Habermann, Thomas

Background: Perinatal and early-life factors may influence non-Hodgkin lymphoma (NHL) risk, but study results have been mixed and exposure data for childhood ages are limited. Herein, we investigated associations of these exposures with risk of NHL and common subtypes. Methods: This case–control study included 2280 NHL cases and 2253 controls, enrolled from 2002 to 2014 at the Mayo Clinic Rochester. Self-reported perinatal and early-life exposures included maternal age at birth, birth order, birthweight, time breastfed, height and weight at ages 7, 12, and 18 years relative to peers, and age and weight when growth ceased. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for design variables and potential confounders. Linear trend tests were performed for ordinal variables, and heterogeneity tests were performed to evaluate whether associations varied across four NHL subtypes. Results: After multivariable adjustment, greater birth weight (OR = 1.15 for quartile 4 vs. 1; p-trend = 0.04), weight at age 7 relative to peers (compared to average, OR = 1.05 for heavy and OR = 0.87 for thin; p-trend = 0.002), and weight when growth ceased (OR = 1.30 for quartile 4 vs. 1; p-trend < 0.001) were associated with increased NHL risk. An inverse association was observed for breastfeeding duration with NHL risk (OR = 0.77 for >6 months vs. never; 95% CI 0.61–0.97). Associations did not significantly vary by major NHL subtype (p-heterogeneity > 0.05). Other perinatal and early-life exposures were not associated with NHL risk. Conclusions: Greater body weight at birth and through childhood may be associated with increased NHL risk, potentially extending the life-course perspective on adiposity and lymphomagenesis, with implications for prevention.

Abstract Germinal center (GC)-derived lymphomas arise within a specialized immune ecosystem, yet whether malignant cells direct its remodeling remains unclear. Integrating genomic, transcriptomic, spatial, and functional analyses across follicular lymphoma and diffuse large B-cell lymphoma, we define a developmental framework linking malignant B-cell differentiation state to tumor microenvironment (TME) organization. Rather than segregating by histology, lymphomas align along a shared differentiation continuum in which proliferative dark zone (DZ) states associate with immune-depleted TMEs, whereas post-GC/memory B-cell (MBC) states drive inflamed but immunosuppressed TMEs. Spatial profiling reveals collapse of GC architecture and emergence of suppressive myeloid niches along this trajectory. Single-cell lineage reconstruction uncovers a DZ-to-MBC developmental axis underlying lymphoma evolution. Genetic reprogramming in vivo demonstrates that malignant differentiation state is sufficient to instruct TME remodeling. Collectively, these findings establish malignant differentiation state as a causal determinant of immune architecture across GC-derived lymphomas and identify lineage-directed immune reprogramming as a potential therapeutic strategy.

BACKGROUND: Anthracyclines are a widely used and effective class of chemotherapy. However, a major limitation for their use is cardiotoxicity, manifesting as systolic dysfunction, congestive heart failure, and arrhythmias. The objective of this study was to identify genes and genetic risk variants for doxorubicin-induced arrhythmia. METHODS: We performed genome-wide association studies and meta-analysis across 2 independent nonoverlapping, genetically homogenous data sets from the Molecular Epidemiology Resource (cases N=77, controls N=1184) and Tapestry (cases N=13, controls N=172). Doxorubicin-related arrhythmia was the primary cardiac outcome, followed by investigation of a broader phenotype of cardiac events. Effects of doxorubicin on top-associated genes were assessed by quantitative polymerase chain reaction on RNA extracted from human cardiomyocytes following treatment with doxorubicin and by echocardiography in a zebrafish model of doxorubicin-induced cardiomyopathy. RESULTS: In the meta-analysis, rs12151014 at the KCTD15 locus was associated with doxorubicin-related arrhythmia at the genome-wide significance (minor allele frequency in Molecular Epidemiology Resource cases 0.195 versus 0.069 in controls; Tapestry cases 0.192 versus 0.079 in controls) P =9.01×10 −9 ; odds ratio, 3.61. MMP 16 rs1094199 was associated with the broader phenotype of arrhythmia and heart failure (minor allele frequency in Molecular Epidemiology Resource cases 0.079 versus 0.019 in controls; Tapestry cases 0.038 versus 0.015) P =1.98×10 − 8 ; odds ratio=6.15. In human cardiomyocytes, MMP16 and KCTD15 gene expression was significantly downregulated by doxorubicin, and in a zebrafish MMP16 knockout was protective of doxorubicin-induced decline in left ventricular ejection fraction. CONCLUSIONS: Genetic variants at KCTD15 and MMP16 are associated with doxorubicin-related arrhythmia and cardiac events. MMP16 is a potential cardioprotective therapeutic target.

Abstract Background: Although some vaccines seem to be associated with a lower risk of lymphoma, their impact on outcomes is largely unknown. Methods: Data from a large prospective lymphoma cohort study were utilized to estimate associations of self-reported history of vaccination against hepatitis A, hepatitis B, influenza, and yellow fever with event-free survival (EFS) and overall survival (OS) using Cox proportional hazard models. Results: None of the vaccines were associated with EFS [hazard ratio (HR) 0.77–1] or OS (HRs 0.96–1.04). Similarly, there were no significant associations between the vaccines and outcomes for each lymphoma subtype. Conclusions: Prior vaccination against selected viruses was not associated with EFS or OS among patients with lymphoma. Impact: We did not find evidence for an impact of prior vaccination on lymphoma prognosis.

Abstract Therapeutic options for Waldenström macroglobulinemia (WM) have expanded but improvements in overall-survival (OS) are difficult to interpret due to competing non–WM mortality. We conducted a large single-center retrospective study of 1,020 patients with WM to evaluate survival trends. Patients were stratified by era of active WM diagnosis using a two-era model (1996–2005 and post-2005) and a four-era model (pre-2001, 2001–2007, 2008–2013, and post-2013). OS did not differ significantly across eras in the overall cohort (p = 0.64 and p = 0.86 for the two- and four-era models). However, among patients aged < 65 years at the time of active WM diagnosis in the 2-era model, OS improved in the post-2006 era (median 18.8 vs 14.1 years, p = 0.018). Cause-specific-survival (CSS) improved across all eras, increasing from 15.6 years in 1996–2005 to 18.9 years post-2006 (p < 0.0001), and from 13.7 years pre-2001 to not reached in later periods in the four-era model (p < 0.0001). Competing-risk-analysis (CRA) demonstrated a reduction in WM-related mortality over time (p < 0.001). However, excess mortality persisted, with a standardized mortality ratio (SMR) of 2.79 (p < 0.001) among patients < 65 years compared with a matched U.S. population. Our findings highlight improvements in WM-specific survival, while gains in OS are observed in younger patients.

ABSTRACT One quarter of patients with diffuse large B‐cell lymphoma (DLBCL) who achieve a complete response following front‐line therapy will eventually experience disease relapse. Existing prognostic models use baseline factors to predict outcomes from the start of initial therapy and are not intended for use following completion of treatment. We developed a conditional event‐free survival (cEFS) tool that predicts a patient's risk of lymphoma recurrence after completing front‐line therapy taking into consideration baseline risk characteristics plus the time the patient has been in remission. Model development used pooled and harmonized data from two observational cohorts and four randomized trials of patients with newly diagnosed DLBCL treated with immunochemotherapy and either achieving a complete response or not experiencing an event within 12 weeks of end of therapy. Cox proportional‐hazards regression modeling with backwards stepwise selection was utilized for model development. External validation was performed using a large independent data registry. In total, data from 2757 patients were used for model development. The risk of experiencing an event at a time point after having survived a period of time could be computed parsimoniously using four basic predictors: age, ECOG performance status grade, Ann Arbor stage, and lactate dehydrogenase level. C‐index in the model development cohort was 0.65 (95% CI, 0.63–0.68), compared to 0.64 (95% CI, 0.62–0.66) in the external validation cohort. We believe that this dynamic risk prediction tool will not only aid clinicians in providing data‐driven recommendations for surveillance, but also assist patients themselves with key decisions, such as family planning.