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Abstract Introduction Diffuse large B-cell lymphoma (DLBCL) is a heterogenous disease with varied expressions of CD30. Brentuximab vedotin (BV) is a CD30-directed antibody-drug conjugate approved for treatment of patients with relapsed or refractory DLBCL in combination with lenalidomide (Len) and rituximab (R). In the phase 3 ECHELON-3 study (NCT04404283), BV + Len + R showed significant overall survival (OS) benefit compared with placebo + Len + R in patients with relapsed or refractory DLBCL. Subgroup analysis from this study showed that BV + Len + R provided clinical benefit regardless of CD30 expression level. We hypothesized that even sub-threshold levels of CD30 expression, below the detection limits of immunohistochemistry (IHC), may be sufficient to elicit the antitumor activity of BV. Here, we further investigated whether trace amounts of CD30 staining are required for patients to benefit from BV + Len + R. Methods In the ECHELON-3 study, patients with relapsed or refractory DLBCL were randomized 1:1 to receive BV + Len + R or placebo + Len + R. The primary endpoint was OS, with progression-free survival (PFS) and objective response rate (ORR), per Lugano 2014, as key secondary endpoints. CD30 expression was assessed by IHC by central and/or local testing. CD30 positivity was scored as the percentage of CD30 positive cells out of neoplastic cells or out of total lymphocytes, when neoplastic cells could not be distinguished. In this updated analysis, patients with CD30 <1% staining by central laboratory IHC were further grouped into CD30 <1% with trace staining and CD30 <1% with no staining. Results Overall, 60 patients in the BV + Len + R group had CD30 <1% expression; of these, 34 had CD30 <1% with trace staining and 26 had CD30 <1% with no staining. In the placebo + Len + R group, 63 patients had CD30 <1% expression; of these, 36 had CD30 <1% with trace staining and 27 had CD30 <1% with no staining. In the overall CD30 <1% groups, numerically greater OS and PFS benefits were observed with BV + Len + R vs placebo + Len + R (HR for OS, 0.57; 95% CI, 0.36-0.89 and HR for PFS, 0.53; 95% CI, 0.34-0.82). In patients with CD30 <1% with trace staining, BV + Len + R showed a numerically higher OS compared with placebo + Len + R, with HR of 0.48 (95% CI, 0.26-0.90); median OS was 15.6 vs 5.2 months. In patients with CD30 <1% with no staining, there was a trend toward higher OS with BV + Len + R vs placebo + Len + R, with HR of 0.66 (95% CI, 0.34-1.28); median OS was 14.8 vs 11.8 months. Similarly, in patients with CD30 <1% with trace staining, BV + Len + R showed a trend toward longer PFS compared with placebo + Len + R, with HR of 0.60 (95% CI, 0.33-1.11); median PFS was 2.8 vs 1.5 months. In patients with CD30 <1% with no staining, a numerically longer PFS benefit was observed with BV + Len + R vs placebo + Len + R, with HR of 0.41 (95% CI, 0.21-0.79); median PFS was 4.2 vs 2.7 months. In the overall groups, ORR was 60.0% with BV + Len + R and 34.9% with placebo + Len + R. Higher ORR was observed with BV + Len + R compared with placebo + Len + R in both CD30 <1% with trace staining (55.9% vs 25.0%) and CD30 <1% with no staining (65.4% vs 48.1%) groups. Conclusions Results from this updated analysis indicate that visible CD30 detection by IHC is not required for response to BV + Len + R in patients with relapsed or refractory DLBCL. Treatment with BV + Len + R showed efficacy benefit compared with placebo + Len + R regardless of CD30 expression level, including in patients with no visible CD30 IHC staining. These results are consistent with those from the overall ECHELON-3 study population, in which significant improvement in OS was demonstrated with BV + Len + R compared with placebo + Len + R.

Abstract Introduction Although chemo-free regimens are increasingly used in elderly patients with large B-cell lymphoma (LBCL), most still receive conventional chemoimmunotherapy. Patients up to 75–80 years old are usually treated with full-dose R-CHOP, while 80+ patients receive the attenuated R-miniCHOP regimen as standard of care. Prior studies have shown that in patients aged 65+ years, R-CHOP was associated with improved survival based on propensity score matching (PSM) analysis (Al-Sarayfi, Am J Hematol, 2023), though this did not include comorbidity data. Furthermore, no formal studies have focused specifically on 80+ patients. We aimed to perform a PSM comparison of R-CHOP versus R-miniCHOP to better inform treatment decisions in this population. Methods We harmonized and pooled data from 237 LBCL patients receiving chemotherapy with rituximab (out of all 263 80+ patients) from the prospective LEO cohort (USA, n=147; 2015–2020) and NiHiL registry (Czech Republic, single center, n=116; 2010–2023). Of them, 205 (86%) receiving anthracycline(A)-based regimens were included. Baseline characteristics, comorbidities, treatments, and outcomes were collected. PSM (1:1, caliper 0.2) was performed to compare R-CHOP and R-miniCHOP using age, ECOG performance status (PS), clinical stage, lactate dehydrogenase (LDH), and major comorbidities (heart disease, history of stroke, and other recent cancer) as matching variables. The endpoints were overall survival (OS), event-free survival (EFS), and lymphoma-specific survival (LSS, defined as death attributed to lymphoma progression). Results Among 205 A-treated patients, median age was 83 years (range 80–99); 30% had ECOG PS 2–4, 67% clinical stage III–IV, 34% ≥2 involved extranodal sites, 59% elevated LDH, and 58% had International Prognostic Index (IPI) scores 3–5. Median follow-up was 5.5 years; median OS and EFS were 4.1 and 3.4 years, resp. A-based regimens comprised full-dose R-CHOP-like (n=79; 39%; R-CHOP n=74, DA-EPOCH-R n=5) and R-miniCHOP (n=126; 61%). Patients receiving R-CHOP-like regimens had more favorable baseline characteristics (median age 82 vs 83 years, P=0.04; ECOG PS 2–4: 16% vs 39%, P<0.01; IPI 3–5: 46% vs 66%, P=0.03) and a lower, though not statistically significant, comorbidity burden (mean 1.14 vs 1.39; heart disease 35% vs 45%, P=0.22; history of stroke 4% vs 6%, P=0.64; other cancer 6% vs 5%, P=0.87). R-CHOP-like regimens vs R-miniCHOP had superior OS (median 6.3 vs 3.4 years; HR=0.61, 95% CI 0.42–0.90; P=0.01) and EFS (median 5.3 vs 2.1 years; HR=0.58, 95% CI 0.40–0.83; P<0.01), with no significant difference in LSS (2-year 89% vs 82%, HR=0.77, 95% CI 0.39–1.54, P=0.46). To mitigate selection bias, we performed PSM on patients with available baseline characteristics treated with R-CHOP (n=69) and R-miniCHOP (n=121), resulting in 63 matched pairs. Matched cohorts were well-balanced on age (median 82 years in both cohorts; P=0.68), ECOG PS 2–4 (17% vs 19%; P=0.82), IPI 3–5 (52% vs. 59%; P=0.41), and comorbidity burden (mean 1.10 vs. 1.29; P=0.30). The presence of heart disease (40% in both cohorts), history of stroke (5% vs 6%), and cancer (5% vs 6%) were similar. Survival modestly favored R-CHOP, but differences were not significant: median OS 5.3 vs 3.5 years (HR=0.73; 95% CI 0.46–1.15; P=0.17), median EFS 3.8 vs 2.8 years (HR=0.76; 95% CI 0.49–1.18; P=0.23), and 2-year LSS 88% vs 84% (HR=1.09; 95% CI 0.45–2.63; P=0.85). Treatment-related mortality was similar in both cohorts (16%). Among R-miniCHOP patients, survival outcomes did not differ between matched (n=63) and unmatched (n=63) groups (OS P=0.72; EFS P=0.23; LSS P=0.27). Unmatched (n=16) R-CHOP patients had a trend toward improved survival compared to matched (n=63) individuals (OS P=0.10; EFS P=0.049; LSS P=0.24). Conclusion This is the first PSM-based analysis comparing R-CHOP and R-miniCHOP in LBCL patients 80+ years old. Despite inherent limitations of a non-randomized design and limited number of matched patients, our findings – derived from two prospective cohorts – suggest that R-miniCHOP may offer outcomes comparable to R-CHOP, particularly with respect to LSS. While these results support R-miniCHOP as an appropriate frontline option, treatment decisions remain highly individualized. These data may help inform clinical decision-making and provide a basis for designing future trials targeting this population, where R-miniCHOP could serve as a comparator arm. Funding: NU21-03-00411, U01 CA195568.

Abstract Introduction: The CARTITUDE-4 (NCT04181827) trial compared cilta-cel, a chimeric antigen receptor (CAR)-T cell treatment (tx) targeting B-cell maturation antigen (BCMA), with 2 standard-of-care regimens in patients (pts) with RRMM and 1–3 prior lines of therapy (LOT). Cilta-cel significantly improved overall survival (hazard ratio [HR] 0.55) and progression-free survival (PFS; HR 0.29). The DREAMM-7 (NCT04246047) and DREAMM-8 (NCT04484623) trials evaluated belamaf, an anti-BCMA antibody-drug conjugate (ADC), in combination with bortezomib and dexamethasone (BVd) and with pomalidomide and dexamethasone (BPd), respectively. Both trials demonstrated improved survival and response rates with belamaf in pts with ≥1 prior LOT. International Myeloma Working Group (IMWG) guidance for RRMM tx recommends using anti-BCMA T-cell redirecting therapy (TCRT), such as CAR-T (eg, cilta-cel), before anti-BCMA ADCs (eg, belamaf). As cilta-cel and belamaf have not been compared head to head, we conducted unanchored matching-adjusted indirect comparisons (MAICs) to estimate relative efficacies using CARTITUDE-4 study individual patient data (IPD) and published data from DREAMM-7 and DREAMM-8. Methods: Unanchored MAICs were performed using IPD from apheresed pts in the CARTITUDE-4 cilta-cel arm. Eligibility criteriafrom DREAMM-7 and DREAMM-8 were applied to the cilta-cel cohort. Further adjustments were made by weighting cilta-cel IPDto match reported baseline characteristics (including refractory status [for DREAMM-8], cytogenetic risk, International Staging System stage, and presence of extramedullary disease) from DREAMM-7 and DREAMM-8. Outcomes were compared using weighted IPD for cilta-cel and reported response rates and simulated IPD based on published Kaplan–Meier PFS curves for BVd and BPd. For each matched population, we compared PFS, ORR, and very good partial response or better (≥VGPR) and complete response or better (≥CR) rates. A weighted Cox proportional hazards model was used to estimate PFS HRs and 95% CIs. A weighted logistic regression analysis was used to derive relative response ratios (RRs) with 95% CIs to compare relative tx effects. Results: The MAICs included 208 apheresed pts from CARTITUDE-4 (cilta-cel), 243 pts from DREAMM-7 (BVd), and 155 pts from DREAMM-8 (BPd). To form comparable cohorts, we excluded cilta-cel pts who would not have been eligible for DREAMM-7 (n=87) or DREAMM-8 (n=55). Cilta-cel pts were most commonly excluded from the DREAMM-7 MAIC due to bortezomib refractoriness or anti-CD38 refractoriness (n=55 and n=50, respectively), and from the DREAMM-8 MAIC due to bortezomib refractoriness (n=55). After exclusions, 121 and 153 cilta-cel pts remained in the MAICs with BVd and BPd, respectively. After adjustment, cilta-cel was associated with significantly lower risk of progression or death compared with BVd (HR 0.46 [95% CI 0.28–0.75]; P=0.0020) and BPd (HR 0.61 [95% CI 0.39–0.96]; P=0.0320). ORR was significantly higher with cilta-cel vs BVd (92.9% vs 82.7%; RR 1.12 [95% CI 1.03–1.22]; P=0.0087) and vs BPd (89.3% vs 77.4%; RR 1.15 [95% CI 1.04–1.29]; P=0.0100). Rates of ≥VGPR and ≥CR were also higher with cilta-cel vs BVd (≥VGPR: 89.7% vs 65.8%; RR 1.36 [95% CI 1.21–1.53]; ≥CR: 86.0% vs 34.6%; RR 2.49 [95% CI 2.04–3.03]; both P<0.0001) and vs BPd (≥VGPR: 86.6% vs 63.9%; RR 1.36 [95% CI 1.18–1.56]; ≥CR: 81.8% vs 40.0%; RR 2.05 [95% CI 1.65–2.53]; both P<0.0001). Sensitivity analyses were consistent with the adjusted comparisons and showed statistically significant PFS and tx response benefits with cilta-cel vs BVd and BPd. Conclusions: These MAICs demonstrated superior PFS and response rates with cilta-cel compared with 2 belamaf-containing regimens (BVd and BPd). Results should be interpreted with caution as there were substantial differences in the pt populations of CARTITUDE-4 vs DREAMM-7 and DREAMM-8. However, adjusted cilta-cel cohort sizes remained large enough for robust comparisons that showed statistically significant differences across efficacy outcomes. Another limitation is the remaining potential unmeasured residual confounding differences. Nonetheless, these findings support IMWG guidance recommending anti-BCMA TCRTs prior to ADCs and provide valuable comparative evidence in the absence of head-to-head trials.

Abstract Introduction: Bispecific T-cell engagers (TCE) targeting BCMA (teclistamab, elranatamab) and GPRC5D (talquetamab) are important therapeutic options in relapsed/refractory MM (RRMM). However, data on the independent prognostic impact of individual cytogenetic abnormalities and functional high-risk MM on outcomes with TCEs remains limited. Methods We included RRMM patients treated with BCMA TCEs (teclistamab, elranatamab) and talquetamab across 15 centers in the US. Patients where TCEs were used only as bridging therapy to CAR-T were excluded. High-risk cytogenetic abnormalities (HRCA) included del(17p), t(4;14), t(14;16), 1q gain/amplification (1q21+), del(1p) before initiation of TCE. Functional high-risk disease (FHRMM) was defined as PFS <18 months with frontline therapy. Extramedullary disease (EMD) included visceral or soft tissue disease and excluded paraskeletal disease. Progression-free survival (PFS) was estimated from TCE initiation using the Kaplan–Meier method and compared using the log-rank test. Univariate and multivariable Cox proportional hazards models were used to identify predictors of PFS in the entire cohort and the subcohorts of BCMA TCEs and talquetamab (Talq). Results We analyzed 943 treatment initiations with TCEs in RRMM, comprising 577 BCMA-directed TCEs [teclistamab (n=436) and elranatamab (n=141)] and 366 talquetamab initiations. The median follow-up from TCE initiation was 13.4 months (95% CI: 12.5–14.2) and median age was 68 years (interquartile range 61-75 years). Two ore more HRCAs were noted in 30% of the cohort (34% in Talq vs. 28% in BCMA TCEs, p=0.04), EMD was present in 21% of patients (26% in Talq vs. 18% in BCMA TCEs, p=0.002), and 45.5% of patients had FHRMM (47% in Talq vs. 45% in BCMA TCE, p=0.54). The median prior lines of therapy was 6 (interquartile range: 5-8), with 92% being triple-class refractory (TCR); 60% received prior BCMA-directed therapy (85% in Talq vs. 45% in BCMA TCE, p<0.0001) and 45% had prior CAR-T in 45% (57% in Talq vs. 37% in BCMA TCE, p<0.001). The best overall response rate (ORR) was 67.1 % for the entire cohort (66.4% for BCMA cohort and 68.2% for Talq), with 32.5% patients achieving a ≥ complete response. The median PFS was 7.7 months (95% CI: 6.7–8.6) for the entire cohort, with a median PFS of 10.1 months (95% CI: 7.5-13.4) for teclistamab and 10.1 months (95% CI: 3.9-NR) for elranatamab. In the more heavily pretreated talq cohort, the median PFS was 6.4 months (95% CI: 5.1-7.5). In a univariate analysis (UVA), several HRCAs were associated with inferior PFS−del(17p) (HR 1.59), t(4;14) (HR 1.43), del(1p) (HR 1.54), and ≥2 HRCAs (HR 1.64), all p<0.01. Apart from HRCAs, adverse disease characteristics included FHRMM (HR 1.20) and EMD (HR 1.46); all p<0.05. Among laboratory markers, hemoglobin <9 g/dL (HR 2.10), platelet count <75 ×10⁹/L (HR 1.96), and elevated ferritin (≥600 ng/mL; HR 2.17) (all p<0.01) were prognostic for PFS. ECOG ≥2 (HR 1.62), prior BCMA-directed therapy (HR 1.56), and prior CAR-T (HR 1.44) (all p<0.001) were also associated with inferior PFS. In a multivariable analysis (MVA), prior BCMA therapy (HR 1.72, p<0.0001), ferritin >600 ng/mL (HR 1.68, p<0.0001), hemoglobin <9 g/dL (HR 1.53, p=0.001), ECOG PS ≥2 (HR 1.52, p=0.0009), del(17p) (HR 1.44, p=0.0034) and FHRMM (HR 1.26, p=0.047), were associated with inferior PFS. Within the talq cohort (n=366), EMD (HR 1.64), del(17p) (HR 1.42), del(1p) (HR 1.54), FHRMM (HR 1.34), ECOG ≥2 (HR 1.56), ferritin >600 (HR 1.88), hemoglobin <9 g/dL (HR 1.6), platelet count <75 ×10⁹/L (HR 1.36) and leukopenia <0.25 x 10⁹/L (HR 1.52) were adverse prognostic markers on UVA. A MVA confirmed the independent impact of ferritin >600 ng/mL (HR: 1.77), ECOG ≥2 (HR 1.61) and functional high-risk status (HR 1.52) on PFS, whereas del(17p) and EMD were trending toward significance. Within the BCMA TCE cohort (n=577), prior BCMA therapy (HR 1.9), ferritin >600 (HR 1.79), ECOG ≥2 (HR 1.55), Hb <9 g/dL (HR 1.54), and del(17p) (HR 1.52) were independently associated with inferior PFS on a MVA.Conclusions: In this large real-world cohort of TCE, outcomes varied by fitness, disease biology, and treatment history. The ECOG PS, elevated ferritin, functional high-risk status and del(17p) were consistently associated with inferior PFS. Prior BCMA exposure was an independent risk factor for inferior PFS in the BCMA TCE cohort, but not with talquetamab.

Abstract Background: Prognostication for patients with non-transformed relapsed/refractory (R/R) follicular lymphoma (FL) is not well defined. Progression of disease within 24 months (POD24) and number of lines of prior therapy are commonly used to benchmark outcomes and for trial eligibility in this space. However, a comprehensive model for risk prediction in R/R FL is lacking. Here we utilize patients from the LEO Consortium for Real World Evidence (CReWE) and Iowa/Mayo Clinic Lymphoma SPORE MER to develop a clinical prediction model for R/R FL. Methods: Patients with grade 1-3A FL were prospectively enrolled at diagnosis in the MER and/or initiated second line or later therapy (2L+) for non-transformed FL at one of the 8 LEO Centers from a previous LEO CReWE study (Casulo et al, Lancet Haem 2022). All available lines of therapy were abstracted; lines of therapy after histologic transformation were not used in the analyses. A management plan of observation was considered as a type of therapy in the 1L setting but not in the 2L+ setting. Clinical variables and outcomes were abstracted at each line of therapy. Variables considered for modeling included demographics, clinical labs, treatment history, and pertinent clinical variables (including FLIPI and FLIPI24 components). Multiple imputation was used to address missing data in modeling; beta-2 microglobulin (B2M) was unable to be imputed due to the amount of missing data. Index therapy was defined as the date of initiation of a line of therapy (2L, 3L or 4L) for non-transformed FL. The primary endpoint for model development was the time from index therapy until the histologic transformation or lymphoma-related death (HT/LD). Cox proportional hazards models were used for model development. Modeling was first performed separately for each line of therapy and then evaluated across lines. Bootstrapping on imputed datasets was used to assess optimism in model performance. Results: N=1001 patients initiated 2L+ therapy and were utilized for modeling. Of these patients, N=654 initiated 3L and N=344 initiated 4L therapy. Median age at index therapy was (60, 61, and 62) for lines 2-4, respectively. Median follow-up by line of therapy was 8.2, 6.1, and 6,1 years and number of HT/LD events for modeling was 272, 154, and 88, respectively. Observed outcomes decreased modestly as the line therapy increased: median event-free (1.6, 1.5, and 1.2 years) and overall survival (17.6 years, 14.5 years, and 12.3 years), for lines 2-4, respectively. 5-year estimates of HT/LD by line of therapy were 21.6% (95% CI: 18.9-24.3), 23.7% (95% CI: 19.9-27.4) and 29.3% (95% CI: 23.3-34.7), respectively. A clinical prediction model was independently developed for each line of therapy; the final model for each line consisted of the same variables: increasing age, male sex, higher LDH, lower hemoglobin, higher white blood cell count, prior immunochemotherapy exposure, and shorter time since initial diagnosis. The parameter estimates for these variables were broadly similar across the different lines of therapy. The model output is an individual patient's risk of HT/LD. Patients with high-risk FLP-R, as defined using the upper quartile of FLP-R risk scores for each line, had observed 5 year HT/LD rates of 43%, 44% and 51% in lines 2-4, respectively. In contrast, patients with the lower quartile of FLP-R risk scores had observed 5 year HT/LD rates of 10%, 6% and 8% in lines 2-4, respectively. The optimism-corrected c-statistic for the FLP-R model across all lines of therapy was 0.685. This added significant information beyond FLIPI diagnosis (c=0.533) FLIPI at index line (c=0.563), the line of therapy (c=0.525), POD24 status (c=0.578), or all 4 variables combined (c=0.614). Conclusions: The FLP-R model identifies a group of patients with non-transformed FL in the R/R setting who are at very high risk of transformation and/or lymphoma-related death across lines of therapy. FLP-R features 4 of the 5 components of the 1L FLIPI24 prediction model (B2M was unavailable for modeling) with the addition of sex, treatment history and time since initial diagnosis. The number of prior therapies is not sufficient to identify high-risk populations for clinical trial enrichment in the R/R FL setting and model discrimination for FLP-R was greatly improved over FLIPI and/or POD24 across lines of therapy. A Shiny app will be provided for model implementation; external validation is planned.

Abstract Introduction Short diagnosis-to-treatment interval (DTI) is associated with aggressive disease biology and inferior outcomes in diffuse large B-cell lymphoma (DLBCL), and is recognized as a potential source of selection bias in clinical trials if not properly addressed. However, its prognostic significance in follicular lymphoma (FL) remains poorly characterized. We aimed to evaluate the prognostic significance of DTI in newly diagnosed FL patients who received frontline (1L) immunochemotherapy (IC), using a large international dataset and an independent external validation cohort. Methods For the discovery dataset, we evaluated patients diagnosed between 2002 and 2018 from ten observational cohorts as part of the FLIPI24 Consortium. External validation was conducted using data from patients enrolled in the Lymphoma Epidemiology of Outcomes (LEO) Cohort between 2010 and 2015. All patients had FL grade 1–3A and received 1L IC within 100 days of diagnosis. Patients with a concurrent DLBCL were excluded. Missing baseline laboratory values were addressed via multiple imputation. The primary endpoint was event-free survival at 24 months (EFS24); secondary endpoint was 5-year overall survival (OS), both calculated from treatment initiation. DTI was analyzed as continuous (via splines) and dichotomized variable (≤14 vs >14 days; as defined in DLBCL). Results In the discovery cohort (n=3,907), median age was 61 years (IQR 53–69), and 50% were male; 49% of patients were high-risk according to FLIPI, 26% according to PRIMA-PI, and 38% according to FLIPI24. Included patients received R-CHOP (54%), R-CVP (26%), or B-R (20%) as 1L treatment, followed by anti-CD20 maintenance in 60%. The median DTI was 30 days (IQR 17–48). Using the 14-day cut-off, 851 patients (22%) had short DTI. These patients had more adverse baseline characteristics, including B symptoms (42% vs 32%, P<0.01), ECOG performance status ≥2 (15% vs 8%, P<0.01), elevated LDH (51% vs 40%, P<0.01), hemoglobin <12 g/dL (30% vs 17%, P<0.01), and elevated β2-microglobulin (56% vs 44%, P<0.01). Prognostic indices (PIs) were also more frequently high-risk in the short-DTI group: FLIPI (56% vs 47%), PRIMA-PI (36% vs 24%), and FLIPI24 (51% vs 34%, all P<0.01). Spline modeling showed a decreasing EFS24 rate with increasing DTI, reaching a plateau at 30–40 days. In logistic regression model, each additional week of DTI improved EFS24 (OR 0.92, P<0.01). DTI attenuated but remained prognostic after adjusting for PIs (OR 0.93 for FLIPI, 0.95 for PRIMA-PI, 0.96 for FLIPI24, all P<0.01). When analyzed as a dichotomized variable, short DTI was associated with inferior EFS24: OR 1.74 adjusted for FLIPI, 1.63 for PRIMA-PI, and 1.53 for FLIPI24 (all P<0.01). The 2-year EFS of short vs long DTI groups was 71% vs 82% (HR 1.50, 95% CI 1.34–1.67, P<0.01), 5-year OS was 80% vs 86% (HR 1.38, 95% CI 1.21–1.56, P<0.01), and the 5-year cumulative risk of histologic transformation was 7.7% vs. 5.4% (P<0.01). In the validation cohort (n=516), median age was 61 years (IQR 52–69 years), 55% were male; 36% of patients were high-risk according to FLIPI; 29% according to PRIMA-PI, and 33% according to FLIPI24. Patients received B-R (59%) or R-CHOP (41%) as 1L treatment. The median DTI was 31 days (IQR 19–48), 84 patients (16%) had DTI ≤14 days. Similar patterns were observed; patients with short DTI had adverse baseline characteristics, PIs, and shorter 2-year EFS (72% vs 84%, HR 1.69, 95% CI 1.13–2.55, P=0.01). DTI remained associated with EFS24 when analyzed as a continuous variable (per week: OR 0.88 unadjusted, 0.90 with FLIPI, 0.89 with PRIMA-PI, and 0.89 with FLIPI24), and dichotomized (≤14 vs >14 days: OR 1.83 adjusted for FLIPI, 1.88 for PRIMA-PI, and 1.73 for FLIPI24). Conclusion Short DTI, defined as ≤14 days (observed in 22% of FL patients vs 46% in DLBCL), is a strong and independent predictor of inferior outcomes in newly diagnosed FL patients treated with IC. While DTI correlates with adverse baseline features and established PIs, it retains independent prognostic value. Although a 14-day threshold is reasonable for risk modeling, DTI contains greater informational value when modeled as a continuous variable. Among PIs, FLIPI24 most strongly attenuated the DTI effect, underscoring its superior discriminative power over FLIPI and PRIMA-PI. Clinical trials designs should mitigate any potential barriers to enrollment of FL patients requiring urgent therapy.

Abstract Background Myeloproliferative neoplasms (MPNs) can progress from chronic phase to accelerated or blast phase (MPN-AP/BP), a transition with poor prognosis and limited treatment options. While some abnormalities have been described, the genomic and clonal drivers of transformation remain poorly defined. We characterized mutational and structural alterations in MPN-AP/BP, leveraging paired samples to trace clonal evolution. Methods We profiled 186 samples from 160 individuals, including 159 MPN-AP/BP and 27 chronic-phase MPN samples (26 MF, 1 PV), using targeted sequencing of a 588 gene panel (mean depth: 709x). Paired pre- and post-transformation samples were available for 26 patients (n= 52). A consensus pipeline was used to detect somatic mutations, copy number variations (CNVs), and copy-neutral loss of heterozygosity (cnLOH). Clinical cytogenetic data were integrated when available. Single-cell validation is ongoing. Results Genomic complexity was widespread: 99% of patients harbored ≥1 oncogenic mutation (median 4; range 1–10). In total, 859 mutations were identified, most commonly in JAK2 (68%), ASXL1 (28%), TET2 (26%), SRSF2 (24%), TP53 (22%), and RUNX1 (22%). 684 structural alterations were identified in 86% of patients (median 3; range 1-20), including arm-level (22.5%), segmental (>5 Mb; 60%), and focal (<2 Mb; 9%) alterations. Recurrent events included 9p cnLOH (16%), del(5q) (13%), del(17p) (10%), and focal deletion of 21q22.12 involving RUNX1 (10%). Complex karyotypes (≥3 abnormalities) were observed in 55% of patients. Biallelic mutations accounted for 21% (183/859) of mutations, affecting 58% of patients across 21 genes, most frequently JAK2 V617F (28%), TP53 (17%) and TET2 (14%). Patients with biallelic mutations in these genes had significantly higher blast percentages compared to those with monoallelic mutations (p<0.05), highlighting an association with aggressive disease. In 26 patients with longitudinal samples (chronic phase MPN and MPN-AP/BP), 87% (125/144) of mutations were already detectable during the chronic phase, on average more than 7 years prior to transformation. Only 11% (16/144) of mutations were newly acquired, including additional RUNX1 and TP53 hits, or structural changes that converted pre-existing JAK2 V617F and TP53 R248Q mutations from monoallelic to biallelic via 9p cnLOH or 17p loss, respectively. These findings suggest transformation is often driven by outgrowth of pre-existing high-risk clones, indicating that these clones likely have a competitive advantage and that the mutations within these clones have a cooperative biological interaction which underlies this competitive advantage. To investigate this hypothesis, we examined whether patterns of recurrent co-mutations were identifiable in this cohort. We identified recurrent co-occurring mutations in SRSF2-IDH2, ASXL1-SRSF2, and ASXL1-EZH2, which were enriched at transformation (p < 0.05; Fisher exact test). Importantly, presence of these co-mutations was consistently associated with a higher transformation risk in two independent cohorts of MF patients from Mayo Clinic (n= 405) and University of Florence (n= 518). Clonal architecture analysis revealed that these co-mutations frequently arose within the same malignant clone: 100% for SRSF2-IDH2, 80% for ASXL1-SRSF2, and 85% for ASXL1-EZH2, and are often within the dominant clone. Prior studies have demonstrated mechanistic interplay between SRSF2 and IDH2 (Yoshimi et al.), as well as ASXL1 and SRSF2 (Sui et al.) mutations in myeloid malignancies. We assessed functional synergy of ASXL1-EZH2 using a murine model and identified that dual deletion caused a rapidly fatal myeloid neoplasm with shorter survival than single-gene loss. These results reinforce that functional synergy emerges within a shared cellular context, supporting clonal co-dependence as a driver of progression. Single-cell RNA sequencing of ASXL1-EZH2 mutant cases is ongoing and will be presented. Conclusions Transformation to MPN-AP/BP is driven by gradual clonal remodeling and expansion of pre-existing high-risk abnormalities. Biallelic and multi-hit alterations in TP53, JAK2, TET2, and RUNX1 promote clonal dominance and blast progression. Recurrent co-mutations such as IDH2-SRSF2 and ASXL1-EZH2 arise within the same clone, exhibit functional synergy, and are linked to poor outcomes. These findings support the clinical utility of early clonal and co-mutational profiling to guide risk-adapted intervention.

Abstract Outgrowth of a founder mutant clone is an initial event in leukemogenesis. The corresponding somatic hit likely conveys a fitness advantage over a polyclonal background. Several factors may modulate the competitiveness of hematopoietic stem or progenitor cells, including aging, genotoxic stress, repeated cycles of stress hematopoiesis, and inherited genetic fitness deficiency. The nature of these conditions provides a particularly fertile environment in which only certain mutant clones thrive. For instance, chemotherapy facilitates expansion of PPMD1MT or TP53MT clones, aging-related loss of fitness predisposes to outgrowth of TET2MT clones, while many inherited bone marrow failure (BMF) syndromes are associated with specific clonal acquisitions due to somatic gene rescue. Identification of factors enabling the expansion of clones with specific mutations may help to develop targeted preventive, screening, or therapeutic strategies. Recently, high levels of erythropoietin (EPO) induced by frequent blood donation were shown to favor the emergence of DNMT3AR882 clones due to their increased EPO sensitivity1. We theorized that this may be a more general phenomenon operating in other diseases characterized by high EPO levels. Thus, we selected 644 patients in whom endogenous serum EPO levels had been assessed and who underwent mutational NGS analysis. Given that this cohort consisted of patients with hematologic neoplasms, EPO levels were broad with the majority falling outside the normal clinical reference range. For this study we used EPO levels ≥100mU/mL as the threshold to define high and low EPO groups. This threshold laid above the 75th percentile for our cohort (M=31.1; IQR=109.7) to capture outliers more likely to reflect biologically significant erythropoietic stress. DNMT3AMT were present in 14% of high EPO and in 12% of low EPO groups (p=0.5). However, in the high EPO group, R882 constituted 32% of DNMT3AMT while in the low EPO group R882 was found in only 11% of DNMT3AMT cases (p=.02). In a reverse fashion, the mean level of EPO in DNMT3AR882 was 441.7mU/mL while it was 215.3mU/mL in other DNMT3AMT carriers (p=0.03) and 186.2mU/mL in DNMT3AWT cases (p<0.001). To assess whether the effect on DNMT3A was dependent on EPO levels rather than anemia, we determined mean hemoglobin levels in R882 (µ=10.2g/dL), other DNMT3AMT (µ=10.4g/dL), and wild type cases (µ=10.9g/dL) and found no significant differences (p=0.33). To assess whether R882-EPO sensitivity was related to EPO-R expression levels, we compared EPO-R expression in R882 (µ=2.7), non-R882 (µ=2.6) mutations, and WT cases (µ=2.8) and found no significant difference. To assess whether the impact of high EPO states was specific to DNMT3AMT we next analyzed the distribution of other mutations. We observed that frameshift mutations in BCOR (p = 0.013) and BCORL1 (p=0.036) were significantly more frequent in high EPO patients. BCORMT was also overall more prevalent in the high EPO group (p=.001), while BCORL1 frequency was similar across EPO strata (p=0.77) showing a similar trend to DNMT3AMT. Beyond these genes, other patterns emerged, particularly within CH-associated genes. Individuals with U2AF1MT had elevated EPO (p=.0087), with variant-specific enrichment: p.S34F was more common in high EPO (p=.038) whereas p.Q157P predominated in low EPO patients (p=0.038). No significant EPO associations were observed for other CH-related genes such as ASXL1, CBL, and TET2. The limitations of this study notwithstanding, these findings support a biologically meaningful relationship between elevated EPO levels and the acquisition or enrichment of specific CH-associated mutations in patients with hematologic malignancies. The association of high EPO with DNMT3AR882, frameshift mutations in BCOR/L1, and variant-specific enrichment in U2AF1 suggests that EPO-driven stress may contribute to clonal selection or expansion. Our study of high EPO levels and DNMT3AMT analysis illustrates that external conditions may influence selection pressure for specific mutations. However, selection pressure may be a complex combination of factors. Non-malignant conditions with high EPO, such as hypoxia or intrinsic BMF, may also create conditions facilitating the acquisition of specific somatic hits. Recognition of evolutionary pressures and their associations with specific mutations may improve our understanding of CH pathogenesis, and conceptualization of therapeutic or preventative measures.

Abstract Background The expansion of hematopoietic stem and progenitor cells (HSPCs) in the bone marrow is universally associated with adverse outcomes and disease progression in all chronic myeloid neoplasms, to include chronic myelomonocytic leukemia (CMML). However, HSPCs are a heterogeneous cellular compartment and the impact of its composition on clinical outcomes remains poorly defined. Single cell RNA-sequencing (scRNA-seq) represents an optimal strategy to annotate cellular composition but no large clinically annotated scRNA-seq datasets are currently available. To address this, we have embarked to generate a clinically annotated 500 patient CMML scRNA-seq atlas from CD34+ enriched BMNCs to establish among the largest clinically and genetically annotated single cell references for any chronic myeloid malignancy. Here we report the interim analysis of 113 clinically annotated cases that demonstrates massive reshaping of HSPC composition that is independently a predictor of overall survival. Methods Single-cell RNA expression profiling was performed on 113 CD34-enriched CMML BMNC samples using 10x Genomics GEM-X Universal 3' Gene Expression v4 (4-plex) chemistry. Libraries were sequenced on NovaSeq S4 flow cells in two runs, and data were processed using Cell Ranger to generate gene expression matrices. A total of 502,659 single cells from 113 samples were processed using Seurat. The upper threshold for gene count was defined as the mean number of detected genes plus two standard deviations data normalization was performed using the log-normalization method. Batch correction and integration were conducted with Harmony to mitigate technical variation across pools. Descriptive statistics were used to tabulate clinical and genetic parameters. KM curves, log-rank test, and cox regression were used to calculate survival, test for statistical differences, and perform multivariate analysis, respectively. Results To derive high resolution cell annotations, we employed the SingleR algorithm using a large hematopoietic reference of over 300,000 single cells (Zhang, X. Nature Immunology, 2024). Using this approach a diverse set of cell types were identified that included HSCs, 23 myeloid progenitors, 18 erythroid progenitors, and 18 lymphoid progenitors. This diverse cellular repertoire displayed massive reshaping relative to the normal CD34 enriched reference including a >53x expansion of multilineage GMPs and a >100x depletion of B-cell progenitors consistent with the known myeloid skewing seen in this disease. To understand whether expansion of specific progenitors was associated with outcomes we iteratively evaluated key progenitor populations and observed that expansions of HSC (HR 0.468 p<0.005) and MEP (HR 0.485, p<0.005) were associated with improved survival while GMP (HR 1.729, p=0.029) expansions were associated with inferior survival when using a cut point derived with a maximally selected ranks statistics approach. To achieve a more comprehensive metric of HSPC composition we explored GMP ratios to include GMP/HSC ratios and GMP/MEP ratios and observed that both were associated with inferior survival in univariate and multivariate when considering clinical and genetic features such as the CPSS-molecular prognostic score and FAB classification. When considering both GMP/HSC and GMP/MEP ratios in a multivariate model only GMP/MEP ratios and CPSS molecular remained independently prognostic. As an orthogonal approach, pseudotime projections were carried out using a reference map from Setty et al., 2019 to calculate differentiation potential and branch probabilities. This approach enabled both cell identity assignment and placement of cells along the hematopoietic differentiation trajectory. Samples were classified as monocyte-biased, MEP-biased, or normal-like, as previously described (Ferrall-Fairbanks et al. 2022) and demonstrated that increased GMP ratios are associated with a monocytic biased trajectory and that this trajectory is also associated with overall survival. Conclusion This study represents an interim analysis of among the largest scRNA-seq cohorts generated in chronic myeloid malignancies. This enabled us, for the first time, to demonstrate that HSPC composition is independently prognostic even when considering modern CMML prognostic models. As this cohort continues to increase, validation of these findings and examining the impact of therapy on HPSC composition in serial samples will be prioritized.

Abstract Introduction: Standardized reporting of clinical trials results for MDS is essential to improve clinical interpretation and cross-study comparison. However, reporting of patient characteristics, response criteria, and endpoints in publications is often inconsistent; there is no systemic analysis of MDS trial reporting available. We conducted a systematic review of published MDS trial manuscripts on behalf of the international consortium for MDS (icMDS) to assess variability in reporting practices. Methods We searched ClinicalTrials.gov to identify all clinical trials registered for adults (≥18 years) with MDS that reported results between 2015-2024. Clinical trials that included acute myeloid leukemia (AML) or MDS/myeloproliferative neoplasms (MPN) were included if they enrolled ≥5 MDS patients. We excluded trials without an MDS cohort; non-therapeutic trials; trials focused on transplant interventions; or those which enrolled solid malignancies or other hematologic malignancies (chronic myeloid leukemia or lymphoid diseases). Finally, trials were required to have a manuscript available on Larvol, PubMed, or Google Scholar. Trials were categorized by disease risk (lower-risk [LR] vs. higher-risk [HR]) and trial phase (early phase [EP] vs. late phase [LP]). Results We identified 502 MDS trials on ClinicalTrials.gov, of which 351 did not meet inclusion criteria and 79 lacked a manuscript. A total of 72 trials (32 EP, 40 LP) with 80 publications (34 EP, 46 LP) were analyzed. Frequently reported baseline characteristics included age (100% EP, 100% LP), disease risk (74% EP, 74% LP), Eastern Cooperative Oncology Group performance status (85% EP, 72% LP), prior treatments (71% EP, 67% LP), and RBC transfusion dependency (32% EP, 70% LP). Less frequently reported characteristics included blood counts (hemoglobin [Hb; 38% EP, 54% LP], platelet count [38% EP, 54% LP], neutrophil count [24% EP and LP]) and bone marrow blasts (29% EP, 43% LP). Although disease risk was widely reported, definitions varied: IPSS and IPSS-R were each reported in 54% of manuscripts, while IPSS-M appeared in only 3%. Cytogenetic risk was separately reported in 39% of manuscripts (38% EP, 39% LP), and mutational data in 45% (47% EP, 43% LP). Responses per IWG 2006 criteria were reported in 84% of manuscripts. The primary endpoint involved safety/tolerability in 85% of EP manuscripts, though definitions were variable; recommended phase 2 dose was the most common (26% of EP manuscripts). In LP trials, primary endpoints were risk-specific: transfusion independence (TI) in 77% of LR, overall response rate (ORR) in 28% of HR, and complete remission (CR) or overall survival (OS) in 22% of HR. In HR manuscripts, CR was reported in 100%, ORR in 73%, hematologic improvement (HI) in 48%, RBC-TI in 23%, and OS in 80%. However, seven different definitions were used for ORR: CR + marrow CR + partial remission + HI per IWG 2006 was most common (35%). Event-free survival was reported in 25%; progression-free survival and relapse-free survival in 13%; and leukemia-free survival in 5%. Early mortality rate was reported in 35% (18% EP, 56% LP) and transplant rate in 58% (50% EP, 67% LP). Only 47% of HR and 90% of LR manuscripts identified HI-eligible patients. In LR-MDS, RBC-TI was reported in 72% of manuscripts but used six definitions. The most common were RBC-TI ≥8 weeks at any time during treatment (24%), ≥8 weeks within 28 weeks of treatment (13%), ≥8 weeks with Hb increase ≥1.0 (4%), ≥12 weeks with Hb increase ≥1.5 (4%), and ≥16 weeks within 24 weeks of treatment (12%). The remainder did not report RBC-TI, did not define it, or used a custom definition not used in another trial. HI was reported in 80% of LR papers with most of those reporting HI using IWG 2006 criteria (90%). Conclusion Reporting of baseline characteristics, response criteria, and outcomes is inconsistent in MDS clinical trials, with wide variability in response definitions, including ORR and TI. This heterogeneity limits interpretability, hampers historical comparisons and may obscure efficacy signals. Our findings highlight the need for standardized reporting guidelines to ensure clarity and consistency in MDS trial publications. As a next phase of this effort, we will conduct a formal Delphi process among icMDS experts to establish consensus recommendations for minimal and optimal MDS clinical trial reporting in manuscripts by disease risk (LR/HR) and trial phase (EP/LP).