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Background: Although Covalent BTKis have revolutionized treatment of CLL/SLL, cardiotoxicity is a known side effect, which can increase the total costs to the healthcare system. This study evaluated the real-world healthcare resource utilization (HCRU) and costs in patients who did and did not experience incident cardiovascular adverse events (CVAEs) during cBTKi treatment. Methods: Adult patients diagnosed with CLL/SLL who initiated ibrutinib or acalabrutinib treatment (index date) between 2020-2023 in the United States were identified using claims data from Optum's de-identified Clinformatics® Data Mart Database and followed up to 36 months post-index. Patients were stratified into two cohorts based on the presence of an incident CVAE during treatment with index cBTKi, defined as the occurrence of a CVAE not present in a patient's medical history. HCRU and costs were evaluated on a per 1,000 patient-months basis. Z tests and univariate gamma general linear models were used to compare HCRU and cost rates. HCRU between those who received ibrutinib or acalabrutinib were also assessed. Results: Overall, 2,069 eligible patients were identified with a mean ± SD age of 73.7 ± 9.1 years, and 40.4% were female. The mean ± SD [median] treatment-specific observation period was 11.4 ± 9.5 [8.5] months. Of the total cohort, 442 (21.4%) experienced at least one incident CVAE, while 1,627 patients (78.6%) experienced no CVAEs. Among those without a pre-index history of the specific CV AE of interest, the proportion of patients with incident events were 21.4% for hypertension, 9.8% for atrial fibrillation, 9.2% for atrial flutter, and 9.6% for ventricular arrhythmias. Patients who experienced an incident CVAE had 4,334 total days with medical service compared to 3,138 days in those who did not (p<0.001). The drivers of differences in total medical service days between those with and without CVAEs were inpatient days (690 vs 230), followed by outpatient days (2,798 vs 2,425), other visits (e.g., hospice; 662 vs 375), and emergency room (ER) visits (184 vs 109). Total days with medical service were 3,458 in those who received ibrutinib and 3,410 with acalabrutinib. Total healthcare cost rates in those who experienced an incident CVAE were $20,250,560 compared to $17,413,460 in those without CVAEs (p<0.001). Inpatient costs drove differences in total costs between those with CVAEs and those without ($3,417,948 vs $915,839, p<0.001), followed by outpatient ($2,415,060 vs $1,769,628, p<0.01) and ER costs ($186,820 vs $87,585, p<0.001). Pharmacy costs were the largest contributor to total cost rates for both cohorts ($14,016,900 for those with a CVAE vs $14,473,270 without any CVAEs, p<0.001). Regarding specific incident CVAEs, the cost difference in total costs between those with and without the event were $3,789,820 for atrial fibrillation (higher in those with the event), $3,867,160 for atrial flutter, $3,674,860 for ventricular arrhythmias, and $721,840 for hypertension. Inpatient costs were the largest driver in total cost differences between those with and without the specific CVAE of interest; inpatient cost differences were $3,255,699 higher in those with atrial fibrillation, $3,436,913 with atrial flutter, and $3,299,371 with ventricular arrhythmia. For hypertension, pharmacy costs drove differences in total costs and were $346,570 higher in those with the CVAE. Summary/Conclusion: Overall, the economic burden remains high in patients treated for CLL/SLL, especially in cBTKi patients experiencing an incident CVAE. These findings highlight the importance of careful treatment selection, safety monitoring, and early management of CVAEs in order to improve patient outcomes and reduce the downstream impacts on healthcare resources and costs.

Introduction: Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) Prognosis is highly variable due to underlying biological and molecular heterogeneity. The first-line (1L) treatment paradigm for MCL continues to evolve with increasing use of bruton tyrosine kinase inhibitors (BTKi) and decreasing use of autologous stem cell transplant (ASCT). TP53 alterations are associated with inferior outcomes in MCL. The aim of this retrospective study is to determine treatment strategies and clinical outcomes in MCL patients based on TP53 gene mutation status. Methods: Retrospective data were collected from 19 institutions in the United States from 1/1993 to 1/2024. We examined treatment patterns and outcomes among MCL patients >18 years of age with known TP53 mutation status by sequencing. Patients who did not receive treatment were excluded. The analysis was stratified based on presence of TP53 mutations. Systemic therapies were categorized as chemo-immunotherapy (CIT), non-chemotherapy (including monoclonal antibodies, lenalidomide, venetoclax, and novel agents on clinical trial), and regimens containing BTKi. The primary outcome was overall survival (OS) and secondary outcomes were progression free survival (PFS) and time to next treatment (TTNT). OS and PFS were estimated with the Kaplan-Meier method and log-rank tests were used to compare groups. Results: 645 patients were included in the study, with 468 men (72.6%) and median age was 64 years (range 30-89). 230/645 patients (35.7%) had a TP53 mutation, of which 182 (79%) were identified prior to 1L. While the male/female distribution was the same between the mutated and unmutated groups, median age at diagnosis and MIPI risk score was higher in the TP53 mutated group (age 65.9 vs 63.1 yrs, p= 0.015; MIPI 6.4 vs 6.1, p<0.001). TP53 unmutated patients had a median of 1 line of therapy vs. 2 for the mutated group (p<0.001, range 1-8). Blastoid histology and higher ki67 were also associated with the TP53 mutated group (p=0.045, 0.01 respectively) The median OS was 14.2 years for TP53 unmutated and 8.3 years for TP53 mutated patients (p<0.0001). PFS in 1L was 0.95 years in TP53 mutated compared to 2.02 years in TP53 unmutated group (p<0.0001). Selection of 1L therapeutic strategy was not associated with presence of TP53 mutation (Χ2 p= 0.21) although more patients in the TP53 unmutated group underwent ASCT (119/415 vs 38/230; Χ2 p=0.0006) TP53 mutation was associated with inferior survival compared to TP53 unmutated patients for CIT in 1L but the difference did not reach statistical significance when non-chemotherapy regimens and regimens containing BTKi were used. For CIT in 1L, 5 year OS was 78% [71-84%] for unmutated compared to 58% [48-67%] for the mutated group (p=0.0001 ). For non-chemotherapy regimens, 5 year OS for unmutated patients was 73% [52- 86%] compared to 52% [25-73%] for the mutated group (p=0.09). For regimens containing BTKi, 5 year OS for unmutated was 93% [81-97%] compared to 57% [28-78%] for mutated (p=0.07). Within the TP53 mutated group, there were no differences in any clinical outcomes between those receiving CIT, non-chemotherapy, or BTKi in 1L. While median OS appeared numerically longer in the BTKi group (14.4 yrs vs 8.8 yrs for CIT and 6.8 yrs for non-chemotherapy), the difference did not reach statistical significance (p=0.58). In contrast,TP53 unmutated patients who received CIT in 1L had better TTNT (p=0.0039) compared to those in non-chemotherapy and BTKi groups. There was no improvement in PFS (p=0.79) or OS (p=0.47). Conclusions To our knowledge this is the largest retrospective real world dataset of MCL treatment outcomes stratified by TP53 mutation. As in prior studies, TP53 mutation portends a worse prognosis in MCL compared to TP53 unmutated patients, but outcomes are better than historically reported. CIT in 1L was not associated with improved OS in either group. Irrespective of TP53 mutation status, incorporation of BTKi in first line was not associated with improved clinical outcomes. The gap in OS between TP53 mutated and unmutated MCL may be narrowing as treatment paradigms shift away from intensive induction chemotherapy and ASCT, and due to an increasing number of effective therapies for relapsed patients. Clinical trials of novel agents are needed to further improve the OS of TP53 mutated MCL patients.

Aim: The definition of high-risk (HR) in Multiple Myeloma (MM) is ever evolving with the discovery of new genomic abnormalities and increasing therapeutic options. There are various stratification models incorporating laboratory and genetic features with different definitions of high-risk and varied emphasis on individual risk factors. Recognized high-risk cytogenetic abnormalities (HRCA) include t(4;14), t(14;16), t(14;20), del(17p) with recent inclusion of del(1p) and gain/amplification (amp) of 1q (+1q) . In addition to del(17p), the presence of biallelic del(1p) and ≥2 HRCAs (“double-” or “triple-hit”) appear to confer poorer outcomes. A new definition proposed by the International Myeloma society (IMS) defines HR as the presence of del(17p) and/or TP53 mutation; an IgH translocation - t(4;14), t(4;16) or t(14;20) along with +1q and/or del(1p); monoallelic del(1p32) along with +1q; bi-allelic del(1p32); or β2 microglobulin ≥5.5 with normal creatinine (<1.2mg/dL). Herein, we report real-world outcomes on these HRCAs and the new IMS consensus definition of HR MM. Method: We retrospectively reviewed newly diagnosed MM patients from the Australian and New Zealand Myeloma and Related Diseases Registry across 4 Australian states. Patients with FISH and/or SNP microarray testing for IgH translocations, 1q21 (CKS1B), del(1p32) (CDKN2C) and del(17p) (TP53) were identified. Positive threshold was 30%. We used Kaplan-Meier methods to compare progression free survival (PFS) and overall survival (OS) between groups and first performed univariate analysis (UA) for each HRCA. We next analyzed patients with gain1q vs amp1q and monoallelic vs biallelic del(1p). In the final analysis, two risk groups were formed: cases meeting the new IMS-defined HR criteria were considered IMS-HR and the rest were considered standard risk (IMS-SR). Indeterminate cases with missing variables that could influence risk classification were excluded. Results: Of 839 newly diagnosed patients (pts) included, 31% had ISS (International staging system) stage 3 disease. High-risk IgH translocations t(4;14) and t(14;16) were present in 8% and 4%. Secondary HRCAs del(17p), del(1p), gain1q and amp1q were present in 9%, 14%, 30% and 11% respectively. In this cohort, 41% received ASCT. Of the transplant eligible pts, 41% received triplet therapy (PI, IMiD and corticosteroid) and 57% received PI-based induction. Of the transplant ineligible pts, 31% received triplet therapy, 47% PI-based and 19% IMiD-based therapy. Frontline Anti-CD38 antibody use was <1%. Median follow up was 35 months[m] (IQR 18-60). On UA, the risk of progression and/or death was increased with ISS III vs I, amp1q, del(17p), t(14;16), del(1p) and gain1q in descending order by hazard ratio. The risk remained significant in ISS III, del(17p), amp1q and gain1q after multi-variate analysis (MVA). The risk of death was increased with ISS III vs I, del(17p), amp1q, del(1p) and t(14;16), ISS II vs I in descending order by hazard ratio. After MVA, the risk remained significant for ISS stage III, del(17p), amp1q and t(14;16). Of the 117 pts with del(1p32), 108 had monoallelic and 9 had biallelic loss. Pts with biallelic del(1p32) had an inferior PFS (median 16.3 vs 23.2m, p<0.001) and OS (median 24.8m vs NR, p<0.001) compared to those with monoallelic del(1p32). In pts with 1q+, pts with amp1q had an inferior PFS (median 16.3 vs 27.5m, p<0.001) and OS (median 37.0m vs NR, p<0.001) vs pts with gain1q. Based on the new definition of HR myeloma - 385 pts met the criteria for IMS-HR and 216 for IMS-SR. There were 238 indeterminate cases due to missing data. The IMS-HR group had an inferior PFS (median 20.2 vs 39.7m, p<0.001) and OS (median 44.2m vs NR, p<0.001) when compared to IMS-SR. Noting that the IMS-HR group had a higher median age, poorer performance status and lower rates of ASCT use, adjusted analysis for these variables still showed an inferior PFS (aHR 1.68; 95% CI 1.30-2.16, p<0.001) and OS [aHR 1.72; 95% CI 1.21-2.44, p=0.002). Conclusion: ISS III, del(17p), amp1q are the strongest predictor of OS and PFS. Differentiating between monoallelic vs biallelic del(132p) and gain vs amp1q21 has important prognostic value. The IMS- HR definition which takes into account del(1p), “double-” and “triple-hit” disease predicts for a group of patients with a PFS of ~20 months and inferior OS, and provides a standardized approach to risk stratification in MM.

Introduction: Progression-free survival (PFS), a common endpoint used in multiple myeloma (MM) trials, is defined as the time to the earliest occurrence of disease progression or death. Disease progression in MM is determined by the International Myeloma Working Group (IMWG) Uniform Response Criteria based on imaging and biomarkers from blood, urine, and bone marrow biopsy testing. In clinical trials, IMWG-recommended assessments are protocol-based. However, in routine care, they are often performed and recorded differently based on a multitude of factors. Algorithms to ascertain progression events using routinely collected biomarker data are important to classify disease progression and align with trial-defined endpoints. The aim of this study was to construct and evaluate an optimized real-world Progression (rwP) algorithm using real-world data (RWD) and demonstrate how biomarker data are captured and used to derive endpoints in routine practice. Method: A cohort of 270 transplant ineligible newly diagnosed MM (NDMM) patients starting on lenalidomide and dexamethasone (Rd) and meeting select MAIA (NCT02252172) trial eligibility criteria were included from the nationwide Flatiron Health electronic health record-derived deidentified database from 2015 to 2023. A rwP algorithm was developed using key IMWG-recommended biomarkers, including serum protein electrophoresis (SPEP), urine protein electrophoresis (UPEP), and serum free light chains (FLCs). The initial baseline value for each biomarker was identified, if available, during either the pre-treatment period (45 days prior through 7 days after first line treatment (1L) start) or the on-treatment period (8 days after 1L start through 1L end). Available biomarkers were followed for disease assessment. If any subsequent lab value during 1L treatment was less than the initial baseline value, the subsequent “on-treatment baseline” value was adopted as the new lowest value; otherwise, the initial value was used as the “on-treatment baseline” value for assessing progression events. Three hierarchies, which describe the order of utilizing key IMWG-recommended biomarkers to define rwP events, were explored, including: i) strict hierarchy (SH) [SPEP > UPEP > FLCs], ii) partial hierarchy (PH) [SPEP = UPEP > FLCs], and iii) no hierarchy (NH) [SPEP = UPEP = FLCs]. The PH option closely resembles the IMWG criteria, with FLCs only used for rwP assessments when no measurable SPEP/UPEP are identified. The NH approach considers all available biomarkers equally and resembles how they are utilized in real-world clinical practice. The feasibility of requiring confirmatory events following the first suggestion of progression was also explored. Assays following the progression event up to the end of 1L were considered as confirmatory progression events if they met IMWG criteria. Results: We applied the rwP algorithm with each hierarchy to all eligible NDMM patients (N = 270). The SH, PH, and NH approaches respectively identified 106 (39.3%), 106 (39.3%), and 123 (45.6%) patients with progression events. Results from the SH and PH approach are consistent likely due to the rarity of UPEP usage in clinical practice. The NH approach captured more progression events because FLCs are used in the presence of measurable SPEP or UPEP, resulting in 73 progression events captured by FLCs in comparison to 32 from other approaches, potentially increasing false-positive capture due to the volatility of FLC results. Among the 106 PH-identified patients who progressed, 84 (79.2%) had IMWG-recommended tests following their progression event, and 74 (69.8%) had their progression confirmed before the end of 1L, with 35 (33.0%) receiving their confirmatory reading within 2 months after progression. These results suggest that requiring confirmatory testing as part of the rwP is feasible, though it may introduce false negatives for patients receiving clinical progression confirmation instead of getting confirmatory labs in routine clinical practice. Conclusion: We present a comprehensive assessment of important design choices for an rwP algorithm for NDMM, including a hierarchy of key assays and the inclusion of confirmatory testing. Further validation of the algorithm with health care provider assessments and the inclusion of bone marrow biopsy and imaging data is important for evaluating the performance of the algorithm in RWD.

Introduction E1910 randomized pts with ALL aged 30-70 years who were measurable residual disease negative (MRD-) by multi-color flow cytometry (FC) after intensification to conventional chemotherapy (chemo) with or without blinatumomab (blina). The addition of blina resulted in improved overall survival (OS) (Litzow, NEJM 2024) and led to a new standard of care. Older ALL pts have inferior outcomes when compared to younger pts in part due to increased treatment toxicity. In E1910, exposure to dexamethasone and pegasparagase was reduced for older pts (age >55 years). We present results of subgroup analyses describing outcomes of older pts enrolled in E1910. Methods Details of the E1910 protocol remission induction (step 1), high dose methotrexate with pegaspargase intensification (step 2), blina randomization (step 3), and maintenance (step 4) or allogeneic hematopoietic stem cell transplant (HCT) were previously presented (Litzow, NEJM 2024). MRD status was determined after step 2 centrally with 6-color FC with MRD- defined as <0.01% in the bone marrow (BM). Following approval of blina in the US for MRD positive (MRD+) disease in 2018, MRD+ pts were assigned to the blina arm and no longer randomized. The primary objective was to compare the OS and relapse free survival (RFS) among older pts aged >55 years (pre-specified stratification factor) who received chemo + blina to that of pts who received chemo alone (step 3 treatment). Estimates of OS and RFS were calculated using the Kaplan-Meier method. Comparison of OS and RFS between treatment arms was conducted using the two-sided stratified log-rank test and Cox model with CD20 status, rituximab use, and whether pts intended to receive HCT or not as stratification factors. Stratified Multivariate Cox models of OS and RFS were used to further evaluate the effect of step 3 treatment, adjusted by gender, white blood cell count (WBC), platelets, hemoglobin, peripheral blood blasts, BM blasts, performance status and combined molecular risk category. Results Among the 488 enrolled pts, 211 were ≥55 years old with median age of 61 (range 55-70). Among older pts, 49.3% were female and 83.4% were white, 17 (8.1%) pts had WBC >30.000/uL at the time of diagnosis. 156 (73.9%) pts had CD10+ early B-ALL and 46 (21.8%) had CD10- B-ALL immunophenotype. The most common genetic subgroups were low hypodiploid (n=58, 27.5%), BCR::ABL1-like (n=34, 16.1%) and KMT2A rearranged (n=26, 12.3%). 8.1% of pts had low, 9.0% intermediate, 63.5% high combined molecular risk disease and in 19.4% of pts risk could not be assigned. Baseline characteristics were not significantly different in chemo + blina and chemo only pts. The median follow-up for this analysis from step 1 registration was 54.6 months. Complete response with (CR) or without (CRi) count recovery after induction was observed in 174 (82.5%) pts (167 CR, 7 CRi). 93 (44%) pts were MRD-. 32 (15.1%) pts received HCT on study and 24 (11.4%) pts received it off study. Among MRD- pts (n=93), 46 were randomized to and 45 received blina: 6 (13.3%) pts had 1, 14 (31.1%) had 2, 2 (4.4%) had 3 and 23 (51.1%) had 4 cycles. 3-year OS were 71% and 67% for the blina and the chemo only arm (univariate model: HR 0.75, 95% CI: 0.37-1.50; multivariate model: HR 0.56, 95% CI: 0.25-1.27). 3-year RFS were 69% and 59% for the blina and the chemo only arm (univariate model: HR 0.75, 95% CI: 0.39-1.45; multivariate model: HR 0.67, 95% CI: 0.32-1.42). Among MRD+ pts (n=25), 14 were randomized to and 11 received blina: 7 (63.6%) pts had 2, and 4 (36.4%) had 4 cycles. 3-year OS were 66% and 44% for the blina vs the chemo only arm (univariate model: HR 0.66, 95% CI: 0.12-3.64). 3-year RFS were 64% and 31% for the blina vs the chemo only arm (univariate model: HR 0.64, 95% CI: 0.15-2.74). Frequency of treatment-related toxicities among older pts during different study phases and treatment assignments will be presented. Conclusion Despite evidence of improved outcomes in the whole study cohort, the addition of blina to consolidation chemo for older pts with ALL was not associated with statistically significant improvement of OS or RFS in this exploratory analysis not powered to detect the difference in subgroups. This is possibly due to sample size but may be due to biologic differences in the older adult population. Further studies are needed to definitively determine tolerance and benefit of blina addition to consolidation for older pts with ALL.

Background and significance: Paroxysmal nocturnal hemoglobinuria (PNH) is a rare condition caused by a somatic mutation in the PIG-A gene, leading to complement-mediated hemolysis and severe complications such as anemia and thrombosis. Patients often experience fatigue, dyspnea, and abdominal pain, impacting their daily lives and emotional well-being. This study aims to comprehensively explore the impact of PNH on health-related quality of life (HRQoL), alongside real-world treatment utilization and symptom burden patterns, especially as new treatments become available to this patient population. These results are based on interim baseline data from currently enrolled study participants, providing an initial assessment of their PNH disease experience. This analysis does not include any data collected prospectively during the data collection period. Study design and methods: This ongoing, prospective, observational study (NCT06411626) aims to enroll at least 128 US-based participants aged 18 or older with PNH, regardless of treatment usage. Participants are recruited through clinician-based referrals, patient advocacy organizations, and community-based online channels. All activities can be completed remotely using the Folia Health app, the single site for this study. This app-based study aims to comprehensively assess patient-reported symptom burden, treatment use patterns, and impacts of PNH on health and FACIT-Fatigue through self-reported home-reported outcomes (HROs). Participants will track symptoms and treatment use, including recently approved treatments (e.g., iptacopan, danicopan, crovalimab). HROs consist of participants' self-identified symptoms and personalized treatment plan that are tracked longitudinally against self-reported baselines. Semi-structured interviews and collaborative feedback sessions with PNH patients and clinicians yielded a comprehensive outcomes inventory for tracking key health outcomes specific to PNH. This inventory includes the ability to track infusion treatments and denote flare-ups in fatigue. Participants can customize their data collection to track symptoms in additional domains beyond those initially suggested (e.g., respiratory or immune). At enrollment, participants report baseline health status and select their relevant symptoms and treatments to routinely track for 6 months. Monthly in-app surveys will collect data on overall health and the FACIT- Fatigue. The Folia app allows participants to visualize symptoms trends, set treatment reminders, and generate reports for their care team. Results: Enrollment began on June 11, 2024. As of July 22, 2024, an interim data analysis was conducted on 20 participants; 65% (n=13) enrolled through online community-based channels and 35% (n=7) enrolled through clinic referrals. Participants selected 37 distinct symptoms and measurements and 26 distinct treatments to track over the 6-month period. The most common symptoms selected at baseline include fatigue (n=19), brain fog (n=17), and dark colored urine (n=15). PNH treatments selected for tracking include iptacopan (n=9), ravulizumab (n=5), eculizumab (n=4), and pegcetacoplan (n=3). The mean baseline FACIT- Fatigue score (n=18) was 35.7 and the median was 40 (IQR= 16). Further descriptive analyses stratified by primary treatment use will be conducted assessing characteristics of symptom burden, satisfaction with treatments-in-use, and self-reported impact on HRQoL. Conclusions: Initial interim baseline data of recently enrolled participants with PNH show a variable disease experience. This app-based, observational study aims to establish a new real-world data source to understand patient priorities related to symptom variability, treatment patterns and preference, and impacts of condition management on HRQoL.

Splenic marginal zone lymphoma (SMZL) is a B-cell malignancy with a typically indolent course. However, some patients have more aggressive disease and initial treatment can range from observation to chemoimmunotherapy. The reason for this spectrum of disease behavior is incompletely understood but the tumor microenvironment (TME) likely plays a role as recent studies have shown that an optimized antitumor immune response in SMZL patients would allow the immune system to better target malignant B cells and irradicate the disease. Regulatory CD4+T cells (Tregs) are crucial in maintaining TME homeostasis by suppressing effector T cells and malignant B cells and in this study, we therefore explored the key factors influencing the function and development of intratumoral Tregs in SMZL patients. We identified two distinct Treg subsets in the TME of SMZL patients: CD26+Tregs and CD161+Tregs, each with unique phenotypic profiles, functions, and prognostic significance. CD161+Tregs suppress CD8+T cells and malignant B cells more effectively than CD26+Tregs, which only inhibit CD8+T cells. Clinically, patients with inferior outcomes have significantly higher numbers of CD26+Tregs and fewer CD161+Tregs. To delineate differences between these subsets, we performed Cellular Indexing of Transcriptomes and Epitopes Sequencing (CITE-seq) on biopsies from 7 SMZL patients. We found that cytokine-inducible SH2-containing protein (CISH) is the most highly expressed gene in CD26+Tregs compared to CD161+Tregs, aside from FOXP3. CISH has been reported to be a negative regulator of immune effector cell activation in tumor models. Although CISH deficiency leads to a loss of Foxp3 expression and reduced Treg suppressive function, the mechanism by which CISH modulates Treg function, especially immune suppression in hematologic malignancies, remains largely unknown. To further investigate the mechanism of CISH in Treg function in MZL patients, we conducted CITE-seq analysis on a larger cohort of MZL patients (n=12), divided into groups based on outcomes (EFS24 failed, n=4; EFS24 achieved, n=8). The CITE-seq analysis results showed significantly higher CISH expression in Tregs from patients with inferior outcomes (P=1.07E-06). We then explored factors influencing CISH expression and found that TCR engagement and treatment with cytokines (IL-15, IL-2, and IL-7) elevated CISH expression in Tregs. While we previously observed that lymphoma B cells could enhance Foxp3 expression in CD4+CD25-T cells, this study we found that B cells could also enhance CISH and CD26 expression in CD4+CD25-T cells in vitro, indicating that a high frequency of B cells in the environment may lead to increased CISH expression in Treg cells leading to an unfavorable outcome in patients. We further investigated the role of CISH in the function of Treg cells. Following CISH knockdown in Treg cells, we observed decreased CD26 expression and reduced suppressive function on CD8+ T cell proliferation. Using CRISPR-Cas9, we knocked out CISH in the Karpas 299 cell line, a human T cell lymphoma line that constitutively expresses CD25, Foxp3, and CISH. CISH-KO Karpas 299 cells showed significantly less apoptosis and Foxp3 expression compared to CISH-WT cells. Bulk RNA-seq analysis of CISH-KO and CISH-WT Karpas 299 cells revealed that CISH-KO cells showed enhanced DNA replication and cell cycle pathway activity. Taken together, our results suggest that high expression of CISH in Tregs may predict an unfavorable outcome in SMZL patients. Malignant B-cells in the TME of SMZL patients may promote expression of CD26 and CISH in Tregs, thereby modulating Treg function. Targeting CISH could decrease the immunosuppressive activity of Tregs in the TME, potentially optimizing antitumor immunity in SMZL patients.

Introduction: Despite advent of multiple tyrosine kinase inhibitors (TKIs) and newer treatment methods for both AML and ALL, the outcomes of patients (pts) with chronic myeloid leukemia in blast phase (CML-BP) remain poor. Consensus guidelines on treatment of CML-BP are scarce. A recent study from the European leukemia network (ELN) blast phase registry reported outcomes of 240 CML-BP pts. They also reported marked heterogeneity in treatment patterns and lack of an accepted standard. Hence, we are undertaking this study through the H Jean Khoury Cure CML Consortium (HJKC3) to study the treatment patterns and outcomes of pts with CML-BP in the US. Methods: This is a multi-institution, retrospective study. IRB approval was obtained at each institution separately and data sharing agreements were executed. All pts diagnosed with CML-BP based on modified MD Anderson Criteria (≥30% blasts in the blood or bone marrow or extramedullary (EM) disease) from 2010 to 2024 were included. Categorical variables were compared using the Chi-square test. Overall survival (OS) was calculated from the time of diagnosis to death from any cause. Survival probabilities were computed using the Kaplan-Meier method and compared with the log-rank test. Results: Of the 72 pts with CML-BP included in this analysis, 29 (40.3%) were female and 43 (59.7%) were males. At the time of diagnosis, 36 (50%) had CML-CP (chronic myeloid leukemia in chronic phase), 11 (15.3%) pts were diagnosed with CML-AP (accelerated phase CML) and 25 (34.7%) pts with de-novo CML-BP. For the 47 pts that were initially diagnosed with CML-CP or CML-AP, the median time to progression to CML-BP was 26 months (1-207 months). Median age at diagnosis of CML-BP was 54 years (range 21-86 years). EM disease was present in 17 (23.6%) pts (7 myeloid sarcoma, 5 central nervous system and 5 skin) with 3 pts presenting with EM disease only. Blasts were of myeloid phenotype in 41 (56.9%), lymphoid in 29 (40.3%) and mixed in 2 (2.8%) pts. The bcr-abl protein was p210 in 59 (81.9%), p190 in 5 (6.9%) and p230 in 1 (1.4%) pt. Four pts had prior allogeneic stem cell transplant (alloSCT) for CML-CP. Of the pts who had an ABL kinase domain mutation tested, 42.9% (18/42) pts were found to have an ABL kinase domain mutation. The most common TKD mutation was T315I (n=6). Next generation sequencing was performed in 32 pts. The most common mutations were ASXL1 (n=10), RUNX1 (n=4), BCOR (n=2), BCORL1 (n=2), DNMT3A (n=2) and 1 each in CSF3R, KMT2A, EZH2, NF1 and TP53. Of the 72 pts, 68 underwent CML-BP directed therapy. While only 9 (13.2%) pts were treated with TKI alone (4 dasatinib, 2 imatinib, 2 ponatinib and 1 asciminib), 54 (79.4%) pts were treated with a combination of chemotherapy with TKI (24 dasatinib, 13 ponatinib, 9 imatinib, 6 nilotinib, 1 bosutinib and 1 asciminib), and 5 (7.4%) pts were treated with chemotherapy alone. The response rate after CML-BP directed therapy was 72.1% (n=49). Best response was return to CML-CP in 17 pts, CHR with PCyR in 1 pt, CCyR in 11 pts, MMR in 5 pts, MR4 in 4 pts, MR4.5 in 5 pts and MR5 in 6 pts. Rate of response with third and second generation TKI was significantly better than first generation TKI (80% and 77.1% vs 36.3%; p=0.02287). 30 (44.1%) pts proceeded to alloSCT. Of the 49 pts that responded, 16 (32.6%) relapsed. The median time to relapse was 5 months (range 1-46 months). At a median follow up of 57 months, the median OS for all pts was 18 months. There was no difference in OS based on blast phenotype (14 months for myeloid, 21 for lymphoid and 7.5 for mixed; p=0.1185), initial diagnosis (38 months CP-CML, 13 for CML-AP and 16 for de-novo BP pts; p=0.6380), or TKI (13 months for first generation, 20 for second and not reached for third generation TKI; p=0.1729). The OS of pts that were treated with a combination of TKI and chemotherapy was significantly longer compared to pts treated with TKI or chemo alone (28 vs 13 or 4.5 months; p=0.0003). Of the 32 pts that responded, OS for pts that underwent alloSCT was significantly longer compared to pts that did not (not reached vs 14 months; p= 0.0022). Conclusion: CML-BP continues to have a dismal prognosis. Treatment is heterogenous involving various combinations of TKI and chemotherapy. In our analysis, treatment with second or third generation TKI led to better responses. In addition, treatment with chemotherapy in combination with TKI and alloSCT led to improved OS. Updated results from further multi-institution analysis will be presented at the meeting.

Introduction: HIV-associated diffuse large B-cell lymphoma (HIV-DLBCL) is a significant complication in HIV-positive individuals, presenting unique clinical challenges and a poorer prognosis compared to patients with de novo DLBCL. Epstein-Barr Virus (EBV) status is a critical factor influencing the pathogenesis, clinical behavior, and therapeutic responses in these lymphomas. Plasmablastic lymphomas (PBL) have shared some overlapping genomic abnormalities with HIV-DLBCL including MYC rearrangements. This study aims to elucidate the differences in the genetic profiles and pathway activations between EBV(+) and EBV(-) HIV-DLBCL through comprehensive genomic profiling. Methods: Cases of DLBCL were identified in patients living with HIV from a multi-institute cooperative group. Cases of Burkitt lymphoma and PBL were excluded. We performed whole exome sequencing (WES) on 106 tumors of HIV-DLBCL and RNA sequencing on 39 tumors and mapped the reads to hg38 reference genome using BWA and STAR, respectively. EBV status of cases was determined by in situ hybridization and/or reads mapped on EBV genome in sequencing data. Somatic mutations were identified using variant callers (Strelka2, Mutect2) with WES data. For those mutated genes in COSMIC, allele frequency cutoff was set at 0.03. Mutations with an artifact score larger than 0.7 in SOBDetector and those located in segmental duplications were further removed. They were annotated with Ensembl Variant Effect Predictor, manually checked, and plotted with maftools. RNAseq read counts aligned to each gene were obtained by featureCounts and DEseq2 was used for differential expression (DE) analysis between EBV positive and negative groups. Pathway analysis with the DE genes was performed using GSEA. FISH analysis was performed using MYC, BCL2, and BCL6 break-apart probes. Results: There were 41 cases of EBV(+) HIV-DLBCL and 65 cases of EBV(-) HIV-DLBCL. FISH of EBV(+) HIV-DLBCL identified 42% (3/7) with MYC rearrangement (MYCr), none with BCL2 rearrangements (BCL2r) (0/6), and 33% (2/6) positive for BCL6 rearrangement (BCL6r) with 1 tumor having a MYCr/BCL6r. For EBV(-) HIV-DLBCL, there were 35% with a MYCr (6/17), 18% with BCL2r (2/11), and 27% with a BCL6r (3/11) with 2 tumors with MYCr/BCL6r, and 1 tumor with MYCr/BCL2r/BCL6r. The most frequent mutations seen in EBV(+) HIV-DLBCL were STAT3 (32%), DDX3X (22%), and TP53 (15%). For EBV(-) HIV-DLBCL, the most frequent mutations were KMT2D (25%), TP53 (23%), GNA13 (22%), and TET2 (22%). Pathways that were most commonly associated with EBV(+) HIV-DLBCL were JAK/STAT (42%) (STAT3, JAK1) and NF-kB (39%)(DDX3X, TNFAIP3) while EBV(-) HIV-DLBCL was associated with epigenetic modifiers (62%)(KMT2D, TET2, EP300), JAK/STAT (45%)(SOCS1, JAK3) and PI3K/mTOR (40%)(GNA13, MTOR). Significant disparities between EBV(+) and EBV(-) were KMT2D (24% vs 50%, P=0.0025), TET2 (10% vs 26%, P=0.008), SOCS1 (29% vs 39%, P=0.04), DDX3X (15% vs 5%, P=0.03), and GNA13 (5% vs 24%, P=0.001). RAS mutations (KRAS, NRAS) were infrequent in HIV-DLBCL (EBV(+), 12%; EBV(-), 6%), in contrast to prior studies of PBL. Gene expression profiling showed enrichment of MYC targets, oxidative phosphorylation, and the mTORC pathway in EBV(+) as compared to EBV(-) HIV-DLBCL. Conclusion: EBV(+) HIV-DLBCL show a distinct mutational profile compared to EBV(-) HIV-DLBCL, with EBV(+) cases showing frequent mutations with STAT3 and DDX3X in contrast to EBV(-) cases with frequent mutations associated with epigenetic modification pathways (KMT2D, TET2). These genetic profiles underscore the need for tailored therapeutic approaches depending on EBV status. Although the analysis is limited and requires confirmation in a larger cohort, this is the largest study at present evaluating these tumors.

Introduction: Brexucabtagene Autoleucel (brexu-cel) is the first CD19-targeting chimeric antigen receptor (CD19.CAR) T-cell therapy approved for the treatment of relapsed/refractory (r/r) B-cell acute lymphoblastic leukemia (B-ALL) in adult (≥18 yo) patients (pts) based on results from the ZUMA-3 trial. However, data on the safety and efficacy of CAR-T cells in older pts (≥60 yo) remains limited, with only 8 pts >65 yo enrolled in the ZUMA-3 trial. We evaluated the treatment characteristics and outcomes with use of brexu-cel amongst patients ≥60 yo in the Real-World Outcomes Collaborative for CAR-T in ALL (ROCCA) consortium database. Methodology: ROCCA is a consortium of over 30 U.S.-based institutions with a database of adult pts with B-ALL who received brexu-cel as standard of care therapy. We identified pts ≥60 yo and further stratified them into two cohorts: 60-69 yo and ≥70 yo. Outcomes of interest included OS, PFS, ORR, and toxicities (CRS and ICANS). Both OS and PFS were calculated from the day of brexu-cel infusion. Response assessment occurred on day +28, and MRD evaluation was per institutional practices. CRS and ICANS were graded according to the American Society for Transplantation and Cellular Therapy criteria. Results: Of 280 brexu-cel recipients in the ROCCA database, 73 (26%) were ≥60 yo, of which 58 (79%) were between 60-69 yo and 15 (21%) were ≥70 yo. Among pts ≥60 yo, the median age at infusion was 65 (range 60-81). Pts were heavily pretreated with a median of 3 prior lines of therapy (range 2-9). Prior therapies included: allogeneic HSCT (38%), inotuzumab ozogamicin (41%), and blinatumomab (62%). Forty pts (55%) had Ph-negative B-ALL, 24 (33%) had Ph+ B-ALL and 9 (12%) had Ph-like B-ALL. When grouped by HCT-CI equal to 0, 1-2 or ≥3, a higher proportion of pts ≥60 yo had HCT-CI ≥3 (19% vs. 7% in <60 yo; p=0.004). Pre-apheresis, 33 pts (45%) had active disease (>5% marrow blasts or extramedullary disease), 34 (47%) were in CR (of whom 14 were MRD-negative) and 6 had unknown disease status. Following brexu-cel, 43 (59%) achieved MRD-negative CR, 20 (27%) had MRD + or CR with unknown MRD status, 6 (8%) had refractory disease and 5 had no disease evaluation available. The ORR was similar between pts 60-69 and ≥70 yo (MRD-negative CR rate: 58% vs 61%, r/r to brexu-cel: 9% vs 6%) and was comparable to pts <60 yo (MRD-negative CR 66%; r/r disease of 9%). The rate of all grade ICANS was higher in pts ≥70 (77%) than in pts 60-69 (47%) or pts <60 (49%), with grade 1-2 ICANS occurring at a significantly higher rate in pts ≥70 (44% vs. 20% in 60-69 and 20% in <60, p=0.049). Grade 3-4 ICANS were similar between the groups: 33%, 27% and 29% in the ≥70, 60-69, and <60 groups, respectively. Conversely, rates of CRS were similar across age groups (80-84%). There was no statistically significant difference in the rate of grade 3-4 CRS which was 17% in pts ≥70, 4% in pts 60-69, and 11% in pts <60 yo. With a median follow-up of 332 days (range 8-936 days) from infusion, pts ≥60 yo had a median PFS of 395 days compared to 547 days in pts <60 yo. Median PFS was lower in the ³70 yo (231 days) compared to 677 in the 60-69 yo cohort. No statistically significant difference was found between the <60 and ≥60groups in 6- and 12-month PFS rates (6 months PFS: 66% vs 64%, p=0.77 and 12 months PFS: 57% vs 57%, p=1.00). When pts ≥60 yo were stratified by age, pts ≥70 yo had similar 6-month PFS compared to other age groups but significantly lower 12-month PFS (38%; vs. 64% in pts 60-69and 57% in pts <60, p=0.001). Median OS was not reached in any of the age groups, and there was no statistically significant difference in 6-month OS (72% in ≥ 70 vs. 82% in the 60-69 vs. 82% in <60, p=0.14) or 12-months OS (61% in ≥ 70 vs. 69% in 60-69 vs. 73% in <60, p=0.18). Conclusion: This is the largest study to date of older B-ALL pts receiving CAR-T cells. We observed that older pts, particularly those aged 60-69, have similar outcomes to younger pts. However, pts ≥70 yo had lower median and 12-month PFS when compared to younger patients. Additionally, pts ≥70 yo had higher rates of grades 1-2 ICANS. An important limitation of this analysis is the potential selection bias among clinicians when selecting older patients for this treatment. Longer follow-up, including inclusion of additional pts ≥70 yo is needed to confirm these results, and further studies are needed to identify the optimal approach for use of CAR T-cell therapy in patients in this age group.