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Abstract Background: In R/R DLBCL/FL, T-cell engager therapy (TCET) using chimeric antigen receptor T-cell therapy (CART) or bispecific antibodies (BsAbs) are promising options. Patients (pts) with R/R disease post TCET experience dismal outcomes with overall survival (OS)< 5 months (mos). Lonca, an antibody drug conjugate (ADC) targeting CD19 (FDA approved for R/R DLBCL and beneficial in R/R FL) has been increasingly used post-TCET. RWDA of Lonca is limited, especially regarding: 1) impact of CD19 expression on activity, 2) adverse events (AEs) in non-clinical trial setting, and 3) impact of sequencing Lonca and TCET. Thus, we conducted a RWDA of Lonca efficacy and toxicity in R/R DLBCL and FL pre- and post-TCET. Methods: We conducted a multicenter retrospective study of R/R DLBCL or FL pts ≥18 years who received Lonca from 2017 to 2025 at 10 US academic sites. Demographic, pathological, treatment, and AEs were collected. Efficacy outcomes included overall response rate (ORR), complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD). Progression-free survival (PFS) and OS were analyzed by Kaplan-Meier method. CD19 expression by immunohistochemistry (IHC) and/or flow cytometry (FC) prior to Lonca administration was correlated to outcomes. Results: Among 120 pts (DLBCL n= 101, FL n=19), all but 2 pts received Lonca monotherapy. At a median follow-up of 6.1 mos, median PFS and OS were 2.6 mos and 6.7 mos, respectively for the entire cohort. For DLBCL, median age was 66 years (18-89). Median prior lines of therapy (LOT) were 4 (1-11). ORR was 37.7% (CR: 17%, PR: 20.7%), SD: 6%, and PD: 56%. Median PFS was 2.1 mos, and median OS was 5.8 mos. For FL, median age was 62 years (28-88). Median prior LOT was 6 (2-8). ORR was 49.4% (CR: 28%, PR: 21.4%), SD: 14%, and PD: 35.7%. Median PFS was 6.7 mos, and median OS was 6.8 mos. OS by best response (entire cohort) was 11.3 mos and 11.8 mos in those who had CR and PR, respectively, 10.6 mos in SD and 3.5 mos in those with PD. Lonca LOT (2nd-12th line) was not associated with improved OS (p=0.58). Bulky disease (>7.5 cm) was not associated with worse OS (p=0.07). PD to Lonca was associated with PD at 2nd line treatment (OR: 4.3; 95% CI: 1.7–10.9) and 3rd-line treatment (OR: 4.2; 95% CI: 1.5–11.5), elevated lactate dehydrogenase (OR: 1.9; 95% CI: 1.2–2.9), and each subsequent increase of extranodal sites >1 prior to Lonca (OR: 1.5; 95% CI: 1.04–2.1). Among pts with available CD19 status prior to Lonca administration, 28 were FC-positive and 22 were IHC-positive. Of the CD19 FC-positive pts (n=23), 22% (5/23) achieved CR, 26% (6/23) had PR, 8% (2/23) had SD, and 43% (10/23) developed PD. Of the CD19 IHC-positive pts (n=20): 15% (3/20) achieved CR, 20% (4/20) had PR, 5% (1/20) had SD, and 60% (12/20) developed PD. Among all CD19-negative pts (n=7), two achieved CR, one had SD, and four with PD. Any grade AE was seen in 84% of pts. Any grade ≥3 (G3) AE was seen in 62% of pts. Notable G3 AEs included: anemia (35%), lymphopenia (34%), neutropenia (21.6%), thrombocytopenia (20%), infection (17%), fatigue (9%), peripheral edema (5%), pleural effusion (4%), photosensitivity (2.5%), and pruritus (2.5%). Treatment discontinuation due to AEs occurred in 17% (n=21) of pts. Fifty-five pts (50 DLBCL, 5 FL) received both Lonca and CD19 directed CART (Pre-Lonca n=54; Post-Lonca n=1). There was no significant difference in PFS or OS between pts who received CART and those who did not (PFS: 2.7 mos vs 3 mos; OS: 7.4 mos vs 5 mos). BsAb was used in 41 pts (34 DLBCL, 7 FL) (Pre-Lonca n=30; Post-Lonca n=11). No significant difference in PFS or OS was observed between pts who received BsAb pre- or post-Lonca. There was also no significant difference in PFS between pts who received a BsAb (2.2 mos) and those who did not (2.9 mos), nor in OS.Conclusion: In this large RWDA of Lonca, pts who achieved any form of clinical response experienced a significantly longer OS than previously reported for heavily pre-treated pts. Lonca was predominantly administered after TCET; however, there was no significant difference in efficacy between pts who received CART and BsAbs and those who did not. CD19 positivity and earlier utilization of Lonca did not appear to have an impact on response rates. Our findings support a role for Lonca in the treatment of R/R DLBCL pts not candidates for TCET. This RWDA highlights the need to further investigate the sequencing of Lonca in R/R DLBCL and FL.

Abstract Introduction The International Prognostic Index (IPI, NEJM, 1993) has guided risk stratification in large B-cell lymphoma (LBCL) for over three decades. Its simplicity and clinical utility have driven its widespread adoption, even in the era of precision medicine. However, the prognostic value of the IPI and its components may not be uniform across the age spectrum of LBCL patients. We evaluated the contemporary prognostic performance of the IPI in a large international cohort, focusing on age-stratified performance and the relative contributions of its individual components, grouped as patient- and disease-related factors. Methods We harmonized and pooled data from 6,941 patients with newly diagnosed systemic LBCL treated with R-CHOP-like regimens (R-CHOP, R-miniCHOP, DA-EPOCH-R, R-CHOEP, R-CHOP+X) with complete IPI data from three prospective cohorts: NiHiL (Czech Republic, n=4,590; 2010–2023), LEO (USA, n=1,789; 2015–2020), and MER (USA, n=562; 2010–2015). IPI components included age, ECOG performance status (PS) as patient-related, and Ann Arbor clinical stage, serum lactate dehydrogenase (LDH), and extranodal (EN) involvement as disease-related factors. Prognostic performance was evaluated using multivariable Cox regression models and C-statistics. Age-stratified analysis was performed for: ≤40 years (7%; n=492), 41–60 years (28%; n=1,909), 61–80 years (59%; n=4,080), and >80 years (7%; n=460). The primary endpoint was overall survival (OS). Results In the pooled cohort, the median age was 66 years (range 18–95). Compared to the original IPI cohort (n=3,273), our cohort was older (age >60 years: 66% vs 41%) but otherwise comparable: ECOG PS 2–4 (25% vs 24%), clinical stage III–IV (63% vs 66%), elevated LDH (60% vs 52%), and >1 EN involvement (32% vs 30%). In multivariable analysis, age (≤60 vs >60 years) was the strongest predictor of OS (HR=2.78; vs HR=1.96 in original IPI report), followed by ECOG PS (HR=2.07; vs 1.80), clinical stage (HR=1.50; vs 1.47), LDH (HR=1.41; vs 1.85, all P<0.01); EN involvement was not significant (P=0.50, HR=1.03 vs 1.48). Risk group distribution shifted from the original IPI: 28% were low-risk (0–1 factor; vs 35%), 23% low-intermediate (2; vs 27%), 24% high-intermediate (3; vs 22%), and 25% high-risk (4–5; vs 16%). Corresponding 2-year OS rates were 95%, 86%, 78%, and 63%, superior to those of the original IPI cohort (87%, 67%, 55%, 44%; pre-rituximab era). Age was associated with an increasing risk of mortality, with a more pronounced rise beyond 60 years. In a piecewise Cox model, the HR per year was 1.04 for ages ≤60 (linear), 1.05 for 61–69 (accelerated), and 1.06 for ≥70 years (exponential, all P<0.01). ECOG PS retained prognostic significance across age groups: HRs were 1.87 (P=0.06) for ≤40 years, 1.63 (P<0.01) for 41–60, 2.22 (P<0.01) for 61–80, and 1.43 (P<0.01) for >80 years. The strength of other IPI components declined with age. Clinical stage showed decreasing impact: HR 2.08 (P=0.09), 1.97 (P<0.01), 1.49 (P<0.01), and 1.31 (P=0.05). LDH was significant only up to age 80 years: HRs were 2.07 (P=0.04), 1.96 (P<0.01), 1.32 (P<0.01), and 1.21 (P=0.13). EN involvement was non-significant across all groups: HRs were 1.37 (P=0.34), 1.26 (P=0.05), 0.98 (P=0.74), and 1.06 (P=0.67). The IPI C-statistics was 0.676 overall and declined with age: ≤40 years (0.708), 41–60 years (0.683), 61–80 years (0.641), and >80 years (0.598). We next stratified the IPI factors into patient- (age, ECOG PS) and disease-related (clinical stage, LDH, EN involvement). In patients ≤40 years, disease-related factors outperformed patient-related (C-index 0.693 vs 0.602), as in the 41–60 group (C-index 0.677 vs 0.589). In patients aged 61–80, predictive values were comparable (0.613 vs 0.622). In >80-year-olds, both declined substantially (0.580 vs 0.568). Conclusion The IPI remains a valuable prognostic tool in LBCL, particularly among younger patients. However, its overall predictive accuracy declines with age. In patients ≤60 years old, prognosis is primarily driven by disease-related factors, suggesting a role for molecular classifiers to enhance risk stratification. In older patients, incorporation of additional patient-level factors, such as comorbidities and nutritional status could be considered. These findings underscore the need for more individualized prognostic tools for LBCL patients. Funding: NU21-03-00411, P50 CA97274, U01 CA195568, Charles University Haematology-Oncology Cooperatio Program.

Abstract Introduction Pronounced disparities in pediatric B-lymphoblastic leukemia (B-ALL) outcomes by race and ethnicity persist in the contemporary era. Gaps in overall survival (OS) from initial diagnosis are wider than event-free survival, suggesting that post-relapse mechanisms may contribute. However, data on treatment and outcomes after relapse are lacking. In a large, multicenter, real-world cohort of children and young adults with high-risk 1st relapse of B-ALL, we sought to (1) define survival outcomes by race/ethnicity and (2) explore if differences in therapy utilization drive outcomes. Methods We conducted an analysis within the Retrospective Study of Contemporary Approaches to 1st Relapse in B-ALL (ReCALL-1) cohort, which includes patients <30 years who initiated 1st relapse therapy between 2018-2022. This analysis was restricted to patients treated at US centers for “high-risk” 1st relapse, defined as relapse for which hematopoietic cell transplant (HCT) is generally standard-of-care: Early relapse (medullary <36m; isolated extramedullary <18m), late relapse with persistent end of reinduction disease, Ph+ B-ALL or age ≥18 years. Patients with Trisomy 21, those who received cell therapy before relapse and those who died during reinduction were excluded. The primary exposure was race/ethnicity categorized as Hispanic, non-Hispanic Black (NHB), non-Hispanic White (NHW), and other/unknown. The primary outcome was OS from relapse. Multivariable Cox regression models were constructed to include other social drivers of health (SDOH; health insurance, preferred language) and disease characteristics. Results Of 479 patients in ReCALL-1, 311 from 31 centers met inclusion for this analysis (41% Hispanic, 7% NHB, 46% NHW, 5% NH-other/unknown). With a median follow-up of 47m, OS differed by race/ethnicity (log-rank p=0.017): Hispanic, 4y OS 59%; NHB, 37%; NHW, 68%. Compared to NHW patients, NHB patients had an increased hazard of death (HR 2.3, 95% CI 1.3-4.3, p=0.006), while Hispanic patients were more similar to NHW patients (HR 1.3, 95% CI 0.9-2.0, p=0.16). Adjustment for SDOH only marginally attenuated the risk for NHB patients (aHR 2.0, 95% CI, 1.1-3.7, p=0.031) and led to equivalent outcomes for Hispanic patients (aHR 0.9, 95% CI, 0.5-1.5, p=0.66). Adjusting for disease characteristics that differed by race/ethnicity at p<0.2 (time to relapse, Ph+, Ph-like, KMT2Ar, age ≥18, or relapsed infant ALL) did not diminish the risk for NHB patients (aHR 2.0, 95% CI, 1.1-3.7, p=0.032) while outcomes remained equivalent for Hispanic patients (aHR 1.2, 95% CI, 0.8-1.8, p=0.40). Point estimates of cumulative incidence of non-relapse mortality (NRM) were highest in NHB patients (Hispanic, 4y NRM 13%, NHB 22%, NHW 11%), but this trend was not statistically significant (Gray’s p=0.52). Only 17% of patients initiated therapy for relapse on a clinical trial with no differences observed by race/ethnicity. Most patients received definitive treatment for relapse with either CAR T cell therapy (CART) or HCT: 79% overall, 74% Hispanic, 91% NHB, and 83% NHW. CART and HCT were utilized equally (39% and 40%, respectively) and the proportion that received each therapy did not vary by race/ethnicity. Time to CART/HCT, external referral for treatment, receipt of investigational v commercial CART, and use of post-CART consolidative HCT revealed no differences by race/ethnicity. Of the 66 patients (21%) who did not receive cell therapy, 26 had planned for CART or HCT, but did not receive due to disease progression or NRM (n=24; 12 Hispanic, 10 NHW), or insurance barriers (n=2, both Hispanic). After HCT, OS was worse for NHB patients (log-rank p=0.03) with 4y OS of 42% v 85% for NHW and 75% for Hispanic. Post-CART, 4y OS was 40% for NHB v 59% for NHW and 51% for Hispanic, but this difference was not statistically significant. Conclusion In a large real-world cohort of children with high-risk 1st relapse of B-ALL, we found a two-fold increased hazard of death for NHB patients compared to NHW patients, even after adjustment for other SDOH factors and high-risk disease features. In contrast to previous studies of adult patients, children appeared to have equal access to cell therapies across races/ethnicities. We found that Hispanic patients, who comprised >40% of the cohort, had similar survival to NHW children, suggesting that availability of cellular and immunotherapies may be mitigating historically observed disparities for children with relapsed B-ALL.

Abstract Introduction: Patients diagnosed with chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL/SLL) exhibit an elevated risk of developing other cancers (OC) relative to the general population. Historically, chemoimmunotherapy (CIT) represented the cornerstone of CLL/SLL management. A systematic review of clinical trials of CIT for CLL that included 28 studies reported 352/3297 (12.6%) patients developed OC (Csanadi 2022). The introduction of targeted agents beginning in the mid-2010's, including Bruton tyrosine kinase inhibitors (BTKi) and BCL2 inhibitors, has shifted the standard of care toward these novel therapies. In this study, we determined the risk of OC in newly diagnosed CLL/SLL patients cared for at the US Department of Veteran Affairs (VA), The University of Texas MD Anderson Cancer Center, and Mayo Clinic in Rochester, MN. Methods: We identified patients with newly diagnosed CLL/SLL after 1/1/2016 using the VA Central Cancer Registry, MD Anderson, and the Mayo Clinic CLL Databases. The baseline clinical characteristics, CLL treatments, and the occurrence of OC were abstracted by electronic health record (EHR) review. Receipt of CLL directed therapy was categorized into a) CIT only; b) targeted therapy only; c) CIT and targeted therapy; and d) other (including monotherapy with monoclonal antibody therapy). The occurrence of OC was modeled using CLL treatment as a time-dependent variable. Prior and concurrent OC diagnosed within 3 months of CLL/SLL were excluded from analyses, to reduce ascertainment bias. Results: We identified 6844 patients with CLL/SLL who met inclusion criteria. Median follow up was 3.6 years (interquartile range [IQR] 1.9-5.8). The median age at diagnosis of CLL/SLL was 71 years (range, 23 - 102); most patients were white (81%) and male (90%). Although many patients had missing values, among those with available information, IGHV genes were unmutated in 884 (51%), CLL FISH panel showed del17 in 213 (7%), del11q in 389 (13%), trisomy 12 in 674 (23%), and del13q in 1508 patients (50%). A total of 2344 patients received CLL directed therapy during follow-up: 278 (12%) received CIT only, 1809 (77%) received targeted therapy (+/- monoclonal antibody), only 99 (4%) received CIT and targeted therapy and 150 (6%) monoclonal antibody therapy only. Among patients treated with targeted therapies, 950 (50%) received ibrutinib, 381 (20%) received acalabrutinib, 164 (9%) received zanubrutinib, 4 (<1%) received orelabrutinib, 280 (15%) received venetoclax, and 3 (<1%) received sonrotoclax. Other treatments included combinations of a covalent BTKi (cBTKi) and BCL2i in 52 (3%) patients, among others. A total of 583 patients were diagnosed with OC during the study period. Types of OC observed included neoplasms of the prostate (n=129, 22%), lung (n=118, 20%), hematologic malignancies (n=91, 16%), gastrointestinal tract (n=68, 12%), melanoma (n=66, 11%), kidney and bladder (n=44, 8%), head and neck (n=19, 3%), and other/unknown (n=48, 8%). Estimated risk of occurrence of OC was 4.2% (95%CI 3.8-4.8%) at 24 months and 9.7% (95%CI 8.9-10.6%) at 60 months after a diagnosis of CLL/SLL. Multivariable analyses demonstrated that older age (HR: 1.013, 95%CI: 1.00-1.021), male sex (HR: 1.6, 95%CI: 1.1-2.3), and receipt of CLL directed therapy (HR: 1.4, 95%CI: 1.2-1.7) were associated with an increased risk of OC. When considering different types of CLL directed treatments, those who received CIT with or without targeted therapies had the highest risk of development of OC (HR: 1.6, 95%CI: 1.2-2.1). Risk of OC were also increased for those who received CIT only (HR: 1.41, 95%CI: 0.97-2.05) and those who received targeted treatments alone (HR: 1.27, 95%CI: 1.02-1.58). Conclusion: In this large dataset of newly diagnosed patients with CLL/SLL in the past ten years, approximately 10% patients developed OC at 5 years. Receipt of CLL directed therapy was associated with a 40% increased risk of development of OC compared to those patients who did not receive therapy. The risk was highest among patients who received CIT with or without targeted therapy and was still elevated in those who received CIT only or targeted therapy only.

Abstract Background Although myeloproliferative neoplasm-unclassifiable (MPN-U) stands as a distinct entity in the International Consensus Classification (ICC) for myeloproliferative neoplasms, its diagnosis and management remain challenging due to the overlapping clinico-pathological characteristics with other MPNs. In the current study, we describe a well-defined cohort of patients with MPN-U and compare their presentation and outcome with those of a separate cohort with essential thrombocythemia (ET). Methods Diagnostic criteria were according to the ICC (Blood 2022; 140:1200). Non-driver mutations were screened by next-generation sequencing (NGS) and were available for subsets of patients with MPN-U or ET. Conventional statistical methods were employed, using JMP Pro 18.0.0 software SAS Institute, Cary, NC, USA. Results Thirty Mayo Clinic patients who met the ICC criteria for MPN-U (median age 64 years; range 33-94; 60% males) and 658 with ET (median age 60 years; range 18-90; 36% males) were included in the current study. Table 1 outlines a comparative list of presenting characteristics (including mutations), clinical outcomes, and treatment details between patients with MPN-U vs. ET. JAK2 mutations were significantly more prevalent in MPN-U cohort (87% vs. 63% in ET; p<0.01) and CALR mutations less common (3% vs. 25%; p<0.01). Other somatic mutations, including ASXL1, SRSF2, and EZH2 were more frequently observed in the MPN-U group (p<0.05 in all). Abnormal karyotype was reported in 14% of patients with MPN-U vs. 8% with ET (p=0.3). Compared to patients with ET, those with MPN-U were more likely to be males (60% vs. 36%; p<0.01) and, as expected from disease presentation and indications for diagnostic work up of suspected cases, present with venous thrombosis (43% vs. 10%; p<0.01) and palpable splenomegaly (40% vs. 8.5%; p<0.01). Similarly, they were less likely to display thrombocytosis or leukocytosis (p<0.01 for both). Portal, superior mesenteric, and hepatic vein thromboses constituted 77% (vs. 27% in ET; p<0.01) of the venous events in MPN-U; in contrast, the incidences of pre-diagnosis arterial events were similar between the two groups (10% vs. 12%; p=0.7). At a median follow-up of 2.8 years in the MPN-U cohort, 6 (20%) deaths and 1 (3%) leukemic transformation were documented while 3 (10%) patients progressed to meet the diagnostic criteria for polycythemia vera. Four (13%) patients with MPN-U experienced venous thrombo-embolic events (VTEs) including 2 with recurrent VTEs, despite active therapy with systemic anticoagulation and aspirin. The ET cohort was followed for a median of 7.3 years with 161 (24%) deaths, 23 (3%) leukemic transformations, and 66 (10%) VTEs. Among the latter, 27 (41%) had recurrent episodes despite treatment with systemic anticoagulation, aspirin, and/or cytoreductive drugs. Notably, patients with MPN-U were less likely to receive aspirin and cytoreductive therapy during the clinical course (77% vs. 91% and 37% vs. 79%; p<0.01 for both, respectively). Long-term survival rates were similar between MPN-U and ET (15-year survival 70% vs. 65%; p=0.1). Consistent with previous associations seen in ET, patients with JAK2-mutated MPN-U were more likely to be males (58% vs. 30%; p<0.01, Table 2), and display a lower platelet and leukocyte count at the time of diagnosis (p<0.01 for both). These patients were also more likely to present with venous thrombosis (50% vs. 12% in JAK2 wild-type cases; p<0.01) and palpable splenomegaly (46% vs. 9%; p<0.01). Of note, the incidences of pre- and post-diagnosis arterial and post-diagnosis venous events were similar between JAK2-mutated MPN-U vs. JAK2-mutated ET patients (12% vs. 14%; p=0.7, 4% vs. 12.5%; p=0.1, and 15% vs. 12%, p=0.6, respectively). Similarly, long-term outcomes including deaths (15% vs. 26%; p=0.2), leukemic transformations (4% vs. 4%; p=0.9), and 15-year survival rates (78% vs. 60%; p=0.9) were also comparable between the two groups. Conclusion The findings from the current study were not unexpected and underline the ongoing challenges that face formal classification systems in formulating accurate diagnostic criteria for patients with MPN-U whose clinical presentation is biased by disease definitions. Regardless, it is comforting to document a favorable long-term outcome that appeared to be similar to that of ET while venous thrombosis remains a treatment challenge in both groups.

Abstract Introduction: The epidemiology and clinical characteristics of familial myelodysplastic syndromes/acute myeloid leukemia (MDS/AML) remain poorly understood, particularly among Native Hawaiians and Other Pacific Islanders (NHOPI). Methods: To investigate the real-world evidence in this area, we conducted a retrospective study at the Queen's Medical Center (QMC), Hawaii's largest tertiary referral hospital. The data was gathered from QMC's electronic medical record. Familial MDS or familial AML patients in this study were defined as MDS or AML occurring in a patient with a family history of MDS and/or AML. Patients with acute promyelocytic leukemia (APL), as well as those with a family history of APL, were excluded given the differences in disease characteristics and its genetic phenotype from other AML subtypes. Unspecified leukemia was defined when a patient had a family history of leukemia but the specific subtype was unavailable. Some patients underwent comprehensive panel testing, while others had targeted next-generation sequencing (NGS) assays ordered at the discretion of their treating physicians. NGS was performed at Clinical Laboratory Improvement Amendments (CLIA)-certified commercial laboratories. NGS panels typically included the following genes: ASXL1, BCOR, BRAF, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, HRAS, IDH1, IDH2, JAK2, KIT, KRAS, MLL, NPM1, NRAS, PDGFRA, PHF6, PML, PTPN11, RUNX1, SETBP1, STAG2, TET2, TP53, and WT1. Results: Among 1,686 MDS/AML patients presented between January 2012 and July 2023, 12 (0.71 %) had familial MDS/AML and 25 (1.48%) had a family history of unspecified leukemia. While no NHOPI were identified among familial MDS/AML cases, 20% of patients with a family history of unspecified leukemia were NHOPI. The median age at diagnosis of familial MDS/AML was 70 years, and 50% of familial MDS patients had MDS with low blasts based on the World Health Organization 2022 classification. Based on International Consensus Classification 2022 criteria, 25% had MDS, not otherwise specified (NOS) with multilineage dysplasia, and 25% had MDS, NOS with single lineage dysplasia. Among the eight patients with familial MDS, the median overall survival (OS) was 12.7 years, with an estimated 5-year OS rate of 75.0% (95% CI: 12.8–96.1), based on Kaplan–Meier analysis. In contrast, the three patients with familial AML had a median survival of 10.2 months and a 3-year OS estimate of 33.3% (95% CI: 0.90–77.4). For patients with a family history of unspecified leukemia, the median survival was not reached during the follow-up period. The estimated 5-year OS rate was 53.3% (95% CI: 12.5–82.7) for the 10 familial MDS cases and 53.3% (95% CI: 20.9–77.3) for the 13 familial AML cases. When combining all familial cases, the median OS for familial MDS (n = 18) was 12.7 years with a 5-year OS rate of 61.9% (95% CI: 26.8–84.0). The median OS for familial AML (n = 16) was 0.90 years, and the estimated 5-year OS rate was 48.2% (95% CI: 20.8–71.3). When all cases were combined, there was no statistically significant difference in overall survival between patients with familial AML (n = 16) and those with familial MDS (n = 18), based on the log-rank test (p = 0.22). Regarding NGS, ASXL1 mutations were the most frequent in the cohort, detected in six of the 32 NGS tests performed (18.8%). Among patients with familial MDS, recurrent somatic mutations were observed in several genes. ASXL1 mutations were identified in two patients; one had a brother with MDS, and the other had a maternal uncle with unspecified leukemia. DNMT3A mutations were also found in two patients with familial MDS; one had a brother with MDS, and the other had a paternal uncle with MDS. SRSF2 mutations were detected in two patients; one had a brother with MDS, and the other had a granddaughter with leukemia. Additionally, SF3B1 mutations were found in two patients; one had a mother with MDS, and the other had a paternal uncle with MDS. Two patients with familial AML were found to have ASXL1 mutation, both with fathers who had unspecified leukemia. Otherwise, no other repeated mutations were found. None of the cases involved NHOPI patients. Conclusion: Our study offers new insights into familial MDS/AML within Hawaii's multiethnic population. Although no NHOPI patients were identified among the familial cases, our findings underscore the genetic heterogeneity and clinical variability of these disorders.

Abstract Introduction Surface proteins in cancer not only reflect tumor–microenvironment interactions but also serve as targets for diagnostic flow cytometry and precision therapies, including monoclonal antibodies and CAR-T cell therapies. A better understanding of plasma cell immunophenotypes could inform flow cytometric prognostic assays and development of targeted therapies. Methods RNA-seq and Seq-FISH data from CD138-enriched bone marrow plasma cells, along with corresponding clinical annotations, were obtained from the Multiple Myeloma Research Foundation-CoMMpass Study. A curated list of surface genes was assembled by integrating three sources: the Human Protein Atlas (plasma membrane and cell junction annotations), the Gene-Set Enrichment Analysis membrane-associated gene set (Ontology:0016020), and the Cell Surface Protein Atlas (validated high-confidence category). A total of 4,579 genes coding for cell surface proteins were identified. Genes below the 25th variance percentile were removed. PCA (≥90% variance) followed by k-means (k=2, silhouette) and confirmed by hierarchical clustering. A Plasma Cell Maturity (PBM) score was computed using singscore on 84 mature plasma cell–associated genes to compare cluster phenotypes. Pathway analysis was done using GSEA software for Hallmark pathways. Clinical biomarkers and survival kinetics were compared between the clusters. Results 761 newly diagnosed patients were included. (Age: 27-93 years, median overall survival/OS: 29 months/mo). Clustering revealed two groups which we termed Atypical/Aggressive Cluster 1 (C1, n=105, 13.8%) and Classical Cluster 2 (C2, n=656, 86.2%), based on the patterns and clinical characteristics. Among non-missing cases, high-risk disease per the International Myeloma Society–International Myeloma Working Group (IMS–IMWG) definition was observed in 27.7% of patients in C2 (n = 552) and 24.7% in C1 (n = 90) (p = 0.4).C1 exhibited enrichment for t(14;16)-MAF (OR = 2.6, 95% CI: 1.1–6.1, p = 0.04) and t(11;14)-CCND1 (OR = 1.7, CI: 1.01–2.8, p = 0.04). In contrast, hyperdiploidy was more common in C2 (OR for C1 = 0.6, CI: 0.4–0.9, p = 0.04). Elevated LDH was observed in C1 (OR = 2.6, CI: 1.6–4, p < 0.001). Median serum Beta-2 microglobulin was lower in C1.(p=0.009) Upregulated genes in C1 in decreasing order of log Fold Change(logFC): AHNAK, MT-ND1, EEF2, EZR, HLA-B, TXNIP, HLA-E, TRIB1, MCL1, RHOB, CD74, CFLAR, HLA-A, HERPUD1, RPSA, ERN1, HSP90AB1, RAPGEF2, ADGRE5, and LAPTM5. Downregulated genes in C1 in descending order of |logFC|: B2M, SDC1 (CD138), HSP90B1, SEL1L, CALR, CANX, PECAM1, SLAMF7, STT3A, TNFRSF17 (BCMA), FCRL5, STT3B, PALM2AKAP2, CD53, PARP1, CCR2, RPN1, CD38, EDNRB, and LMAN2. Upregulated pathways in C1: proliferation (MYC, E2F, PI3K/AKT/mTOR, KRAS, Wnt); evasion of apoptosis (p53, TGF-β, Notch, NF-κB, IL6/JAK/STAT3); Epithelial to Mesenchymal Transition (angiogenesis, apical junction); inflammatory (interferon, TNF-α, complement, IL2/STAT5); metabolic reprogramming (oxidative phosphorylation, lipid/cholesterol); and stress (DNA repair, unfolded protein response). The PBM score for C1 was significantly lower, suggesting a less differentiated phenotype. C1 patients had inferior survival (n = 93, median OS 43.9 mo, p = 0.04) compared to those in the C2 cluster (n = 559, median OS 102.5 mo). Patients in the C1 + IMS–IMWG high-risk status had the shortest survival (20.7 mo), compared to C1+low (50 mo), C2/high (68.3 mo), and C2+low (not reached). In a multivariable analysis, C1 status (HR = 1.93; 95% CI: 1.1–3.4, p = 0.02) was an independent predictor, along with older age (1.05), UAMS70 (1.02), EMC-92 (1.4). In C1, early (<18 mo) progression occurred in 76.3% (n=71) (p < 0.001). In patients receiving first line of treatment(LOT1), median PFS was 39.7 mo in C1vs. 47.3 mo in C2 (p=0.8). Among patients who received stem cell transplant in LOT1, the median survival for the C2 was 102.5 mo, compared to 44.5 mo for C1 (n = 52) (p = 0.01). Among non-SCT patients on Immunomodulator + Proteasome Inhibitor therapy, C1 (n=28) had shorter survival of 50.0 vs. 71.7 C2 (n=137; p =0.8). Conclusion Our transcriptomic analysis identified a higher-risk group of patients (C1) exhibiting downregulation of myeloma specific markers (CD38, CD138, BCMA, SLAMF7, FCRL5) and inferior outcomes. It is important to diagnose and find appropriate therapy for these patients as they don't obtain the same benefit from the current standard of therapy as the remaining patients.

Abstract Overview: The emergence of effective immune therapies for multiple myeloma has highlighted the importance of understanding the roles of less abundant components within the tumor microenvironment. Single-cell analyses provide snapshots of the functional relationships of individual cells at precise moments in time, as well as insight into the overall cellular composition. By integrating single-cell datasets from multiple studies, we improve our ability to identify trends within rare cell populations, such as macrophages, and explore their clinical implications. We investigate human data here because our prior research of murine models indicated that macrophages expressing C1q, particularly those co-expressing Fcgr4, tend to correlate positively with increased tumor burden. Methods: We combined 56 human bone marrow samples – primarily collected at baseline, post-induction, or post-ASCT – with three publicly available data sets: GSE210079 (post CAR-T bone marrow microenvironment); GSE223060 (single-cell analysis of the MMRF cohort); and GSE271107 (disease progression from healthy donors and MGUS to SMM and NDMM). These data sets were integrated using Seurat to generate robust cellular clusters from over 300,000 cells across 117 samples. We validated our single-cell findings with bulk Affymetrix, whole bone marrow gene expression data (collected at baseline and post-baseline) from the Total Therapy clinical trials (GSE136324). Results: A distinct cluster of C1QA/B/C-expressing macrophages was consistently identified in all single-cell cohorts. These cells co-express FCER1G, CSF1R, and CD68 (markers also expressed in murine C1Q macrophages) and typically cluster adjacent to FCGR3A-expressing monocytes. Within the disease progression cohort, C1Q macrophages were found in all phases of progression: healthy donors, MGUS, SMM, and NDMM. However, C1Q macrophages in progressive disease (SMM and NDMM) have distinct expression features including lower levels of MRC1 and higher levels of APOBEC3A and ISG15 – genes linked to inflammatory responses. Among 11 post-induction samples submitted to lenalidomide maintenance, five with shorter responses displayed elevated expression of APOBEC3A and ISG15 in C1Q-expressing macrophages compared to six samples with longer responses. In a cohort of 22 samples 100 days post-ASCT, seven poor responders showed both an increased frequency of C1Q macrophages and elevated APOBEC3A expression compared to good responders. The MMRF cohort indicated that higher baseline frequencies of C1Q macrophages often preceded rapid disease progression (e.g. MMRF_1720, MMRF_1641). Anecdotal evidence from the CAR-T therapy cohort suggests that expansion of C1Q macrophages could serve as an early warning for tumor recurrence; sample 16 showed retention and expansion of C1Q macrophages 28 days post-CAR-T, that was subsequently followed by increased tumor cell counts at 3 months post-therapy. Analysis of bulk, whole bone marrow gene expression revealed that elevated levels of C1Q genes correlated with poorer outcomes, particularly in post-baseline samples. Multivariate Cox survival analysis revealed that high C1Q expression independently predicted inferior overall survival in post-baseline samples after adjusting for age, ISS stage, high levels of tumor-associated markers (SDC1, JCHAIN, DERL3), and high-risk UAMS7 subtypes (MF, MS, PR). Moreover, post-baseline GEP70 risk scores (from matched bone marrow aspirates) positively correlated with elevated C1Q expression in whole bone marrow samples. Conclusion: Both single-cell and bulk analyses indicate that the persistence of immunosuppressive C1Q macrophages following therapy is associated with inferior clinical outcomes. Although the precise mechanisms are yet to be fully understood, the close proximity of similar macrophages to tumor cells–as observed in other cancers–likely also occurs in myeloma and reflects the crucial relationship between tumor cells and macrophages within the bone marrow. While C1Q macrophages are typically rare in individual samples, analysis of combined cohorts is building evidence of their crucial role in immune cross-talk and therapeutic resistance mechanisms.

Abstract Introduction Ciltacabtagene autoleucel (cilta-cel) has demonstrated unprecedented response rates and progression-free survival (PFS) in relapsed/refractory multiple myeloma (RRMM), but a proportion of patients experience early relapse. Identifying these patients is essential to guide future therapeutic strategies, such as enhanced bridging therapy or consolidation, while avoiding overtreatment in those likely to achieve durable disease control. Methods We conducted a multi-center study of patients treated with cilta-cel at 15 U.S. academic centers. Outcomes were evaluated based on high-risk (HR) features, including functional HR disease (FHR; relapse within 18 months of first-line therapy initiation), true extramedullary disease (EMD), traditional HR cytogenetics as defined in CARTITUDE-1 [deletion 17p, t(4;14), t(14;16)], and a 2024 IMS-IMWG-adapted HR definition (deletion 17p; t(4;14) or t(14;16) with gain 1q or deletion 1p; and gain 1q with deletion 1p). Multivariable Cox regression was used to examine the association of HR features (FHR, adapted IMS-IMWG HR, and EMD, individually and collectively) with PFS while adjusting for baseline ferritin, prior BCMA, and ECOG performance status (PS ≥2). Among patients with ≥18 months of follow-up, we evaluated predictors of early relapse (≤18 months post infusion) using logistic regression. Results Our cohort included 598 patients treated with cilta-cel between 5/2022 and 12/2024 who had available data on all HR features. The median age was 65 years (range 33-83), and the median prior lines of therapy (pLOT) was 5 (range: 1-18, 84% with >3 pLOT); 8% had received prior BCMA-directed therapy, and 27% were penta-refractory. Most patients (88%) received bridging therapy and 30% achieved ≥ partial response. In our cohort, 33% (n=195) had FHR, 43% (n=258) had traditional HR cytogenetics, 42% (n=253) had adapted IMS-IMWG HR disease, and 11% (n=64) had EMD. Median follow up was 10.6 months (range 0.4-34.1). Overall response rate (ORR) and complete response (CR) rates were lower in patients with vs without HR features: FHR (ORR: 89% vs 94%, CR: 61% vs 75%), traditional HR (ORR: 90% vs 94%, CR: 65% vs 74%), adapted IMS-IMWG HR (ORR: 91% vs 94%, CR: 64% vs 75%) and EMD (ORR: 77% vs 94%, CR: 61% vs 71%). Corresponding 12-month PFS was also lower in patients with vs without HR features: FHR (55% vs 79%), traditional HR (63% vs 78%), adapted IMS-IMWG HR (61% vs 80%) and EMD (59% vs 73%). ORR, CR rate, and 12-month PFS in patients without any HR features compared to those with ≥1 HR feature were 96% vs 90%, 81% vs 64%, and 83% vs 65%, respectively. In multivariable models, each HR feature (FHR, adapted IMS-IMWG HR, and EMD) was independently associated with inferior PFS after adjusting for baseline ferritin, prior BCMA, and ECOG PS ≥ 2. However, because early relapse cannot always be identified a priori based on traditional risk factors, we sought to identify predictors of relapse within 18 months of cilta-cel in a subset of patients with ≥18 months of follow-up (N=247; infused by 12/2023). Notably, while FHR (OR=3.04, 95% CI=1.59-5.89) and adapted IMS-IMWG HR (OR=2.07, 95% CI=1.10-3.89) were independently associated with odds of relapse within 18 months, EMD was not (OR=0.90, 95% CI=0.32, 2.40) when accounting for prior BCMA, ECOG PS ≥ 2, and baseline ferritin. We also used a time-varying Cox model to examine each HR feature associated with PFS at two time periods, <18 and ≥18 months, while adjusting for baseline ferritin, ECOG PS, and prior BCMA. We confirmed that FHR and adapted IMS-IMWG HR were both associated with relapse <18 months (HR=2.05, 95% CI=1.48-2.83 and HR=1.56, 95% CI=1.11-2.19) but not in the ≥18-month time period (HR=0.70, 95% CI=0.19-2.59 and HR=0.76, 95% CI=0.24-2.40). The magnitude of the association for EMD with PFS was similar across both time periods (<18 months HR=1.67, 95% CI=1.09-2.57 and ≥18 months HR=2.17, 95% CI=0.45-10.40). Conclusion While cilta-cel leads to high response rates and durable PFS in RRMM, a subset of patients with FHR and adapted IMS-IMWG HR remains at increased risk for early relapse. In this large multi-center cohort, we describe PFS outcomes across high-risk subgroups and identify key predictors of relapse within 18 months of cilta-cel. These findings inform risk-adapted therapeutic strategies and interventional trials, including bridging, consolidation, or maintenance approaches, to improve outcomes in the highest-risk RRMM patients.

Abstract Introduction: Cilta-cel is approved in the US and the EU for the treatment of patients (pts) with lenalidomide-refractory multiple myeloma (MM) after ≥1 prior line of therapy (pLOT), including a proteasome inhibitor and an immunomodulatory agent based on the CARTITUDE-1 (CART-1, NCT03548207) and CARTITUDE-4 (CART-4, NCT04181827) studies. Cilta-cel led to deep and durable responses and significant survival benefit in pts with relapsed/refractory MM (RRMM) after ≥3 pLOT in CART-1. In CART-4, cilta-cel led to a significant overall survival benefit with a higher proportion of pts achieving deep, sustained minimal residual disease negativity vs standard of care in pts with lenalidomide-refractory MM after 1–3 pLOT. We investigated the mechanism of action of cilta-cel by correlating biomarkers from peripheral blood and the bone marrow TME with progression-free survival (PFS) and number of pLOT in pts with RRMM from CART-1 and CART-4. Methods: Biomarker analyses were performed using peripheral blood and bone marrow aspirates (BMAs) collected in both CART-1 and CART-4 studies. Immunophenotyping by flow cytometry was performed using peripheral blood at baseline/time of apheresis in samples from both studies. Immune fitness at baseline was assessed in pts by pLOT and in association with PFS. Gene set enrichment scores were derived from RNA sequencing data of the TME using BMAs. Mixed-effects models were used to identify signatures/pathways modulated over time (day [D] 28 and at 6 months [mo] post infusion vs screening) and in association with PFS and pLOT. Results: In total, 176 CART-4 and 97 CART-1 pts received cilta-cel as study treatment. Immunophenotyping data were available from 248 peripheral blood samples (1 pLOT, n=56; 2 pLOT, n=61; ≥3 pLOT, n=131). At apheresis, CD4+ naïve T cells (%) were higher in pts with 1 or 2 pLOT, compared with those with ≥3 pLOT, while no difference was found in pts with ≥3 pLOT with further breakdown (i.e., 3–4 vs 5–6 vs ≥7 pLOT). Further, higher baseline levels of CD4+ naïve T cells were associated with longer PFS. These data suggest that the negative impact on peripheral immune fitness with the addition of LOT may plateau when pts have received ≥3 pLOT. TME gene expression data were available from 148 BMA samples (screening, n=50; D28, n=50; 6 mo, n=48) from CART-4. Analyses of gene expression signatures suggest depletion of B cells and antibodies at D28 post cilta-cel infusion, with partial recovery at 6 mo. This was corroborated in parallel by flow cytometry and immunoglobulin quantification. Further, elevated expression of genes associated with myeloid cells, including tumor-associated macrophages (TAM, likely M1), and of genes associated with cytotoxic T cells were also observed at D28. Elevated expression of genes associated with B-cell receptors, T-cell differentiation and activation, and cytokine signaling pathways were found at both D28 and 6 mo. Pts with longer PFS (>18 mo) had higher levels of M1 TAM at D28, while those with shorter PFS had higher levels of regulatory T cells and more suppressed interferon pathway genes at 6 mo, suggesting that relapse may be associated with a more suppressive immune response. In pts with fewer pLOT, more profound B-cell depletion on D28, better recovery at 6 mo, and elevated B-cell receptor signaling were inferred from gene expression data. Pts with 1 pLOT also demonstrated higher elevation of M1 TAM expression on D28 from screening as compared with pts with 3 pLOT, similar to what was observed in pts with longer PFS. Conclusions: Correlative biomarker data suggest that longer PFS is associated with better immune fitness at baseline and stronger immune responses post cilta-cel infusion, as observed in peripheral blood and within the TME of pts with RRMM in CART-1 and CART-4. The peripheral immune fitness was more pronounced in pts with 1 and 2 pLOT vs 3 pLOT and beyond, where deterioration plateaued. This suggests the impact of T-cell immune fitness on PFS may be limited beyond the third LOT. Importantly, other covariates, including factors within the immune TME and tumor burden, may play a significant role in balancing this compromised intrinsic T-cell immune fitness at apheresis, thereby contributing to PFS durability after 3 pLOT. Overall, these results support increased benefits in treating pts with MM with cilta-cel in earlier LOTs.