Cerhan, James R.

AbstractTo address the current and long‐term unmet health needs of the growing population of non‐Hodgkin lymphoma (NHL) patients, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/). A total of 7735 newly diagnosed patients aged 18 years and older with NHL were prospectively enrolled from 7/1/2015 to 5/31/2020 at 8 academic centers in the United States. The median age at diagnosis was 62 years (range, 18–99). Participants came from 49 US states and included 538 Black/African‐Americans (AA), 822 Hispanics (regardless of race), 3386 women, 716 age <40 years, and 1513 rural residents. At study baseline, we abstracted clinical, pathology, and treatment data; banked serum/plasma (N = 5883, 76.0%) and germline DNA (N = 5465, 70.7%); constructed tissue microarrays for four major NHL subtypes (N = 1189); and collected quality of life (N = 5281, 68.3%) and epidemiologic risk factor (N = 4489, 58.0%) data. Through August 2022, there were 1492 deaths. Compared to population‐based SEER data (2015–2019), LEO participants had a similar distribution of gender, AA race, Hispanic ethnicity, and NHL subtype, while LEO was underrepresented for patients who were Asian and aged 80 years and above. Observed overall survival rates for LEO at 1 and 2 years were similar to population‐based SEER rates for indolent B‐cell (follicular and marginal zone) and T‐cell lymphomas, but were 10%–15% higher than SEER rates for aggressive B‐cell subtypes (diffuse large B‐cell and mantle cell). The LEO cohort is a robust and comprehensive national resource to address the role of clinical, tumor, host genetic, epidemiologic, and other biologic factors in NHL prognosis and survivorship.

Abstract Monoclonal B-cell lymphocytosis (MBL) progresses to chronic lymphocytic leukemia (CLL) requiring therapy at 1% to 5% per year. Improved prediction of progression would greatly benefit individuals with MBL. Patients with CLL separate into 3 distinct epigenetic subtypes (epitypes) with high prognostic significance, and recently the intermediate epitype has been shown to be enriched for high-risk immunoglobulin lambda variable (IGLV) 3-21 rearrangements, impacting outcomes for these patients. Here, we employed this combined strategy to generate the epigenetic and light chain immunoglobulin (ELCLV3-21) signature to classify 219 individuals with MBL. The ELCLV3-21 high-risk signature distinguished MBL individuals with a high probability of progression (39.9% and 71.1% at 5 and 10 years, respectively). ELCLV3-21 improved the accuracy of predicting time to therapy for individuals with MBL compared with other established prognostic indicators, including the CLL international prognostic index (c-statistic, 0.767 vs 0.668, respectively). Comparing ELCLV3-21 risk groups in MBL vs a cohort of 226 patients with CLL revealed ELCLV3-21 high-risk individuals with MBL had significantly shorter time to therapy (P = .003) and reduced overall survival (P = .03) compared with ELCLV3-21 low-risk individuals with CLL. These results highlight the power of the ELCLV3-21 approach to identify individuals with a higher likelihood of adverse clinical outcome and may provide a more accurate approach to classify individuals with small B-cell clones.

Introduction: Assessing baseline cardiovascular (CV) risk factors is crucial for identifying cancer patients at higher risk of cardiotoxicity (CT). While both CT specific scores, including Heart Failure Association-International Cardio Oncology Society (HFA-ICOS) and our institutional score, as well as general CV scores like Atherosclerotic cardiovascular disease (ASCVD), have been used to assess CT risk; in lymphoma patients undergoing anthracycline therapy, their utility remains unknown. Aim: Evaluate the performance of each risk score to predict CT in a cohort of newly diagnosed lymphoma patients undergoing anthracycline treatment, followed for a median of 5.4 years. Methods: 326 Hodgkin and non-Hodgkin lymphoma patients treated and followed from 2013 to 2021 were prospectively assessed. Baseline measurements of the three risk scores were obtained. ASCVD score was not assessed in patients >80 or <40 years old or without baseline cholesterol. CT was defined during or after one year of chemotherapy as severe, moderate, or mild according to 2022 ESC guidelines. Logistic regression and AUC were used to assess the association of each score and compare the models. Results: Among 326 patients, 78 developed CT (8 severe, 21 moderate, 49 mild). A high-risk score from HFA-ICOS was significantly associated with severe and moderate CT(OR: 6.1, p=0.001), sensitivity 37%, and specificity 88%. A very high-risk classification of the institutional score was associated with severe and moderate CT (OR: 8.4, p=0.006), sensitivity 44%, and specificity 81%. No association was found between the ASCVD score stratification and CT. When mild CT was included in the analysis, the AUC values were lower (see Table 1). Conclusions: Cardio-oncology risk scores were associated with severe and moderate CT, outperforming ASCVD, but their predictive capacity was weak. Incorporating other serum or imaging biomarkers into the models may improve the predictive accuracy of CT risk assessment.

Introduction: The use of standardized, evidence-based classification systems is crucial for the accurate diagnosis and treatment of diseases. Moreover, standardized classification facilitates research and epidemiologic studies and promotes consistency in communication among healthcare professionals. Since 2016, the revised 4 th edition of the World Health Organization classification (WHO-HAEM4R) has been the global standard for diagnosis of lymphoid malignancies. With the emergence of new data, 2 new classification systems were developed and published in 2022: the 5 th edition of the WHO Classification (WHO-HAEM5) and the International Consensus Classification (ICC). Both WHO-HAEM5 and ICC maintain a shared fundamental concept of disease classification that integrates clinical, pathologic, and molecular data. However, they differ on nomenclature, establishment of new entities, and/or diagnostic criteria for some disease categories. To evaluate the impact of these differences on real-world diagnosis of non-Hodgkin lymphoma (NHL), we examined the diagnostic classification of NHL in the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study (NCT02736357). Methods: Initiated in 2015, LEO is an ongoing prospective observational study of patients aged ≥18 years with newly diagnosed NHL. Patients are enrolled at 8 major U.S. medical centers. Clinical, epidemiologic, pathologic, and treatment data are abstracted at baseline and active follow-up is conducted for all patients. Lymphoma subtype is coded for each case based on expert hematopathology re-review of the diagnostic pathology slides, the pathology report, biomarker data, and clinical data. Of note, NHL subtype distribution is similar to SEER data. We studied all patients enrolled in LEO between 7/1/2016 (the date LEO pathology review started using WHO-HAEM4R diagnostic codes) and 5/31/2020. WHO-HAEM4R diagnoses and additional clinicopathologic data, when relevant, were used to map cases into the corresponding WHO-HAEM5 and ICC diagnoses. Differences between WHO-HAEM5 and ICC were annotated for each case as: None - same disease entity; Minor - difference in nomenclature with similar diagnostic criteria; Major - difference in disease category and/or diagnostic criteria; or Unevaluable - insufficient data to assign WHO-HAEM5 and/or ICC diagnosis. Results: LEO enrolled 6143 patients during the study period. Of these, comparison between WHO-HAEM5 and ICC was evaluable in 5730 (93.3%). Unevaluable cases included those without a specific WHO-HAEM4R diagnosis at enrollment (N=384; e.g., patients with a low-grade B-cell lymphoma that could not be definitively sub-classified) and those with a specific WHO-HAEM4R diagnosis, but with insufficient clinicopathologic data to assign a specific WHO-HAEM5 and/or ICC diagnosis (N=29). Of the 5730 evaluable cases, 5376 (93.8%) showed no difference between WHO-HAEM5 and/or ICC diagnosis, 311 (5.4%) showed minor differences (nomenclature only), and 43 (0.8%) showed major differences (Table 1). The 43 major differences all involved B-cell NHLs; 20 (46.5%) were attributable to different approaches to classifying double-hit lymphomas, 21 (48.9%) to classification of splenic/leukemic B-cell lymphomas, and 2 (4.6%) to classification of B-cell lymphomas occurring at specific anatomic sites (Table 2). Conclusion: In a large, prospective lymphoma cohort reflecting real-world clinical practice at 8 major U.S. medical centers, major diagnostic differences in the classification of NHL using WHO-HAEM5 or ICC classification criteria were seen in 0.8%, whereas the remaining 99.2% of diagnoses were either the same or showed differences in nomenclature only. The existence of 2 concurrent classification systems presents potential for discrepancies in pathologic diagnosis, clinical practice, clinical trials, and other lymphoma research. Furthermore, some of the differences between WHO-HAEM5 and ICC are clinically and potentially therapeutically significant, and their resolution requires further study. Nevertheless, our findings argue that the proportion of patients affected would be small in real-world practice settings. This appears largely related to incidence rates of specific lymphoma subtypes, with major differences between the 2 classifications predominantly affecting rare entities, while there is general concordance on the most common forms of NHL.

Introduction: PET/CT is the standard-of-care for staging and therapy response assessment in lymphoma. Fluorodeoxyglucose (FDG)-avidity in extranodal marginal zone lymphoma (EMZL) remains controversial with some variability by extranodal location. The current Lugano classification recommends the use of CT scans only in staging and follow-up for EMZL. However, emerging data from small studies have challenged this suggestion. In this study we aimed to determine the ability of PET/CT to detect FDG-avid EMZL during staging work-up. Methods: First, we retrospectively analyzed the University of Miami (UM) MZL database (period 2/2016-1/2023) searching for patients who underwent staging PET/CT. Images were reviewed by expert radiologists to ascertain avidity of tumor and not surrounding tissue, with specific attention to ocular and GI locations; if scans were not available (n=15), we retrieved data from reports (results presented in part at ICML2023). Next, we aimed to validate the initial UM results additionally analyzing data from imaging reports for patients prospectively enrolled in the Lymphoma Epidemiology of Outcomes (LEO) MZL cohort (period 7/2015-5/2020), excluding LEO patients from Miami to avoid overlap. Patients with high-grade transformation at diagnosis were excluded. For patients with &gt;1 extranodal site, each location was counted independently. We considered FDG-avid disease if SUVmax was ≥2 as this value is commonly observed between mediastinal blood pool (BP) and liver background. To normalize data, we calculated ratios of lymphoma SUVmax versus both BP and liver background, as available. Patients without measurable disease were excluded from analysis. Results: Among 210 patients with EMZL in the UM cohort, 152 had staging PET/CT and were analyzed. Twenty-two patients demonstrated &gt;1 extranodal site providing a total of 187 locations. The LEO cohort included 411 patients from 7 centers, with 235 having available imaging reports. Fifty-two patients in this cohort demonstrated &gt;1 extranodal site providing a total of 306 locations. Disease distribution is depicted in Table 1. Among 187 EMZL locations in the UM cohort, the most common were gastric (n=33, 17.6%), ocular (n=31, 16.6%), lung (n=30, 16%), skin and soft tissue (n=16, 8.6%, each). Similarly, lung (n=63; 20.6%), soft tissue (n=46; 15%), gastric and ocular (n=34 each; 11%) were common locations in the LEO cohort. EMZL demonstrated FDG-avidity (SUVmax ≥2) across all locations with identical values in both cohorts (UM= 78.1% & LEO= 76.5%). FDG-avidity by location is shown in Table 1A & B with salivary gland (100% & 100%), lung (93.3% & 95.2%), soft tissue (93.8% & 100%), and airways (90.9% & 100%) demonstrating high avidity in both cohorts. Contrarily, skin was commonly non-FDG avid (93.8% & 81%). The median size of FDG-avid lesions was 2.4cm (range, 0.7-17.4) in UM and 2.9cm (range, 0.1-12) in LEO cohorts. In patients with &gt;1 extranodal site FDG-avidity was nearly universal across sites (UM=93% & LEO=100%). We observed a significant correlation between lymphoma size and FDG-avidity for UM (r=0.33; P=0.001), and for LEO (r=0.55; P&lt;0.0001). In patients with background FDG-avidity data in the UM cohort (n=150), a BP index and liver index ≥1 detected lymphoma in 79.3% & 71.5% cases, respectively. We were unable to calculate indexes in LEO cohort since only limited data on BP (n=26) and liver (n=19) background was available in imaging reports. Conclusions: This study represents the largest analysis evaluating accuracy of PET/CT to determine initial tumor burden in 387 patients with EMZL. We demonstrate that EMZL is largely an FDG-avid disease across two cohorts, and PET/CT should be included in the staging of these patients while acknowledging possible limited sensitivity in GI locations due to physiologic uptake. Furthermore, we observed that patients with multiple extranodal locations demonstrate uniform FDG-avidity across all sites except for skin involvement. Based on our results we recommend the incorporation of PET/CT into standard staging of EMZL in planned revised Lugano classification guidelines. In those demonstrating initial FDG-avidity, a lower SUVmax threshold of SUVmax ≥2, comparison to mediastinal BP rather than to liver background activity and evaluating for resolution of focal FDG-avidity should be considered to assess treatment response in routine care and clinical trials.

Introduction: Molecular classifications have been developed to characterize the heterogeneity of diffuse large B cell lymphoma (DLBCL), with activation of BCL6 and Notch signaling pathways acting as driving pathogenic features in C1/BN2 subtype tumors. Among C1/BN2 defining variants are truncating/inactivating SPEN mutations. SPEN regulates the Notch signaling pathway by initiating formation of a repressive complex that facilitates transcriptional repression of Notch target genes. Our group has identified SPEN mutations enriched in DLBCL cases failing to achieve event-free status at 24 months (EFS24). This contrasted with generally favorable outcomes in C1/BN2 tumors, suggesting a potential high-risk molecular feature with unexplored significance. Presenting an opportunity to expand underlying mechanisms and risk stratification in C1/BN2 tumors, we aimed to use a functional genomic approach, combined with clinical data, to characterize the alternative biology stemming from SPEN truncating mutations. Methods: FFPE tumor biopsies from newly diagnosed DLBCL cases (N=444) enrolled in the Mayo Clinic/Iowa Lymphoma Molecular Epidemiology Resource (MER) program were analyzed by WES (n=404) and RNA-seq (n=321). Biologic and clinical variables were annotated for all cases. CRISPR/Cas9 introduced truncating mutations to the endogenous SPEN locus in OCI-LY3 & SU-DHL-2 ABC-type human cell lines to establish models of SPEN depletion. Functional in vitro analysis utilized standard methods for RNA-seq, cell proliferation, western blot, and flow cytometry. Results: WES identified 29/404 ndDLBCL (7.2%) harboring SPEN mutations; n=17 missense and n=12 nonsense or frameshift insertions/deletions (truncating variants - [trunc]), the later considered as the focal point of our study. Against all cases, SPEN trunc cases displayed enrichment for high-risk factors including non-GCB COO (p=0.06, OR=3.7, 95% CI [0.9, 22.2]) and primary refractory disease (PTR; p=0.02, OR=5.0, 95% CI [1.05, 19.9]), and demonstrated inferior OS (p=0.06, HR=2.2), where a majority of clinical progression events occurred within 12 months of diagnosis. Leveraging RNA-seq, we observed 11 of 11 SPEN trunc cases exhibiting a double-hit negative gene expression signature, 9/11 cases with inflammatory or depleted microenvironment (LME), and 8/11 with a signature associating with intermediate/high risk of EFS24 failure. Applying the LymphGen algorithm, 5/12 SPEN trunc cases received the BN2 classification, observing co-occurring mutations with CD70 (p&lt;0.01, OR=9.68), BRCA2 (p=0.03, OR=5.84), TET2 (p=0.02, OR=4.91), IRF4 (p=0.02, OR=7.27), and PTPRD (p&lt;0.01, OR=8.31) genes, and were mutually exclusive with ARID1A, BCL2, EZH2, FAS, HLA-B, IRF8, and TMEM30A mutations ( Figure 1A). Isolating SPEN trunc against BN2 cases without SPEN variants (n=14), despite similar clustering of non-GCB COO (p=0.7), PTR was exclusively observed in SPEN trunc cases, accompanied again by inferior OS (p=0.07, HR=4.2; Figure 1B). In the OCI-LY3 SPEN depletion model, GSEA analysis from RNA-seq revealed activation of E2F (NES=2.7; p=9.4E-20) and MYC target genes (NES=2.3; p=4.1E-6), while both OCI-LY3 and SU-DHL-2 models featured depletion of antigen presentation genes (NES= -1.8, p=5.7E-4; NES= -2.2, p=3.8E-7, respectively). A decrease of MHC class II proteins (HLA-DR, HLA-DP) was confirmed by flow cytometry in both models (p&lt;0.01). Hypothesizing loss of SPEN enhances reliance on the BCL6-HDAC3 axis featured in BN2 tumors, we treated both SPEN depletion models with a class-I HDAC inhibitor highly selective for HDAC3, BRD-3308, and indeed observed a 1.4 and 2.4-fold increase in sensitivity compared to WT cells (p=0.07, p&lt;0.01, respectively). Significance: We find SPEN trunc mutations in poor acting DLBCL cases with clinical and biologic characteristics that diverge from C1/BN2 biology. The enhanced rate of clinical progression highlights urgency to better characterize these tumors. Our data suggests loss of SPEN regulatory mechanisms may act cooperatively with C1/BN2 biology to facilitate tumor immune evasion and drive progression through Notch-mediated pathways. Importantly, in vitro evidence shows SPEN deficient lymphoma cells are susceptible to targeted therapeutics against dependent pathways, providing rationale for advancing individualized care strategies for affected patients.

Background: Although marginal zone lymphoma (MZL) typically exhibits an indolent course, transformation to diffuse large B-cell lymphomas (DLBCL) is associated with a poorer outcome and remains a clinical challenge in managing patients with MZL. The limited existing literature reports various cumulative incidence rates, ranging from 2.5% and 4.7% (Finnish Cancer Registry, 1995-2018) to 6.6% and 8.4% (Florida Cancer Registry, 1995-2016) at 5 and 10-years, respectively, likely in part driven by varying study designs, ascertainment, and study population. Similarly, reported outcomes after transformed MZL (tMZL) have been variable. We evaluated the cumulative incidence of histological transformation (HT) to LBCL in a well-characterized prospective cohort of MZL patients from the upper Midwest, USA, and overall survival (OS) after transformation. Methods: Patients ≥ 18 years old with newly diagnosed MZL were prospectively enrolled in the University of Iowa/Mayo Clinic Molecular Epidemiology Resource (MER) cohort from 2002-2015. Clinical and treatment data were abstracted from medical records using a standard protocol. Patients were actively followed for retreatment, transformation, and death through 2022. Pathology was classified according to WHO 4/4R, including all transformations. The cumulative incidence of HT to LBCL was determined using death as a competing risk. Time to HT (TTHT) was defined as time from the date of MZL diagnosis to the date of transformation. We evaluated potential predictors of HT using a stepwise approach, and derived hazard ratios (HR) and 95% confidence intervals (CI) from Cox proportional hazards models. To assess predictors of OS after HT, patients ≥ 18 years old with newly diagnosed tMZL (into DLBCL) at Mayo Clinic between 1995 and 2002 (N=7) were combined with the MER cases. Results: We identified 524 patients with MZL in the MER cohort: 362 extranodal (EMZL; lung 18%, stomach 16%, orbit 13%, parotid 10%, skin 10%), 84 splenic (SMZL), and 78 nodal (NMZL). The median age at diagnosis was 63 years (range 18-92); 56% were female, and 83% were non-Hispanic white. During a median follow-up of 18.8 years (95% CI 16.7, NA), there were 25 HT (including 8 patients under observation) and 158 deaths. Eight Ten-year OS was 67% and 77% in the groups with and without HT, respectively. The overall cumulative incidence of HT was 1.5% at 2 years after diagnosis, 2.9% at 5 years, 4.5% at 10 years, and 5.7% at 15 years (Panel 1). The cumulative incidence of HT varied by subtype (e.g., at 5 years: 2%, 4% and 6%, in EMZL, NMZL and SMZL, respectively; Panel 2). The median time to HT also varied by subtype: 76 months (interquartile range (IQR) 43, 81) for EMZL, 30 months (IQR 16, 52) for SMZL, and 18 months (IQR 14, 23) for NMZL. In univariable analysis, predictors of HT were Stage III/IV (HR=3.4, 95% CI 1.36-8.53, p=0.009), elevated LDH (HR=2.98, 95% CI 1.25-7.12, p=0.014), and presence of ≥2 extranodal sites (HR=2.69, 95% CI 1.22-5.94, p=0.014). In multivariable analysis, elevated LDH was the only non-composite predictor of HT (HR=2.65, 95% CI 1.08-6.52, p=0.034). MALT-IPI score 2-3 (HR=3.61, 95% CI 1.06-12.25, p=0.040) and FLIPI score 3-5 (HR=2.19, 95% CI 1.22-8.22, p=0.018) also predicted HT. We analyzed OS after HT in 32 cases of tMZL (21 tEMZL, 7 tSMZL, 4 tNMZL). At HT, median age was 68 years (range 39-89); 24 (80%) patients presented with stage III/IV disease, 11 (58%) with elevated LDH, 12 (55%) with hemoglobin &lt;12g/dL, 3 (14%) with platelet count &lt;100x10 9/L and 9 (39%) with biopsy-proven bone marrow involvement. Twenty-six (81%) were treated with a systemic therapy, mainly CHOP-backbone therapy (R-CHOP n=13, CHOP n=4, R-EPOCH n=3, lenalidomide-R-CHOP n=1). Among these patients, the overall response rate was 85% (n=22/26). Three of the 4 non-responders died within 1 year. At last follow-up, 18/32 (56%) patients had died, and 6/13 (46%) alive patients had relapsed (MZL 3/6, DLBCL 3/6). After HT, 2-, 4- and 10-year OS were 76%, 55% and 55%, respectively. In univariable analysis, the only predictor of OS at HT was age ≥70 (HR 3.57 ,95% CI 1.34-9.48, p=0.011). Conclusion: In this North American prospective cohort of mainly non-Hispanic White patients, we found a low cumulative incidence of HT in MZL of 2.9% and 4.5% at 5- and 10-year, which was consistent with the Finnish findings (Kalashnikov et al., 2023). At HT, age was associated with OS and there was a high response rate to CHOP-backbone therapies.

Background: Anaplastic large cell lymphomas (ALCLs) are CD30-positive T-cell lymphomas that share pathologic features but differ in clinical presentation, outcome, and molecular features. The World Health Organization (WHO) and International Consensus Classification (ICC) classify ALCLs by presence or absence of ALK rearrangements (R) and clinical presentation (systemic, cutaneous [c], or breast implant-associated [BIA]). ICC, but not WHO, recognizes DUSP22-R as defining a new genetic subtype of ALK- ALCL. The classifications otherwise do not reflect additional molecular heterogeneity in genetics (e.g., TP63-R) or therapeutic vulnerabilities (e.g., JAK-STAT3 pathway activation). Methods: ALCLs (N=689) underwent expert consensus review (WHO/ICC) through the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). All cases also underwent genetic subtyping (ALK, DUSP22, TP63, and triple-negative [TN]) using fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC), as well as IHC for phospho-STAT3 Tyr705 (pSTAT3). RNAseq was performed and evaluable in 393 cases; the remaining cases had insufficient tissue, tumor content, RNA yield or quality, and/or sequencing data quality. Sequenced and non-sequenced sub-cohorts had similar demographics and subtype distribution. Results: Unsupervised gene expression profiling (GEP) identified 2 main molecular types of ALCL. Type I ALCLs predominantly included ALK+ ALCLs, BIA-ALCLs, and a subset of TN ALCLs (designated TN-I), whereas Type II ALCLs predominantly included ALCLs with DUSP22-R, TP63-R, or both (double-hit; DH), and the remaining TN ALCLs (TN-II). Type I ALCLs were strongly associated with pSTAT3 expression (74.2±26.4% positive malignant cells vs 9.9±22.7% for Type II; P&lt;0.0001). An independently derived pSTAT3 staining threshold of 30% assigned Type I vs II with 91% accuracy. A third cluster of ALCLs, mostly cALCL, showed an epithelial GEP signature rather than a lymphoma signature; these cases were assigned to Types I or II based on pSTAT3 IHC. Distinct sub-signatures were identified for ALK+, DUSP22-R, TP63-R, and BIA ALCL (Fig. 1), but not ALK- ALCL or cALCL. Gene set enrichment analysis showed Type I ALCLs to be enriched for JAK-STAT3 signaling genes (normalized enrichment score [NES], 2.22; FDR&lt;0.0001) and related pathways, such as TNFα-NFκB signaling (NES, 2.21; FDR&lt;0.0001). In contrast, Type II ALCLs were enriched for cell cycle, DNA repair, epigenetic, and metabolic pathway genes, but not for major tyrosine kinase-mediated signaling pathway genes. Enriched epigenetic pathways included chromatin modifying enzymes (NES, -1.86; FDR=0.002) and histone methylation (NES, -1.71; FDR=0.002). EZH2 was the most overexpressed gene in Type II ALCLs (fold-change, 7.74; FDR=8.84×10 -306). At the protein level, EZH2 IHC H-scores were 275±45 in Type II and 168±70 in Type I ALCLs (P&lt;0.0001); H3K27me3 H-scores were 170±81 and 76±63, respectively (P&lt;0.001). The top metabolic gene set involved cholesterol biosynthesis (NES, -1.88; FDR=0.002). Overall survival (OS) data were available in 257 systemic ALCL patients (145 sequenced and 112 non-sequenced; cALCL and BIA-ALCL were excluded). Non-sequenced TN ALCLs were assigned to TN-I or TN-II using pSTAT3 IHC. The results supported earlier data indicating favorable prognosis of DUSP22-R ALCL (5 y OS, 95%) and ALK+ ALCL (87%), intermediate prognosis of TN ALCL (TN-I, 52% and TN-II, 38%; P=NS), and poor prognosis of TP63-R/DH ALCL (0%)(P&lt;0.0001; Fig. 2). Conclusions: Two overarching molecular types of ALCL exist, predominantly associated with the presence (Type I) or absence (Type II) of the JAK-STAT3 signaling program. Distinct GEP signatures exist for ALK+ ALCL and BIA-ALCL (predominantly Type I), and DUSP22-R ALCL and TP63-R ALCL (predominantly Type II). TN ALCLs lacking ALK-R, DUSP22-R, and TP63-R can be stratified into TN-I and TN-II subtypes. pSTAT3 IHC has &gt;90% accuracy as a surrogate for GEP-based subtyping. ALK- ALCL and cALCL cluster by molecular subtype rather than by defining GEP signatures. Type II ALCLs are enriched for targetable epigenetic and metabolic pathways, including EZH2/histone methylation and cholesterol biosynthesis. This molecular classification is diagnostically, prognostically, and potentially therapeutically relevant, and can be applied using FISH and IHC in routine practice and in the clinical trial setting.

Background: QOL can be affected by disease burden, side effects of treatment, and psychosocial effects of living with cancer. Although MZL is considered incurable, we previously found that patients diagnosed from 2002-2015 had a good QOL both at baseline (BL) and the first decade after diagnosis, regardless of treatment choice (Bommier et al., submitted). Here, we evaluate whether these findings can be extended to the 2015-2020 treatment era and a more diverse US cohort. Methods: Adults with newly diagnosed MZL from 8 academic centers were prospectively enrolled within 6 months of diagnosis from 2015-2020 in the LEO cohort (NCT02736357). Participants were actively followed for disease progression/relapse, retreatment and death. QOL was measured at BL, and at 1, 2, 3 and 5 years after diagnosis using the Functional Assessment of Cancer Therapy-Lymphoma (FACT-Lym) scale (range 0-164), which consists of the FACT-General (FACT-G, range 0-104) plus a lymphoma-specific scale (range 0-60). Total FACT-G measures 4 QOL domains (range): physical (0-28), social/family (0-28), emotional (0-24), and functional (0-28) well-being (WB). We also used the Trial Outcome Index (TOI; range 0-112), which consists of FACT-G physical and functional WB plus the lymphoma-specific scale and is commonly used as an endpoint in treatment trials. All MZL patients with both BL and at least one follow-up QOL questionnaire were eligible for analysis. Patients were grouped by initial management: active surveillance (observation), local/antibiotic therapy (radiation, surgery, or anti- H. pylori therapy), or systemic therapy (chemotherapy, targeted agents, or antibody therapy). Change in QOL scores over time was analyzed using mixed models for repeated measurements, and initial treatment groups were compared. Results: Of 384 patients, 60% were female, 91% were White, 6.6% were Black/African American, and 13% were Hispanic (all races). The median age was 64 years (range 19-94). For initial management, 28% (N=106) were observed, 31% (N=118) received local/antibiotic therapy, and 42% (N=160) received systemic therapy. Across treatment groups, there were no significant differences by age, gender, race, or performance status, while there were differences by Hispanic ethnicity (p=0.006), Ann Arbor stage (p&lt;0.001) and MALT-IPI score (p&lt;0.001) (Table). At BL, patients receiving systemic therapy had lower physical WB (p=0.008), emotional WB (p=0.04), functional WB (p=0.03), FACT-G total score (p=0.008), lymphoma subscale (p&lt;0.001), FACT-Lym (p=0.001) and TOI (p&lt;0.001) compared to observation and local/antibiotic therapy (Table). While FACT-G total scores were largely stable through 5 years after diagnosis, social/family WB declined from BL for patients initially receiving either local/antibiotic therapy (mean at 1-year -1.4, p&lt;0.05; 2-year -2.1, p&lt;0.05; 3-year -1.6, p&lt;0.05; 5-year-2.9, p&lt;0.05) or systemic therapy (mean at 2-year -1.2 , p&lt;0.05; 3-year -1.4, p&lt;0.05; and 5-year -1.2, p&lt;0.05), while this was stable for observed patients. In patients receiving initial systemic therapy, there was a transient improvement in the lymphoma-specific scale (mean +1.7, p&lt;0.05) and TOI (mean +3.7, p&lt;0.05). Otherwise, QOL remained stable over time and global QoL (FACT-G, FACT-Lym), TOI, Lymphoma-specific scale (Figure), and the other FACT-G subscales (physical, emotional, or functional WB) did not differ by initial treatment strategy. Conclusions: In the diverse LEO cohort from the recent treatment era, we confirm our prior findings for newly diagnosed MZL patients that QOL is globally stable over the first 5 years after diagnosis; emotional WB is not associated with initial treatment type, providing evidence that being initially observed does not negatively impact emotional health; and there is a decline in social/family WB (support from friends and family, family acceptance of illness, family communication, close to partner), which supports the need to consider interventions for patients to address these unmet needs. In addition, this study extends these findings to the lymphoma-specific scale, FACT-Lym, and TOI, which all showing largely stable trends in the 5 years after diagnosis and suggest that recent MZL treatment strategies, including systemic therapies, neither impair nor improve QOL.

Introduction: Splenic marginal zone lymphoma (SMZL) is a rare, indolent disease. There is no universally accepted standard therapy and long-term outcome data are limited. Rituximab monotherapy is increasingly used over splenectomy in the first-line setting despite a paucity of comparative studies. In the absence of randomized trials, large-scale international real-world data studies are critical to evaluate outcomes of different treatment interventions and to understand the natural history of SMZL in the rituximab-era. Methods: Adult patients with SMZL diagnosed between Jan 1 st 2000 and Dec 31 st 2018 were identified using regional/nationwide population-based registries or hospital registries in Europe, the UK, North America, and Australia. Medical records and pathology reports from eligible patients were reviewed locally by clinicians with specialty experience in hemato-oncology. SMZL cases were required to meet the diagnostic criteria by Matutes et al. Detailed data on clinico-pathological features, comorbidities, treatments (including treatment intention), treatment responses and survival outcomes were entered in a central study database. Overall survival (OS) was defined as time from diagnosis until death from any cause or censoring at last follow-up unless stated otherwise. Event-free survival (EFS) was defined as the time from diagnosis until histological transformation, initiation of new chemotherapy or death from any cause. Survival probabilities were estimated using the Kaplan-Meier estimator. Cumulative risk of transformation was estimated with death as a competing risk. Primary endpoints were 10-year OS and 5-year EFS respectivly. Results: A total of 934 patients from 25 sites were included. Median age at diagnosis was 68 years (IQR 60-76) and 54% were female. Bone marrow involvement was present in 96% (564/590) of those assessed, anemia (Hb &lt;12g/dL for women or &lt;13g/dL for men) in 58%, LDH &gt;UNL in 46%, lymphocytosis (&gt;5 x10 9/L) in 34%, and B-symptoms in 34%. Treatment data were available for 97% of patients. Median follow-up was 9.1 years (range 0-23). Watch and wait was the initial strategy in 28% and 88% of patients received at least one line of treatment during follow-up with the most common being splenectomy (45%), immuno-chemotherapy (19%) or rituximab monotherapy (8%). Fifteen percent received “other” treatments (i.e., combinations of listed therapies and/or radiation). The overall response rate to first-line treatment was 88% (95%CI: 85-90%) with 61% (95%CI: 57-64%) achieving CR. Second line (2L) therapy was needed in 34% during follow-up, 3L in 20% and 4L+ in 9%. The 5-year EFS and OS for all patients were 61% (95%CI: 57-65%) and 77% (95%CI: 74-80%) respectively. The 10-year OS and lymphoma-specific mortality (with non-SMZL deaths as competing risk) estimates were 60% (95%CI: 57-64%) and 11% (95%CI: 9-14%) respectively. The 5-year OS after 2L and 3L were 61% (95%CI: 55-68%) and 51% (95%CI: 42-61%) respectively (figure 1). The 10-year cumulative risk of histological transformation was 17% (95%CI: 13-21%), with 5-year post-transformation OS of 42% (32-54%). At the time of transformation, 60% were chemo-naive and 52% had never been treated for SMZL. The 5-year OS for chemo-naive patients with transformation was 54% (95%CI: 41-71%) versus 24% (95% CI: 13-44%) for transformations after (immuno)chemotherapy (p = 0.01). When comparing patients intended for treatment in first line with splenectomy (n=312) versus rituximab (n=70), patients treated with splenectomy more frequently presented with extra-hilar lymphadenopathy (35% vs 18%), splenomegaly (92% vs 87%) and anemia (64% vs 48%). OS was similar for the two groups (Figure 2, p = 0.53). The 5-year EFS were 63% (95%CI: 57-68%) and 64% (95%CI: 54-77%), respectively (p = 0.31). Conclusions: To date, this is the largest real-world study of SMZL with detailed treatment and outcome data. The study shows that histological transformation was not uncommon with 10-year risk of 17%. However, outcomes for the entire cohort were excellent irrespective of initial treatment and both OS and EFS were similar after first line rituximab versus splenectomy. Long-term survival remained relatively high even following multiple lines of therapy.