Glimelius, Ingrid

Abstract Background: Mantle cell lymphoma (MCL) is an aggressive and rare B-cell non-Hodgkin lymphoma with poor prognosis, even with treatment. Despite its clinical importance, the etiology of MCL remains largely unknown. Some studies have reported a positive association with family history, suggesting that genetic factors could contribute to risk. Methods: To identify germline genetic variants associated with risk, we conducted the first genome-wide association studies (GWAS) and GWAS meta-analysis for MCL, comprising 1,163 cases and 61,271 controls. The most significant loci were taken forward for replication in three independent studies, including 576 cases and 771,773 controls. To identify potential target genes and pathways of discovered loci, we conducted F-MAGMA, colocalization, and transcriptome-wide association study (TWAS) analyses. To gain insight into underlying regulatory mechanisms, we performed integrative epigenomic analyses using DNase I hotspots and histone mark ChIP-seq data across diverse cell types applying the FORGE2 framework. Results: In the joint analyses, we identified eight genome-wide significant loci (P<5x10-8) associated with MCL risk, several of which were located near genes with known DNA repair (ATM), telomere (TERT), or RNA-binding functions (RBM20). Further analyses using F-MAGMA, which uses DNase-seq data to prioritize genes from GWAS, identified genes that were significantly associated with risk, including SP140, a chromatin reader and immune regulator of pathogen response. This gene also displayed strong colocalization with our lead variant in whole blood (COLOC posterior probability PP4=0.97). TWAS demonstrated significant associations with SP140 and ACTA2, which has been linked to cell proliferation (P<3x10-6). Enrichment for DNase I hotspots was observed in B and T lymphocytes (q-value<0.05), providing evidence for a role in immune cell-specific regulatory regions. Enrichment for enhancer-associated histone mark H3K4me1 was observed in B cells (q-value<0.01), highlighting a role for immune cell-specific enhancers. Transcription factor (TF) motif enrichment analysis pointed to TFs critical for B-cell development and differentiation, notably TCF3 and EP300 (q<0.01 for both), suggesting an association between B-cell lineage regulation and MCL risk. Finally, genome-wide SNP-based heritability was estimated to be 17%, underscoring the importance of common variants in MCL risk. Conclusion: Our study provides novel insight into the inherited susceptibility of MCL by identifying eight significant loci and estimating substantial common variant heritability. These findings highlight a role for several distinct biological pathways -specifically DNA repair, telomerase function, and B-cell differentiation- in the etiology of MCL, offering new targets for mechanistic investigation. Citation Format: Charles E. Breeze, Alyssa Clay-Gilmour, Hanla A. Park, Ólafur B. Davíðsson, Angelica Macauda, Brenda M. Birmann, Elizabeth E. Brown, Murat Güler, Michelle A. T. Hildebrandt, Alexandra Nieters, Krystle Ong, Jojo Biel-Nielsen Dietz, Karin E. Smedby, Karl Smith-Byrne, Rosalie Griffin, Sophia S. Wang, Susan Slager, James R. Cerhan, Jonathan N. Hofmann, Qing Lan, Nathaniel Rothman, Ingrid Glimelius, Henrik Hjalgrim, James Mckay, Sonja I. Berndt. Genome-wide association study of mantle cell lymphoma identifies novel loci suggesting a critical role for B-cell chromatin readers and DNA repair mechanisms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3602.

Abstract Patients with myeloproliferative neoplasms (MPNs) are inherently at increased risk of both thrombotic and bleeding events due to the nature of the condition. Disease management often includes anticoagulants, antiplatelet agents, and/or cytoreductive therapy to mitigate these risks. On the contrary, these therapies can also increase the risk of bleeding, presenting a clinical challenge in balancing the prevention of thrombosis with the management of bleeding complications. The relationship between treatment type, thrombotic events, and bleeding risk remains underexplored in large, real-world populations. This Swedish population-based study aimed to describe how the risk of bleeding in patients living with MPN differs by treatment strategy, and how timing of thrombotic events influences this risk. A total of 15,495 patients diagnosed with MPN between 2006 and 2021, aged 18–90, were identified through the Swedish Cancer Register and the Swedish Patient Register. Bleeding rates were estimated using Cox proportional hazards models with time-split survival data. Treatment categories were defined as follows: no therapy, anticoagulant monotherapy (e.g., warfarin, direct oral anticoagulants [DOACs]); antiplatelet monotherapy (e.g., aspirin, clopidogrel); cytoreductive monotherapy (e.g., hydroxyurea, interferon); and combination therapy, defined as any combination of at least two of the three aforementioned therapies. All treatment categories were compared to anticoagulant monotherapy. Both treatment exposure and thrombotic status were modelled as time-varying covariates, allowing individuals to contribute across multiple thrombosis and treatment combinations over time. Models were adjusted for age at diagnosis, sex, year of diagnosis, and MPN subtype. The cohort was 52% female, with a median age at diagnosis of 71 years (IQR 60–79). The most common MPN subtypes were polycythemia vera (39%) and essential thrombocythemia (38%), followed by MPN-unclassifiable (16%) and primary myelofibrosis (7%). A history of thrombosis at MPN diagnosis was present in 22% of patients, and 19% had a history of bleeding. Among the 10,487 patients receiving combination therapy, the majority included antiplatelet agents: 57% received antiplatelet + cytoreductive therapy, 12% received antiplatelet + anticoagulant therapy, and 22% received all three therapies. Only 8% received anticoagulant + cytoreductive therapy without antiplatelet agents. Patients receiving no therapy had the lowest bleeding rate overall (HR 0.63, 95% CI 0.53–0.75), likely reflecting individuals with less severe disease or contraindications to treatment. Among patients with no thrombotic event, those receiving antiplatelet monotherapy had a 35% lower rate of bleeding compared to those on anticoagulant monotherapy (HR 0.65, 95% CI 0.56–0.76). Combination therapy was associated with a reduced rate of similar magnitude (HR 0.68, 95% CI 0.59–0.78), while cytoreductive monotherapy showed no significant difference (HR 0.96, 95% CI 0.76–1.21). In patients with a prior thrombotic event, antiplatelet monotherapy remained protective (HR 0.59, 95% CI 0.43–0.79), and combination therapy was associated with a slightly lower bleeding rate compared to anticoagulant monotherapy (HR 0.78, 95% CI 0.61–0.99). The estimate for cytoreductive monotherapy in this group (HR 2.04, 95% CI 0.89–4.68) was based on a small number of patients and had wide confidence intervals, limiting interpretability. These findings suggest that bleeding risk in MPN patients is influenced by both treatment type and thrombotic history. Antiplatelet monotherapy and combination therapy were associated with lower bleeding rates than anticoagulant monotherapy, both in patients with and without prior thrombosis, though the effect was more pronounced in those without prior thrombosis. By accounting for the complete patient pathway and modelling treatment and thrombotic status as time-varying exposures, a more accurate representation of real-world treatment dynamics is presented here. Given that the majority of combination therapy regimens included antiplatelet agents, these results underscore the potential protective role of antiplatelet therapy in managing bleeding risk. These insights may support clinical decision-making, and guide personalized treatment strategies and risk assessment in patients diagnosed with MPN.

AbstractBackgroundChronic lymphocytic leukemia (CLL) is a heterogeneous disease. Whereas some patients have an indolent disease, others experience an aggressive course and early death. Our aim was to investigate if modifiable and non‐modifiable medical history and lifestyle factors prior to diagnosis had an impact on the natural course of the disease.MethodIn 1154 CLL patients, we assessed if the weight, physical activity, smoking, and alcohol consumption or non‐modifiable characteristics including family history of lymphoid malignancy and medical history were associated with time‐to‐first‐treatment (TTFT) and adjusted all results for the CLL‐International Prognostic Index (CLL‐IPI).ResultsTTFT was shorter for patients with high/very high‐risk CLL‐IPI than those with low/intermediate risk CLL‐IPI. In the adjusted analysis we did not find additional impact on TTFT besides CLL‐IPI from any environmental characteristics assessed.ConclusionsWe found limited impact of environmental factors on the natural course of CLL (measured as the TTFT in treatment naïve patients) providing valuable knowledge, and potential relief, to share with patients at the time of diagnosis.

PURPOSE Patients diagnosed with advanced-stage Hodgkin lymphoma (aHL) have historically been risk-stratified using the International Prognostic Score (IPS). This study investigated if a machine learning (ML) approach could outperform existing models when it comes to predicting overall survival (OS) and progression-free survival (PFS). PATIENTS AND METHODS This study used patient data from the Danish National Lymphoma Register for model development (development cohort). The ML model was developed using stacking, which combines several predictive survival models (Cox proportional hazard, flexible parametric model, IPS, principal component, penalized regression) into a single model, and was compared with two versions of IPS (IPS-3 and IPS-7) and the newly developed aHL international prognostic index (A-HIPI). Internal model validation was performed using nested cross-validation, and external validation was performed using patient data from the Swedish Lymphoma Register and Cancer Registry of Norway (validation cohort). RESULTS In total, 707 and 760 patients with aHL were included in the development and validation cohorts, respectively. Examining model performance for OS in the development cohort, the concordance index (C-index) for the ML model, IPS-7, IPS-3, and A-HIPI was found to be 0.789, 0.608, 0.650, and 0.768, respectively. The corresponding estimates in the validation cohort were 0.749, 0.700, 0.663, and 0.741. For PFS, the ML model achieved the highest C-index in both cohorts (0.665 in the development cohort and 0.691 in the validation cohort). The time-varying AUCs for both the ML model and the A-HIPI were consistently higher in both cohorts compared with the IPS models within the first 5 years after diagnosis. CONCLUSION The new prognostic model for aHL on the basis of ML techniques demonstrated a substantial improvement compared with the IPS models, but yielded a limited improvement in predictive performance compared with the A-HIPI.

Background: Event-free survival at 24 months (EFS24) after frontline immunochemotherapy (IC) is an important endpoint in diffuse large B-cell lymphoma and follicular lymphoma, and patients who achieve EFS24 have similar survival compared to age- and sex-matched general population. The role of EFS24 in predicting subsequent survival has not been established in mantle cell lymphoma (MCL), possibly due to perceived poor survival historically. In the last decade, the outcomes of MCL are improving in the evolving treatment landscape. In this international multicenter study, we investigated conditional survival and cause of death in patients with MCL who achieved EFS24 after frontline IC in the older and more recent eras. Methods: Outcomes after frontline IC were evaluated in 5 independent cohorts that included over 3000 patients in total: Mayo/Iowa MER prospective cohort, BC Cancer retrospective population-based cohort, US 12-center retrospective cohort, Swedish Lymphoma Registry, and Danish National Lymphoma Registry. For each cohort, 2 treatment eras were defined based on cohort-specific shifts in treatment patterns (Table 1). Overall survival (OS) after diagnosis and after achieving EFS24 were compared to the background age- and sex-matched general population using a standardized mortality ratio (SMR). Cumulative incidences of cause-specific deaths were analyzed using a competing risk model. Results: In the MER cohort, patients treated in Era M1 (2002-2009; n=147) and Era M2 (2010-2015; n=153) both had inferior OS compared to the general US population. A lower SMR in Era M2 vs M1 (2.25 vs 3.46) suggests a narrower gap in OS compared to the general US population. Lymphoma was the leading cause of death in both eras. In Era M1, patients who achieved EFS24 still had inferior OS compared to the general US population (SMR=2.40, 95% CI 1.76-3.19), and lymphoma remained the leading cause of death. For patients in Era M2 who achieved EFS24, the difference in OS compared to the general US population was not statistically significant with current follow-up (SMR=1.43, 95% CI 0.93-2.09), and lymphoma was no longer the leading cause of death (Table 2). In the BC cohort, patients treated in Era B2 (6/2013-2019; n=188) vs Era B1 (2003-5/2013; n=250) had a narrower gap in OS compared to the general British Columbia population (SMR 4.53 vs 6.69). Lymphoma was the leading cause of death in both eras. For patients achieving EFS24, the gap in OS was narrower in Era B2 vs B1 (SMR 3.56 vs 4.99). After achieving EFS24, lymphoma was the single leading cause of death for patients in Era B1 but not in Era B2 (Table 2). In the US 12-center cohort, patients treated in Era U1 (2002-2011; n=312) and Era U2 (2012-2016; n=417) both had inferior OS compared to the general US population (SMR 2.68 and 2.92, respectively). In patients who achieved EFS24, with current follow up, the difference in OS compared to the general US population was statistically significant in Era U1 (SMR=2.01, 95% CI 1.50-2.64) but not in Era U2 (SMR=1.44, 95% CI 0.82-2.34). Lymphoma was not the leading cause of death after achieving EFS24 (Table 2). In the Swedish cohort, the gap in OS compared to the general Swedish population was narrower in Era S2 (2013-2018; n=439) vs S1 (2006-2012; n=442), both after frontline IC (SMR 4.8 vs 5.4) and after achieving EFS24 (SMR 2.6 vs 3.4). After achieving EFS24, lymphoma was the leading cause of death for patients in Era S1 but not in Era S2 (Table 2). In the Danish cohort, patients treated in Era D2 (2014-2020; n=370) vs Era D1 (2004-2013; n=461) had a slightly narrower gap in OS compared to the general Danish population (SMR 1.90 vs 2.10). For patients who achieved EFS24, those in Era D1 still had inferior OS compared to the general Danish population (SMR=1.44, 95% CI 1.22-1.68), but the OS difference compared to the general Danish population in Era D2 was not statistically significant (SMR=1.27, 95% CI 0.92-1.72) with current follow-up (Table 2). Cause of death data were not available in this cohort. Conclusion: Survival in patients with MCL who achieved EFS24 after frontline IC improved in the more recent treatment era and moved closer to the background expected survival. After achieving EFS24, lymphoma-related mortality was no longer the leading cause of death in the more recent era. EFS24 following frontline treatment may become a critical endpoint for predicting subsequent outcomes in patients with MCL in the modern era.