Cerhan, James R.

Background: Monoclonal B-cell lymphocytosis (MBL) is a precursor condition to chronic lymphocytic leukemia (CLL) characterized by the presence of circulating monoclonal B-cell populations in the peripheral blood of otherwise healthy individuals. MBL increases risk of several adverse clinical outcomes, including development of hematological malignancies. Mosaic chromosomal alterations (mCAs) are a form of clonal hematopoiesis which affect large segments of DNA and include gains, losses, and copy number neutral loss of heterozygosity events. mCAs can be detected from SNP-array genotyping. Prior work has suggested mCAs as a potent risk factor for hematological malignancies. However, the nature of the relationship between mCAs and MBL is unknown. We sought to determine 1) the association between mCAs and MBL and 2) their combined effect on risk of hematological malignancies, in a large, prospectively collected, and well-annotated cohort of individuals with known MBL, mCA, and clinical outcomes. Methods: We examined the prevalence of mCA in a cohort of individuals from the Mayo Clinic Biobank who were screened for MBL using a sensitive eight-color flow cytometry assay. We classified MBL by the size of the clone relative to total B-cells, with high count (HC) defined as those individuals who had a percent clonal B-cell count ≥85% out of total B-cell count and low-count (LC) otherwise. Autosomal mCAs were detected from whole blood DNA collected at the time of MBL screening using a SNP-array-based assay. The MoChA pipeline was used to identify mCA events. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CIs). To examine incident hematological cancers, we identified and validated all hematological cancers through medical record abstraction using the International Statistical Classification of Diseases codes. Cox regression was used to calculate hazard ratios (HR) and 95% CIs, stratified by MBL status or autosomal mCA status. All models were adjusted for age and sex. Results: We evaluated the prevalence of autosomal mCA in 3,764 individuals (792 individuals with MBL of whom 64 had HC-MBL and 2,972 without MBL). The prevalence of autosomal mCA was 7.7% ( n=288) with a median mCA cell fraction of 0.09 (range 0.01-1). Among those with and without MBL overall, the prevalence of mCA was 15.5% ( n=123) and 5.6% ( n=165), respectively (Figure 1). Compared to those without an autosomal mCA, individuals with an autosomal mCA were 2.4-fold more likely to have MBL (95% CI 1.9-3.2; P =2.0x10 -11; Figure 1). CLL-associated mCA (i.e., those commonly altered in CLL including trisomy 12 and deletion of 6q, 11q, 13q, and 17p) were present in 42 individuals, of whom 38 (90.5%) had MBL overall and 30 (71.4%) individuals had HC-MBL. Compared to those without a CLL-associated mCA, individuals with a CLL-associated mCA were 539.39-fold more likely to have HC-MBL (95% CI 190.3-1975.9; P <2.0x10 -16) and 6.7-fold more likely to have LC-MBL (95% CI 2.0-26.5; P =0.0031; Figure 1). Next, we evaluated the relationship between MBL and mCA with risk of developing a hematologic malignancy in 3,009 individuals with follow-up data (median 10 years). Forty-one individuals developed an incident hematological malignancy (68.3% lymphoid). When we evaluated the effect of autosomal mCA stratified by MBL status we observed elevated but non-significant risk of hematological malignancies (Figure 2). When we evaluated the effect of MBL stratified by autosomal mCA status we observed elevated and significant increased risk of developing a hematological malignancy (Figure 2). Conclusions: We found that the presence of an autosomal mCA is highly associated with having MBL. In particular, >90% of CLL-associated mCA carriers had MBL with ~7- and ~540-fold increased association for LC- and HC-MBL, respectively. These results suggest that almost all individuals in large biobanks with CLL-associated mCAs have undiagnosed MBL. However, not all individuals with MBL have an mCA. When evaluating risk of hematological malignancies, we found autosomal mCAs had >2-fold elevated but non-significant effects when stratified by MBL status while MBL remained a significant risk factor regardless of autosomal mCA status. Collectively these results support that MBL remains an important risk factor and suggests that mCAs hold potential to identify a subgroup of individuals at greater risk of developing a hematological malignancy.

Background Peripheral T-cell lymphomas (PTCLs) comprise a rare, heterogeneous group of non-Hodgkin lymphomas of mature T-cell origin. Most systemic (s) PTCL subtypes typically have poor outcomes with conventional anthracycline-based chemotherapy. Biomarker-driven and subtype-specific treatments are promising but unmet needs. Few benchmark studies exist to characterize the current real-world landscape of clinical and pathologic practice. We report the patterns of care and updated outcome data for PTCL patients enrolled in the LEO-MER multi-center prospective cohort study (ClinicalTrials.gov NCT02736357). Methods Patients aged 18 years or older with newly diagnosed PTCL were prospectively enrolled in the University of Iowa/Mayo Clinic MER cohort (2002-2015) or the expanded LEO cohort (2015-2020). Clinical, pathology, treatment, and outcome data were abstracted from medical records using a standard protocol in both cohorts. Pathology underwent expert re-review based on WHO criteria. Overall survival (OS) was calculated from date of diagnosis to date of death or last follow-up. Event-free survival (EFS) was calculated from date of diagnosis to disease progression, initiation of 2 nd line therapy, or death from any cause. EFS and OS were evaluated using Cox model and Kaplan-Meier estimator. Log-rank test was used to test the significance of difference between groups. Results LEO-MER enrolled 1132 PTCL patients during the study period (462 MER and 670 LEO). Of these, 722 were sPTCLs (281 MER and 441 LEO), including PTCL-NOS (N=253, 35%), anaplastic large cell lymphoma (ALCL; N=180, 24.9% [74 ALK+, 106 ALK-]), angioimmunoblastic T-cell lymphoma (AITL, N=164, 22.7%), extranodal NK-TCL (N=50, 6.9%), adult T-cell leukemia/lymphoma (N=33, 4.6%), enteropathy-associated TCL (N=19, 2.6%), and hepatosplenic TCL (N=13, 1.8%) ( Table 1). Median age at diagnosis was 60 years. M:F ratio was 1.5. Comparing LEO to MER, African American population was 15.4% vs 0.7%, and Hispanic was 10% vs 2.2%. Clinical characteristics were comparable between MER and LEO overall: PS≥2, 20.9%; elevated LDH, 50.7%; stage III-IV, 67.6%; and IPI 2-5, 65.7%. The most common 1 st line chemotherapy regimens overall were CHOP-based (N=506, 70%), including 60% receiving CHOP-like chemotherapy in both MER and LEO cohorts (CHOP [N=268, 37%], CHOEP [N=91, 13%] or EPOCH [N=75, 10%]), and 16% with CHOP-like in combination with novel agents in LEO cohort (BV+ [N=41, 9.3%], azacitidine+ [N=11, 2.5%], pralatrexate+ [N=10, 2.3%], lenalidomide+ [N=8, 1.9%]) ( Table 1). More patients received etoposide in LEO (40.3%) than in MER (20.3%). 74 patients (10.3%) underwent consolidative SCT following induction chemotherapy (71 auto and 3 allo). 65 patients (11.2%) received frontline therapy on clinical trials. At a median follow-up of 9.4 years in MER and 4 years in LEO, 177 (MER) and 269 (LEO) events, and 150 (MER) and 206 (LEO) deaths were observed, respectively. The 3-year EFS and 4-year OS estimates for sPTCL were 46.3% and 59.1% in MER, and 40.4% and 51.3% in LEO. EFS and OS correlated with IPI scores and differed by sPTCL subtypes ( Figure 1). ALCL had superior survival, with 3-year EFS and 4-year OS of 78.2% and 90.5% for ALK+, and 65.9% and 76.9% for ALK-. Non-ALCL subtypes including PTCL-NOS and AITL had inferior outcomes, with 3-year EFS and 4-year OS of 31.4% and 42.8% for PTCL-NOS, and 33.4% and 50.7% for AITL. In subset analysis, the addition of etoposide to CHOP chemotherapy as either CHOEP or EPOCH was associated with improved OS for ALK- ALCL (p=0.038, log-rank), but not for ALK+ ALCL (p=0.75) or non-ALCL subtypes of PTCL-NOS and AITL (p=0.88). Conclusion The LEO-MER study is the largest prospective cohort study of PTCL to date. Patterns of care in the LEO cohort begin to incorporate novel agents in frontline therapy. Outcomes continue to mature with longitudinal follow-up and ongoing accrual, which poise to shape benchmarks in the contemporary era. The lack of benefit of etoposide adding to CHOP induction and poor overall survival of non-ALCL subtypes underscores the unmet need of therapeutic breakthrough for non-ALCL frontline treatment, particularly through clinical trials with biomarker-guided approaches incorporating novel agents.

Background The therapeutic landscape of mantle cell lymphoma (MCL) has evolved significantly since the early 2000s. We previously reported that a shift in frontline immunochemotherapy choices from 2002−2009 to 2010−2015 was associated with improved event-free survival and overall survival (OS) in both younger (age ≤65) and older (age >65) patients in a prospective Mayo Clinic/University of Iowa cohort (Castellino, Blood Advances, 2022). In addition, we recently reported that changes in treatment for relapsed/refractory (R/R) disease over the last two decades were associated with steady improvements in OS for R/R MCL (Tawfiq, ASH, 2022). In this study, we utilized data from the National Cancer Database (NCDB) to investigate the impact of therapy in the modern era on survival outcomes of patients with MCL in the US since 2004. Methods The NCDB is an outcomes database of more than 1,500 hospital-based cancer registries covering approximately 70% of newly diagnosed cancers in the US. The latest version of NCDB was used to identify patients with newly diagnosed MCL from 2004 to 2020. Three treatment eras were defined as Era 1 (2004−2009), Era 2 (2010−2014), and Era 3 (2015−2020), based on immunochemotherapy changes (from Era 1 to Era 2) and increased access to novel agents such as Bruton's tyrosine kinase (BTK) inhibitors (from Era 2 to Era 3). Overall survival between different eras was stratified and analyzed based on 3 age groups: <65, 65−79, and ≥80 years. Survival analysis was performed using the Kaplan-Meier method and all Cox proportional hazards models were adjusted for age and sex. Results A total of 32,746 patients with newly diagnosed MCL was identified, 12,847 (39.2%) patients were age <65, 14,297 (43.7%) age 65−79, and 5,602 (17.1%) age ≥80. For every age group, the distributions in sex, stage, Charlson-Deyo score, and treatment facility type (academic vs non-academic) were largely similar between eras. As expected, the median OS was significantly worse for patients age ≥80 years (19.8 months) compared to patients age 65-79 years (60.9 months) and patients age <65 years (143.9 months; p <0.001). In patients age <65 years, OS in Era 2 was improved when compared to Era 1, with a 5-year OS rate of 72.1% vs 67.6% (logrank p<0.001) (Figure 1) and an age- and sex-adjusted hazard ratio (HR) of 0.83 (95% CI 0.78−0.89, p<0.001). OS in Era 3 was similar to that in Era 2, with a 5-year OS rate of 72.2% vs 72.1% (logrank p=0.61) and an age- and sex-adjusted HR of 0.97 (95% CI 0.89−1.06, p=0.51). In patients age 65-79 years, similar trends in OS changes between eras were observed. The 5-year OS rate in Era 1, Era 2, and Era 3 was 43.3%, 52.8%, and 54.9%, respectively (p<0.001 comparing Era 2 vs Era 1, and p=0.05 comparing Era 3 vs Era 2). Age- and sex-adjusted HR was 0.83 (95% CI 0.78−0.87, p<0.001) comparing Era 2 vs Era 1 and 0.95 (95% CI 0.89−1.01, p=0.07) comparing Era 3 vs Era 2. In patients age ≥80 years, the improvement in OS from Era 1 to Era 2 was less prominent than other age groups. The 5-year OS rate was 22.9% vs 19.5% (p=0.03), and age- and sex-adjusted HR was 0.88 (95% CI 0.81−0.94, p<0.001). OS in Era 3 vs Era 2 was similar, with a 5-year OS rate of 23.1% vs 22.9% (logrank p=0.79) and an age- and sex-adjusted HR of 0.98 (95% CI 0.91−1.06, p=0.67). Conclusions This large NCDB study demonstrated that survival of patients with newly diagnosed MCL has improved over the last two decades. The results are consistent with our Mayo Clinic/University of Iowa prospective cohort study and confirm an improved OS after 2010, which was most likely driven by both frontline immunochemotherapy changes and better access to novel agents for R/R disease. The 5-year OS in patients diagnosed in 2015−2020 did not appear to be superior to those in 2010−2014, despite presumably having better access to novel agents such as BTK inhibitors in the R/R setting. This lack of a difference in OS may be partially due to short follow-up, but may also suggest that further improvement in frontline therapies by incorporating novel agents may be required to improve OS. The OS of patients age ≥80 years is limited and has only minimally improved after 2010, highlighting a significant unmet need for therapies with improved tolerability and efficacy in this age group.

Background: Marginal Zone Lymphoma (MZL) is considered indolent but incurable, with a variety of initial treatment strategies including observation. Quality of life (QOL) can be affected by disease burden, side effects of treatment, and psychosocial effects of living with an incurable cancer. However, little is known about long-term QOL in patients with MZL. We investigated QOL at baseline (BL), and up to nine years after a diagnosis of MZL. Methods: Newly diagnosed MZL patients aged 18 years and older were prospectively enrolled within 9 months of diagnosis in the Iowa/Mayo Clinic Molecular Epidemiology Resource from 9/2002 - 6/2015. Pathology was reviewed by a hematopathologist. All MZL participants with both BL and at least one follow-up (FU) QOL questionnaire were eligible for this analysis. QOL was measured at BL and years 1-, 2-, 3-, 6- and 9-year FU with the Functional Assessment of Cancer Therapy-General (FACT-G) scale (range 0-108), which measures 4 QOL domains (range): physical (0-28), social/family (0-28), emotional (0-24), and functional (0-28) well-being (WB). Clinical data were abstracted according to a standard protocol and patients were systematically followed for events (progression, re-treatment, and death). Patients were grouped into initial management with active surveillance (observation), local/antibiotic therapy (including radiation, surgery, and anti- H. pylori therapy), or systemic therapy (including chemotherapy, targeted agents, or antibody therapy). Change in QOL scores over time was analyzed using mixed models for repeated measurements, and comparisons were made according to initial treatment group. Results: Of 324 participants in the analysis, 59% were female, 98% were White and the median age was 63 years. For initial management, 36% (N=118) were observed, 30% (N=96) received local/antibiotic therapy and 34% (N=110) received systemic therapy. Across the initial treatment groups, there were no statistically significant differences by age, gender, or performance status, while there were differences for Ann Arbor Stage IV (observation 50%, local/antibiotic 27%, systemic 67%, p<0.001) and MALT-IPI score 2+ (observation 23%, local/antibiotic 18%, systemic 28%, p<0.001). At BL, mean FACT-G total score was 85.7 (SD 13.1), and physical, social/family, emotional, and functional WB scores were 20.3 (SD 4.2), 24.4 (SD 3.9), 18.9 (SD 3.5), 22.1 (SD 5.3); these scores were similar across initial treatment groups (all p>0.05). FACT-G total score was largely stable over time by treatment group (Panel 1). However, it declined at years 6 (mean -4.0, p<0.05) and 9 (mean -3.7, p<0.05) in the observation group (Panel 2), driven by a decline in functional WB, although this change was not significantly different from the other treatment groups. Further, in comparison with other treatment groups, local therapy was associated with a short-term 1-year improvement of FACT-G total score (mean +2.8, p=0.04), driven by improvements in both functional and emotional WB. For the subscales, we identified two major trends irrespective of treatment group: an overall improvement from BL of emotional WB at years 1 (mean +0.6, p<0.05), 2 (mean +0.7, p<0.05), 3 (+1.3, p<0.05), 6 (+1, p<0.05), and 9 (+1.3, p<0.05) and an overall decline of social/family WB at years 1 (mean -1.1, p<0.05), 2 (mean -1.7, p<0.05), 3 (-2.1, p<0.05), 6 (-2.7, p<0.05), and 9 (-2.2, p<0.05). There was no notable change from BL for physical or functional WB. Conclusions: This analysis is the first to provide prospective real-world QOL data on a longitudinal cohort of MZL patients with long follow-up. At BL, initial treatment was associated with stage and MALT-IPI score, but not QOL. Except for the transient 1-year QOL improvement in patients under local/antibiotic therapy, initial treatment groups had no impact on QOL over time. Irrespective of treatment group, emotional WB showed improvement over time, suggesting psychosocial adaptation by the patient, as it was found in aggressive lymphomas (Thompson et al., 2018). Further, emotional WB over time did not vary across treatment groups, suggesting that being initially observed did not lead to more emotional stress than being actively treated. Finally, decline in social/family WB (support from friends, family, family acceptance of illness, family communication, close to partner) suggests a need to consider interventions to patients and families to address these needs.

Background: Recently, large B-cell lymphomas (LBCLs) have undergone major shifts in classification and treatment paradigm, particularly with the advent of CD19-targeted chimeric antigen receptor T cell therapy (CAR-T). Initially approved as third-line treatment in LBCL in 2017, as of early 2022 CAR-T is indicated for second-line therapy (2L) in patients with relapsed or refractory (R/R) disease within 12 months of frontline treatment or who are not candidates for autologous stem cell transplant (ASCT). Given this quickly changing landscape, we aimed to describe disease characteristics, patterns of care, and survival outcomes in patients with R/R LBCL receiving two or more lines of systemic therapy across modern treatment eras. Methods: We developed a database of patients with R/R LBCL from 8 U.S. academic centers in the Lymphoma Epidemiology of Outcomes (LEO) Cohort study (NCT02736357) and Consortium for Real World Evidence (CReWE). Unlike the SCHOLAR-1 dataset (M Crump et al, Blood 2017), our cohort included any patient receiving 2L, regardless of timing of progression/relapse. For this analysis, eligible patients were aged ≥18 years and received 2L between 2002-2022. Patients with histologic transformation, post-transplant lymphoproliferative disorder, primary CNS lymphoma, primary mediastinal B-cell lymphoma, Burkitt lymphoma, or plasmablastic lymphoma were excluded. Prognostic factors, therapy details (including intent for ASCT and/or CAR-T), and outcomes, including treatment response, event-free survival (EFS), and overall survival (OS), were abstracted for all lines of therapy. Treatment eras were defined as pre-CAR-T (2002-2010), CAR-T available via clinical trial (2011-2017), and post-FDA approval of CAR-T (2018-2022). Results: Of 1760 patients initiating 2L for R/R disease, 1523 were eligible for analysis. Median age at start of 2L was 62 (interquartile range [IQR] 53-70), and 65% were male; 11% were non-White, and 8% were Hispanic. High-grade subtypes comprised 16% of all cases. IPI was available for 1013 patients at time of 2L therapy, with 54% having IPI 3-5. Median time from diagnosis to 2L was 8.7 months (IQR 5.6-18.5), with 834 patients not having achieved complete response (CR) to 1L, 285 patients relapsing <12 months after 1L, and 404 patients relapsing ≥12 months after 1L. The median number of total lines of therapy received was 4 (range 2-18), with 586 and 347 receiving ASCT and CAR-T, respectively, at any line of treatment. At a median follow-up of 48 months from the start of 2L, 926 patients (61%) had died. Progressive lymphoma was the primary cause of death in 75% of deceased patients, with 8% of reported deaths due to therapy. 2L was received at an academic medical center in 83% cases, and 209 patients (14%) received 2L on a clinical trial. ASCT and/or CAR-T was planned at 2L for 989 patients (65%), of whom 463 ultimately received ASCT, 88 received CAR-T, and 21 received allogeneic transplant at 2L. 494 patients were not considered for ASCT or CAR-T at 2L, and 40 were unknown for ASCT/CAR-T intent. Breakdown by treatment era (n = 1518 with available treatment start date) is shown in the Table. Median EFS from start of 2L was 4.2 months (95% confidence interval [CI]: 3.8-4.8). Median OS from start of 2L was 18 months (95% CI: 17-22), and 2- and 5-year OS estimates were 46% (95% CI: 44-49%) and 35% (95% CI: 33-38%), respectively. EFS and OS improved significantly for patients initiating 2L between 2011-2017 compared to 2002-2010. However, EFS and OS in the 2018-2022 era remained similar to 2011-2017 (Figure). Conclusions: To our knowledge, this study is the first-ever large-scale attempt to describe patterns of care and outcomes in LBCL 2L in the modern era, inclusive of all treatment approaches. The rich and unique LEO CReWE dataset captures evolving practice approaches over time in terms of both intent for and receipt of cellular therapies. Likely reflecting the rapid development of many novel immune effector cell products and bispecific antibodies, we observed increased enrollment on 2L clinical trials in the 2018-2022 period, including a substantial proportion of patients receiving CAR-T in 2L. Importantly, survival increased in treatment eras during which CAR-T was available. Ongoing analyses of factors associated with improved survival will be presented at the meeting.

Background: We previously reported thatearly events in follicular lymphoma (FL), defined as progression of disease within 24 months (POD24) or early transformation to a more aggressive histology, are significantly associated with increased risk of lymphoma related death. To refine clinical management, the FLIPI24 prognostic model was developed to predict the risk of early events after starting immunochemotherapy (IC) (Maurer et al, 2022). The FLIPI24 model was found to be significantly superior to standard clinical models for prediction of both event-free survival at 24 months (EFS24) and overall survival (OS) in internal and external validation sets of patients receiving IC. We sought to evaluate the prognostic ability of the FLIPI24 model in patients with FL not receiving IC. Methods: The cohort consists of prospectively enrolled patients in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) and the multicenter Lymphoma Epidemiology of Outcomes (LEO) Cohorts. Data were collected from medical records by standard protocol with all events verified by medical record review. Eligible patients were those diagnosed with grades 1-3A FL and initiated observation, rituximab monotherapy, radiation, or other non-IC therapy. The FLIPI24 model utilizes 5 continuous variables: age (linear 60-90 years with inflection at age 75), HGB (linear 8-17 g/dL), WBC (linear 4-11x10 9/L), LDH/ULN (linear 0.5-5), and B2M (linear 1-10 mg/L). FLIPI24 risk is grouped as follows: low risk (≤10%], low-average risk (10-15%], average risk (15-20%], high risk (20-40%], very high risk (>40%) for an early event. EFS was defined as time from diagnosis to progression, relapse, (re)treatment, histologic transformation, or death due to any cause. OS was defined as the time from diagnosis until death from any cause. Cox models and Kaplan Meier curves were used to evaluate association between FLIPI24 and EFS or OS. Results: 1542 patients initiating non-IC management approaches at diagnosis from 2002-2020 were identified. 51% were >60 years (IQR 52-70), and 49% were male. Most patients (86%) had FL grade 1-2. 61% of patients met any criteria for high tumor burden per GELF, BLNI, or GITMO based on available variables. Treatment approaches were 833 observation (54%), 315 rituximab monotherapy (20%), 186 radiation (12%), and 208 other non-IC approaches (14%). At median follow-up of 58 months, EFS24 was 73.8% (95% CI: 71.6%, 76.1%), 5-year OS was 90.9% (95% CI: 89.3%, 92.5%) and 253 (16%) patients died. The FLIPI24 score identified poor outcomes among patients with high/very high-risk score (FLIPI24 >20%), with median EFS of 1.8 years (95% CI, 1.3, 3.28) and 5 year OS of 65.1% (95% CI: 55.9-75.8) (Figure 1). When evaluating patient subsets, for patients with high tumor burden (defined based on available variables) and high/very high-risk score, median EFS was 1.6 years and 5 year OS was 64.6% (95% CI: 54.9%-76.1%). Among patients with low tumor burden FL and high/very high-risk score, median EFS was 2.0 years (95% CI: 0.84-NA) and 5 year OS was 66.2% (95% CI: 42.4%-100%). Patients undergoing observation with high/very high-risk score similarly had shortened median EFS of 1.53 years (95% CI: 1.25-NA) and 5 year OS of 68.9% (95% CI: 56.4%-84.1%). The FLIPI24 had superior concordance for OS (c=0.726) compared to the FLIPI (c=0.646) when evaluated in patients not treated with IC. Results were comparable in the subsets of patients observed (c=0.706 vs 0.596) and receiving rituximab monotherapy (c=0.764 vs 0.721). Conclusion: The FLIPI24 model has been previously validated to provide an individual risk score at diagnosis for the likelihood of experiencing an event within 24 months from starting IC. Here we demonstrate that a high FLIPI24 score predicts for poorer outcomes following non-IC strategies including observation, treatment with radiation, and rituximab monotherapy. The FLIPI24 has better prognostic performance for OS than FLIPI in this non-IC population. High FLIPI24 in patients not treated with IC identifies a patient population who should be considered for IC and/or novel frontline therapies when feasible.

Introduction: Non-Follicular Low-Grade B-Cell Lymphomas (LGBCL) are a subset of lymphomas that share overlapping clinical and histologic features. While most cases of LGBCL have an indolent course, some experience aggressive disease with no definitive biomarkers to identify aggressive cases at diagnosis. Significant advances have been made in the molecular classification of other lymphomas, yet molecular profiling and identification of mechanisms driving aggressive disease in LGBCL remain an unmet need. We previously used a multi-omic approach to characterize the molecular and immune landscapes of LGBCL tumors and identified a transcriptomic signature associated with cell proliferation and inferior overall survival (OS) in two independent cohorts (HR 7.82; 95% CI 2.4-25.4; p < 0.001 & HR 10.07; 95% CI 2.00-50.61; p = 0.005) and cases that transformed to DLBCL (Hopper et al., 2023). Here, we identify the oncoprotein DEK as a novel transcriptional regulator of this signature and use a functional genomic approach to further interrogate the role of DEK in B-cell lymphoma. Methods: Tumors from 64 newly-diagnosed/untreated LGBCL cases enrolled in the University of Iowa/Mayo Clinic Molecular Epidemiology Resource were included in this study (SMZL = 48, NMZL = 6, LPL = 5, B-NOS = 3, EMZL = 2). Tumor RNA-seq and paired tumor-normal WES were used to assess DEK expression and identify copy number alterations (CNAs), respectively. DEK deficient (KO) cell line models were generated using CRIPSR/Cas9. DEK expression was assessed by western blot (WB) and immunofluorescence (IF) using standard techniques. Proliferation was assessed by MTT assay. Results: To identify transcriptional regulators of our previously identified signature, we used the tool MAGIC to mine publicly available ChIP-seq data and identified DEK, an oncoprotein associated with tumorigenesis and poor prognosis in several cancers, as a key regulator of genes in our signature (p = 0.008). RNA-seq indicated that high levels of DEK expression associated with inferior OS in LGBCL (HR 2.99; 95% CI 1.21-7.36; p = 0.02). Additionally, we identified DEK as a target of copy number gains/amps in LGBCL (7% of cases), which corresponded to significantly higher DEK expression (p = 0.04). The association of DEK with aggressive lymphoma was confirmed when we assessed its expression in public cell line RNA-seq data and observed the highest expression in lines derived from aggressive lymphomas, which we further validated at the protein level in a panel of B-cell lymphoma cell lines by WB and IF confocal microscopy. Additionally, we detected nuclear localization of DEK, consistent with its role as a transcriptional regulator. As a model of DEK overexpression for functional characterization, we used the SUDHL6 lymphoma cell line, which has an amplification of DEK at 6p22.3 and expresses high levels of DEK protein. Using CRISPR technology, we generated DEK deficient SUDHL6 and tested the impact of loss of DEK expression. DEK KO cells proliferated significantly slower than WT SUDHL6 cells in vitro (p < 0.0001)(Panel A), indicating DEK plays a role in regulating proliferative capacity in lymphoma. To identify mechanisms responsible for reduced proliferation in DEK KOs, we assessed baseline protein expression levels of apoptosis proteins in WT versus KO cells. We found near complete abrogation of anti-apoptotic protein Bcl-2 and reduction of Bcl-xL expression in DEK KO cells (Panel B). These results indicate DEK may contribute to tumor proliferative capacity by regulating susceptibility to apoptosis. Conclusion: DEK has been implicated in regulation of gene expression, but its precise role has remained elusive, with little known about its role in lymphoma. Using an integrative molecular and functional genomics approach, we identified DEK as a novel oncoprotein in LGBCL that is upregulated in cases with inferior clinical outcome and is regulated by copy number gains/amps. DEK plays a role in regulating tumor proliferative capacity by altering susceptibility to apoptosis through regulation of Bcl-2 and Bcl-xL. Collectively, this data suggests high-risk LGBCL tumors may enrich for cells with DEK overexpression or CNAs as a mechanism driving oncogene addiction, highlighting DEK, and its downstream targets, as potential therapeutic targets in a subset of high-risk LGBCL.

Background Diffuse large B cell lymphoma (DLBCL) is the most common aggressive lymphoid malignancy in adults. Though standard immunochemotherapy regimens can result in clinical remission and cure in a majority of patients, approximately 30% of patients are primary treatment resistant or eventually relapse (rrDLBCL), and their prognosis is very poor. Recent molecular classification by large scale genomic and transcriptomic profiling of newly diagnosed DLBCL tumors has resulted in a deeper understanding of disease drivers, however, the molecular heterogeneity of rrDLBCL is yet to be fully explored. Therefore, in this study, we used an unsupervised approach to better define transcriptional and genetic programs in rrDLBCL samples hypothesizing that molecular stratification within this high-risk group may lead to a better understanding of this disease, which remains an unmet need, and a more personalized therapeutic approach. Methods Data used in this study included RNA (n=143) and whole exome (n=126) sequencing data from available FFPE tumor samples at the time of a relapse (any line of treatment, r1-r10 relapse timepoints included in analysis, one per patient), consented to the Molecular Epidemiology Resource (n=61), banked in the Mayo Lymphoma Biobank (n=50), or consented to the CC-122-ST-001 clinical trial (n=32, NCT01421524). Unsupervised clustering was performed on protein coding gene expression values using the non-negative matrix factorization (NMF) approach. NMF was carried out by performing 200 runs on cluster sizes from 2 to 6. Cell of origin (COO) was determined using the method described by Reddy et al. The tumor microenvironment was analyzed using CIBERSORTx and Lymphoma Microenvironment Classification (LME). Genetic classification was done using LymphGen. Results In order to identify unique transcriptional programs in rrDLBCL, we implemented NMF and consensus clustering to define an ideal quantity of stable patient clusters. We identified 4 rrDLBCL patient clusters (rrC1-rrC4) as the most stable solution, based on consensus clustering selection criteria of iterative NMF runs. While relapse timepoint was not associated with individual clusters, we did observe significant differences in tumor characteristics between the clusters. COO classification found that rrC1 and rrC4 were enriched for GCB-DLBCL while rrC3 was enriched for ABC-DLBCL classification (P < .001). To explore the biologic programs in each cluster, we used pathFindR, which leverages protein-protein interaction networks to identify disease related pathways, rrC1 and rrC4 were defined by pathways involved in cell cycle and mismatch repair; oxidative phosphorylation in rrC2; and MAPK and NF-kB in rrC3. Next, LME classification was done to define patterns in the tumor microenvironment and we found a significant difference between groups (P < .001), with rrC2 and rrC4 tumors enriched for a depleted TME, while rrC1 and rrC3 had a more immune rich or inflammatory TME. This was supported by CIBERSORTx analysis identifying significant differences (P > .001) in abundance of CD8 T cells, memory CD4 T cells, and M1 macrophages between clusters, with rrC4 having the lowest abundance. We then explored genetic patterns in each cluster. Gene level mutation enrichment analysis showed BCL7A mutation exclusively in C4 (6/6, P = .03). The clusters were not associated with LymphGen classification. Lastly, our recently published high risk signature classification that is associated with early clinical failure and is characterized by metabolic dysregulation, a depleted TME, T53 alterations, and poor outcome, was significantly different between the groups (P = .03) with enrichment for high-risk cases in rrC4. In summary, we show for the first time that rrDLBCL patients can be classified into four gene expression clusters that are associated with distinct pathway, TME, and genetic programs. These clusters should now be tested to learn if they can help select patients for newer therapies for rrDLBCL such as CAR-T and bispecific antibodies.

Introduction: The treatment of chronic lymphocytic leukemia (CLL) has evolved over the past two decades, from finite duration chemoimmunotherapy (CIT) to an era of targeted agents such as Bruton Tyrosine Kinase (BTK) inhibitors, BCL2 inhibitors, and anti-CD20 monoclonal antibodies. Little is known about how initial management strategy (watch and wait [W&W] vs. treatment) at diagnosis impacts patient reported outcomes (PROs) in CLL survivors over time, particularly in light of therapeutic advances over the last decade. Methods: Newly diagnosed CLL patients were prospectively enrolled within 9 months of diagnosis in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER1) study between 9/1/02 and 6/30/15, and within 6 months of diagnosis in the MER Phase 2 (MER2) study between 7/1/15 and 5/1/20. PROs were measured using the Functional Assessment of Cancer Therapy-General scale (FACT-G), which generates Physical (PWB, range 0-28), Social/Family (SFWB, 0-28), Emotional (EWB, 0-24), and Functional Well-Being (FWB, 0-28) scores and a Total Score (0-108), with higher scores indicating better WB. In both cohorts, FACT-G was measured at enrollment and at years 1, 2, and 3 after diagnosis, while the timing of later assessments varied slightly by study (MER1: 6 yrs and 9 yrs; MER2: 5 years). We employed a generalized linear mixed model to evaluate change from baseline between groups with groups defined by each participant's initial management strategy (W&W vs. upfront systemic treatment). Initial management strategy was determined by the treating physician. The study was approved by the Mayo Clinic IRB. Results: A total of 722 patients were identified in MER1 and 256 patients in MER2. The median age at diagnosis was 63 years in MER1 and 66 years in MER2 (P<0.05); 66% were male in MER1 and 68% were male in MER2 (P>0.05). More patients initiated upfront systemic therapy in MER1 (n=380, 53%) than in MER2 (n=110, 43%). Other baseline clinical characteristics were similar between the cohorts ( Table 1). There was no statistical difference in the mean FACT-G total score at baseline between MER1 (85.0, SD 12.5) and MER2 (85.2, SD 12.7). In the MER1 cohort, statistically significant lower baseline QOL scores were observed in patients initiating upfront treatment compared to W&W on the FACT-G total score (P=0.002) as well as the PWB (P=0.01), EWB (P=0.03), and FWB (P=0.006) subscales. We also observed that over time, EWB and FWB scores were consistently lower amongst those treated upfront compared to W&W. Further, EWB scores steadily improved over time regardless of initial management ( Figure 1), whereas the FWB and PWB subscales were largely stable over time. Mean SFWB scores dropped amongst patients who received upfront therapy at 3 years, which then steadily improved through year 9 but did not recover back to baseline. SFWB scores were stable among W&W patients. In the MER2 cohort, no statistically significant differences in any of the baseline QOL scores were noted between the W&W vs. initial treatment groups. Despite this, we observed consistently lower mean EWB scores among patients who initiated upfront treatment compared to W&W pts over time. No other statistically significant differences in mean QOL scores over time were observed between groups. Similar to MER1, we did observe a drop in mean SFWB scores amongst patients initiating upfront therapy at 3 years of follow-up that remained decreased at year 5. Conclusion: This is the largest longitudinal study of CLL survivors that spanned over 18 years and two treatment eras. We demonstrated that in the novel treatment era, QOL metrics were similar between initial management strategies (W&W vs. treatment), suggesting that initial management had little to no impact on QOL at baseline or over time. In contrast, in the CIT era, we observed differences in QOL metrics at baseline between groups. In both treatment eras, patients with CLL who required upfront therapy demonstrated a decrease in SFWB from baseline at year 3 of follow-up, and the mean EWB scores were lowest at baseline regardless of initial management strategy (W&W vs. upfront treatment) or treatment era (CIT vs. novel agents), but steadily improved over time. These findings suggest opportunities for interventions to improve QOL in patients with CLL, and additional analyses are ongoing. Further follow-up in the era of novel agents is needed.

Background: The goal of clinical trial eligibility criteria is to identify a population of patients that have high risk disease or have unmet needs with standard of care therapy. Frontline trials of diffuse large B-cell lymphoma (DLBCL) include patients with International Prognostic Index (IPI) scores of 3-5 as a way to identify a high risk population. Trials typically include patients with IPI score=2, and sometimes IPI score=1, to expand the eligible patient population. However, broader patient populations must be balanced by the potential inclusion of low-risk patients with excellent outcomes to standard of care therapy, leading to potentially underpowered trials. IPI is a sum of dichotomous variables which makes implementation easy but can result in heterogeneity in outcomes within IPI scores. This heterogeneity may be caused by unequal prognostic information across IPI variables, loss of information within IPI variables due to the use of cutoffs, as well as information captured by variables that are not included in the IPI. In prior modeling of outcomes in DLBCL (Maurer et al, AJH 2016), we identified that: i) LDH has a strong prognostic ability beyond the upper limit of normal (ULN) and ii) bulky disease is an independent variable for prognosis. Here we evaluate if the presence of either of these two variables, easily captured at diagnosis within the current standard clinical work-up, can identify a high-risk subset of patients within the population of those with IPI scores of 1-2. Methods: Patients with newly diagnosed lymphoma were enrolled within 6 months of diagnosis in the LEO Cohort at 8 academic medical centers from 2015-2020 and prospectively followed. Inclusion criteria for this analysis was aggressive B-cell lymphoma typically included in frontline trials (e.g. DLBCL, high grade B-cell lymphoma, FL3B), IPI 1-5, frontline therapy with rituximab and anthracycline-based chemotherapy, stage II-IV disease and ages 18-80 years. Event-free survival (EFS) was defined as the time from diagnosis until progression, initiation of 2 nd line therapy, or death due to any cause; EFS was evaluated at 24 months (EFS24). Very high LDH was defined as LDH>1.3xULN based on prior modeling (Maurer et al, AJH 2016) and bulky disease was defined as maximum tumor diameter (MTD) of 7cm or greater. IPI 1 and 2 were first evaluated separately and then combined due to similar outcomes in patients with very high LDH and/or bulky disease. High risk IPI1-2 was defined as the presence of either bulky disease and/or very high LDH within an IPI score of 1-2. Confirmation was performed in a similar cohort of patients enrolled in the Iowa/Mayo SPORE Molecular Epidemiology Resource (MER) from 2002-2015; bulky disease was defined using a 10cm cutoff per availability in MER data collection forms. Results: 1560 patients from LEO were analyzed; median age was 64 years (IQR: 54-71), 42% were female and 83% had stage III/IV disease; subtype was DLBCL, NOS in 1335 (86%). IPI was 1-2 in 766 patients, 3 in 496 patients and 4-5 in 298 patients ( table). 391 (51%) with IPI1-2 had either bulky disease and/or very high LDH (high risk IPI1-2) and 375 had low-risk IPI1-2. EFS24 in high risk IPI1-2 (71.6%, 95% CI: 67.2-76.3) was significantly inferior to IPI1-2 without bulky disease or very high LDH (85.2, 95% CI: 81.7-88.9 logrank p=0.0035, figure) and similar to patients with IPI3 (70.7%, 95% CI: 66.8-74.9). Consistent results were observed in 1014 patients analyzed in the MER using a higher cutoff for bulky disease (10cm) due to data availability ( table). Patients with high risk IPI1-2 had significantly shorter diagnosis to treatment interval (DTI) in both the LEO (per-week OR=0.83, 95% CI: 0.77-0.88) and MER (per-week OR=0.77, 95% CI: 0.68-0.87) cohorts compared to low risk IPI1-2, both p<0.0001). In sensitivity analysis, LEO results were similar when performed in the subset of patients with DLBCL, NOS. Conclusion: The presence of either bulky disease and/or very high LDH at presentation identifies a high-risk subset of patients with IPI 1-2 that have similar outcomes to patients with IPI 3 disease. These simple criteria can be easily implemented within existing clinical trial diagnostic work-ups. Future trial designs in frontline aggressive B-cell lymphoma should include patients with IPI 3-5 and patients with IPI 1-2 with either bulky disease and/or very high LDH to better define a high-risk population of patients for clinical trial eligibility.