Habermann, Thomas

Abstract Glioblastoma (GBM), isocitrate dehydrogenase wild-type (IDHwt) and central nervous system diffuse large B-cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. Deep learning on T1 postcontrast and T2-weighted MRI sequences were used to differentiate GBM and CNS-DLBCL. A three-stage temporal study design was utilized. Model development was performed on 146 patients with CNS-DLBCL and 146 age-matched, sex-matched, and MRI year–matched patients with GBM diagnosed at Mayo Clinic between 1998 and 2019. Models were tested on independent temporal test cohorts. Initial testing included 240 independent GBM diagnosed at Mayo Clinic between 1998 and 2019. The prospective test cohort included 37 patients with CNS-DLBCL and 256 patients with GBM diagnosed at Mayo Clinic after January 1, 2020, and 36 patients with CNS-DLBCL diagnosed at an external institution. Of the patients diagnosed at Mayo Clinic, 47% had MRIs generated from non-Mayo institutions. Two different model approaches were compared: (i) ensemble approach using area under the receiver operating characteristic curve (AUC) and cross-validation for model selection and (ii) loss approach minimizing cross-entropy loss and cross-validation to evaluate prediction performance. The AUCs on the prospective test cohort were 0.84 [95% confidence interval (CI), 0.78–0.90] and 0.83 (95% CI, 0.77–0.88) for the ensemble and loss approaches, respectively. Stability of ensemble prediction improved with the increasing number of models. Stratified AUC analysis demonstrated consistent performance across sex and age. We utilized a robust temporal study design and applied 2 different analytic approaches to develop a classification model. The findings confirm the feasibility of using MRI-based deep learning models to differentiate GBM from CNS-DLBCL. Significance: GBM, IDHwt and CNS-DLBCL are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. We developed MRI-based deep learning models to differentiate GBM, IDHwt from CNS-DLBCL using a rigorous three-stage temporal design that included prospective validation. The model AUC on a prospective cohort was 0.84.

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 162 patients with relapsed secondary central nervous system lymphoma (R‐SCNSL) (median age, 65 years; male, 59.9%) including central nervous system (CNS)‐only ( n = 120) and concomitant CNS/systemic relapse ( n = 42) were retrospectively analyzed. Overall, 21.9% of patients were classified as high risk according to the CNS International Prognostic Index (CNS‐IPI). Several biological and clinical features were significantly associated with leptomeningeal involvement, including double‐ or triple‐hit (DHL/THL) status, MYC rearrangement, negative BCL6 expression by IHC, bone marrow involvement, and concomitant R‐SCNSL. Multivariable analysis showed that leptomeningeal involvement independently predicted inferior OS and was associated with a 98% increase in the hazard of death compared with parenchymal relapse (HR = 1.98, 95% CI: 1.20–3.26, p = 0.008). Based on anatomical localization, R‐SCNSL was classified into four subtypes: parenchymal‐only involvement (parenchymal‐CNS [P‐CNS], 68/42%) and parenchymal involvement plus systemic relapse (parenchymal‐concomitant [P‐concomitant], 17/10.5%); and leptomeningeal with or without parenchymal involvement (leptomeningeal‐CNS [LM‐CNS], 52/32.1%) and leptomeningeal with systemic relapse (leptomeningeal‐concomitant [LM‐concomitant], 25/15.4%). This anatomical classification significantly impacted OS and PFS ( p < 0.001). Two‐year OS and PFS were 58.2% and 29.1% for P‐CNS, 32.4% and 17.7% for P‐concomitant, 22% and 13.9% for LM‐CNS, and 7.1% and 0% for LM‐concomitant, respectively. ASCT showed a trend toward improved survival among patients with a response (CR/PR) in a 4‐month landmark analysis. These findings support the clinical application of the anatomical classification in the management of R‐SCNSL.

PURPOSE Although most patients with follicular lymphoma (FL) can expect an indolent course, progressive lymphoma remains the primary cause of death during the first decade after diagnosis. Progression of disease within 24 months (POD24) of starting first-line (1L) immunochemotherapy defines a high-risk population with poor survival, but better risk stratification at diagnosis is needed. METHODS The FLIPI24 model was developed and internally validated to predict 24-month event rates using individual data from 4,485 patients treated with 1L immunochemotherapy from 10 observational cohorts of FL. Overall and cause-specific survival was further evaluated in FLIPI24 risk groups. External validation in the 1L immunochemotherapy setting was performed using the prospective observational Lymphoma Epidemiology of Outcomes (LEO) cohort (N = 565) and three randomized phase III trials (N = 3,192); extension to all patients with FL (any 1L therapy) was performed in the LEO cohort (N = 1,445) and its Molecular Epidemiology Resource subcohort (N = 1,074). RESULTS The FLIPI24 model uses age and four blood-based variables (hemoglobin, lactate dehydrogenase, beta-2 microglobulin, and WBC count). FLIPI24 showed consistent performance across validation and extension data sets, which was superior to existing prognostic tools. Across the four external immunochemotherapy validation data sets, patients with high-risk FLIPI24 (23%-32% of patients) had significantly higher 24-month event rates (22%-35%) and inferior 5-year overall survival (77%-83%) compared with patients with low-risk FLIPI24 (29%-31% of patients, 24-month event rates: 10%-12%; 5-year OS: 96%-97%). Results were consistent when evaluating lymphoma-related death and when extended to all patients with FL. CONCLUSION The FLIPI24 model robustly stratifies, at diagnosis, patients with FL at increased risk of lymphoma-related death versus patients with very low lymphoma-related mortality during the first decade after diagnosis. FLIPI24 can be used to enrich future clinical trial designs in newly diagnosed FL.

ABSTRACT Newly diagnosed patients with non‐Hodgkin lymphoma (NHL) often have a history of other diseases, and these comorbidities can impact patient treatment and management options, as well as overall survival (OS). We developed the Lymphoma Epidemiology of Outcomes (LEO) comorbidity index (LCI) as a sum of 10 comorbidities adapted from the Self‐Report‐Generated Charlson Comorbidity Index (SRG‐CCI) for use in the LEO cohort, a national prospective study of newly diagnosed NHL. Of the 5502 participants with self‐reported comorbidity data, 3107 (56.4%) were male and the mean age at diagnosis was 60.9 years (range, 18–99 years). The LCI ranged from 0 to 6, with 48.6% having 0, 30.2% having 1, 21.2% having 2 or more comorbidities. With a median follow‐up of 62.4 months among surviving participants, 2099 patients had an event and 1219 died. Continuous LCI similarly predicted both 1‐year mortality (c‐statistic = 0.654) and OS (c‐statistic = 0.655), while it showed a weaker but still statistically significant predictive ability for lymphoma‐specific (c‐statistics = 0.617) and event‐free (c‐statistic = 0.574) survival. Participants with 1 (HR = 1.21, 95% CI 1.05–1.39) and 2+ (HR = 1.80, 95% CI 1.56–2.08) comorbidities had inferior OS compared to those with no comorbidities after adjustment for age and sex (c‐statistic = 0.654), and performance strengthened after adjustment for the International Prognostic Index (c‐statistic = 0.672). LCI predicted OS most strongly in marginal zone (c‐statistics = 0.748) and weakest in T‐cell (c‐statistic = 0.579) lymphoma. The cumulative incidence of death due to lymphoma, lymphoma treatment, and other causes all increased with increasing comorbidities, with the greatest increase observed for death due to other causes. The LCI performs comparable to other published comorbidity indices, supporting its use in the LEO cohort to better model real‐world outcomes and more generally providing an approach to implementing comorbidity indices in cancer survivorship cohorts.

ABSTRACT Anaplastic lymphoma kinase‐positive large B‐cell lymphoma (ALK+ LBCL) is a rare, aggressive subtype of diffuse large B‐cell lymphoma with poor outcomes using standard chemotherapy. In this multi‐institutional retrospective study, we analyzed 39 cases of ALK+ LBCL identified at six US academic centers from 2002 to 2024, with treatment including conventional cytotoxic regimens in frontline and biologically informed and nonchemotherapy‐based strategies in the relapsed setting. Ninety‐two percent of patients received frontline anthracycline‐based chemotherapy; 43% received intensified regimens, and 15% underwent upfront autologous stem cell transplantation (ASCT). Despite these approaches, outcomes remained poor. At a median follow‐up of 5.4 years, median event‐free survival (EFS) was 0.6 years (95% CI, 0.4–0.9), and median overall survival (OS) was 1.5 years (95% CI, 1.3–NR). One‐ and five‐year EFS rates were 28% and 17%, while corresponding OS rates were 72% and 42%, respectively. Advanced stage and high IPI scores were associated with inferior outcomes. Twelve patients received ALK inhibitors, with alectinib showing more durable responses than crizotinib. Lenalidomide and immune checkpoint inhibitors also demonstrated activity, including durable complete responses. Five patients underwent allogeneic stem cell transplantation, with three achieving sustained remission. In conclusion, our findings highlight the limited benefit of chemotherapy, even when intensified or followed by ASCT, and support the integration of biologically targeted therapies, which may have contributed to improved OS in our cohort compared to historical outcomes. Prospective, collaborative studies are needed to better understand disease biology and define optimal use of modern therapies in this rare lymphoma.