisms. These findings challenge existing classification systems and support CNS-specific molecular frameworks to guide therapeutic interventions including BTK inhibition for NOTCH-mutated lymphoma. They lay the foundation for precision approaches in EBV⁺ PCNSL, including immune restoration, antigen-specific T cell therapy, and epigenetic modulation.

Abstract Introduction Short diagnosis-to-treatment interval (DTI) is associated with aggressive disease biology and inferior outcomes in diffuse large B-cell lymphoma (DLBCL), and is recognized as a potential source of selection bias in clinical trials if not properly addressed. However, its prognostic significance in follicular lymphoma (FL) remains poorly characterized. We aimed to evaluate the prognostic significance of DTI in newly diagnosed FL patients who received frontline (1L) immunochemotherapy (IC), using a large international dataset and an independent external validation cohort. Methods For the discovery dataset, we evaluated patients diagnosed between 2002 and 2018 from ten observational cohorts as part of the FLIPI24 Consortium. External validation was conducted using data from patients enrolled in the Lymphoma Epidemiology of Outcomes (LEO) Cohort between 2010 and 2015. All patients had FL grade 1–3A and received 1L IC within 100 days of diagnosis. Patients with a concurrent DLBCL were excluded. Missing baseline laboratory values were addressed via multiple imputation. The primary endpoint was event-free survival at 24 months (EFS24); secondary endpoint was 5-year overall survival (OS), both calculated from treatment initiation. DTI was analyzed as continuous (via splines) and dichotomized variable (≤14 vs >14 days; as defined in DLBCL). Results In the discovery cohort (n=3,907), median age was 61 years (IQR 53–69), and 50% were male; 49% of patients were high-risk according to FLIPI, 26% according to PRIMA-PI, and 38% according to FLIPI24. Included patients received R-CHOP (54%), R-CVP (26%), or B-R (20%) as 1L treatment, followed by anti-CD20 maintenance in 60%. The median DTI was 30 days (IQR 17–48). Using the 14-day cut-off, 851 patients (22%) had short DTI. These patients had more adverse baseline characteristics, including B symptoms (42% vs 32%, P<0.01), ECOG performance status ≥2 (15% vs 8%, P<0.01), elevated LDH (51% vs 40%, P<0.01), hemoglobin <12 g/dL (30% vs 17%, P<0.01), and elevated β2-microglobulin (56% vs 44%, P<0.01). Prognostic indices (PIs) were also more frequently high-risk in the short-DTI group: FLIPI (56% vs 47%), PRIMA-PI (36% vs 24%), and FLIPI24 (51% vs 34%, all P<0.01). Spline modeling showed a decreasing EFS24 rate with increasing DTI, reaching a plateau at 30–40 days. In logistic regression model, each additional week of DTI improved EFS24 (OR 0.92, P<0.01). DTI attenuated but remained prognostic after adjusting for PIs (OR 0.93 for FLIPI, 0.95 for PRIMA-PI, 0.96 for FLIPI24, all P<0.01). When analyzed as a dichotomized variable, short DTI was associated with inferior EFS24: OR 1.74 adjusted for FLIPI, 1.63 for PRIMA-PI, and 1.53 for FLIPI24 (all P<0.01). The 2-year EFS of short vs long DTI groups was 71% vs 82% (HR 1.50, 95% CI 1.34–1.67, P<0.01), 5-year OS was 80% vs 86% (HR 1.38, 95% CI 1.21–1.56, P<0.01), and the 5-year cumulative risk of histologic transformation was 7.7% vs. 5.4% (P<0.01). In the validation cohort (n=516), median age was 61 years (IQR 52–69 years), 55% were male; 36% of patients were high-risk according to FLIPI; 29% according to PRIMA-PI, and 33% according to FLIPI24. Patients received B-R (59%) or R-CHOP (41%) as 1L treatment. The median DTI was 31 days (IQR 19–48), 84 patients (16%) had DTI ≤14 days. Similar patterns were observed; patients with short DTI had adverse baseline characteristics, PIs, and shorter 2-year EFS (72% vs 84%, HR 1.69, 95% CI 1.13–2.55, P=0.01). DTI remained associated with EFS24 when analyzed as a continuous variable (per week: OR 0.88 unadjusted, 0.90 with FLIPI, 0.89 with PRIMA-PI, and 0.89 with FLIPI24), and dichotomized (≤14 vs >14 days: OR 1.83 adjusted for FLIPI, 1.88 for PRIMA-PI, and 1.73 for FLIPI24). Conclusion Short DTI, defined as ≤14 days (observed in 22% of FL patients vs 46% in DLBCL), is a strong and independent predictor of inferior outcomes in newly diagnosed FL patients treated with IC. While DTI correlates with adverse baseline features and established PIs, it retains independent prognostic value. Although a 14-day threshold is reasonable for risk modeling, DTI contains greater informational value when modeled as a continuous variable. Among PIs, FLIPI24 most strongly attenuated the DTI effect, underscoring its superior discriminative power over FLIPI and PRIMA-PI. Clinical trials designs should mitigate any potential barriers to enrollment of FL patients requiring urgent therapy.

PURPOSE Although most patients with follicular lymphoma (FL) can expect an indolent course, progressive lymphoma remains the primary cause of death during the first decade after diagnosis. Progression of disease within 24 months (POD24) of starting first-line (1L) immunochemotherapy defines a high-risk population with poor survival, but better risk stratification at diagnosis is needed. METHODS The FLIPI24 model was developed and internally validated to predict 24-month event rates using individual data from 4,485 patients treated with 1L immunochemotherapy from 10 observational cohorts of FL. Overall and cause-specific survival was further evaluated in FLIPI24 risk groups. External validation in the 1L immunochemotherapy setting was performed using the prospective observational Lymphoma Epidemiology of Outcomes (LEO) cohort (N = 565) and three randomized phase III trials (N = 3,192); extension to all patients with FL (any 1L therapy) was performed in the LEO cohort (N = 1,445) and its Molecular Epidemiology Resource subcohort (N = 1,074). RESULTS The FLIPI24 model uses age and four blood-based variables (hemoglobin, lactate dehydrogenase, beta-2 microglobulin, and WBC count). FLIPI24 showed consistent performance across validation and extension data sets, which was superior to existing prognostic tools. Across the four external immunochemotherapy validation data sets, patients with high-risk FLIPI24 (23%-32% of patients) had significantly higher 24-month event rates (22%-35%) and inferior 5-year overall survival (77%-83%) compared with patients with low-risk FLIPI24 (29%-31% of patients, 24-month event rates: 10%-12%; 5-year OS: 96%-97%). Results were consistent when evaluating lymphoma-related death and when extended to all patients with FL. CONCLUSION The FLIPI24 model robustly stratifies, at diagnosis, patients with FL at increased risk of lymphoma-related death versus patients with very low lymphoma-related mortality during the first decade after diagnosis. FLIPI24 can be used to enrich future clinical trial designs in newly diagnosed FL.

Abstract Background: CD20 antibody plus alkylator and/or anthracycline based immunochemotherapy (IC) is a standard frontline therapy for patients with follicular lymphoma (FL) with 10-year event-free survival (EFS) and overall survival (OS) rates of approximately 50% and 80% respectively in long-term follow-up of clinical trials. Currently available clinical prognostic indices for FL have been designed using PFS and OS endpoints. Early events, commonly defined as progression of disease within 24 months (POD24) or early transformation to a more aggressive histology, are associated with inferior outcomes and increased risk of death due to refractory FL. Timely identification of the minority of patients with elevated mortality risk might enhance clinical management and research strategies. The FLIPI24 Consortium was created to develop a clinical prognostic index using early events as the primary endpoint. We report the outcomes for the pooled cohort and investigate the implications of therapy patterns on potential model development. Methods: Individual patient data were pooled and harmonized from 11 prospective observational cohorts from Europe, North America, and Australia. Patients who were diagnosed with grades 1-3A FL and initiated frontline IC were eligible. EFS was defined as time from start of IC to progression, relapse, retreatment (2nd line), histologic transformation, or death due to any cause. Early events were defined using status at 24 months from start of IC. OS was defined as time from start of IC to death due to any cause. Kaplan Meier curves and Cox proportional hazards models were used to evaluate outcomes by clinical features and therapy types. Results: 9006 patients were abstracted and harmonized, 6111 patients initiated frontline IC between 2002 and 2018 and were included in this analysis. Median age at diagnosis was 61 years (IQR 52-69) and 50% were male. Complete FLIPI data were available in 5637 patients (92%) and 46%, 32%, and 22% were low, intermediate, and high risk, respectively. IC type was 3079 R-CHOP or like (50%) , 1529 R-CVP or like (25%), 918 R-bendamustine (B-R) or like (15%), and 585 fludarabine or other alkylator based IC (10%); 3187 received CD20 antibody maintenance (52%). Patients receiving R-CHOP were younger, more frequently grade 3A, and more frequently had elevated LDH; differences in other characteristics by IC type were not clinically meaningful. At median follow-up of 42 months (IQR 17-72), 2647 patients (43%) had an event (any) and 1494 patients (25%) died. Median survival after an early (non-death) event was 49 months (95% CI: 41-58); 5-year OS was 46% (95% CI: 43-49) compared to 89% (95% CI: 88-90) in patients without POD24. Across all IC types, EFS estimates at 2 and 10 years from start of IC were 80% (95% CI:79-81) and 49% (95% CI:48-51) and OS estimates were 92% (95% CI: 91-92) and 70% (95% CI: 69-72), respectively. FLIPI was highly associated with both EFS (c-statistic=0.61) and OS (c-statistic=0.65) from the initiation of IC (both p<0.0001). There were significant differences in EFS and OS by IC type (both p<0.0001) and use of maintenance was associated with prolonged EFS in landmark analyses at both 6 and 12 months from initiation of IC (both p<0.0001). Treatment patterns changed significantly over the study timeframe. Use of B-R and/or maintenance increased to 30% and 70% respectively in N=2937 patients treated in 2010-2018 (Era2) compared to <1% and 40% respectively in N=3174 patients treated 2002-2009 (Era1). EFS was significantly higher for Era2 compared to Era1 (HR=0.77, 95% CI: 0.71-0.83), which remained significant after adjustment for FLIPI (EFS HR=0.82, 95% CI: 0.76-0.89). However, the association between treatment eras and overall survival was weaker (HR=0.89, 95% CI: 0.79-0.99) and not significant after adjusting for baseline FLIPI (OS HR=0.99, 95% CI: 0.88-1.10). Conclusion: EFS and OS from this large pooled analysis of observational cohorts is similar to long-term follow-up of randomized clinical trials in the IC era and support the use of these data for model development. Modeling efforts for early events should adjust for initial IC selection and use of maintenance therapy. Utilization of bendamustine and/or maintenance therapy increased over the study timeframe from 2002-2018, and Era2 was associated with improved EFS but not OS. This cohort provides comprehensive and robust observational data to define clinical predictors in IC treated patients. Figure 1 Figure 1. Disclosures Maurer: Genentech: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Flowers: Janssen: Research Funding; Takeda: Research Funding; National Cancer Institute: Research Funding; Biopharma: Consultancy; BeiGene: Consultancy; Amgen: Research Funding; Celgene: Consultancy, Research Funding; Xencor: Research Funding; Acerta: Research Funding; Bayer: Consultancy, Research Funding; Sanofi: Research Funding; 4D: Research Funding; Adaptimmune: Research Funding; Allogene: Research Funding; EMD: Research Funding; TG Therapeutics: Research Funding; Burroughs Wellcome Fund: Research Funding; Kite: Research Funding; AbbVie: Consultancy, Research Funding; Cellectis: Research Funding; Denovo: Consultancy; Cancer Prevention and Research Institute of Texas: CPRIT Scholar in Cancer Research: Research Funding; Karyopharm: Consultancy; Gilead: Consultancy, Research Funding; Genmab: Consultancy; Epizyme, Inc.: Consultancy; Novartis: Research Funding; Nektar: Research Funding; Morphosys: Research Funding; Iovance: Research Funding; Spectrum: Consultancy; Pfizer: Research Funding; Ziopharm: Research Funding; Guardant: Research Funding; Eastern Cooperative Oncology Group: Research Funding; SeaGen: Consultancy; Pharmacyclics/Janssen: Consultancy; Genentech/Roche: Consultancy, Research Funding; Pharmacyclics: Research Funding. Villa: Janssen: Honoraria; Gilead: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Seattle Genetics: Honoraria; Celgene: Honoraria; Lundbeck: Honoraria; Roche: Honoraria; NanoString Technologies: Honoraria. Weibull: Jansen-Cilag: Other: part of a research collaboration between Karolinska Institutet and Janssen Pharmaceutica NV for which Karolinska Institutet has received grant support. Ghesquieres: Janssen: Honoraria; Mundipharma: Consultancy, Honoraria; Roche: Consultancy; Celgene: Consultancy, Honoraria; Gilead Science: Consultancy, Honoraria. Kridel: Gilead Sciences: Research Funding. Gandhi: Janssen: Research Funding; Novartis: Honoraria. Cheah: Celgene: Research Funding; TG Therapeutics: Consultancy, Honoraria, Other: advisory; Loxo/Lilly: Consultancy, Honoraria, Other: advisory; AstraZeneca: Consultancy, Honoraria, Other: advisory; AbbVie: Research Funding; Beigene: Consultancy, Honoraria, Other: advisory; Ascentage pharma: Consultancy, Honoraria, Other: advisory; Gilead: Consultancy, Honoraria, Other: advisory; MSD: Consultancy, Honoraria, Other: advisory, Research Funding; Janssen: Consultancy, Honoraria, Other: advisory; Roche: Consultancy, Honoraria, Other: advisory and travel expenses, Research Funding. Hawkes: Gilead: Membership on an entity's Board of Directors or advisory committees; Merck Sharpe Dohme: Membership on an entity's Board of Directors or advisory committees; Antigene: Membership on an entity's Board of Directors or advisory committees; Regeneron: Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squib/Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck KgA: Research Funding; Specialised Therapeutics: Consultancy; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Other: Travel and accommodation expenses, Research Funding, Speakers Bureau; Janssen: Speakers Bureau. Seymour: Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sunesis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: 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; Gilead: 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, Research Funding, Speakers Bureau; Mei Pharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Morphosys: Honoraria, Membership on an entity's Board of Directors or advisory committees; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau. Freeman: Amgen: Honoraria; Celgene: Honoraria; Sanofi: Honoraria, Speakers Bureau; Incyte: Honoraria; Abbvie: Honoraria; Teva: Research Funding; Roche: Research Funding; Janssen: Honoraria, Speakers Bureau; Seattle Genetics: Honoraria; Bristol Myers Squibb: Honoraria, Speakers Bureau. Clausen: Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel expences ASH 2019; Gilead: Consultancy, Other: Travel expences 15th ICML ; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Wahlin: Gilead Sciences: Research Funding; Roche: Consultancy, Research Funding. Link: Novartis, Jannsen: Research Funding; Genentech/Roche: Consultancy, Research Funding; MEI: Consultancy. Ekstroem Smedby: Janssen Cilag: Research Funding; Takeda: Consultancy. Sehn: Genmab: Consultancy; Novartis: Consultancy; Debiopharm: Consultancy. Trněný: Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Portola: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; 1st Faculty of Medicine, Charles University, General Hospital in Prague: Current Employment; Celgene: Consultancy; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Amgen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria; Gilead Sciences: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses; Incyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. El-Galaly: ROCHE Ltd: Ended employment in the past 24 months; Abbvie: Other: Speakers fee. Cerhan: Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding; NanoString: Research Funding.

Abstract Primary central nervous system lymphoma (PCNSL) is confined to the brain, eyes, and cerebrospinal fluid without evidence of systemic spread. Rarely, PCNSL occurs in the context of immunosuppression (eg, posttransplant lymphoproliferative disorders or HIV [AIDS-related PCNSL]). These cases are poorly characterized, have dismal outcome, and are typically Epstein-Barr virus (EBV)-associated (ie, tissue-positive). We used targeted sequencing and digital multiplex gene expression to compare the genetic landscape and tumor microenvironment (TME) of 91 PCNSL tissues all with diffuse large B-cell lymphoma histology. Forty-seven were EBV tissue-negative: 45 EBV− HIV− PCNSL and 2 EBV− HIV+ PCNSL; and 44 were EBV tissue-positive: 23 EBV+ HIV+ PCNSL and 21 EBV+ HIV− PCNSL. As with prior studies, EBV− HIV− PCNSL had frequent MYD88, CD79B, and PIM1 mutations, and enrichment for the activated B-cell (ABC) cell-of-origin subtype. In contrast, these mutations were absent in all EBV tissue-positive cases and ABC frequency was low. Furthermore, copy number loss in HLA class I/II and antigen-presenting/processing genes were rarely observed, indicating retained antigen presentation. To counter this, EBV+ HIV− PCNSL had a tolerogenic TME with elevated macrophage and immune-checkpoint gene expression, whereas AIDS-related PCNSL had low CD4 gene counts. EBV-associated PCNSL in the immunosuppressed is immunobiologically distinct from EBV− HIV− PCNSL, and, despite expressing an immunogenic virus, retains the ability to present EBV antigens. Results provide a framework for targeted treatment.

Abstract Background. Recent clinical trials based on immunotherapies targeting the PD-1/PD-L1 pathway have shown striking durable responses in a subset of patients with solid cancers. The Programmed death 1 (PD-1) protein is a key immune checkpoint inhibitor expressed by activated T cells. Its ligand, PD-L1, was reported highly expressed by tumor cells in some diffuse large B-cell lymphomas (DLBCL) of non-Germinal Center phenotype. We recently reported on the French multicenter GOELAMS075 trial that pre-treatment soluble PD-L1 (sPD-L1) in plasma was elevated in DLBCL patients compared to controls, and that elevated sPD-L1 was associated with inferior overall survival (OS), independent of the International Prognostic Index (IPI) and other clinical factors (Rossille et al., Leukemia 2014). Here, we replicate and extend these findings in two independent studies from Australia and the US. Methods. The protein expression of sPD-L1 was evaluated using a commercial ELISA kit. The French discovery cohort consisted of 288 adults with newly diagnosed aggressive DLBCL, age 18 to 60 years, and treated with R-CHOP or high dose chemotherapy plus rituximab followed by autologous stem cell support (clinicaltrials.gov: NCT00561379); there were also 60 controls. The Australian study consisted of 51 DLBCL patients age 18 to 71 years, all stages, treated with R-CHOP14, along with 57 controls. The US study was an observational cohort from the Iowa/Mayo Lymphoma SPORE and consisted of 225 DLBCLs, age 19 to 92 years, all stages, treated with immunochemotherapy, along with 98 controls. Plasma samples were collected pre-treatment using EDTA tubes for the Australian and the US cohorts, BDª P100 tubes for the French cohort. sPD-L1 expression was measured in Rennes, France (French & US samples) and in Brisbane, Australia (Australian samples).The Kaplan-Meier method and Cox regression were used to model the association of sPD-L1 with OS. The 95th percentile of the sPD-L1 levels in each matched control group was used as the cutoff point to define elevated sPD-L1 levels. Results. Replicating the French findings, sPD-L1 levels were significantly higher for DLBCL patients compared to controls in both the US (P<0.0001) and Australian (P<0.0001) studies (Figure 1). The odds ratios for elevated sPD-L1 among patients compared to controls were 10.7 (95% CI 3.3-22.0), 8.9 (95% CI 3.1-25.3) and 12.6 (95% CI 2.7-28.0) for the French, US and Australian studies, respectively. In the French cohort, elevated sPD-L1 levels were associated with inferior OS (Hazard Ratio (HR)=2.05; 95% CI 1.18-3.57), and this was replicated in the US cohort (HR=1.71; 95% CI 0.97-3.01) (Figure 2). Due to the similarity of the results, we next pooled the French and US cohorts to increase power for multivariate and subset analyses. The median age at diagnosis of the 513 patients was 54 years; 29% were more than 60 years old; 69% of the patients had stage III-IV disease; 56% were IPI intermediate-risk and 9% were IPI high-risk patients. The median follow-up was 48 months (range, 0.5-126) overall, and 66 months for the patients still alive; there were 102 deaths. Using a cutpoint of 1729 pg/mL from the combined studies, patients with elevated sPD-L1 had inferior OS compared to patients without elevated sPD-L1, with 3-year OS rates estimated at 78% (95% CI 71.8-84.9) vs. 87.8% (95%CI 84.5-91.4) (P<0.01). In multivariate analysis, elevated sPD-L1 (HR=1.75; 95%CI 1.16-2.64), age (HR=1.03; 95%CI 1.02-1.05), high-risk IPI score (HR=3.71; 95%CI 1.91-7.21) and ALC ² 1 G/L (HR=2.19; 95%CI 1.44-3.33) were all significant at P<0.01. In analyses stratified by IPI, the 3-year OS rates among high-risk patients (IPI 4-5) was 40.9% (95% CI 23.6-71.0) for elevated sPD-L1 vs. 82.1% (95% CI 69.1-97.6) for not elevated sPD-L1 (P<0.01). There was no association of sPD-L1 with 3-year OS among low risk (IPI 0-1) or intermediate-risk (IPI 2-3) patients. Conclusion. We confirmed that sPD-L1 levels are higher in pre-treatment plasma samples of newly diagnosed DLBCL patients compared to controls, and that elevated levels of sPD-L1 are associated with inferior OS in DLBCL patients treated with immunochemotherapy, and this is independent of IPI and other clinical factors. Among high risk patients, we identified a subgroup with less than 50% survival. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures No relevant conflicts of interest to declare.