Mwangi, Raphael

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 treatment resistant or eventually relapse (rrDLBCL), and their prognosis is very poor. Recent molecular classification by large scale genomic and transcriptomic profiling of newly diagnosed DLBCL tumors has resulted in a deeper understanding of disease drivers, however, the molecular heterogeneity of rrDLBCL is yet to be fully explored. Therefore, in this study, we used an unsupervised approach to better define transcriptional and genetic programs in rrDLBCL samples hypothesizing that molecular stratification within this high-risk group may lead to a better understanding of this disease, which remains an unmet need, and a more personalized therapeutic approach. Methods Data used in this study included RNA (n=143) and whole exome (n=126) sequencing data from available FFPE tumor samples at the time of a relapse (any line of treatment, r1-r10 relapse timepoints included in analysis, one per patient), consented to the Molecular Epidemiology Resource (n=61), banked in the Mayo Lymphoma Biobank (n=50), or consented to the CC-122-ST-001 clinical trial (n=32, NCT01421524). Unsupervised clustering was performed on protein coding gene expression values using the non-negative matrix factorization (NMF) approach. NMF was carried out by performing 200 runs on cluster sizes from 2 to 6. Cell of origin (COO) was determined using the method described by Reddy et al. The tumor microenvironment was analyzed using CIBERSORTx and Lymphoma Microenvironment Classification (LME). Genetic classification was done using LymphGen. Results In order to identify unique transcriptional programs in rrDLBCL, we implemented NMF and consensus clustering to define an ideal quantity of stable patient clusters. We identified 4 rrDLBCL patient clusters (rrC1-rrC4) as the most stable solution, based on consensus clustering selection criteria of iterative NMF runs. While relapse timepoint was not associated with individual clusters, we did observe significant differences in tumor characteristics between the clusters. COO classification found that rrC1 and rrC4 were enriched for GCB-DLBCL while rrC3 was enriched for ABC-DLBCL classification (P < .001). To explore the biologic programs in each cluster, we used pathFindR, which leverages protein-protein interaction networks to identify disease related pathways, rrC1 and rrC4 were defined by pathways involved in cell cycle and mismatch repair; oxidative phosphorylation in rrC2; and MAPK and NF-kB in rrC3. Next, LME classification was done to define patterns in the tumor microenvironment and we found a significant difference between groups (P < .001), with rrC2 and rrC4 tumors enriched for a depleted TME, while rrC1 and rrC3 had a more immune rich or inflammatory TME. This was supported by CIBERSORTx analysis identifying significant differences (P > .001) in abundance of CD8 T cells, memory CD4 T cells, and M1 macrophages between clusters, with rrC4 having the lowest abundance. We then explored genetic patterns in each cluster. Gene level mutation enrichment analysis showed BCL7A mutation exclusively in C4 (6/6, P = .03). The clusters were not associated with LymphGen classification. Lastly, our recently published high risk signature classification that is associated with early clinical failure and is characterized by metabolic dysregulation, a depleted TME, T53 alterations, and poor outcome, was significantly different between the groups (P = .03) with enrichment for high-risk cases in rrC4. In summary, we show for the first time that rrDLBCL patients can be classified into four gene expression clusters that are associated with distinct pathway, TME, and genetic programs. These clusters should now be tested to learn if they can help select patients for newer therapies for rrDLBCL such as CAR-T and bispecific antibodies.

Background: Relapsed DLBCL occurs in up to 40% of patients and has a poor prognosis. Current prognostic tools such as the international prognostic index (IPI) and newer forms (NCCN-IPI) only include baseline clinical features. PET/CT features have not yet been incorporated into prognostic risk models despite being essential for staging and response assessment. Deep learning computer algorithms have consistently demonstrated the ability to analyze imaging data and identify features that are not readily apparent to the human eye. Using a deep learning computer vision model that automatically extracted radiomic features from PET/CTs, we examined the association of changes between baseline PET and interim PET (PET2) radiomic features on survival outcomes and compared the prognostic performance with NCCN-IPI. Methods: Adult patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL) between 2005 and 2015 and enrolled in the prospective MER cohort were included. Native DICOM images from FDG PET/CT scans at baseline and interim PET (PET2, after 2-3 cycles of chemotherapy) were preprocessed for regularity and then segmented using the nnU-Net architecture with an external lymphoma-specific model. Feature extraction and standard uptake value (SUV) characterization were accomplished with PyRadiomics and NiBabel. Our computational method included no manual segmentation correction. Individual radiomics features (n=115) and the % change above (Δ High) and below (Δ low) 50 th quartile from baseline to PET2 were evaluated for association with event free survival (EFS) and overall survival (OS) using a univariate Cox regression model and by Kaplan Meier analysis. EFS was defined as time from PET2 to first systemic relapse or death from any cause. OS was defined as time from PET2 to death from any cause. Additionally, Spearman and Pearson correlation matrices were used to guide feature selection while minimizing collinearity. We then assessed the association of the highest scoring radiomics features with EFS in a multivariate cox regression model. Results: A total of 506 patients had baseline and PET2 scans available for radiomic feature extraction. Median age at diagnosis was 61 years (range 18-90), 43% were females. NCCN-IPI composition and outcomes of our cohort was comparable to the previously published NCCN cohort, with patient distribution and 5-year OS as follows: Low (9%, 5-y OS 83%), Low-intermediate (38%, 5-y OS 49%), High-intermediate (41%, 5-y OS 31%), High (11%, 5-y OS 12%). At a median follow up of 81 months,there were 308 events, and272 patients had died.Several radiomics features were associated with EFS including change in tumor surface area (SA Δ) (HR: 1.75, 95% CI 1.36-2.24, p<0.005, median of 26,927 mm 2, Figure 1A) and change in total metabolic tumor volume (TMTV Δ) (HR: 1.64, 95% CI 1.27-2.10, p<0.005, median of 120,473 mm 3, Figure 1B). As a reference, NCCN-IPI univariate Cox regression analysis of EFS produced a Harrell's C-statistic (c) of 0.624. Single radiomics features of SA Δ and TMTV Δ individually produced unadjusted c-statistics of 0.616 and 0.614 respectively. Combinations of radiomics features (SA Δ, TMTV Δ and NCCN-IPI classification) demonstrated cumulative benefit (c=0.652). Conclusion: Automatic PET-CT radiomic feature extraction using deep learning models is feasible among patients with newly diagnosed DLBCL. The change in tumor SA and TMTV appear to be promising radiomic biomarkers. A low decline in either tumor SA or TMTV by PET2 is associated with higher risk of relapse and poor survival outcomes. As individual characteristics, these features are similar prognostic indicators of EFS as the NCCN-IPI. Further investigation into risk stratification when combining radiomics with clinical and genomic variables is warranted. Figure 1. Event free survival for DLBCL patients with A) a change in tumor surface area by PET2 less than 50% percentile (SA_Δ Low) and greater than 50 th percentile (SA_Δ High) and B) a change in TMTV by PET2 less than 50% percentile (TMTV_Δ Low) and greater than 50 th percentile (TMTV_Δ High).

Background: Shorter diagnosis to treatment interval (DTI) has been shown to be associated with more aggressive disease features and inferior outcomes in diffuse large B-cell lymphoma (DLBCL; Maurer et al, JCO 2018). Additional confirmatory studies have also shown that DTI is related to tumor volume (Alig et al, JCO 2021) and molecular phenotype (Aluaij et al, Blood 2023). Here we evaluate DTI in a large multicenter cohort of patients prospectively enrolled and followed as part of the Lymphoma Epidemiology of Outcome (LEO) cohort. Methods: Patients were enrolled within 6 months of diagnosis at one the 8 LEO cohort academic medical centers in the United States between 2015 and 2020. Patients in this analysis had aggressive B-cell lymphoma (BCL) treated with anthracycline-based chemotherapy. DTI was defined as the initial lymphoma biopsy date until the start of initial chemotherapy; patients with DTI between 0-100 days were evaluated. Short DTI was defined as DTI ≤ 14 days (DTI≤14) as previously described in prior publications (e.g. Maurer et al, JCO 2018) and confirmed via examination of functional forms via splines. Event-free survival (EFS) was defined as the time from start of treatment until progression/relapse, retreatment, or death due to any cause. Overall survival (OS) was defined as the time from start of treatment until death due to any cause. Results: 2565 patients with aggressive B-cell lymphoma were evaluated. Median age was 62 years (IQR 51-71) and 1469 (57%) were male. 297 patients (12%) were self-reported non-White race and 314 patients (12%) were self-reported Hispanic or Latino. The majority had DLBCL, NOS subtype (N=1927, 75%), while 227 (9%) had high-grade BCL with MYC and BCL2 and/or BCL6 rearrangements (HG, DH) and 90 (4%) had high-grade BCL NOS (HG, NOS). Clinical characteristics are summarized in the table. At median follow-up of 49 months (IQR 36-68), 800 patients (31%) had an event and 578 patients (23%) died. EFS at 24 months (EFS24) was 76% (95% CI: 74-77). Median DTI across all subtypes was 21 days (IQR 12-33) and 845 patients (33%) had DTI≤14. Patients with DTI≤14 were significantly younger (median age 59 years) but there was no association between DTI and gender, race, or ethnicity. Patients with DTI≤14 were more likely to have HG, DH or HG NOS subtypes, ECOG PS 2-4, advanced stage, elevated LDH, CNS involvement, B symptoms, and bulky disease ( see table). Patients with DTI≤14 were more likely to receive R-EPOCH-based or intensive therapies (41%) and less likely to receive 1L therapy on a clinical trial (3.8%) compared to DTI>14 (26% and 10.1%, respectively). Consistent with previously reported data, DTI≤14 was associated with inferior EFS (HR=1.62, 95% CI: 1.41-1.87, figure), OS (HR=1.73, 95% CI: 1.47-2.04), and EFS24 (OR=1.93, 95% CI: 1.60-2.38). The association between DTI and outcomes remained significant after stratifying for subtype (EFS HR=1.68, 95% CI: 1.46-1.94; OS HR=1.78, 95% CI: 1.50-2.10) and adjustment for IPI (EFS HR=1.43, 95% CI: 1.24-1.65; OS HR=1.47, 95% CI: 1.24-1.74). In subset analysis, DTI≤14 was significantly associated with inferior outcomes within the subtypes of HG, DH (EFS HR=2.70, 95% CI: 1.82-4.01; OS HR=2.97, 95% CI: 1.92-4.60); HG, NOS (EFS HR=2.07, 95% CI: 0.93-4.60; OS HR=2.36, 95% CI: 1.03-5.43); and DLBCL, NOS (EFS HR=1.51, 95% CI: 1.27-1.78; OS HR=1.52, 95% CI: 1.45-1.85). Analysis was limited in other subtypes due to number of events. Notably, within the subset of patients with DTI>14, there was no significant difference in EFS between subtypes for DLBCL, NOS (EFS24=80%, EFS HR=ref), HG, DH (EFS24=73%, EFS HR=1.26, 95% CI: 0.92-1.73) and HG, NOS (EFS24=83%, EFS HR =0.84, 95% CI: 0.40-1.78), logrank p=0.29; similar results were observed for OS (p=0.22). Conclusions: Patients requiring early initiation of therapy for aggressive B-cell lymphoma represent a distinct population of patients with more aggressive clinical features and inferior outcomes. In patients with longer DTI, high grade subtypes had similar outcomes to DLBCL, NOS. Efforts should be made to include patients with anticipated short DTI in clinical trials and translational studies to fully capture the spectrum of patients with aggressive B-cell lymphoma.

Introduction Lymphoid malignancy (LM) is a heterogenous neoplasm with respect to biology, aggressiveness, and treatment with over 100 subtypes, including Hodgkin lymphoma (HL), non-Hodgkin lymphoma (NHL), and multiple myeloma (MM). Genome-wide association studies have identified common variants associated with risk of specific LM subtypes, but less is known about the contribution of rare inherited pathogenic variants (PV) in the genetic architecture of LM risk. Rare PV have been shown to contribute to the genetic architecture of solid tumor cancer risk, many of which have been found in genes that are important to the DNA-damage repair (DDR) pathway (e.g., BRCA1, BRCA1, ATM). Here, we investigated the prevalence of PV in cancer predisposition genes regularly included on multi-gene panel testing based on NCCN guidelines and correlated with risk of LM overall and by common subtypes. Methods In this association study, cases were newly diagnosed lymphomas (excluding chronic lymphocytic leukemia) from Mayo Clinic who were enrolled between 2002 and 2015 in the Lymphoma SPORE Molecular Epidemiology Resource (MER) and MM from Mayo Clinic enrolled primarily between 1998 and 2022 in a clinical registry. Controls were from the Mayo Clinic Biobank who were enrolled between 2009 and 2016, from which we excluded individuals with a history of hematologic malignancy. All participants provided a blood sample for whole exome sequencing, performed by Regeneron on an Illumina NovaSeq panel (mean coverage of 48X). Variants were called using GATK v4 and variant annotation was performed using BioR. All loss-of-function variants (i.e., nonsense, frameshift, and consensus splice sites) and pathogenic missense in 19 cancer predisposition genes with a minor allele frequency < 0.5% were included in the analyses. Logistic regression was used to estimate odds ratio (OR) and 95% confidence intervals (CI) for the association between mutation status by gene (burden test) and risk of LM overall, and by subtype that had more than 5 mutation carriers. All analyses were adjusted for age (at diagnosis for cases and at enrollment for controls) and sex. Results A total of 6990 cases and 42432 controls were included. Median age was 63 years for both cases and controls (case range 18-94 years, control range 18-99 years). Males accounted for 58.5% (n=4090) of the cases and 41.7% (n=17762) of the controls. MM accounted for 31% (n=2138) of the cases, followed by diffuse large B-cell lymphoma (DLBCL, n=1146) and follicular lymphoma (FL, n=1132) each accounting for 16% of cases. CHEK2 (1.0%), ATM (0.4%), BRCA2 (0.4%), and BRCA1 (0.3%) had the most PV carriers in controls; these frequencies are in the range of published control populations. A total of 1816 (3.7%) individuals had a PV across the 19 genes, with 4.7% of cases and 3.5% of controls carrying any PV (OR=1.34, 95% CI: 1.18-1.51). ATM (OR=1.86, 95% CI: 1.36-2.49), CHEK2 (OR=1.74, 95% CI: 1.42-2.13) and TP53 (OR=9.07, 95% CI: 4.51-18.87) were all significantly associated with increased risk of LM overall (Figure 1). When investigating subtypes (Table 1), CHEK2 (OR=1.93, 95% CI: 1.23-2.89) and TP53(OR=10.97, 95% CI: 3.06-31.43) were significantly associated with DLBCL. ATM (OR=2.22, 95% CI: 1.13-3.90) was significantly associated with FL. ATM (OR=1.97, 95% CI: 1.16-3.12), CHEK2 (OR=1.75, 95% CI: 1.24-2.41) and TP53 (OR=7.67, 95% CI: 2.43-20.72) were significantly associated with MM and ATM (OR=8.62, 95% CI: 4.47-15.12), NBN (OR=6.94, 95% CI: 2.41-15.76) and TP53 (OR=38.30, 95% CI: 10.27-116.69) were significantly associated with mantle cell lymphoma (MCL). When subset to LM cases overall, there was no evidence of enrichment for young onset (age <60 years), male sex, or family history of hematologic malignancy between PV carriers and non-PV carriers. However, FL cases with an ATM PV tended to be less than 60 years (OR=3.21, P=0.09) compared to non- ATM PV carriers. Similarly, MM cases with a TP53 PV tended to be less than 60 years of age (OR=7.39, P=0.07) compared non-carriers. Discussion In this large case-control study, PV in established cancer predisposition genes were associated with increased risk of LM overall, demonstrating that rare inherited variants may play an important etiologic role. This study also suggests that PV in cancer predisposition genes may be subtype specific. These results will help inform LM risk for individuals who undergo genetic testing of cancer predisposition genes.

Background: Primary central nervous system lymphoma (PCNSL) is a rare form of non-Hodgkin lymphoma with two-year overall survival (OS) rates of 66-70% reported in prospective clinical trials. Induction therapy with high-dose methotrexate (HD-MTX) followed by consolidation has become the mainstay of treatment, however, there are few contemporary and robust prognostication indices widely available for clinical use. Some of the most used indices were developed prior to the routine use of rituximab and include the International Extranodal Lymphoma Study Group (IELSG; 1980-1999), Memorial Sloan-Kettering Cancer Center (MSKCC; 1983-2003), Nottingham/Barcelona (NB; 1986-2001), and Taipei Score (TS; 2003-2015). Herein, we describe a contemporary comparison of clinical prognostication indices using a single-center cohort of PCNSL patients treated at the Mayo Clinic. Methods: Patients with a diagnosis of PCNSL who received HD-MTX as part of induction therapy at Mayo Clinic between October 2010 and June 2022 were identified and retrospectively reviewed. Patients with prior or concurrent systemic lymphoma were excluded. Primary endpoints were progression-free survival (PFS) defined as time from diagnosis to relapse, progression, or death due to any cause; and OS defined as time from diagnosis to death due to any cause. PFS and OS were evaluated using Kaplan-Meier curves and compared by risk scores using a log-rank test. The association between baseline characteristics and survival outcome were assessed in univariate Cox regression models. Any characteristics showing significant (p-value <0.05) association with outcome were combined using a multivariate Cox regression model. All characteristics that maintained significant association with outcome were combined into a new prognostic model. We compared the performance of each prognostic index model using Harrell's C (HC). Results: A total of 148 patients were identified (50.7% female) with median age at diagnosis of 66 years (range 29-85), with 48 patients (32.4%) age >70 (Table 1). Most had multifocal disease (60.1%) and deep brain involvement (67.6%) at diagnosis with elevated CSF protein (58.1%) but no documented CSF involvement (93.9%). In total, 117 patients (79.1%) received methotrexate, rituximab, and temozolomide (MRT) induction therapy, and the remaining 31 patients (20.9%) received methotrexate and rituximab (MR) induction therapy with various consolidation strategies. The median follow-up for all patients was 4.5 years and the two-year OS was 79% (95% CI: 73-86%). This cohort was stratified using previously published prognostication indices (Table 1). Upon analysis, PFS was not accurately predicted using the IELSG (score 4-5: HR 0.7 (CI 0.3-2.0); HC 0.6), MSKCC (3: 1.3 (0.4-4.0); 0.5), NB (3: 0.9 (0.4-2.5); 0.6), or TS (3: 0.9 (0.1-7.2); 0.5) prognostication indices. Furthermore, OS was not accurately predicted using the IELSG (4-5: 1.5 (0.6-4.0); 0.6), MSKCC (3: 1.2 (0.5-3.2); 0.6), NB (3: 1.2 (0.5-3.2); 0.6), or TS (3: 1.3 (0.2-9.8); 0.6) prognostication indices. Upon multivariate analysis, no variables listed in Table 1 were associated with PFS within this cohort. The two variables predicting a worsened OS were an ECOG performance status of 2 or more (1.9 (1.01-3.6)) and an MR induction regimen instead of MRT (2.1 (1.05-4.3)) (Figure 1). The two-year OS with no risk factors was 86.1% (95% CI: 78.8-94.1%), one risk factor was 75.7% (95% CI: 63.6-90.1%), and two risk factors was 61% (95% CI: 43-86%) (Figure 1). Conclusions: This study reports overall improved outcomes in patients with PCNSL compared to prior prospective and retrospective cohorts, likely in part due to treatment advances and supportive care strategies. This single-center, retrospective cohort of rituximab-exposed patients with PCNSL were not well prognosticated using previously published indices, indicating that further study and more sophisticated approaches to prognostication are warranted. Although multivariate analysis did not demonstrate any variables associated with PFS, it did demonstrate an inferior OS with a performance score of 2 or more and in patients treated with MR rather than MRT.

Background: Primary central nervous system lymphoma (PCNSL) is a rare form of non-Hodgkin lymphoma with historically poor outcomes. Induction therapy with high-dose methotrexate (HD-MTX)-based regimens followed by consolidation with autologous stem cell transplant (auto-SCT) has become the mainstay of treatment with overall response rates (ORR) of 69-87% and two-year overall survival (OS) of 66-70% reported in prospective clinical trials. Limited data are available regarding a maintenance approach with single-agent HD-MTX, particularly in patients who are not auto-SCT candidates. Herein, we describe a comparison of outcomes in patients with PCNSL who underwent HD-MTX-based induction followed by either HD-MTX maintenance or auto-SCT consolidation at Mayo Clinic, Rochester. Methods: Patients with a diagnosis of PCNSL who received HD-MTX as part of induction therapy at Mayo Clinic between October 2010 and June 2022 were identified. Patients with prior or concurrent diagnosis of systemic lymphoma were excluded. Primary endpoints were progression-free survival (PFS) defined as time from post-induction treatment initiation to relapse, progression, or death due to any cause; and OS defined as time from post-induction treatment initiation to death due to any cause. We compared baseline characteristics by post-induction therapy using descriptive statistics. The primary endpoints PFS and OS were evaluated using Kaplan-Meier curves and compared by risk scores using a log-rank test. Results: A total of 148 patients were identified (51% female, 95% white) with median age at diagnosis of 66 years (range 29-85), with 48 patients (32%) age > 70. Most patients had multifocal disease (n=89, 60%) and deep brain involvement (n=100, 70%) at diagnosis. Few had vitreoretinal (n=15, 10%) or CSF involvement (n=9, 6%) at diagnosis. Using the Memorial Sloan Kettering (MSKCC) prognostic score for PCNSL, 35 patients (26%) scored class 3 (poor prognosis), 85 (62%) scored class 2, and 17 (12%) scored class 1. In total, 117 patients (79%) received methotrexate, rituximab, and temozolomide (MRT) induction therapy, and the remaining 31 patients (21%) received methotrexate and rituximab (MR) induction therapy (Table 1). A total of 70 patients (47%) underwent consolidation with auto-SCT and 37 patients (25%) received maintenance methotrexate. The patients who received maintenance methotrexate had higher median age of 72 versus 62 years, higher proportion of patients older than 70 (54% versus 16%, p<0.001), higher proportion of MSKCC prognostic score class 3 patients (33% versus 17%, p=0.026), and trend towards higher proportion of patients ECOG 2 or higher (41% versus 29%, p=0.109). A higher proportion of patients who underwent auto-SCT received MRT (vs MR) induction (n=64, 91%) compared to those who received maintenance methotrexate (n=24, 65%, p=0.004) (Table 1). The median follow-up for all patients was 4.5 years. At 1-, 3-, and 5-years post-induction treatment initiation, the PFS in the auto-SCT cohort was 85.8% (95% CI 77.7-94.9), 81.0% (95% CI 72.0-91.0), and 74.6% (95% CI 63.3-87.9), respectively; and the PFS in the HD-MTX maintenance cohort was 88.6% (95% CI 78.7-99.8), 72.6% (95% CI 58.8-89.8), and 72.6% (95% CI 58.8-89.8), respectively. At the same time points, the OS in the auto-SCT cohort was 94.0% (95% CI 88.4-99.9), 81.3% (95% CI 71.8-92.0), and 76.0% (95% CI 65.0-89.0), respectively; and the OS in the HD-MTX maintenance cohort was 94.3% (95% CI 86.9-100.0), 87.5% (76.8-99.8%), and 82.4% (69.0-98.4), respectively. Overall, there was no significant difference in PFS (p=0.64) or OS (p=0.95) based on post-induction treatment (Figure 1). Conclusions: Our study demonstrates comparable outcomes in PCNSL between a post-induction treatment approach with maintenance HD-MTX and consolidation auto-SCT, even though baseline characteristics indicate that patients who went on to receive auto-SCT were younger and had overall better performance status. This suggests that maintenance HD-MTX is a reasonable, time-limited strategy for patients with PCNSL responding to initial induction therapy, particularly in patients who are not candidates for auto-SCT.

Background: High Grade B cell Lymphoma (HGBL) with MYC and BCL2 and/or BCL6 rearrangements(R) was introduced as an entity in 2016 by the WHO revised 4 th edition. In 2022, both the WHO 5 th edition (beta version) and the International Consensus Classification (ICC) separated DHL- BCL2 (+/- BCL6-R)from DHL- BCL6 given differences in biology . However, while the ICC has maintainedDHL- BCL6 as a provisional entity, the WHO has removed the category, thus removing the requirement to FISH for BCL6-R in this setting. Clinical data on DHL- BCL6 is much more limited, as these cases represent only 10-20% of DHL and have been combined with BCL2-R cases in prior studies. Outcomes are variable in retrospective studies with no consistent data on prognosis or optimal therapeutic strategies. By retaining the category of DHL-BCL6 as a provisional entity, the ICC emphasized the need for further, multicenter, prospective studies evaluating the clinical and biological features of this disease. We herein report a comprehensive comparison of clinical characteristics and outcomes in patients with DHL- BCL6 compared to diffuse large B-cell lymphoma (DLBCL), not otherwise specified (NOS); DLBCL with MYC rearrangement only; DHL- BCL2; and HGBL, NOS in a large, multicenter, prospective cohort of patients from Lymphoma Epidemiology of Outcomes (LEO). Methods: Adult patients with newly diagnosed large B-cell or HGBL were enrolled within 6 months of diagnosis at one the 8 LEO cohort academic medical centers in the US between 2015 and 2020. Baseline characteristics were abstracted at the time of diagnosis per protocol. Based on FISH data patients were further sub mgrouped into DLBCL, NOS (without MYC rearrangement); MYC-R DLBCL, NOS; HGBL, NOS; DHL- BCL2 and DHL- BCL6. Event-free survival (EFS) was defined as the time from diagnosis until progression/relapse, retreatment, or death. Overall survival (OS) was defined as the time from diagnosis until death due to any cause. Results: A total of 1526 eligible patients were identified during this time period. All FISH data was available at the time of diagnosis and the choice of treatment was based on physician discretion. Median age at diagnosis was 63 years (IQR 53-72), with 148 (10%) patients in the AYA category, and 128 (8%) patients > 80 years. 58% (891) were male, 11% self identified as Hispanic or Latino, and 7% as Black/African American. The median diagnosis to treatment interval (DTI) was 20 days (IQR 12-32), and 33% had DTI < 14 days. The FISH-based subgroups were MYC-negative DLBCL, NOS (N=1146, 75%), MYC-R DLBCL,NOS 227 (N = 96, 6%), DHL- BCL2 (N=154, 10%), DHL- BCL6 (N=38, 3%), and HGBL, NOS (N=92, 6%). When available, COO by Hans algorithm was 92% GCB in DHL- BCL2 and 50% GCB in DHL- BCL6. Clinical characteristics can be found in the table. At a median follow-up of 49 months (IQR 36-67), 490 patients (32%) had an event and 356 patients (23%) died. EFS at 24 months (EFS24) was 75% (95% CI: 73-77). Patients with DHL- BCL6 were younger at diagnosis (median 60 years), had more extranodal site involvement (40%), more often stage III/IV disease (70%), and more often treated with a higher intensity regimen than R-CHOP (69%) compared to DLBCL,NOS and MYC-R DLBCL. DHL- BCL6 also had fewer patients that were males (47%), with DTI <=14 days (33%), NCCN IPI ≥ 4 (45%), elevated LDH (53%) than HGBL, NOS and DHL- BCL2. The 2-year EFS and OS rates were noted to be significantly better in the DHL- BCL6 (EFS 79%, 95% CI: 67-93; OS 92%, 95% CI: 84-100) as compared to DHL- BCL2 (EFS 58%, 95% CI: 50-66; OS 70%, 95% CI 63 - 78) and HGBL, NOS (EFS 74%, 95% CI: 65-84; OS 74%, 95% CI: 65-84 ), (Figure 1) but were comparable to that of DLBCL, NOS (EFS 78%, 95% CI: 76-81; OS 87%, 95% CI: 86-89). Conclusions: Our data support separating DHL- BCL6 from DHL -BCL2 as these patients form a unique subgroup with some clinical characteristics comparable to both DLBCL, NOS as well as HGBL, NOS and DHL- BCL2 subtypes. In this cohort, clinical outcomes are more comparable to DLBCL, NOS than DHL- BCL2 or HGBCL, NOS. More frequent use of intensive chemotherapy in DHL- BCL6 compared with DLBCL may account for this finding, although larger multicenter studies are needed. Our results support continued identification of DHL- BCL6 in the clinical setting to better understand optimal therapy and biology of this cohort.

SummaryMantle cell lymphoma (MCL) is clinically and biologically heterogeneous. While various prognostic features have been proposed, none currently impact therapy selection, particularly in older patients, for whom treatment is primarily dictated by age and comorbidities. Herein, we undertook a comprehensive comparison of clinicopathological features in a cohort of patients 60 years and older, uniformly treated with bendamustine and rituximab, with a median survival of >8 years. The strongest prognostic indicators in this cohort were a high‐risk call by a simplified MCL international prognostic index (s‐MIPI) (HR: 3.32, 95% CI: 1.65–6.68 compared to low risk), a high‐risk call by MCL35 (HR: 10.34, 95% CI: 2.37–45.20 compared to low risk) and blastoid cytology (HR: 4.21, 95% CR: 1.92–9.22 compared to classic). Patients called high risk by both the s‐MIPI and MCL35 had the most dismal prognosis (HR: 11.58, 95% CI: 4.10–32.72), while those with high risk by either had a moderate but clinically relevant prognosis (HR: 2.95, 95% CI: 1.49–5.82). A robust assay to assess proliferation, such as MCL35, along with stringent guidelines for cytological evaluation of MCL, in combination with MIPI, may be a strong path to risk‐stratify older MCL patients in future clinical trials.