Citations

Abstract Twenty percent of patients with follicular lymphoma relapse early with poor outcomes; however, the molecular mechanisms underlying this aggressive behavior are unknown. Using a multiomic approach, we show that patients with follicular lymphoma with elevated IRF4 expression (IRF4hi) have increased transformation risk, dysregulated immune signaling, and a suppressive tumor microenvironment. Loss- and gain-of-function experiments in IRF4hi lymphoma cells, along with chromatin profiling, demonstrate that IRF4 impairs their interaction with T cells by repressing antigen presentation and co-receptor gene modules while promoting the expression of cytokines that antagonize T-follicular helper cell and regulatory T-cell functions. Additionally, IRF4 rewires tumor metabolism and restricts glucose availability to immune cells. Silencing of IRF4 inhibits tumor cell growth and restores immune surveillance mechanisms, thus representing a promising target for therapy. Our data suggest that IRF4hi lymphoma cells co-opt a developmental mechanism used to exit the germinal center response in promoting a more aggressive cancer via engagement of multiple immune-evasive mechanisms. Significance: We show that IRF4 controls immune and metabolic signaling with functional effects on the cross-talk between B and T cells, resulting in a suppressive immune microenvironment when IRF4 is overexpressed in lymphoma. This underscores the importance of IRF4 as a pivotal therapeutic target to restore antitumor immunosurveillance for IRF4-associated lymphomas.

7073 Background: The Optimized HLH Inflammatory (OHI) index (Zoref-Lorenz et al., Blood , 2022), based on serum soluble CD25 (sCD25) and ferritin, is a prognostic tool identifying inflammation in the hemophagocytic lymphohistiocytosis (HLH) spectrum and early mortality risk. Prior studies were retrospective and enriched with HLH-suspected cases. We hypothesized that the OHI index would predict outcomes in unselected diffuse large B-cell lymphoma (DLBCL). Methods: 670 newly diagnosed DLBCL patients from a prospective cohort (2002–2015) were analyzed: 335 for discovery and 335 for validation. Pre-treatment serum sCD25 and ferritin levels were quantified via ELISA, and we evaluated original thresholds (sCD25 ≥ 3,900 U/mL; ferritin ≥ 1,000 ng/mL) and developed DLBCL-optimized thresholds (using receiver operator curves) for predicting 500-day mortality. We also evaluated event-free survival (EFS), EFS at 24 months (EFS24), and overall survival (OS). Results: The median age was 64, and 51% were male. Using original thresholds, 4.2% (n=14) of patients were OHI+, with a 5.6-fold higher risk of 500-day mortality (95% CI 1.6–17; p<0.001). Optimized thresholds identified 23.6% (n=78) as OHI+ with a 9.2-fold higher 500-day mortality risk (95% CI 4.0–24; p<0.001). Optimized OHI+ also had a higher risk of EFS24 failure and inferior EFS and OS (Table). OHI+ patients had higher rates of B symptoms (35% vs. 20%; p=0.027), elevated LDH (76% vs. 34%; p<0.001), worse performance status (ECOG ≥2: 38% vs. 12%; p<0.001), and advanced-stage disease (Stage IV: 57% vs 38%; p<0.001), though IPI scores (3–5) were not significantly different (44% vs 36%; p=0.28). Adjusting for age and IPI, OHI+ independently predicted 500-day mortality (OR=5.0; CI 1.9–13; p=0.001), EFS24 failure (OR=3.2; CI 1.5–6.5; p=0.0018), and inferior long-term EFS (HR=2.2; CI 1.1–4.3; p=0.030) and OS (HR=2.0; CI 1.0–4.0; p=0.040) at a median follow up of 9.8 years in living patients. In validation, optimized OHI predicted 500-day mortality, EFS24 failure, and long-term OS and EFS (Table). Cytokine profiling revealed elevated inflammatory markers in OHI+ patients, including IL1a (p=0.008), CCL2 (p=0.03), CXCL10 (p<0.001), and CXCL9 (p<0.001), reflecting systemic hyperinflammation. Conclusions: The OHI index is a powerful predictor of early and long-term outcomes in DLBCL patients. Optimized thresholds identify a larger OHI+ group, highlighting hyperinflammation’s critical role in poor outcomes. These findings support its use in routine management and clinical trial design for novel therapies. Odds ratios or hazard ratios and p-values for optimized OHI+ and DLBCL prognosis. Outcome Discovery Validation OR for 500-day mortality 9.2; p<0.001 4.0; p=0.002 OR for EFS24 failure 5.2; p <0.001 6.3; p<0.001 HR for OS 2.3; p<0.001 1.8; p=0.006 HR for EFS 2.4; p<0.001 2.5; p<0.001

7052 Background: Secondary central nervous system lymphoma (SCNSL) is a rare but serious complication that occurs in 2-10% of patients (pts) with diffuse large B-cell lymphoma (DLBCL). The CNS-International Prognostic Index (CNS-IPI) is a validated tool used to assess the risk of CNS relapse. However, with advancements in molecular profiling and treatments, the predictors of SCNSL, including the predictive ability of CNS-IPI combined with other molecular markers and treatment regimens, have become uncertain. This study evaluates new prognostic markers for CNS relapse in DLBCL, focusing on cell-of-origin (COO), gene rearrangements, and treatment types. Methods: DLBCL pts enrolled from 2002-2015 in the Mayo Clinic and University of Iowa Lymphoma Molecular Epidemiology Resource were prospectively followed for incidence of CNS relapse. Pts with primary CNS lymphoma or CNS involvement at diagnosis, and pts treated with high-dose methotrexate containing regimens were excluded. COO classification (GCB vs non-GCB) was determined using Hans algorithm and/or NanoString data. Multivariate Cox regression models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for predictors of SCNSL. Survival analysis was performed from time of DLBCL diagnosis using Cox proportional hazards model. Results: Among 1278 newly diagnosed DLBCL pts included (median age: 63 years; 43.6% female), SCNSL occurred in 46 (3.6%) pts. Pts with SCNSL were more likely to have intermediate/high CNS-IPI scores (80.4%) than pts without SCNSL (63.9%, p=0.02). The 3 yr SCNSL incidence was 0.016 (0.008-0.0033) in low CNS-IPI vs 0.043 (0.031-0.0060) in high CNS-IPI. Those with SCNSL were significantly more likely at baseline to have non-GCB COO (56.3% vs. 36.5%, p=0.02), and advanced stage (76.1% vs. 59.9%, p=0.03) compared to those without SCNSL. The incidence of SCNSL was not influenced by MYC, BCL2, or BCL6 rearrangements, nor by treatment with R-CHOP, R-EPOCH, or other immunochemotherapy regimens. MVA showed that intermediate CNS-IPI (HR 2.32, 95% CI 1.09-4.92, p=0.029), high CNS-IPI (HR 3.59, 95% CI 1.49-8.62, p=0.004), and non-GCB COO (HR 2.19, 95% CI 1.08-4.42, p=0.0029) were independently associated with increased SCNSL risk. After a median follow-up of 12 years (IQR 9–15), overall survival (OS) was 52.1% for the cohort, with OS significantly worse for SCNSL pts (17.4% vs. 53.4%, p<0.001). Conclusions: This large cohort with extensive follow-up highlights the role of COO as an additional prognostic factor for SCNSL while reinforcing CNS-IPI’s prognostic value. Non-GCB COO pts had a higher risk of SCNSL even when adjusted by CNS-IPI risk. Despite advancements in management, SCNSL pts continue to have poor outcomes. Strategies to reduce the incidence of CNS relapse in high-risk pts require further investigation. MER CNS relapse hazard ratios (95% CI). Characteristics Hazard Ratio 95% CI P-Value CNS-IPI Group 0-1 Low Ref Ref Ref 2-3 Intermediate 2.32 1.09 - 4.92 0.029 4+ High 3.59 1.49 - 8.62 0.004 Cell of Origin* GCB Ref Ref Ref non-GCB 2.19 1.08 - 4.42 0.029 Double Hit* non-DHL Ref Ref Ref DHL 1.08 0.14 - 8.3 0.941 Not Done/Missing 1.38 0.76 - 2.51 0.297 Double Expressor* Negative Ref Ref Ref Positive 2.36 0.71 - 7.85 0.162 Not Done/Missing 1.91 0.89 - 4.08 0.097 IC Group* R-CHOP R-EPOCH Ref 1.63 Ref 0.71 - 3.74 Ref 0.249 Other IC 1.18 0.57 - 2.46 0.660 Any EN Involvement* No Ref Ref Ref Yes 0.98 0.51 - 1.88 0.946 Albumin Group* >=Normal Ref Ref Ref <Normal 1.70 0.75 - 3.85 0.201 Head & Neck Involvement* No Ref Ref Ref Yes 0.35 0.048 - 2.63 0.310 *Adjusted by CNS-IPI risk group.

Abstract Family history of hematologic malignancy (FHHM) is an established risk factor for developing lymphoma, but studies examining associations between self-reported FHHM and lymphoma prognosis during the recent treatment era are limited. Utilizing a prospective cohort study, we evaluated associations between FHHM and prognosis for common lymphoma subtypes, including diffuse large B-cell (DLBCL), follicular (FL), marginal zone (MZL), mantle cell (MCL), Hodgkin (HL), and T-cell (TCL) lymphomas. We used the Mayo Clinic component of the Molecular Epidemiology Resource, a prospective cohort study of newly diagnosed lymphoma patients enrolled from 2002 to 2015. Self-reported FHHM (HL, NHL, leukemia, or multiple myeloma) in a first-degree relative was obtained via questionnaire. Primary outcomes were overall survival (OS) and event-free survival (EFS; time from diagnosis to disease progression, initiation of second-line therapy, or all-cause death). Secondary outcomes were failure to achieve 24 months of event-free survival (EFS24; associated with aggressive disease and poor outcomes) and lymphoma-specific survival (LSS; time from diagnosis to death from lymphoma or lymphoma treatment-related complications). We used multivariable Cox proportional hazards regression to estimate hazard ratios (HRs) and 95% confidence intervals (CI) for the association of FHHM with OS, EFS, and LSS, and logistic regression to estimate odds ratios (ORs) and 95% CI for the association with failure to achieve EFS24. All models were adjusted for sex and a lymphoma subtype specific prognostic index. The cohort consisted of 650 DLBCL, 679 FL, 291 MZL, 178 MCL, 254 HL, and 196 TCL patients. The prevalence of FHHM ranged from 9.7% in TCL to 14% in FL. FHHM was not associated with OS in any subtype, but MCL patients with FHHM showed an inferior EFS (HR=1.70, 95% CI 1.02-2.85; p=0.04). For EFS24, FHHM was associated with failure to achieve EFS24 only in FL (OR=1.57, 95% CI 0.99-2.48; p=0.05). Similarly, FHHM was associated with inferior LSS in FL patients (HR=1.98, 95% CI 1.11-3.53; p=0.02). In a treatment subgroup analysis of FL patients, the FHHM associations with failure to achieve EFS24 (OR=2.48, 95% CI 1.04-5.74; p=0.04) and inferior LSS (HR=2.68, 95% CI 1.09-6.58; p=0.03) strengthened among those treated with frontline immunochemotherapy (IC). In summary, there were no evidence of associations between FHHM and OS across lymphoma subtypes, but MCL patients with FHHM displayed inferior EFS. FL patients with FHHM were more likely to not achieve EFS24 and to ultimately die of their lymphoma or a lymphoma treatment-related complication. This finding was stronger in more aggressive FL requiring frontline IC. This novel finding would suggest that genetic or environmental factors associated with FHHM may underlie pathways that impact disease aggressiveness and early clinical failure in FL. Citation Format: George Cholack, Raphael Mwangi, Thomas M. Habermann, Verena Hinder, Rosalie Griffen, Dennis Robinson, Andrew L. Feldman, Thomas E. Witzig, Stephen M. Ansell, Brian K. Link, Yucai Wang, Carrie A. Thompson, Susan L. Slager, Matthew Maurer, Anne J. Novak, James R. Cerhan. Family history of hematologic malignancy and prognosis across lymphoma subtypes: Novel association with poor outcomes in follicular lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7344.

Abstract Background: Diffuse large B-cell lymphoma (DLBCL) is clinically heterogeneous, and gene expression profiling has identified at least two biologically distinct DLBCL subtypes defined by their cell of origin (COO): germinal center B cell (GCB) and activate B cell (ABC) or non-GCB. We evaluated a variety of putative DLBCL risk factors for etiologic heterogeneity by the COO in a clinic-based study of newly diagnosed DLBCL cases (N = 638) and frequency-matched controls (N = 2,253). Methods: The COO was determined on formalin-fixed, paraffin-embedded tumor tissue, with DLBCL classified as GCB (N = 283), non-GCB (N = 188), or undetermined/missing (N = 167; mainly because of lack of tissue). Multivariable logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). Results: We identified heterogeneity by the COO for low socioeconomic status (SES), which was only associated with non-GCB DLBCL (OR = 1.88 for low vs. average SES; 95% CI, 1.08–3.27); alcohol use, which was only associated with GCB DLBCL (OR = 0.48 for former drinkers; 95% CI, 0.29–0.80 and OR = 0.47 for current drinkers; 95% CI, 0.32–0.71); and borderline heterogeneity for the regular use of regular/extra-strength aspirin, which was only associated with non-GCB DLBCL (OR = 0.36; 95% CI, 0.16–0.85). In contrast, there was no significant heterogeneity by the COO for family history, medical history, or other lifestyle factors. Conclusions: Although requiring confirmation, most risk factors for DLBCL did not show etiologic heterogeneity by the COO, with some notable exceptions including alcohol use, SES, and perhaps regular use of regular/extra-strength aspirin showing associations. Impact: Mechanistically, these findings suggest that most of the DLBCL risk factors evaluated here influence lymphomagenesis prior to differentiation into COO subtypes, with selected factors acting later.

Background: The Optimized Hemophagocytic Lymphohistiocytosis (HLH) Inflammatory (OHI, Zoref-Lorenz et al, Blood, 2022) index, defined by the combined elevation in serum soluble CD25 (sCD25) and ferritin, has emerged as a promising prognostic tool for patients with newly diagnosed hematologic malignancies, demonstrating superior performance in predicting 500-day mortality compared to HLH-2004 criteria. However, previous studies were retrospective, with a substantial proportion (65%) of patients suspected clinically to have HLH. We evaluated the performance of the OHI index in an unselected, prospective cohort of newly diagnosed diffuse large B-cell lymphoma (DLBCL) patients. Methods: We analyzed the predictive utility of the OHI index in 331 newly diagnosed DLBCL patients enrolled from 2002-2015 in the prospective Iowa/Mayo Molecular Epidemiology Resource cohort. Ferritin and sCD25 levels were quantified in pre-treatment serum samples using R&D ELISA kits. OHI values were also optimized based on 500-day mortality in the cohort using receiver operating curve analysis with internal validation. Patients were classified as OHI+ using the original and newly optimized thresholds for sCD25 and ferritin. The primary endpoint was 500-day survival, and the secondary endpoints were event-free survival (EFS) at 24 months (EFS24), EFS, and overall survival (OS). The predictive capability of the OHI index was evaluated using logistic regression to determine odds ratios (OR) and 95% confidence intervals (CI) for 500-day mortality and EFS24, as well as Cox regression to calculate hazard ratios (HR) and 95% CIs for EFS and OS. Results: The median age at diagnosis of the 331 patients was 63.5 years (interquartile range, 54.5-74), and 168 (51%) were male. Using the original thresholds (sCD25 3,900 U/mL and ferritin 1,000 ng/mL), 4.2% of patients were OHI+, with a more than 5-fold higher 500-day mortality risk compared to OHI- patients (OR=5.6; CI 1.6-17, p&lt;0.001). After optimizing thresholds for sCD25 (2,400 U/mL) and ferritin (250 ng/mL) to predict 500-day mortality, 23.6% were OHI+ and the OHI+ group had a 9-fold higher 500-day mortality risk (OR=9.2; CI 4.0-24, p&lt;0.001), with 31% mortality in the OHI+ vs 5% in the OHI- group. OHI+ patients exhibited more B-symptoms (35% vs 20%, p=0.027), elevated LDH levels (76% vs 34%, p&lt;0.001), poorer performance status (Eastern Cooperative Oncology Group 2+: 38% vs 12%, p&lt;0.001), and more advanced stage disease (Stage IV: 57% vs 38%, p&lt;0.001), although the frequency of a high International Prognostic Index (IPI) was not statistically different between the groups (IPI 3-5: 44% vs 36%, p=0.28). After adjusting for age and IPI, OHI+ remained a strong predictor of 500-day mortality (OR=5.0; CI 1.9-13, p=0.001). Further adjustment for the cell of origin did not impact the results. The association of OHI+ status with 500-day mortality was similar in IPI 0-2 (OR=5.8; CI 1.2-29, p=0.033) and 3-5 (OR=6.8; CI 0.6-73, p=0.11). OHI+ patients were also more likely to not achieve EFS24 (45% vs 13%), with a 3-fold greater risk after adjusting for age and IPI (OR=3.2; CI 1.5-6.5, p=0.0018). The OHI index also retained its predictive ability over longer-term follow-up (median 9.8 years for living patients) for both OS (HR=2.0; CI 1.0-4.0, p=0.040) and EFS (HR=2.2; CI 1.1-4.3, p=0.030) after adjusting for age and IPI. Cytokine profiling using multiplex ELISA identified elevated inflammatory markers in OHI+ patients, underscoring the role of systemic inflammation in prognosis. The distribution of cytokines was significantly different between the groups, with consistently higher means in the OHI+ vs OHI- group, including IL1a (1,628 vs 759 pg/ml, p=0.008), CCL2 (1,020 vs 724 pg/ml, p=0.028), CXCL10 (165 vs 53 pg/ml, p&lt;0.0001), and CXCL9 (380 vs 150 pg/ml, p&lt;0.0001). Conclusions: While the original OHI index for prediction of 500-day mortality was validated in this unselected cohort of newly diagnosed DLBCL patients, optimization of the OHI thresholds identified a larger OHI+ group (24%), enhanced the identification of hyperinflammation, improved predictive ability for early (500-day) mortality, and predicted EFS24 status and long-term OS. This underscores the clinical relevance of the OHI index, supports the need to evaluate disease-specific thresholds, and suggests its potential for use in routine management and as enrollment criteria in clinical trials for novel therapies.

Introduction: Clonal hematopoiesis (CH) is a common age-related premalignant condition defined by the presence of an acquired somatic mutation in a gene frequently mutated in myeloid malignancies characterized by a variant allele frequency (VAF) of ≥2%, without fulfillment of other diagnostic criteria for myeloid neoplasm. Incidence of CH increases with age and found in 10%-30% of people &gt; 70 years of age. CH-related mutations confer an increased risk of myeloid neoplasms, cardiovascular diseases, and are linked to inferior survival in solid tumor patients treated with chemo/radiation therapy. Such mutations can act as a driver/amplifier of inflammation, especially through myeloid cells. To distinguish true disease drivers from background genetic events related to aging or environmental factors, we need a deeper understanding of the impact of CH in different tissue microenvironments and under therapeutic pressure for better risk stratification of CH carrier patients. Recent reports suggested high prevalence of CH-related mutations in lymphoma. Current analyses aimed to investigate: i) the prevalence of CH-related mutations in two real-world lymphoma cohorts from Molecular Epidemiology Resource (MER) MER-FL and MER-DLBCL, ii) CH-related mutational landscape in DLBCL and FL, iii) the impact of CH-related mutations on clinical outcomes. Methods: Whole exome sequencing (WES) derived from blood/PBMC from lymphoma patients with paired tumor samples was analyzed to identify CH-related myeloid drivers in 42 previously reported genes. We used Sention-Tnhaplotype2 somatic pipeline with a custom panel of normals from whole blood samples. To avoid tumor contamination, we filtered variants for which VAF in the tumor was higher than that in the germline sample. Other filtering criteria included HIGH/MODERATE impact; read count &gt; 1 in both forward and reverse reads; gnomAD_AF &lt; 0.01. We used the R “survival” package Cox regression implementation for outcome and other statistical analysis. Results: Genomic and clinical data of 507 patients from MER-FL and 383 patients from MER-DLBCL cohorts, with median age of 60 and 64 respectively, were available for analysis. CH-related mutations were present in 17.16% (87/507) in FL and 18.28% (70/383) in DLBCL cohorts with a VAF cut off &gt;2%. The most common CH-related mutations were DNMT3A (5%), CREBBP (2%), TET2 (1%), ASXL1 (1%) and PPM1D (1%) in MER-FL while DNMT3A (5%), TET2 (3%), TP53 (3%), ASXL1 (2%) and PPM1D (1%) in MER-DLBCL cohort. Both the prevalence of CH-related mutations and their average VAF increased with age, consistent with literature. Finally, cox regression analysis suggested that CH-related mutations were associated with significantly inferior overall survival (OS) in both FL and DLBCL cohorts (HR 1.6 p=0.028 and HR 2.3 p=&lt;0.001 respectively); however only in DLBCL this association was significant after age correction (HR 1.8 p=0.008). When separated by individual gene mutations, genes of interest with inferior OS included TP53 (n=4, HR 3.1, p=0.057) in FL and PPM1D (n=3 HR 2.6 p=0.1), TP53 (n=8 HR 2.1 p=0.1) and DNMT3A (n=14, HR=2.0, p=0.048) in DLBCL; however, these estimates did not quite reach statistical significance. Conclusions: Taken together, our exploratory analysis indicates that CH-related mutations associate with worse OS in lymphoma patients, supporting the rationale for evaluation of CH for the risk assessment in lymphoma. Furthermore, DLBCL displays of larger size effect, which may be related to different treatment regimes. Additional studies will be needed to elucidate the interaction between high dose chemotherapy regimes and CH-associated adverse events.