Witzig, Thomas E.

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: 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.

Background Limited stage (stage I−II) disease is an uncommon presentation of mantle cell lymphoma (MCL), and its optimal management remains controversial. A British Columbia study (Leitch, Ann Oncol, 2003) and a Surveillance, Epidemiology and End Results (SEER) study (Murthy, Clin Lymphoma Myeloma Leuk, 2014) suggested the importance of radiotherapy (RT). A National Cancer Database (NCDB) study in the pre-BTK inhibitor (BTKi) era showed that chemotherapy (Chemo) plus RT (Chemo+RT) improved overall survival (OS) compared to Chemo or RT alone (Gill, Int J Radiat Oncol Biol Phys, 2015). However, a retrospective International Lymphoma Radiation Oncology Group study (Dabaja, Ann Oncol, 2017) reported comparable OS with Chemo+RT vs Chemo or RT alone. The potential differences in OS with different frontline therapy modalities may be modified by subsequent therapies for relapsed or refractory (R/R) disease. In this study, we used the NCDB data to analyze frontline treatment patterns and outcomes of limited stage MCL in the pre-BTKi vs BTKi eras. Methods The NCDB was queried to identify patients with stage I−II MCL diagnosed in 2004−2020. Because the first BTKi ibrutinib was approved by the FDA for R/R MCL in November 2013, we defined 2004−2013 as pre-BTKi era and 2014−2020 as BTKi era. Frontline treatment modalities were categorized to RT alone, Chemo alone, or Chemo+RT. Survival analysis was performed using the Kaplan-Meier method and the Cox proportional hazards model. Results Among 32,746 patients with newly diagnosed MCL in 2004−2020, 3,836 (11.7%) presented with stage I−II disease, with 2,428 having treatment information available. For patients diagnosed in the pre-BTKi era (n = 2005), 195 (9.7%) received RT alone, 1472 (73.4%) received Chemo alone, and 338 (16.9%) received Chemo+RT. For patients diagnosed in the BTKi era (n = 423), 45 (10.6%) received RT alone, 320 (75.7%) received Chemo alone, and 58 (13.7%) received Chemo+RT. Patients in the RT alone group were older (P <0.001) and had more females (P <0.001), but there were no statistically significant differences in Charlson-Deyo score, international prognostic index, or treating facility type (academic vs non-academic). For patients with stage I disease, in the pre-BTKi era, patients treated with Chemo+RT (n = 182) had improved OS compared to those treated with RT alone (n = 141) or Chemo alone (n = 647), with a 5-year OS of 75.4% vs 71.8% vs 61.4% (P <0.001). Similar results were observed in the BTKi-era, with a 5-year OS of 83.6% vs 69.5% vs 62.9% (P <0.001) for patients treated with Chemo+RT (n = 31), RT alone (n = 30), or Chemo alone (n = 130), respectively. After adjusting for age and sex, Chemo+RT was associated with improved OS compared to Chemo alone (pre-BTKi era, HR = 0.59, 95% CI = 0.46−0.75, P <0.001; BTKi era, HR = 0.34, 95% CI = 0.14−0.79, P = 0.013), but not compared to RT alone (pre-BTKi era, HR = 0.62, 95% CI = 0.23−1.68, P = 0.343; BTKi era, HR = 0.77, 95% CI = 0.56−1.05, P = 0.10) (Figure 1A). For patients with stage II disease, in the pre-BTKi era, patients treated with Chemo+RT (n = 156) had improved OS compared to those treated with RT alone (n = 54) or Chemo alone (n = 825), with a 5-year OS of 70.0% vs 47.3% vs 58.4% (P <0.001). In the BTKi-era, patients treated with Chemo+RT (n = 27) or RT alone (n = 15) both had improved OS compared to those treated with Chemo alone (n = 190), with a 5-year OS of 77.2% vs 78.8% vs 61.9% (P = 0.004) . After adjusting for age and sex, Chemo+RT was associated with improved OS compared to Chemo alone in BTKi era only (pre-BTKi era, HR = 0.85, 95% CI = 0.67−1.07, P = 0.165; BTKi era, HR = 0.49, 95% CI = 0.25−0.95, P = 0.034), but not compared to RT alone (pre-BTKi era, HR = 0.78, 95% CI = 0.53−1.13, P = 0.185; BTKi era, HR = 0.97, 95% CI = 0.35−2.67, P = 0.952) (Figure 1B). Conclusions Treatment pattern for limited stage MCL has not changed significantly from the pre-BTKi era to the BTKi era, with approximately 15% of patients receiving Chemo+RT, 10% RT alone and 75% Chemo alone. In the BTKi era, Chemo+RT appeared to be associated with better OS compared to Chemo alone but not compared to RT alone. Interpretation of the results requires caution because (1) patient numbers are small in Chemo+RT and RT alone groups, (2) longer follow-up may be needed, and (3) selection of therapy was not random, eg, patients receiving Chemo alone may have had higher disease burden such as bulky disease and/or non-contiguous stage II involvement but these details are not available in NCDB.

Background: Clonal cytopenia(s) of undetermined significance ( CCUS) is defined as persistent cytopenias arising in the context of myeloid neoplasm ( MN)-associated somatic mutations ( MT) in hematopoietic stem cells. Patients ( PTs) with TET2MT CCUS have a high probability of progression to MN. To date, no FDA-approved therapies exist for CCUS, and PTs often have similar cytopenias/transfusion needs as those with myelodysplastic syndromes ( MDS). TET2 is an ascorbic acid (AA)-dependent dioxygenase that catalyzes the conversion of 5-methylcytosine ( 5mC) to 5-hydroxymethylcytosine ( 5hmC), providing rationale to study high-dose IV (HI)-AA in TET2MT CCUS. Here we report the final results of this pilot trial. Methods: This is an investigator-initiated, single-institutional, phase II trial assessing the safety and efficacy of HI-AA in PTs with TET2MT CCUS (NCT03418038). PTs≥ 18 years with ≥1 TET2MT with or without additional somatic MTs, without prior treatment, and with any of the following laboratory criteria: (1) hemoglobin ( Hb) ≤10g/dL, (2) absolute neutrophil count ( ANC) ≤1(10^9/L), (3) platelet count ( PLT)≤100 (10^9/L) were eligible. HI-AA (1g/kg, maximum 100g) was given 3 times weekly for 12 weeks. The primary endpoint was hematologic response rates determined by MDS IWG 2018 criteria at week 20. (Platzbecker Blood 2018) and reported as hematologic improvement ( HI)- erythropoietic ( HI-E), platelets ( HI-P), neutrophils ( HI-N). Secondary endpoints include safety and adverse events ( AEs), graded by NCI-CTCAE v4.03. Correlative studies include changes in TET2MT variant allele fraction ( VAF), in vitro colony formation and differentiation, global and sequence-specific DNA methylation/hydroxymethylation, and quantitative 5hmC estimated by IHC in bone marrow biopsy specimens. Results: Ten patients were enrolled, with a median age of 71.4 (range: 65, 79) years, 8 (80%) males. The median number of mutations was 3, with 9 (90%) having co-mutations. All PTs but one [-Y] had normal karyotype. Baseline Hb levels were normal in all but one who was red blood transfusion dependent. Five (50%) PTs were thrombocytopenic, and 5 (50%) PTs had ANC<1 (10^9/L). ( Table). HI-AA was well tolerated with the most common AEs being infusion-related polyuria (40%) and polydipsia (40%, 3 Grade 1, 1 Grade 2). One (10%) PT had constipation and headaches (both Grade 1), and 1 (10%) experienced dyspepsia. No treatment-related Grade 3 or 4 AEs' or deaths were reported. The median follow-up duration was 16.8 months (range: 9.4, 24.1). Overall, no PTs met the criteria for HI. There were no significant differences with regards to median Hb, PLT, and ANC values at baseline, week 20, and 1-year (median Hb: 13.3, 12.5, and 12.7 g/dL, p=0.93; PLT: 97 vs. 120 vs. 92.5X10^9/L, p>0.99, and ANC: 0.9 vs. 1.2 vs. 1.3X10^9/L, p=0.99). By CTCAE grading criteria for cytopenias, 3 (30%) PTs had an improvement in severity of cytopenias, while 2 had worsening. One (10%) PT had an improvement in PLT (baseline vs. week 20: 62 vs 192X10^9/L) but was morphologically deemed to meet criteria for CMML-1 at week 20. Four (40%) PTs met criteria for disease progression (PT_4, 7,8,10); CMML-1- 2 and MDS-2. The median time to progression was 5 months (95% CI: 4.9, unreached). Two PTs had mutational clonal evolution, with 1 (PT_8) acquiring a RUNX1 (VAF: 20%) and 1 (PT_9) acquiring 2 CBL mutations (both VAF:4%) at one-year follow-up. There were no significant differences regarding the clinical characteristics or the TET2 variants between PTs who had stable disease vs. progression. There were no significant differences in TET2 VAF at baseline, week 20, and 1-year (median: 39% vs. 43% vs. 42%, p=0.54). We profiled changes in 5-mC and 5-hmC (Ilumina EpicArray) in PTs pre- and post-IV AA treatment and did not observe global changes. However, we were able to highlight site-specific changes in differentially methylated regions, largely resulting in hypomethylation at enhancer sites and affecting actively transcribed states in PTs with an improvement in cytopenia(s) severity by CTACE criteria ( Figure). Conclusion: We report the final safety and efficacy analysis of HI-AA in PTs with TET2 MT CCUS. The trial data suggest that HI-AA is safe and well tolerated. Although there were no significant responses by IWG MDS criteria, alleviation in severity of cytopenias in a subset of PTs (n=3) along with correlative epigenetic changes in enhancer regions, needs further exploration.

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 Telomere biology disorders (TBDs) are multisystem diseases caused by accelerated telomere shortening that can present with bone marrow failure and pulmonary fibrosis, among other abnormalities. TBD diagnosis is considered when average blood telomere length (TL) measured by clinical flowFISH is <1 st percentile and/or a pathogenic variant in telomere maintenance genes (most commonly TERT, TERC, RTEL1) is identified. Pathogenic variants in genes coding for the telomerase protein ( TERT) and RNA component ( TERC) decrease telomerase activity. Similarly, variants in RTEL1 result in defective unwinding of the t-loop at telomere ends, increasing the levels of free t-circles in cells. Variants in these genes are often classified as variants of uncertain significance (VUSs by ACMG criteria) with additional efforts needed for variant curation. To address this, we describe results of functional testing performed in TBD patients with VUSs involving TERT, TERC, and RTEL1. METHODS TBD suspected patients were identified through the Pre-Myeloid Cancer and Bone Marrow Failure Clinic (Mayo Clinic) where they underwent clinical flowFISH and genetic testing for TBD related genes. Informed consent was obtained with approval from the Mayo Clinic Institutional Review Board. Viable peripheral blood and bone marrow samples were collected along with age matched healthy volunteers. Telomerase activity was measured in samples with TERT and TERC variants through telomeric repeat amplification protocol (TRAP) assays using the TRAPeze XL Telomerase Detection Kit (MilliporeSigma) following manufacturer instructions. HCT116 cells were used as positive controls while heat inactivated samples served as negative controls. Fluorescence was measured in a SpectraMax plate reader. Percentage of total product generated (TPG) relative to healthy age matched controls was calculated. T-circle detection assays were used on RTEL1 samples based on the protocol by Zhang et al. (2017). Final southern blotting was completed using the TeloTAGGG Telomere Length Assay Kit (Roche), and t-circle bands were visualized in a c600 GEL Imaging System (Azure Biosystems). RESULTS Ten patients (mean age = 53 years (27-71), 50% female) were included in our study. Patients 1 to 5 presented VUS in TERT (n=4) or TERC (n=1) and TL <1 st percentile in lymphocytes and/or granulocytes. Patient 6 carried a known pathogenic variant in RTEL1 and was included as a positive control. Patients 7 to 9 with RTEL1 variants presented TL close to the 10 th or between the 1 st-10 th percentile. No TL results were available for patient 10 but was tested due to the presence of a VUS in RTEL1 (Table 1). Similarly, while patient 7 carried a likely pathogenic variant, it was tested due to presenting lymphocyte TL between the 1 st-10 th percentile. TRAP results indicated decreased telomerase activity compared to age matched controls in all samples with TERT and TERC variants suggesting a pathogenic effect (52.%, 10.7%, 48.7%, 4.4% and 5.2% of TPG compared to age matched controls, respectively) (Table 1). On the other hand, t-circles were only seen in patient 6 (Figure 2). DISCUSSION We used TRAP and t-circle assays to explore the telomerase activity and presence of t-circles in patient samples with TERT/TERC and RTEL1 variants. In the case of TERT/TERC, we observed a reduction of telomerase activity in all samples. Together with blood TL below the 1 st percentile, this suggests that these variants are indeed deleterious (Table 1). However, since patient 4 presented two TERT VUSs, additional testing is needed to conclude how each variant impacts telomerase activity independently. In regard to RTEL1 variants, we observed t-circles in patient 6 as expected. No t-circles could be seen on all remaining samples, including patient 7 who carried a variant classified as likely pathogenic (Figure 1). This in-frame deletion has been described once in a TBD family (Cogan et al. 2015) but was not functionally tested. This result, together with the borderline TL seen in this patient, may suggest that some compensatory mechanism exists on this sample, or that the deleterious effect of the variant is not strong enough to be detected by our assay. Further studies are currently ongoing by our group to validate these results using a cell-based transfection disease model. In summary, we show that functional testing can be a helpful tool to determine pathogenicity of VUSs in TERT/TERC and RTEL1.

Introduction: Nanotechnology for cancer therapy aims to increase drug delivery to tumor sites while lowering toxicity. AR160 is a novel 160 nm nano-immunoconjugate consisting of commercial grade nab-paclitaxel (NP) nanoparticles non-covalently coated with rituximab (R) for targeted delivery into tissues expressing CD20. The drug delivery system and clinical grade product was developed in the laboratory of Svetomir N. Markovic, M.D.,Ph.D. Single agent rituximab at a dose of 375 mg/m 2 in relapsed patients with aggressive lymphomas is not utilized and has limited activity in patients with multiple relapses. Taxanes (Younes 1995, Wilson 1995) have modest clinical activity as a single agent with overall response rates of 23% and 17%, respectively, when administered at doses of 200 mg/m 2 and 140 mg/m 2 in previously treated patients with non-Hodgkin lymphoma (NHL). We hypothesized that utilizing the targeted ability of rituximab that the AR160 taxane nanoparticle would have activity in relapsed B-cell NHL and offer a new class of agents for relapsed B-cell NHL. Methods: A 3+3 phase I clinical trial was conducted in patients with relapsed refractory non-Hodgkin lymphoma to determine the maximum tolerated dose of AR160 administered intravenously on days 1, 8, and 15 of a 28-day cycle. Patients were required to have had prior systemic treatment with no other therapy with clinical benefit. Patients with aggressive lymphoma were required to have a stem cell transplant if transplant eligible. AR160 was prepared on-site in the Mayo Clinic Cancer Center Research Pharmacy, and the product was reconstituted by mixing the two agents delivering as one combined infusion at a specific concentration. The starting dose level (DL1) was NP at 100mg/m 2 with R at 40 mg/m 2. These doses were significantly lower than standard doses. Disease evaluations were conducted after every 2 treatment cycles using CT based criteria from the revised 2014 Lugano Classification or PET scans. Patients were treated until disease progression or intolerability. Samples were collected for pharmacokinetic (PK) studies. Results: Nine (7 males and 2 females) patients with a median age of 61 (range 55-84 years) were enrolled (2 follicular lymphoma (FL), 1 previously transformed from FL to diffuse large B-cell lymphoma (DLBCL) followed by FL relapse, 1 high-grade B-cell lymphoma with MYC and BCL2 rearrangements transformed from FL, 1 transformed FL to DLBCL, 2 high-grade B-cell lymphoma with MYC and BCL2 rearrangements, 1 high-grade B-cell lymphoma NOS and 1 mantle cell lymphoma. The median number of prior treatments was 4 (range 3-16). At dose level 1, all 3 of the first 3 patients experienced grade 3 or 4 neutropenia (C1D15, C4D1, and C1D15) with the C4D1 a grade 4 and unlikely related. After the first three patients, de-escalation to dose level -1 was implemented per protocol with NP at 75 mg/m 2 and rituximab at 30 mg/m 2. There was one patient with a grade 3 non-hematological adverse event all possibly related to treatment (anorexia, diarrhea, and enterocolitis). There were 6 partial responses (71%), 1 complete response (14%) with high-grade B-cell lymphoma with MYC and BCL2 rearrangement, 1 stable disease with mantle cell lymphoma and 1 patient had progressive disease. Six of the 9 patients were alive with subsequent therapies. PK evaluation is pending. Conclusion: AR160 therapy is a novel drug delivery system incorporating significantly lower doses of paclitaxel and rituximab that is safe and demonstrates promising clinical activity in patients with low-grade and high-grade previously treated B-cell lymphomas. This principle of treatment is applicable to other disorders. Further clinical testing is warranted in these patient populations.

Background: Understanding the symptoms and quality of life (QOL) over time of adults with follicular lymphoma (FL) is important for treatment decision-making and clinical management. However, there are limited population-level data on the long-term QOL of adults with FL. We aim to describe the real-world, long-term QOL of adults with newly diagnosed FL up to 5/6 years after diagnosis. Methods: We used the Mayo Clinic/Iowa Molecular Epidemiology Resource (MER) and the multi-institutional Lymphoma Epidemiology of Outcomes (LEO) to identify adults with grade 1-3A FL who completed QOL surveys at baseline and follow-up. Participants with lymphoma were prospectively enrolled within 9 months of diagnosis in the MER cohort from 2002-2015 and within 6 months of diagnosis in the multi-institutional LEO cohort study across 8 cancer centers from 2015-2020. The LEO/MER cohort studies systematically collected information on disease status, QOL, health behaviors, and functional assessment. Treatments, disease relapses, and deaths were verified by medical record review. Treating physicians determined clinical management. QOL was measured using the Functional Assessment of Cancer Therapy-General (FACT-G) at years 1, 2, 3, and 5/6 post-diagnosis. A higher FACT-G total score (range 0-108) indicated better QOL across 4 subscales (range): physical (0-28), social/family (0-28), emotional (0-24), and functional (0-28) well-being. We categorized participants based on their frontline management at time of diagnosis: “observation” (surveillance), “treatment” (systemic treatment with immunotherapy +/- chemotherapy), and “local” (radiation) groups. We employed a generalized linear mixed model to evaluate and compare the changes in QOL scores (as a continuous variable) from baseline for the observation, treatment, and local groups, adjusting for sex, race/ethnicity, age, FLIPI risk, and cohort (i.e., LEO or MER). We also evaluated QOL changes by FLIPI risk. Results: Our study included 1,544 participants with FL and QOL data. At the time of enrollment, median age was 61 years (range 19-91), 88% were non-Hispanic White, and 49% were female. Based on initial management, 529 (34%) were in the observation group, 880 (57%) were in the treatment group, and 135 (9%) were in the local group. FLIPI risk was high for 17% in the observation group, 29.3% in the treatment group, and 3% in the local group. The mean (standard deviation) baseline FACT-G total score was lowest in the treatment group with the following baseline scores: 86 (13) for the observation group, 83 (14) for the treatment group, and 88 (12) for the local group (Table 1). The observation and local groups reported a greater worsening of their baseline FACT-G total score vs the treatment group at both the 2-year (-1.2, -0.8 vs +1.8, respectively) and 5/6 year (-5.4, -6 vs. -1.6, respectively) timepoints (Figure 1). This appeared to be driven by worsened physical and functional well-being in the observation (-1.3, -2.2, respectively) and local (-0.9, -2.4, respectively) groups vs the treatment group (0, -0.3, respectively). These differences were statistically significant between the observation vs treatment groups. There were no statistically significant differences in the other subscales, i.e., social/family and emotional well-being, by frontline management. Social/family well-being decreased across all groups by 5/6 years (-2.3 in observation, -2.2 in treatment, and -3 in local, p<0.05). Regardless of FLIPI risk, the total FACT-G scores decreased within each FLIPI risk group at 5/6 years (-4.4 for low, -3.8 for intermediate, and -4.9 for high, p<0.05). This was primarily due to worsened social/family well-being (-2.4 for low, -2.2 for intermediate, and -3 for high, p<0.05) at 5/6 years. There was no statistically significant difference in QOL between FLIPI risk groups. Conclusion: This is one of the first and largest studies with real-world longitudinal QOL data for FL. Our study suggests that frontline systemic treatment initially improved QOL and resulted in a lower degree of QOL decline over time. Social/family well-being decreased over time regardless of frontline management or FLIPI risk. Further research is warranted to explore the impact of timing and specific systemic treatments on QOL, incorporate the patient/caregiver experience to address social/family well-being, and identify the clinical significance of our findings.

Background: Relapsed DLBCL occurs in up to 40% of patients and has a poor prognosis. Current prognostic tools such as the international prognostic index (IPI) and newer forms (NCCN-IPI) only include baseline clinical features. PET/CT features have not yet been incorporated into prognostic risk models despite being essential for staging and response assessment. Deep learning computer algorithms have consistently demonstrated the ability to analyze imaging data and identify features that are not readily apparent to the human eye. Using a deep learning computer vision model that automatically extracted radiomic features from PET/CTs, we examined the association of changes between baseline PET and interim PET (PET2) radiomic features on survival outcomes and compared the prognostic performance with NCCN-IPI. Methods: Adult patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL) between 2005 and 2015 and enrolled in the prospective MER cohort were included. Native DICOM images from FDG PET/CT scans at baseline and interim PET (PET2, after 2-3 cycles of chemotherapy) were preprocessed for regularity and then segmented using the nnU-Net architecture with an external lymphoma-specific model. Feature extraction and standard uptake value (SUV) characterization were accomplished with PyRadiomics and NiBabel. Our computational method included no manual segmentation correction. Individual radiomics features (n=115) and the % change above (Δ High) and below (Δ low) 50 th quartile from baseline to PET2 were evaluated for association with event free survival (EFS) and overall survival (OS) using a univariate Cox regression model and by Kaplan Meier analysis. EFS was defined as time from PET2 to first systemic relapse or death from any cause. OS was defined as time from PET2 to death from any cause. Additionally, Spearman and Pearson correlation matrices were used to guide feature selection while minimizing collinearity. We then assessed the association of the highest scoring radiomics features with EFS in a multivariate cox regression model. Results: A total of 506 patients had baseline and PET2 scans available for radiomic feature extraction. Median age at diagnosis was 61 years (range 18-90), 43% were females. NCCN-IPI composition and outcomes of our cohort was comparable to the previously published NCCN cohort, with patient distribution and 5-year OS as follows: Low (9%, 5-y OS 83%), Low-intermediate (38%, 5-y OS 49%), High-intermediate (41%, 5-y OS 31%), High (11%, 5-y OS 12%). At a median follow up of 81 months,there were 308 events, and272 patients had died.Several radiomics features were associated with EFS including change in tumor surface area (SA Δ) (HR: 1.75, 95% CI 1.36-2.24, p<0.005, median of 26,927 mm 2, Figure 1A) and change in total metabolic tumor volume (TMTV Δ) (HR: 1.64, 95% CI 1.27-2.10, p<0.005, median of 120,473 mm 3, Figure 1B). As a reference, NCCN-IPI univariate Cox regression analysis of EFS produced a Harrell's C-statistic (c) of 0.624. Single radiomics features of SA Δ and TMTV Δ individually produced unadjusted c-statistics of 0.616 and 0.614 respectively. Combinations of radiomics features (SA Δ, TMTV Δ and NCCN-IPI classification) demonstrated cumulative benefit (c=0.652). Conclusion: Automatic PET-CT radiomic feature extraction using deep learning models is feasible among patients with newly diagnosed DLBCL. The change in tumor SA and TMTV appear to be promising radiomic biomarkers. A low decline in either tumor SA or TMTV by PET2 is associated with higher risk of relapse and poor survival outcomes. As individual characteristics, these features are similar prognostic indicators of EFS as the NCCN-IPI. Further investigation into risk stratification when combining radiomics with clinical and genomic variables is warranted. Figure 1. Event free survival for DLBCL patients with A) a change in tumor surface area by PET2 less than 50% percentile (SA_Δ Low) and greater than 50 th percentile (SA_Δ High) and B) a change in TMTV by PET2 less than 50% percentile (TMTV_Δ Low) and greater than 50 th percentile (TMTV_Δ High).