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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: A subset of follicular lymphoma (FL) patients will experience a ‘high-risk defining event’ (HRDE) that portends poor survival due to early progression of disease or transformation to diffuse large B cell lymphoma (TFL). Progression of disease within 24 months (POD24) from front-line immunochemotherapy (ICT) identifies patients with a subsequent five-year OS of 50% compared to a reference group of 90% (Casulo et al. JCO 2015). Although a robust surrogate endpoint for OS in clinical trials (Casulo et al. Blood 2022), it remains to be established if the OS of patents is influenced by the nature of the HRDE. In this study, we examined whether characteristics and clinical trajectory of those with relapsed/progressive FL is the same as that of patients experiencing TFL. Methods: We conducted an international retrospective analysis of newly diagnosed FL patients requiring treatment across 14 academic centres between 2002 and 2021 in the era of rituximab and PET-CT staging. Patients were included with grade 1-3A FL requiring first-line (1L) treatment (ICT, rituximab monotherapy or radiotherapy). We excluded patients with untreated FL, de novo TFL and those with <24 months follow up provided they did not experience a HRDE. Baseline clinical, imaging and laboratory values, treatment details and outcomes were collected. We defined HRDE groups as persistent (relapse or progression) FL within 24 months of 1L treatment (FL24), early TFL (<24 months of 1L treatment) or late TFL (>24 months of 1L treatment). Patients not experiencing a HRDE formed the FL reference group. Landmark overall survival (OS) analysis was performed by Cox regression using risk status as a time-varying covariate for time of HRDE. For the FL reference group, landmark was defined at 24 months after 1L treatment. Results: 501 patients met the inclusion criteria and were categorised as: reference FL (n=378), FL24 (n=50), early TFL (n=28), late TFL (n=15). 24 patients who died within 24 months of 1L treatment without documentation of preceding HRDE and were omitted. Median follow up for patients alive beyond 24 months was 5.1 years. Median age at diagnosis was 60 years, 91% had ECOG performance status 0-1 and 38% were high-risk (>3) FLIPI. 1L chemotherapy regimens included: bendamustine (59%), CHOP (24%), CVP (8%), other (9%); a majority received rituximab (80%) vs obinutuzumab (20%). Maintenance therapy was used in 54% of pts. Expectedly, those experiencing HRDE had an inferior OS compared to the reference group (HR 5.23, p<0.001)(Figure 1). However, among HRDE group, median OS significantly differed: early TFL patients (3.0 yrs) and FL24 (12.6yrs)(HR 2.27, p=0.02) (Table 1). There was no difference in OS after HRDE between early TFL and late TFL ( p=0.81). Biopsy was performed in 84% of TFL cases with no difference in OS between biopsy-proven vs clinically suspected cases ( p=0.23). Multivariate OS analysis assessing HRDE and treatment demonstrated no significant interaction between HRDE group and 1L chemotherapy ( p=0.52), monoclonal antibody ( p=0.29) or maintenance therapy ( p=0.27). Several established prognostic features at baseline were enriched in patients who went on to experience HRDE including: ECOG >1 ( p<0.001), raised LDH ( p<0.001), advanced-stage disease (( p<0.011) and high risk FLIPI ( p=0.005). Baseline FDG-PET was available in 259 patients. Adverse PET metrics were enriched in only early TFL, and not FL24 or late TFL patients, including high SUV max( p=0.009), total metabolic tumor volume ( p=0.015) and total lesional glycolysis ( p=0.01). Conclusions: HRDEs after 1L treatment are associated with inferior OS in FL compared with standard-risk patients. Unlike POD24, this study demonstrates disparate clinical outcomes between patients experiencing early progression with persistent FL and those experiencing TFL. Adverse metabolic characteristics on baseline FDG-PET also suggest biological distinction between HRDE subsets. These findings have important implications for epidemiological studies, biomarker development and clinical trials aiming to improve outcomes in this underserved high-risk FL cohort.

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.

Background: Emavusertib (CA-4948) is a novel oral inhibitor of interleukin-1 receptor-associated kinase 4 (IRAK4), which is essential for toll-like receptor (TLR) and interleukin-1 receptor (IL-1R) signaling in B cell proliferation. Additional inhibitory activity against FMS-like tyrosine kinase 3 (FLT3) and CDC-like kinases (CLK1/2/4) is also present in emavusertib. IRAK4 forms a Myddosome complex with MYD88 adaptor protein and drives overactivation ofnuclear factor-kappa B (NF-κB), causing inflammation and tumor growth. Emavusertib has been reported to be well tolerated and active as monotherapy in heavily pretreated patients with relapsed/refractory (R/R) non-Hodgkin lymphoma (NHL) (Nowakowski 2020). Preclinical studies demonstrated that tumor resistance and survival via IRAK4 activation could be delayed or reversed. Emavusertib crossed the blood-brain barrier in a murine PDX model of PCNS lymphoma, blocked the activated IRAK4 pathway, and induced tumor response and prolonged survival (von Roemeling 2022). In combination with Bruton tyrosine kinase (BTK) inhibitors, emavusertib showed in vitro synergy and re-sensitization of resistant cell lines, overcoming BTK resistance (Guidetti 2023a and 2023b). In vivo synergy in B-cell NHL was also demonstrated. Adaptive chemotherapy treatment resistance through IRAK4 upregulation and activation was also described in other disease models (Melgar 2019, Li 2019). This abstract presents preliminary efficacy and safety data of emavusertib + ibrutinib in R/R NHL patients. Aim:Assessment of safety and clinical activity of emavusertib in combination with ibrutinib. Methods: This is an ongoing open-label trial (NCT03328078) of emavusertib as monotherapy and in combination with ibrutinib. Part A1 - completed; dose escalation of emavusertib as monotherapy; the recommended phase 2 dose (RP2D) is 300 mg BID with continuous oral dosing (Nowakowski 2020). Part A2 - completed; dose escalation of emavusertib in combination with ibrutinib at 420 and 560 mg QD (Joffe 2022). Part B - ongoing; an expansion cohort of PCNSL patients with resistance to prior BTK inhibitors for additional safety and efficacy related to exposure: emavusertib at 100 or 200 mg BID + ibrutinib at 560 mg QD in 28-Day cycles. Results:As of 19 July 2023, 18 heavily pretreated NHL (including five PCNSL) patients received emavusertib at 100, 200, or 300 mg BID in combination with full ibrutinib doses per label. Median age was 63.5 years (range 50-92). Median number of prior lines of anti-cancer therapies was 3 (range 1-10). Eleven of 18 patients failed prior BTK inhibitors. Median treatment duration was 95.5 days (21-587 days), suggesting acceptable safety and tolerability. No DLTs were observed at the 200 mg BID dose level, and two reversible DLTs (stomatitis and syncope) were observed at the 300 mg BID dose level. The preliminary efficacy data of 16 evaluable patients in combination with ibrutinib showed 5 CRs (2 MCL, 3 PCNSL) and 1 PR (1 CLL). All 3 PCNSL patients with CR were previously treated with BTK inhibitors. Conclusion: The combination ofemavusertib plus ibrutinib (ema+ibr) is well tolerated with an acceptable long-term safety profile and promising efficacy, showing several objective responses in heavily pretreated and/or BTK inhibitor resistant patients. Emavusertib may have the potential to overcome BTK inhibitor resistance and the combination of ema+ibr has the potential to show increased anti-cancer activity compared to ibrutinib monotherapy.

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.

Introduction The treatment of Erdheim-Chester disease (ECD) has been revolutionized by the discovery of MAPK/ERK pathway mutations, most common being BRAF-V600E (50%). The US-FDA approved single-agent vemurafenib for BRAF-V600-mutated ECD in 2017 based on a phase II trial that included 22 patients with ECD and 4 with Langerhans cell histiocytosis (LCH), resulting in 100% overall response rate (ORR) by FDG-PET criteria (Diamond et al. JAMA Onc 2018). However, adverse events (AEs) to vemurafenib led to treatment interruption and/or dose modification in all patients, and drug discontinuation in 8 (31%) patients. Long-term outcomes and tolerability of BRAF-inhibitor (BRAFi) monotherapy in real world setting are unknown. In this study, we aimed to address these questions utilizing a large cohort of patients with ECD. Methods Registry-based ( NCT03329274) study of patients with ECD who received BRAFi (vemurafenib or dabrafenib) as any line of treatment. The registry captures detailed longitudinal clinical, treatment, and outcomes data through medical record abstraction. For this study, we focused on the events of discontinuation, dose reductions, and AEs to BRAFi therapy. Time-to-event analyses were conducted using Kaplan-Meier method from the date of initiation of BRAFi. Primary endpoint of the study was event-free survival (EFS), defined as time to progression of disease, discontinuation or alteration of therapy due to any cause (including addition of a MEK inhibitor), or death. Secondary endpoints included progression-free survival (PFS), defined as time to progression of disease or death, and overall survival (OS). Results We included 64 patients with ECD (including 7 with mixed ECD/LCH) in this study. Median age at diagnosis was 56y (range, 26-77) and at initiation of BRAFi was 57y (range, 26-77). Of these, 59 (92%) were BRAF-V600E, 2 (3.1%) were BRAF-wildtype, 1 had BRAF-V471F, 1 had BRAF-PICALM fusion, and 1 had unknown BRAF status. The distribution of organ involvement was bone (91%), neurologic (78%), brain parenchyma (62%), cardiovascular (58%), retroperitoneum (58%), skin (25%), and pulmonary (19%). BRAFi therapy was used as first-line in 38 (59.3%) and as subsequent line in the rest (median 1, range 1-7). The most common initial BRAFi used was vemurafenib (80%) followed by dabrafenib (20%). The median starting dose of vemurafenib was 720 mg bid (range 480-960) and end dose was 480mg bid (range, 240-480). The median start dose of dabrafenib was 100mg bid (range 50-150) and end dose was 50mg bid (range 50-100). Initial dose reduction of BRAFi was required due to AEs in 28 of 52 cases (54%) with final dose data available, encompassing cutaneous (43%), generalized symptoms or fatigue (18%), >1 system affected (14%), lab abnormalities (11%), musculoskeletal (7%), and other (7%) toxicities. Of 60 patients with response data, a response was seen in 51 patients or 85% (42 partial response, 9 complete response, 8 stable disease, and 1 progressive disease). The median follow-up duration was 3.9 years (range 0.2-8.8). Single-agent BRAFi therapy was discontinued in 38 (59%) patients who received it initially (vemurafenib 63% vs. dabrafenib 46%, p=0.28). Reasons for discontinuation included AEs (n=20, 53%), addition of MEK-inhibitor (18%) for reducing cutaneous toxicities (n=5) or augment CNS response (n=2), disease progression (n=4, 11%), death (n=3, 8%), or others (n=4, 11%). 17 patients were rechallenged with a BRAFi after initial discontinuation, and 6 (35%) discontinued it again. The median EFS for the entire cohort from first BRAFi treatment was 2.99y (95% CI 1.6-4.8) and from second BRAFi was 2.82y (95% CI 1.19- not reached). The median PFS and OS were not reached, and 4 patients died at last follow-up (3 from ECD). Conclusions Almost 5 years after the FDA approval of vemurafenib for ECD, our real-world study from long-term follow-up of a large cohort of patients highlights high response rates, but at the cost of adverse events leading to dose reductions and treatment discontinuation in a large subset. Our results also highlight the entity of disease progression on BRAFi therapy. Our results underscore the importance of developing therapies that are efficacious and well-tolerated in this incurable disease.

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).

Purpose The predominant pattern of relapse for patients with B-cell non-Hodgkin lymphoma (NHL) who undergo anti-CD19 Chimeric Antigen Receptor T-cell Therapy (CART) involves sites previously involved by NHL. Bridging radiotherapy (BRT) has shown to be an effective bridging treatment with excellent local control rates. Our previous work defined limited/oligometastatic lymphoma as disease involving <5 sites. This study is the first to report on the role of BRT for patients with limited (<5 involved sites) disease prior to CART. Methods Following Institutional Review Board approval, a retrospective review from 2018 to 2023 across 3 Mayo Clinic sites (Arizona, Florida, and Minnesota) was performed and identified 139 patients with relapsed/refractory (r/r) B-cell NHL without bone marrow involvement who received CART and had <5 disease sites prior to leukapheresis. Ann Arbor staging was used to define the number of involved disease sites. An involved disease site included the Ann Arbor anatomical lymph node region(s) harboring the pathological lymph node(s) or any extranodal lesion. Bridging treatment (radiation and/or systemic therapy) was defined as treatment administered between leukapheresis and CART infusion. The primary endpoint was event-free survival (EFS),defined from CART infusion to any disease progression or initiation of post-CART consolidative/salvage therapy. Secondary endpoints included progression -free survival (PFS),defined from CART infusion to any disease progression, and overall survival (OS), defined from CART infusion to death. Results Prior to CART infusion, 44 (32%) patients received BRT and 95 (68%) did not. Bridging systemic therapy was given to 5 (11%) and 34 (36%) patients in the BRT and no BRT groups, respectively (p=0.003). The median number of involved disease sites prior to leukapheresis was 2 (range: 1-4). There was no significant difference in the baseline characteristics prior to CART infusion between the BRT and no BRT groups, except for extranodal involvement that was more common in the BRT group (Table 1). The median equivalent 2 Gy dose was 27 Gy (Interquartile range 23-34), and the most common BRT regimen was 20 Gy in 5 fractions. Among the 44 BRT patients, 34 received radiation to all visible PET-avid disease sites, and 10 received radiation to some but not all disease sites. The median follow-up was 20 months. The rate of grade ≥2 cytokine release syndrome was 41% in both groups (p=0.99). The rate of grade ≥2 immune effector cell-associated neurotoxicity syndrome was 21% and 37% in the BRT and no BRT groups, respectively (p=0.059). There were no observed grade ≥3 BRT-related toxicities. Objective response rate by PET 5 point scale was higher in the BRT group (93% versus 79%; p=0.036). Crude rates of progression were 30% in BRT and 55% in no BRT patients, with 9/13 (69%) and 43/52 (83%) patients relapsing in pre-existing sites of disease present prior to CART infusion in the BRT and no BRT group, respectively. Seven (16%) BRT patients relapsed in the radiation field. The 2-year EFS was 50% in the BRT group and 39% in the no BRT group (p=0.01). The 2-year PFS was 55% in the BRT group and 45% in the no BRT group (p=0.017). The 2-year OS was 55% in the BRT group and 62% in the no BRT group (p=0.7). Intriguingly, patients who received BRT to all visible PET-avid disease sites (n=34) had further improvement in 2-year EFS (67% vs 39%, p=0.003) and 2-year PFS (71% vs 46%, p=0.008) compared to no BRT or patients who received BRT to some but not all visible disease sites (n=105). Nine patients (2 in BRT and 7 in no BRT groups) received consolidative radiotherapy for day 30 residual disease with only one patient subsequently experiencing progression. Twenty-five patients (6 in BRT and 19 in no BRT groups) received salvage/palliative RT for post-CART relapsed disease. Thirty-seven (39%) patients in the no BRT group remained without disease progression and did not receive radiation in the bridging, consolidative or salvage/palliative setting. Conclusion Bridging radiotherapy prior to CART infusion for patients with limited (<5 involved disease sites) r/r NHL appears to improve response rate, EFS, and PFS without causing significant toxicities. Approximately one third of patients who do not receive BRT will require subsequent post-CART radiation, and another third will remain free of radiation and disease progression.

Introduction Lymphoid malignancy (LM) is a heterogenous neoplasm with respect to biology, aggressiveness, and treatment with over 100 subtypes, including Hodgkin lymphoma (HL), non-Hodgkin lymphoma (NHL), and multiple myeloma (MM). Genome-wide association studies have identified common variants associated with risk of specific LM subtypes, but less is known about the contribution of rare inherited pathogenic variants (PV) in the genetic architecture of LM risk. Rare PV have been shown to contribute to the genetic architecture of solid tumor cancer risk, many of which have been found in genes that are important to the DNA-damage repair (DDR) pathway (e.g., BRCA1, BRCA1, ATM). Here, we investigated the prevalence of PV in cancer predisposition genes regularly included on multi-gene panel testing based on NCCN guidelines and correlated with risk of LM overall and by common subtypes. Methods In this association study, cases were newly diagnosed lymphomas (excluding chronic lymphocytic leukemia) from Mayo Clinic who were enrolled between 2002 and 2015 in the Lymphoma SPORE Molecular Epidemiology Resource (MER) and MM from Mayo Clinic enrolled primarily between 1998 and 2022 in a clinical registry. Controls were from the Mayo Clinic Biobank who were enrolled between 2009 and 2016, from which we excluded individuals with a history of hematologic malignancy. All participants provided a blood sample for whole exome sequencing, performed by Regeneron on an Illumina NovaSeq panel (mean coverage of 48X). Variants were called using GATK v4 and variant annotation was performed using BioR. All loss-of-function variants (i.e., nonsense, frameshift, and consensus splice sites) and pathogenic missense in 19 cancer predisposition genes with a minor allele frequency < 0.5% were included in the analyses. Logistic regression was used to estimate odds ratio (OR) and 95% confidence intervals (CI) for the association between mutation status by gene (burden test) and risk of LM overall, and by subtype that had more than 5 mutation carriers. All analyses were adjusted for age (at diagnosis for cases and at enrollment for controls) and sex. Results A total of 6990 cases and 42432 controls were included. Median age was 63 years for both cases and controls (case range 18-94 years, control range 18-99 years). Males accounted for 58.5% (n=4090) of the cases and 41.7% (n=17762) of the controls. MM accounted for 31% (n=2138) of the cases, followed by diffuse large B-cell lymphoma (DLBCL, n=1146) and follicular lymphoma (FL, n=1132) each accounting for 16% of cases. CHEK2 (1.0%), ATM (0.4%), BRCA2 (0.4%), and BRCA1 (0.3%) had the most PV carriers in controls; these frequencies are in the range of published control populations. A total of 1816 (3.7%) individuals had a PV across the 19 genes, with 4.7% of cases and 3.5% of controls carrying any PV (OR=1.34, 95% CI: 1.18-1.51). ATM (OR=1.86, 95% CI: 1.36-2.49), CHEK2 (OR=1.74, 95% CI: 1.42-2.13) and TP53 (OR=9.07, 95% CI: 4.51-18.87) were all significantly associated with increased risk of LM overall (Figure 1). When investigating subtypes (Table 1), CHEK2 (OR=1.93, 95% CI: 1.23-2.89) and TP53(OR=10.97, 95% CI: 3.06-31.43) were significantly associated with DLBCL. ATM (OR=2.22, 95% CI: 1.13-3.90) was significantly associated with FL. ATM (OR=1.97, 95% CI: 1.16-3.12), CHEK2 (OR=1.75, 95% CI: 1.24-2.41) and TP53 (OR=7.67, 95% CI: 2.43-20.72) were significantly associated with MM and ATM (OR=8.62, 95% CI: 4.47-15.12), NBN (OR=6.94, 95% CI: 2.41-15.76) and TP53 (OR=38.30, 95% CI: 10.27-116.69) were significantly associated with mantle cell lymphoma (MCL). When subset to LM cases overall, there was no evidence of enrichment for young onset (age <60 years), male sex, or family history of hematologic malignancy between PV carriers and non-PV carriers. However, FL cases with an ATM PV tended to be less than 60 years (OR=3.21, P=0.09) compared to non- ATM PV carriers. Similarly, MM cases with a TP53 PV tended to be less than 60 years of age (OR=7.39, P=0.07) compared non-carriers. Discussion In this large case-control study, PV in established cancer predisposition genes were associated with increased risk of LM overall, demonstrating that rare inherited variants may play an important etiologic role. This study also suggests that PV in cancer predisposition genes may be subtype specific. These results will help inform LM risk for individuals who undergo genetic testing of cancer predisposition genes.

Background: Anti-CD19 chimeric antigen receptor T-cell (CART) therapy is a standard of care in patients (pts) with relapsed or refractory (RR) large B-cell lymphoma (LBCL). However, it remains underutilized in elderly pts due to limited efficacy and safety data. We therefore evaluated real world outcomes of CART in such pts. Methods: Seven academic centers participated in this retrospective study. Pts aged ≥65 years with RR LBCL who received a commercial CART product were included. Baseline characteristics, treatment data, CART toxicity, and clinical outcomes were collected. Progression-free survival (PFS; time from infusion to disease progression or death) and overall survival (OS; time from infusion to death from any cause) were analyzed using Kaplan-Meier method. Cumulative incidences of non-relapse mortality (NRM) and disease relapse/progression were estimated accounting for competing risks. Statistical analyses were performed in JMP v15 and XLSTAT v2022.1.2. Results: 209 pts were identified. Baseline characteristics and treatment pattern are shown in Table. Median age at infusion was 71 years (range 65-89), and 25 (12%) were ≥80 years. 131 (63%) were male, 188 (90%) were white, and 27 (13%) had ECOG PS of ≥2. The median HCT-CI was 1 (range 0-6), and 39 (22%) pts had a score of ≥3. 165 (84%) had stage III-IV disease, 131 (70%) had extranodal involvement, 24 (18%) had bulky disease, and 24 (11%) had high grade B-cell lymphoma (HGBL; double- or triple-hit lymphoma, n=15; HGBL, NOS, n=9). The median number of prior lines of therapy was 2 (range 1-8), and 99 (48%) pts had ≥3 prior lines of therapy, 45 (22%) had prior bendamustine, and 44 (21%) had prior stem cell transplant (SCT; auto-SCT, n=41; allo-SCT, n=2; both auto- and allo-SCT, n=1). Bridging therapy was given to 100 (52%) pts; among those, 57 had chemotherapy, 20 had radiotherapy, 6 had both chemotherapy and radiotherapy, 10 had lenalidomide-based regimen, and 7 had CD20 antibody and/or corticosteroids. Axicabtagene ciloleucel (axi-cel) was most frequently used (63%, n=131), followed by lisocabtagene maraleucel (liso-cel) (24%, n=49) and tisagenlecleucel (tisa-cel) (13%, n=27). Cytokine release syndrome (CRS) occurred in 75% of pts, and a minority (6%) had grade ≥3. Immune effector cell associated neurotoxicity syndrome (ICANS) occurred in 55%, and 29% had grade ≥3. The management of CRS and ICANS included corticosteroids in 101 (49%) pts, tocilizumab in 116 (56%) pts, and other biologic agents (anakinra, siltuximab, basiliximab) in 8 (4%) pts. Day 30 response was evaluable in 195 pts with an objective response rate (ORR) of 84%, and a complete response rate (CR) of 52%. 82% of the responders continued to have a response at 3 month follow up. The ORR/CR rates were 86%/53% for axi-cel, 64%/44% for tisa-cel, and 89%/52% for liso-cel, respectively. At a median follow up of 19.1 months (95% CI 16.1-23.6) after infusion, the median PFS was 6.7 months (95% CI 5.1-11.5), with 6- and 12-month PFS rates of 54% (95% CI 47-61) and 43% (95% CI 35-50), respectively. The median OS was 16.5 months (95% CI 13.2-26.7), and the 6-and 12-month OS rates were 70% (95% CI 64-77) and 61% (95% CI 54-68), respectively. The NRM rate was 17% (95% CI 11-24) at 1 year, primarily due to infections including 5 COVID-19 related deaths. In univariate analysis, ECOG PS ≥2, bulky disease, elevated LDH, and the need for bridging therapy were associated with inferior PFS and OS. No significant difference in PFS and OS was seen based on age at infusion with a median PFS of 6.4 vs 9.6 vs 6.4 vs 6.0 months ( P=0.93) (Figure) and OS of 16.4 vs 19.2 vs 28.5 vs 12.7 months ( P=0.85) in age groups ≥65-69 vs ≥70-74 vs ≥75-79 vs ≥80-89. In addition, there was no statistically significant difference in PFS and OS based on type of CART with a median PFS of 6.4 vs 5.6 vs 12.7 months ( P=0.16) and OS of 15.1 vs vs 16.1 vs NR months ( P=0.24) in pts treated with axi-cel vs tisa-cel vs liso-cel. Conclusions: In this large multicenter study of elderly pts with RR LBCL, CART therapy demonstrated favorable efficacy and safety profile comparable to that in pivotal registration trials. Survival outcomes appeared similar regardless of patient age, including those aged ≥80 years, and type of CART product used. Similar to younger pts, high tumor burden and poor performance status at CART infusion were associated with inferior survival. This analysis confirms that older pts should not be excluded from receiving CART therapy solely due to chronological age.