Novak, Anne J

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.

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 Soluble tumor necrosis factor receptor 2 (sTNFR2) is a member of the TNF superfamily whose normal bodily distribution is largely limited to low level expression on lymphoid cells. It has emerged as an important inducible receptor that activates a signaling pathway for cancer growth. We evaluated sTNFR2 as a prognostic biomarker for overall survival (OS) in newly diagnosed lymphoma using a prospective cohort study with banked pretreatment serum samples. sTNFR2 was higher in 1513 lymphoma patients compared to 499 age and sex matched controls ( p < 0.0001). Using Kaplan–Meier curves and Cox proportional hazards models to estimate hazard ratios [HR] (high vs. low tertile), higher levels of sTNFR2 at diagnosis were associated with inferior OS across all seven major lymphoma subtypes: Hodgkin lymphoma ( p < 0.0001; HR = 12.6), diffuse large B‐cell lymphoma ( p < 0.0001; HR = 2.6), follicular lymphoma ( p = 0.00017; HR = 2.5), mantle cell lymphoma ( p < 0.0001; HR = 4.2), small lymphocytic lymphoma ( p = 0.012; HR = 2.4), marginal zone lymphoma ( p = 0.0012; HR = 3.1), and T‐cell lymphoma ( p < 0.0001; HR = 3.1). Using CITE‐seq profiling of tumor microenvironment tissue, we sought to identify cellular source(s) of circulating sTNFR2. In tumor tissue from follicular lymphoma, high TNFR2‐expressing cells were found to be T‐regulatory (Treg) cells, suggestive of a Treg‐driven cancer. In tissue from a case of marginal zone lymphoma, high TNFR2 expression was found on CD4+ and CD8+ T cells, B cells, and monocytes but also directly on tumor cells. We conclude sTNRF2 is a strong prognostic biomarker of OS across major lymphoma subtypes and may be useful to guide therapeutic choices, including targeted therapies against immunosuppressive TNFR2‐expressing Tregs.

Summary Evidence for an association between insulin‐like growth factors (IGF) and multiple myeloma (MM) is inconsistent. We examined total IGF‐I concentrations and risk of MM by combining baseline serological data among UK Biobank participants ( n = 444 187; 732 incident MM) with a two‐sample Mendelian randomisation (MR) analysis using identified genetic variants associated with circulating total IGF‐I and IGF‐binding protein 3 (IGFBP‐3) in the InterLymph consortium (2434 MM and their 2567 controls). Finally, additional lymphoid neoplasm (LN) subtypes were included for comparison with the main hypothesis. Circulating IGF‐I level was positively associated with MM risk Hazard ratio‐HR‐per one standard deviation‐SD‐increase (HR 1‐SD = 1.11, 95% confidence interval [CI]: 1.01–1.22; p ‐value = 0.03), especially closer to diagnosis. Genetically inferred IGF‐I levels were associated with increased MM risk (odds ratio [OR] = 1.27, 95% CI: 1.05–1.54) but not with any other LNs. Genetically inferred IGFBP‐3 levels showed no associations with any LN evaluated. Corroborating previous findings, in a secondary analysis, IGF‐I levels were associated with the risk of chronic lymphocytic leukaemia/small lymphocytic lymphoma (CLL/SLL) in males with higher body mass index (HR 1‐SD in obese male = 1.36, 95% CI: 1.14–1.61). Our serological and MR analyses suggest a contributing role of IGF‐I in the susceptibility of MM; the CLL/SLL findings warrant further investigation considering sex‐specific adiposity.

Summary Family history of haematological malignancy (FHHM) reflects inherited susceptibility to non‐Hodgkin lymphoma (NHL), but its prognostic significance remains poorly understood. We used a cohort study of 1994 NHL patients to evaluate associations between FHHM and clinical outcomes across lymphoma subtypes. We estimated associations, adjusted for sex and lymphoma‐specific prognostic index, of self‐reported FHHM in a first‐degree relative with overall survival (OS), event‐free survival (EFS) and lymphoma‐specific survival (LSS) using multivariable Cox regression models and with failure to achieve EFS at 24 months (EFS24) using logistic regression. FHHM prevalence was 12.8%, and the median follow‐up among survivors was 12.0 years. FHHM was not associated with OS. In subtype‐specific analyses, FHHM was associated with inferior LSS (hazard ratio [HR] = 1.98, 95% confidence interval [CI] 1.11–3.53) in follicular lymphoma (FL); this association and the association with EFS24 failure strengthened among those treated with front‐line immunochemotherapy (EFS24 failure odds ratio = 2.57, 95% CI 1.08–5.99; LSS HR = 2.68, 95% CI 1.09–6.58). In mantle cell lymphoma, FHHM was associated with inferior EFS (HR = 1.70, 95% CI 1.02–2.85). Interaction testing did not demonstrate significant heterogeneity of FHHM effects by lymphoma subtype. FHHM may be associated with adverse outcomes in select NHL groups, particularly FL. These findings warrant further investigation of germline and environmental factors potentially contributing to more aggressive FLs.

Abstract Although follicular lymphoma (FL) typically follows an indolent course, patients with FL who experience early events, such as transformation or progression, have increased risk of death related to lymphoma. The FL24Cx is an algorithm based on a 45-target gene expression profiling (GEP) assay, which was developed and trained using 265 formalin-fixed, paraffin-embedded tissue samples on a reliable platform to predict, at the time of diagnosis, whether a patient will experience an event within 24 months. The modeling also confirmed and relied upon previously reported synergy between immune response (IR) gene expression signatures IR1 and IR2. Once locked, the 5-factor logistic regression FL24Cx model was independently validated in a retrospectively assessed cohort of 232 patients from 2 immunochemotherapy-treated arms of SWOG Cancer Research Network S0016 phase 3 clinical trial, in which it assigned 169 patients to the low-risk group with 29 events before 24 months (17.2%) and 63 patients to the high-risk group with 24 events before 24 months (38.1%). The relative risk of an event within 24 months after registration among patients who were classified into the high-risk group relative to patients who were classified into the low-risk group was 2.2 (95% confidence interval, 1.41 to 3.51). An up-front GEP biomarker, such as the FL24Cx, rigorously validated in a clinical laboratory and with a clinically relevant turnaround time, could identify and steer enrollment of patients at high risk for early events in clinical trials, thus enabling timely interpretation of such trials and increasing the pace of innovation.

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.

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.