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Background: Inotuzumab Ozogamicin (InO) is an antibody-cytotoxin conjugate with high activity in B-cell acute lymphoblastic leukemia (B-ALL). InO targets the B-cell surface protein CD22, which is expressed in most B-ALL cases, albeit with great variability in expression levels. Emerging evidence suggest that this variation is associated with the stage of leukemia differentiation arrest [PMID: 21348573]. However, the exact relationship between CD22 expression and leukemia sensitivity to InO, particularly in the context of leukemia developmental state, remains unclear. Furthermore, our understanding of the molecular mechanisms regulating CD22 transcription in B-ALL is still incomplete. Methods: To comprehensively investigate the genomic basis of variability in leukemia CD22 expression and thus B-ALL sensitivity to InO, we performed a multi-omic characterization of 196 primary human B-ALL samples, using whole transcriptome sequencing (RNAseq), assay for transposase-accessible chromatin with sequencing (ATAC-seq), coupled with ex vivo profiling of InO sensitivity. Additionally, genomic editing studies were performed in Nalm6 and REH B-ALL cell lines, and patient derived xenograft (PDX) models were used for in vitro and in vivo validations. Results: Applying digital cytometry to leukemia bulk RNAseq data to infer the B-ALL developmental state, we found that blast cells with early Pre-pro-B-like signature had low levels of CD22 expression and were resistant to InO. As B-cell differentiation is controlled by stage-specific transcription factors (TFs), we performed a targeted CRISPR library screen of 1,639 TF genes and identified EBF1 as a key activator of CD22 expression (FDR=7.1x10-4). In primary B-ALL samples, EBF1 expression was significantly correlated with CD22 expression (R=0.69, P<0.0001) and leukemia response to InO (measured as LC50, R=-0.42, P<0.0001). In addition, TF footprint analysis of leukemia ATAC-seq data identified EBF1 as the most differentially activated TF comparing InO-sensitive and -resistant B-ALL cases (P=8x10-174). Blocking the EBF1 binding sites within the CD22 promoter by CRISPR interference resulted in a 50-fold and 49-fold decrease in cell surface CD22 expression, and a 22-fold and 25.7-fold increase in InO LC50 for Nalm6 and REH, respectively, confirming the direct impact of EBF1 on CD22 transcription and InO sensitivity. Because BCR::ABL1-positive ALL showed the greatest variability in InO sensitivity among all B-ALL subtypes, we further investigate the role of the EBF1/CD22 axis on InO sensitivity within this subtype. Unsupervised clustering of gene expression profiles revealed two distinct groups, namely BCR::ABL1 ALL with multilineage (BCR::ABL1-M) or lymphoid only (BCR::ABL1-L) involvement [PMID: 38153913]. Compared to BCR::ABL1-L, BCR::ABL1-M displayed markedly reduced CD22 expression (P=8.3×10-11) and resistance to InO (P=1.9×10-4), likely due to the lower expression and frequent somatic alteration of EBF1. Finally, we established PDX models for representative cases of BCR::ABL1-M and BCR::ABL1-L. Strikingly, InO treatment did not affect leukemia progression in the BCR::ABL1-M PDX model, whereas the BCR::ABL1-L PDX model achieved complete remission and has remained leukemia free to date. Conclusion: Collectively, these data demonstrate the direct impact of EBF1 on CD22 expression during B-cell development, and explain the heterogeneity of InO sensitivity, even within the same molecular B-ALL subtype.

Introduction: Cilta-cel is approved in the US and EU for the treatment (tx) of patients (pts) with len-refractory MM after ≥1 line based on the randomized, phase 3 CARTITUDE-4 trial (NCT04181827). At the first interim analysis (15.9-month [mo] median follow-up), cilta-cel significantly improved progression-free survival (PFS) vs SoC (hazard ratio [HR], 0.26 [protocol-specified weighted analysis]; P<0.0001). At the second interim analysis, overall survival (OS) was significantly improved with cilta-cel vs SoC (HR, 0.55; P=0.0009). MRD negativity is a prognostic marker of prolonged survival outcomes for pts with MM. We report MRD negativity, including overall and sustained MRD negativity, overall MRD-negative complete response or better (≥CR), and MRD-negative ≥CR at mo 12, from the prespecified second interim analysis of CARTITUDE-4. Methods: Eligibility criteria were previously described. Pts were assigned 1:1 to cilta-cel or SoC (pomalidomide, bortezomib, and dexamethasone [PVd]/daratumumab, pomalidomide, and dexamethasone [DPd]). Pts in the cilta-cel arm underwent apheresis, received bridging therapy (PVd/DPd), and then a single cilta-cel infusion (target dose, 0.75×106 CAR+ viable T cells/kg) 5-7 days (d) after the start of lymphodepletion. PFS was the primary endpoint; ≥CR rate, overall response rate, overall MRD-negativity rate, and OS were key secondary endpoints. MRD was assessed centrally via next-generation sequencing (clonoSEQ v2.0; Adaptive Biotechnologies). MRD was evaluated at d 56 post infusion in the cilta-cel arm; and in both arms at suspected ≥CR and at 6, 12, 18, and 24 mo post infusion (cilta-cel arm) or cycle 1 d 1 (SoC arm), as well as yearly until progression/start of subsequent therapy in pts in ≥CR. Sustained MRD negativity (10−5) was defined as confirmed MRD negativity ≥12 mo apart and without MRD positivity in between. Pts were evaluable for sustained MRD negativity if they achieved MRD negativity and had ≥1 evaluable MRD sample ≥12 mo after the first negative result or progressed/died/started subsequent tx <12 mo after the first negative result. Results: 419 pts were randomized (intent-to-treat [ITT] set; cilta-cel, n=208; SoC, n=211); 176 pts in the cilta-cel arm received cilta-cel as study tx. As of May 1, 2024, median follow-up for the study was 33.6 mo. At the 10−5 threshold, 145 pts in the cilta-cel arm and 103 in the SoC arm were evaluable for MRD. MRD-negativity rates (10−5) in the ITT set and the MRD-evaluable subset were higher with cilta-cel vs SoC (ITT, 62% vs 18%; MRD evaluable, 89% vs 38%; both P<0.0001). Across subgroups, cilta-cel vs SoC consistently increased overall MRD-negativity rates (10−5). In the ITT set, 48% of the cilta-cel arm achieved MRD negativity (10−5) by d 56, with the MRD-negative rate rising to 60% by 6 mo post cilta-cel infusion. Overall MRD-negativity rates at the 10−6 threshold in the ITT set were higher with cilta-cel vs SoC (57% vs 9%; P<0.0001). In the cilta-cel arm, 119 (57%) pts vs 26 (12%) in the SoC arm achieved overall MRD-negative (10−5) ≥CR (P<0.0001). At the 12-mo MRD assessment, 92 (44%) pts in the cilta-cel arm vs 17 (8%) in the SoC arm (P<0.0001) had MRD-negative (10−5) ≥CR. In pts with MRD-negative (10−5) ≥CR at mo 12, median PFS was not reached (NR; 95% CI, not estimable [NE]-NE) with cilta-cel and 37.8 mo (95% CI, 25.0-NE) with SoC; median OS was NR (95% CI, NE-NE) and NR (95% CI, 37.8 mo-NE), respectively. Sustained MRD-negativity rates (10−5) in the ITT set were 40% in the cilta-cel arm vs 6% in the SoC arm (P<0.0001); among 110 and 26 evaluable pts for sustained MRD, sustained MRD-negativity rates were 75% vs 50% (P=0.0159). Among the 176 pts who received cilta-cel as study tx, overall MRD negativity at 10−5 was achieved by 129 (73%) pts (89% of 145 evaluable pts). Conclusions: At 33.6-mo median follow-up in CARTITUDE-4, cilta-cel vs SoC significantly increased overall MRD-negativity rates >3-fold in the ITT set, with pts achieving MRD negativity rapidly post cilta-cel. The prognostic value of MRD-negative ≥CR at mo 12 was shown, as median PFS was >3 years in pts with MRD-negative ≥CR at mo 12, regardless of tx. These data further underscore the benefit of cilta-cel, which led to significant >3-fold increases vs SoC in rates of MRD-negative ≥CR at any time and at mo 12, and sustained MRD negativity. Our MRD data demonstrate higher rates of deep and sustained MRD negativity achieved with cilta-cel vs SoC in tx of len-refractory MM as early as first relapse.

Background: Risk stratification for suspected pulmonary emboli (PE) remains an area of active research. Current risk stratification algorithms have moderate discriminatory capabilities and are guideline-recommended, but they are poorly utilized in practice, with most clinicians relying predominantly on their clinical training and personal “gestalt.” Our group recently derived an Artificial Intelligence (AI) algorithm using electrocardiograms (ECG) to predict the presence of PE (AUC 0.69) on computed tomography scans of the pulmonary arteries (CTPA) in a cohort of 79K patients. Aim: Validate the AI-ECG algorithm in a contemporary dataset of patients with suspected PE. Methods: Emergency Department (ED) visits between 9/1/2022 and 12/31/2023 across the Mayo Clinic Enterprise were searched using a unified data platform. ED visits in patients over 18 years of age with a discretely documented Wells' PE or PERC Rule, a D-dimer result, or a CTPA were included. Only CTPA imaging and D-dimers performed within 48 hours of ED admission were eligible to be included. Patients were included in the final cohort if an ECG was performed within 6 hours of ED admission, D-dimer testing, or CTPA. Patients were considered negative for PE if CTPA was negative, and when this wasn't performed, a negative D-dimer (high sensitivity) or PERC rule of 0 was considered negative. A previously derived Artificial Neural Network algorithm to analyze the ECG to predict PE was applied to the dataset for validation. Results: A total of 27,028 ED visits in 24,288 unique patients meet inclusion criteria. Among this group, the first ED visit with a CTPA and an ECG within 6 hours was included, leaving 18,936 patients for the final validation cohort. The mean age of the cohort was 54.7 (SD 18.7), and 57% were male. Among the entire cohort, 13,573 underwent D-dimer testing for which 4,895 (36%) were positive at standard thresholds. A total of 10,486 patients underwent CTPA (55% of patients evaluated), of which 455 were positive for PE (4.3%). Using the AI-ECG model from the derivation cohort applied to this validation cohort resulted in an AUC of 0.69, identical to the derivation cohort. Using ECG model estimates alone, low (0.74%, n=2447, NPV 99.3%), elevated (2.27%, n=15404, NPV, 97.72%), and high-risk (8.02%, n=1085, NPV 91.98%) categories for PE can be created. A negative D-dimer in the elevated risk group increased the negative predictive value (NPV) to >99.9% and could be used to reduce imaging in this group further. Using the proposed ECG to D-dimer cascade risk stratification could further reduce the need for PE imaging for an overall NPV of 99.9% and sensitivity of 95.2%. We then used additional clinical parameters to train a new algorithm with additional clinical data and the AI-ECG algorithm estimates. Multiple machine learning algorithms were then evaluated in a dataset divided into training (2/3) and testing (1/3) datasets, after downsampling (to address class imbalance). The best results were obtained with AI-ECG results and D-dimer: Ada Boost (AUC 0.93, F1 score 0.895) compared to standard logistic regression (AUC 0.79, F1 score 0.746). The addition of age, sex, and oxygen saturation did not improve model performance. Conclusion: We have now validated the previously derived AI-ANN ECG algorithm for PE in a contemporary and independent cohort and demonstrate potential for integration into clinical PE assessment algorithms. Unlike prior risk stratification processes, ECGs are invariably performed in patients with cardiopulmonary symptoms and have the potential to prevent missed or delayed PE diagnosis by proactively identifying high-risk patients. Additionally, we demonstrate that the results of this algorithm can be combined with D-dimer values, resulting in a simple, powerful, predictive algorithm (AUC 0.93) that pairs cardiovascular electrophysiology with laboratory biomarkers and could lead to a new paradigm in clinical risk stratification for PE.

Background. Study of myeloid neoplasms (MN) has been rapidly transformed by genome characterization. Gene mutations have been reported to influence disease phenotype and risk of disease progression, and the evaluation of mutational status can provide valuable insights to improve the decision-making process. In this international study, we evaluated the clinical impact of mutational screening in patients with CMML, which is characterized by significant clinical and genomic heterogeneity, including a substantial proportion of patients with poor outcomes and unmet needs. Currently, only limited molecular information has been incorporated into CMML classification and prognostication. Methods. We retrospectively collected 3182 CMML patients. We used MOSAIC, an AI-based framework for multimodal analysis in rare cancers (PMID: 38875514) to develop innovative, molecular-based tools for classification and prognostication. An independent validation of the results on 516 prospectively collected patients was performed. Results. Bayesian Networs and Hierarchical Dirichlet Processes were used to identify genomic associations and define a CMML molecular classification. We identified 11 clusters with distinct clinical and genomic features, including splicing machinery, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures (i.e., AML-like and TP53 mutations). Up to 15% of patients showed clear genomic overlap with other MN. Importantly, extensive multi-color flow cytometry on T lymphocytes, NK and myeloid cells (BD FACSymphony A5 Cell Analyzer) revealed specific immunologic and inflammation signatures associated with molecular subgroups. We then integrated molecular and clinical information to build an international CMML Prognostic Scoring System (iCPSS). We assessed the performance of different statistical and AI-based methods; L1-penalized Cox Model resulted as the best performing method. Selected features included hematological parameters (WBC, Hb, PLT and marrow blasts), cytogenetic abnormalities, and mutations in 10 genes (ASXL1, DNMT3A, EZH2, NRAS, RUNX1, SETBP1, STAG2, TET2, TP53, U2AF1). By Bayesian thresholds optimization, we identified 5 risk classes (i.e., very-low, low, intermediate, high and very-high) with median overall survival (OS) ranging from 99 to 9 months (P<.001), and median leukemia-free survival (LFS) ranging from 210 to 18 months (P<.001). iCPSS provided better patient discrimination across all clinical endpoints compared to currently available prognostic tools, with a Concordance Index (CI) for OS of 0.75 versus 0.62-0.64, respectively. Notably, compared to available scoring systems, up to 40% of patients were reassigned to higher or lower risk classes by the iCPSS. External validation on an independent prospective cohort confirmed that the performance of iCPSS is superior to existing prognostic models (CI for OS 0.71 vs 0.54-0.61, respectively) To demonstrate the clinical utility of iCPSS, we focused on 753 patients who underwent allogeneic stem cell transplantation (HSCT). In multivariable analysis, iCPSS stratified the probability of OS post-HSCT (P<.001) and identified groups of patients with different probabilities of disease relapse, ranging from 9% to 62% (P<.001). We employed a clinical- and genomic-based decision support system (PMID: 38723212) to determine the optimal timing of HSCT. Preliminary analyses indicated that higher-risk patients according to iCPSS (i.e., intermediate, high, and very high) benefit from an immediate HSCT strategy. Lower-risk patients (i.e., very low and low) had life expectancy maximized with delayed HSCT. Modeling decision analysis using iCPSS compared to conventional scores, resulted in a change in transplantation policy for a significant proportion of patients (up to 25%). Conclusion. Molecular information significantly improves the classification of CMML patients, providing a basis for refining diagnostic boundaries with other MN and for a more rational inclusion of patients in clinical trials. The iCPSS demonstrated superior performance over currently available scoring systems and improved HSCT decision making process.

Introduction: T-PLL is a rare, aggressive malignancy with poor prognosis and limited therapies. Outside of prospective trials utilizing alemtuzumab, data is derived primarily from small retrospective series, and limited data on survival outcomes and therapeutic efficacy, particularly beyond frontline therapy are available. In this large multi-center series, with comprehensive clinical data, we evaluated survival and therapeutic outcomes in T-PLL patients, with a focus on identification of prognostic subgroups of T-PLL, that will inform future investigations into the biology and treatment of this disease. Methods: We retrospectively evaluated all patients diagnosed with T-PLL at 15 academic cancer centers throughout the USA between 2000-2023 using the recent TPLL-ISG staging and response criteria with overall response rate (ORR) defined as CR and PR. Overall survival (OS) and progression-free survival (PFS) were assessed using Kaplan-Meier methods and cox proportional hazard models. Single-cell RNA sequencing (scRNAseq) was performed using the standard 10X Genomics platform. Results: 377 patients, with a median follow-up time of 29 months (range: 0-196) were evaluated. The median age at diagnosis was 64 and 51% were male. In evaluated patients (n=223), TCL1A was positive by cytogenetics or FISH in 82%. 61% of patients had CD4+CD8- T-PLL, 11% of patients had CD4-CD8+ T-PLL, and 24% of patients had CD4+CD8+ T-PLL, with 4% unknown. 175 patients (46.4%) had known nodal involvement at diagnosis identified by PET or CT scan. Among treated patients (n=342, 91%), using TPLL-ISG criteria, the ORR to any frontline treatment was 67% (49% CR, 18% PR). Median OS and PFS was 19 months and 10 months in responding patients from the start of treatment initiation. For those treated with frontline alemtuzumab (n=250), the ORR was 74% (58% CR), with a median OS and PFS of 18 and 12 months. 20 patients (5%) were treated with a combination of alemtuzumab/pentostatin frontline with an ORR of 85% (70% CR), which was superior to alemtuzumab alone (ORR 74%, 58% CR). Patients that had frontline chemotherapy (excluding pentostatin, n=48) had a worse ORR of 35% (15% CR) (p<0.001), and a worse PFS of 4 months (p=0.002), when compared to those who received alemtuzumab. Among patients in 1st CR/PR (n=226), 44% (n=99) received an allograft and had an improved 3-year OS of 50% vs 17%, (HR=0.67, 95%CI 0.48-0.93), and 50% improvement in PFS (HR 0.48, 0.33-0.68) compared to those who did not receive an allograft. For patients that received second line treatment (n=176, 52%), re-treatment with alemtuzumab (n=33) produced a 46% ORR (21% CR). Other active second-line treatments included: pentostatin (n=23; 44% ORR, 17% CR), ruxolitinib-based regimens (n=4; 25% ORR, 0% CR), venetoclax-based regimens (n=13; 39% ORR, 8% CR), bendamustine (n=10; 30% ORR, 0% CR), and nelarabine (n=4; 75% ORR, 50% CR). In subgroup survival analysis, TCL1A+ patients had a worse OS and PFS when compared to TCL1A- patients (23 months vs 43 months; p=0.02), and (14 months vs 24 months; p=0.02) respectively, with HR 1.58 (1.08, 2.31) (p=0.02) for OS and HR 1.62 (1.09-2.40) (p=0.02) for PFS. Furthermore, CD4- T-PLL had worse OS (16 months vs 25 months) when compared to CD4+ patients [HR 1.57 (1.08, 2.27), p=0.02]. Single cell RNA seq in 13 patients, including 3 TCL1A- patients, with a total of 66,269 T-PLL cells, demonstrated a unique RNA signature between the CD4+/- and TCL1A+/- patients, suggesting these represent unique molecular subtypes of T-PLL. Conclusions: In this large, multi-center study of T-PLL, frontline treatment with a combination of alemtuzumab/pentostatin improved response rates and OS. Further, among patients who attained a CR, allograft improved OS & PFS vs no allograft. In relapsed T-PLL, retreatment with alemtuzumab had a high ORR, and we report significant activity of multiple novel/alternative agents with the largest reported numbers to date. Intriguingly, TCL1A+, and CD4- T- PLL had worse OS/PFS, and scRNAseq confirmed unique molecular signatures in these populations, suggesting these represent novel molecular subtypes of T-PLL with prognostic significance. These studies form the foundation for future, targeted, therapeutic studies in this rare, aggressive disease with few treatment options.

Introduction: Scant data exist on prognostic factors, survival and treatment (Tx)-related outcomes in SCNSL. We conducted a multicenter international analysis to identify prognostic factors and outcomes in SCNSL at diagnosis (de novo), or after frontline Tx (1L) either with (concomitant) or without (isolated) systemic (syst) relapse. Methods: This study collected data from patients (pts) treated between 2001-2023 at 35 centers. Overall (OS) and progression-free survival (PFS) were calculated from SCNSL diagnosis to first event (death for OS, relapse/death for PFS) or last follow-up. Uni- (UVA) and multivariable (MVA) Cox analyses were performed to assess prognostic factors; Kaplan-Meier method was used to estimate survival. Results: 1173 (US: 863, UK: 273, Canada: 37) pts with SCNSL were included. Baseline characteristics were median age: 62 years (interquartile range 52.5-69), male sex: 58.7%, elevated LDH: 71.1%, stage III/IV: 88.6%, HIV: 3%, transformed LBCL (tLBCL): 13.8%, non-germinal center B-cell like (non-GCB) subtype: 52.3%, double expressor (DE): 40%, MYC rearrangement (MYC-R): 28.3%, MYC/BCL2 double hit: 16.6%, MYC/BCL2/BCL6 triple hit (TH): 6.1%. Among 522 pts with de novo SCNSL, 84.2% had involvement of a single CNS compartment (44.7% brain parenchyma; 40.4% leptomeningeal [lepto]). 1L regimens included 36.2% R-CHOP with high-dose methotrexate (HD-MTX), 12.5% MARIETTA-type, and 9.8% R-CODOX-M/IVAC; 54.6% received intrathecal chemotherapy. Consolidation Thiotepa-based autologous stem cell transplant (TT-ASCT) occurred in 15.3%. The majority of pts who underwent TT-ASCT had previously achieved CR or PR in syst (92.5%) and CNS (72.5%) compartments. At median follow-up 25.7 months (mos), subsequent relapse was observed in 27.5% TT-ASCT recipients: 36.3% had isolated CNS, 27.4% syst, and 36.3% concomitant. 588 pts presented with SCNS after 1L (66.2% isolated, 33.8% concomitant). Brain parenchyma involvement was observed in 56.8%, lepto in 22.6%. Tx included 31.6% HD-MTX combination (eg, R-MPV, MTR); 18.4% HD-MTX +/- rituximab; 16.2% MARIETTA-type; and 9.4% platinum-based regimen. Consolidation TT-ASCT occurred in 22.4% (n=132), and 13.8% (n=81) received CAR-T cell therapy (excluding subsequent relapses in de novo group). Syst (65.1%) & CNS (69.1%) responses (CR/PR) were higher before TT-ASCT compared to CAR-T cell (49.5% & 54.5%, respectively). After TT-ASCT, 52 pts (39.3%) relapsed, mainly in the CNS (n=30, 57.7%), with only 4 (7.7%) concomitant. After CAR-T, 48 pts (59.3%) relapsed: 15 (31.2%) isolated in CNS and 15 (31.2%) concomitant. 12-month cumulative incidence of relapse (with death as competing risk) was 21.1% after TT-ASCT and 55.8% after CAR-T. In 63 pts (5.4%), the first CNS event occurred >2 lines of Tx. With median follow-up of the entire cohort of 24.6 mos, median PFS and OS were 11 and 21 mos, respectively. mPFS and mOS were significantly better in pts with de novo SCNSL (13.4 & 47.4 mos) compared to SCNSL after 1L (10.4 & 14.2 mos) and >2 lines of Tx (6.5 & 9.7 mos); P<0.0001. Factors associated with significantly shorter OS in UVA across all presentations were age >60, male sex, GCB subtype, MYC-R, tLBCL, DE, TH, elevated LDH, ECOG PS ≥2, SCNSL after 1L (vs. de novo), and failure to achieve syst/CNS response to 1L. Of these, age >60, male sex, MYC-R, ECOG PS ≥2, and failure to achieve response to 1L remained significant in MVA. In de novo cases, age >60, DE, ECOG PS≥2, and failure to achieve syst/CNS response to 1L were associated with poorer OS; for pts with SCNSL after 1L, age >60, GCB subtype, and ECOG PS ≥2 were significant. Pts treated with HD-MTX-based regimens after 1L experienced longer OS than those treated with platinum regimens or high-dose cytarabine. In de novo cases, TT-ASCT was significantly associated with longer OS (HR=0.58; P=0.025) in MVA after adjusting for significant factors, 1L type, and response. For SCNSL at relapse, TT-ASCT (HR=0.34; P<.0001) and isolated SCNSL presentation (vs. concomitant HR=0.70, P=0.007) were associated with longer OS, adjusting for significant factors, type of second-line Tx, & site of CNS relapse. Conclusions: This study represents the largest analysis of SCNSL inclusive of all modes of presentation. Concomitant SCNSL at relapse was associated with poor outcomes, while TT-ASCT consolidation was associated with improved OS in de novo & relapsed disease. Despite advances in LBCL SCNSL remains an unmet therapeutic need.

Introduction: GOLCA is a potential first-in-class oral cereblon E3 ligase modulator (CELMoD™) agent for non-Hodgkin lymphoma, purposefully designed to target Ikaros/Aiolos and have favorable pharmacokinetics, resulting in apoptotic and immunomodulatory activity with preferential distribution to lymphoid organs. CC-220-DLBCL-001 (NCT04884035) is an ongoing phase 1b, open-label, multicenter, dose-escalation/expansion trial to assess safety and preliminary 1L GOLCA + R-CHOP efficacy in a-BCL. Although longer follow-up is needed to assess durability of response, MRD negativity (MRD-) is an emerging endpoint in a-BCL. Achieving MRD- on and at end of treatment (EOT) can potentially predict clinical benefit. This study aimed to analyze circulating tumor DNA (ctDNA) kinetics of GOLCA + R-CHOP across the trial population and in defined patient (pt) segments-cell of origin (COO), high baseline ctDNA, and high-risk genomics-and to correlate MRD- with imaging and clinical outcomes. Methods: Eligible pts were ≥ 18 years of age with ECOG performance status ≤2, IPI 0-5 in Part 1 and 2-5 in Part 2, and untreated a-BCL with measurable disease. Pts were treated with GOLCA + R-CHOP for 6 x 21-day (D) cycles (C) or until disease progression/unacceptable toxicity/study withdrawal. Dose escalation phase GOLCA dose levels (DLs) were 0.2 mg D1-7 (DL-1), 0.4 mg D1-7 (DL1), or 0.4 mg D1-10 (DL2). During dose expansion, pts were randomized 1:1 to R-CHOP + GOLCA DL-1 or DL1. The primary endpoint was safety of GOLCA at DL1; efficacy was a secondary endpoint, ctDNA was an exploratory endpoint. ctDNA was analyzed using the PhasED-Seq assay (<10-6 sensitivity) at baseline, C2D1, C3D1, and EOT. MRD- was defined as the absence of detectable ctDNA on-treatment. Pretreatment biopsies were sequenced by whole genome sequencing (WGS) and whole transcriptome sequencing (WTS). Results: At data cutoff (June 3, 2024), the median follow-up was 14.3 months. One-year progression-free survival (PFS) was 85.3% at 0.4 mg and 77.3% at 0.2 mg. Rates of MRD- increased over time but were consistently higher at 0.4 vs 0.2 mg, with values of 44% (14/32) vs 29% (8/28) at C2D1; 63% (17/27) vs 54% (15/28) at C3D1, and 90% (26/29) vs 73% (19/26) at EOT, respectively. Interim MRD- at C3D1 strongly predicted EOT MRD-; all 0.4 mg pts and all but two 0.2 mg pts who were MRD- at C3D1 remained MRD- at EOT. In contrast, fold-changes from baseline ctDNA were similar between 0.4 mg and 0.2 mg. The early molecular response rate (≥102-fold drop from baseline at C2D1) was 81.2% (26/32) at 0.4 mg and 82.1% (23/28) at 0.2 mg. The major molecular response rate (≥102.5-fold drop from baseline at C3D1) was 88.9% (24/27) at 0.4 mg and 85.7% (24/28) at 0.2 mg. Across genetically defined pt segments, EOT MRD- at 0.4 mg was prevalent for both COO subtypes measured by the Hans algorithm: 94% (17/18) among germinal center B-cell (GCB) and 75% (6/8) among non-GCB pts. Of the 29 pts with baseline genomics, 13 were genomically high risk: p53 mutant (VAF >0.5), DZsig and/or A7 subtype. In these pts, EOT MRD- was 80% (4/5) at 0.4 mg but only 20% (1/5) at 0.2 mg. In high baseline ctDNA (>102.5 hGE/mL) pts who were high-risk for R-CHOP failure, EOT MRD- at 0.4 mg was 86.7% (13/15) vs 57.1% (8/14) at 0.2 mg. There was an association between high baseline ctDNA and lower PFS at 0.2 mg (HR, 4.56 [95% CI, 0.53-39.12]), but interestingly the association decreased at 0.4 mg (HR, 2.10 [95% CI, 0.19-23.5]). Combining both arms, MRD- at both C3D1 and EOT trends with improved PFS (C3D1: HR, 0.73 [95% CI, 0.2114-2.523]; EOT: HR, 0.53 [95% CI, 0.1103-2.592]); longer follow-up may be required to demonstrate significance. Conclusions: Interim and EOT levels of MRD- were higher at 0.4 mg vs 0.2 mg GOLCA, with a one-year PFS of 85.3% vs 77.3%, respectively. Although pt numbers were small, the data suggest that 0.4 mg is efficacious in high-risk ctDNA and high-genomic risk pts, independent of COO, and support the 0.4 mg GOLCA + R-CHOP regimen in the randomized phase 3 trial GOLSEEK-1. Interim MRD- may play a role in future adaptive trial designs.

Background: The majority of patients respond to steroid treatment for graft-vs-host disease (GVHD), but the typically high doses and prolonged courses can cause substantial morbidity. GVHD can be classified at onset into two groups with significant differences in treatment response and non-relapse mortality (NRM) by clinical criteria (Minnesota risk) but the more favorable standard risk group still experiences high rates of treatment failure and NRM [MacMillan, BBMT 2015]. We previously validated a serum biomarker-based (ST2+REG3α) risk stratification system, MAGIC algorithm probabilities (MAPs), that can stratify patients both at initiation and during treatment into risk groups for treatment response and NRM [Hartwell, JCI Insight 2017, Srinagesh, Blood Adv 2019]. GVHD that is Minnesota standard risk and has a low MAP (i.e., Ann Arbor 1) at start of treatment represents a low risk group with >80% response rate to steroids and ~10% NRM [Etra, Blood 2023]. We hypothesized that serial monitoring of GVHD symptom severity and MAPs twice (days (d) 7 and 14) in patients with clinical and biomarker defined low risk GVHD could further stratify patients into clinically meaningful groups. Methods: We retrospectively determined MAPs at d7 and 14 in 450 patients with low risk GVHD who participated in a prospective, multi-center, observational trial and were treated with systemic steroids between 2015-2023. MAPs <0.291 at days 7 and 14 were defined as low risk based on a previously validated threshold [Major-Monfried Blood 2018]. Clinical responses were scored as complete (CR), partial (PR), or non-response (NR) by standard criteria. Initiation of second line therapy was considered NR. Patients were categorized into three groups (A-C) based on clinical responses and MAPs at days d7 and 14. A: CR/PR by d14 and low MAP at both d7+14; B: stable or worse GVHD (NR) by d14 with low MAP at both d7 and 14; C: any response with a high MAP at d7 or 14. The endpoints were clinical response at day 28 (overall response rate, ORR=CR or PR), regardless of earlier response status, and 6-month NRM. Results: The median age of the study population was 54 years (range: 0-79); 19% of patients received PT-Cy for GVHD prophylaxis. Target organ involvement was skin ± upper GI (66%), lower GI (23%), isolated UGI (11%), and skin+liver (1%), and GVHD severity was grade I (35%), II (61%), and III (4%) at start of treatment. Patients in group A (n=310, 69%), clinical responders with low MAPs through day 14, had excellent d28 ORR (93%) and very low NRM (4%). GVHD in this group was considered ultra-low risk (ULR) and subset analyses revealed highly consistent d28 ORR and NRM, regardless of target organ severity, age (<18, 18-59, >60), HCT-CI score, conditioning intensity, and GVHD prophylaxis. Group B patients comprised clinical non-responders with low MAPs through day 14 (n=112, 25%); half of them responded by d28 and their NRM was low (8%), albeit double that of group A (p=0.079). Group C was small (n=28, 6%) and included both clinical responders (n=20, 4%) and clinical non-responders (n=8, 2%) who had at least one high MAP through day 14. Their d28 ORR was 54% but NRM increased four-fold (32%) and was significantly worse than patients who maintained low MAPs regardless of clinical response (p<0.001). Conclusion: Serial monitoring by clinical response and biomarkers during the first two weeks of treatment identifies a small number of high risk patients whose GVHD is initially low risk (group C). This group experiences high NRM regardless of clinical response to steroid treatment and may benefit from treatment escalation. Patients with low risk GVHD who do not have an early clinical response to steroids but maintain low MAPs, (group B) have reasonably good long-term outcomes with standard treatment. Finally, serial monitoring identifies a very large subset of patients with ULR GVHD (group A) who respond exceptionally well to standard treatment and experience very low rates of 6-month NRM regardless of pre-transplant characteristics and GVHD prophylaxis. Such patients may benefit from treatment de-escalation strategies such as shorter courses of lower dose steroids, a strategy we are currently testing in a clinical trial (NCT05090384).

Background Endpoints for GVHD treatment trials use early response (i.e, day (D)28 of treatment) as a surrogate for long term survival. Overall response (OR) that combines complete (CR) and partial responses (PR) at day (D) 28 is the conventional endpoint for primary acute GVHD trials because of similar survival outcomes between CR and PR. D28 OR ignores symptom severity at baseline and D28, however, and the PR category encompasses a wide range of responses from minimal improvement to near complete resolution of symptoms. D28 OR is the only endpoint currently approved by the FDA for efficacy, but it has not been re-evaluated as an endpoint for primary treatment (1L) in fifteen years and little is known regarding the prognostic value of D28 OR as an endpoint for second line treatment (2L) of GVHD. We hypothesized that refinement of the current D28 OR criteria, particularly through recategorization of PR in the GI tract, the main driver of nonrelapse mortality (NRM), would more accurately reflect disease control and better predict survival outcomes than current D28 response. Methods The Japanese Society for Transplantation and Cellular Therapy (JSTCT) collaborated with the Mount Sinai Acute GVHD International Consortium (MAGIC) to develop and validate D28 refined response (RR) criteria for 1L and 2L treatment (tx) in patients with Grades II-IV acute GVHD. To maximize the correlation between treatment success (i.e, response) with long term survival, our primary measured metric was the negative predictive value (NPV). We first randomly divided the 1L tx cohort of JSTCT into the training (n=2341) and validation sets (n=1156). In the training set we used a classification and regression tree (CART) algorithm to generate RR criteria that predicted 6-month (mo) NRM based on symptoms both at tx onset and D28. We then compared the two D28 response endpoints (RR vs OR) as surrogates for 6-mo NRM in two validation sets of both 1L tx (JSTCT: n=1156; MAGIC: n=1141) and 2L tx (JSTCT: n=510; MAGIC: n=196). Results The CART algorithm defined a RR as GVHD Grades 0/I at D28 without additional tx; all other D28 grades were considered refined nonresponses. As expected, RR successfully stratified the risk of 6-mo NRM in both 1L tx validation sets (JSTCT: 8% vs 38%, p<0.01; MAGIC: 9% vs 37%, p<0.01). We defined a discordant nonresponse as a nonresponse by RR criteria but a response by OR criteria, which accounted for the majority (~75%) of differences between RR and OR. 6-mo NRM in discordant nonresponders was four fold higher than in responders (JSTCT: 35%; MAGIC: 30%). The large majority (>80%) of discordant nonresponders had persistent GI GVHD at D28. Because the proportion of discordant nonresponders was small (<7% of the total population) in the 1L setting, the improvements of an already high NPV were small (JSTCT: 93% vs 91%; MAGIC: 91% vs 90%). In the 2L tx validation sets, RR also stratified the risk of 6-mo NRM (JSTCT: 26% vs 56%, p<0.01; MAGIC: 13% vs 55%, p<0.01). At the time of 2L tx, the discordant nonresponders are more common and half of the discordant nonresponders experienced 6-mo NRM (JSTCT: 45%; MAGIC: 59%); as a result, RR achieved much higher NPVs than OR (JSTCT: 75% vs 66%; MAGIC: 87% vs 76%). Deaths in responders from acute GVHD (vs. other causes such as infection) were more frequent in OR than RR in both 2L tx validation sets (JSTCT: 41% vs 20%; MAGIC: 41% vs 13%) and 1L tx validation sets (JSTCT: 25% vs 18%; MAGIC: 32% vs 29%). D28 RR is superior to OR because it more accurately reflects control of serious GVHD in four independent validation cohorts, particularly in patients with GI disease. Conclusion We conclude that RR is a more accurate endpoint than OR in patients with grade II-IV GVHD primarily because it classifies persistent GI GVHD at D28 as a non-response instead of a response, which correlates with 6-mo NRM and achieves a higher NPV. This validated RR metric can serve as a better endpoint than OR in assessing treatment efficacy in both primary treatment trials that enrich for high risk GVHD, e.g. GI involvement, and second line treatment trials.

Background: Physical function (PF) is an important outcome that can inform cancer treatment tolerability from a clinical and regulatory perspective. PF can be assessed through different modalities: patient-reported (PRO), clinician-reported (ClinRo), performance tests (PerfO), and digital sensors (wearables). No standard approach for PF measurement has been defined, and each modality bears unique implementation challenges. The Integrating 4 Measures to Assess Physical Function study (In4M, NCT05214144) characterized the performance of these PF modalities in patients receiving cytotoxic chemotherapy, with a goal of guiding an assessment strategy in future cancer trials. Here we present feasibility results of the In4M study in patients with lymphoma. Methods: In4M is a prospective observational study with longitudinal PF assessment of PROs, ClinRo, PerfO, and wearable sensor data for over 9 months in patients initiating chemotherapy for lymphoma or breast cancer at Mayo Clinic and Yale University. Patient-reported PF was assessed using several validated ePRO instruments, ClinRo utilized clinician-reported Eastern Cooperative Oncology Group (ECOG) performance status, PerfO was measured via 6-minute walk test (6MWT), and digital sensor data was obtained from a wearable (Fitbit) provided to all participants. We evaluated the feasibility of implementing these PF modalities through compliance outcomes and a study-specific exit survey. Descriptive statistics included medians and interquartile ranges (IQR) for continuous variables and frequencies for categorical variables. We used a mixed model to estimate mean number of Fitbit compliant days per week. Results: Among 66 patients with lymphoma in the study (median age was 57 years; 52% were male), 90% self-reported as White, 4.9% as Black, 1.6% as Asian, 1.6% as American Indian or Alaska Native, and 1.6% as multiple races. Ethnicity was reported as non-Hispanic/Latino by 93% of patients. Education status was reported as more than high school by 92% of patients, and 49% reported full-time employment at time of enrollment. The overall ePROs completion rate was 80.7% for the entire study period. Baseline ePRO completion rate was 93.9%. Completion rate while undergoing chemotherapy was 91.3% and 75.4% in the post-treatment follow-up. The median time to complete ePROs was 4.1 minutes (IQR 2.8-5.9), ranging from 3.1 minutes for surveys with 37 questions to 5.6 minutes for surveys with 55 questions (survey length varied by timepoint). The baseline 6MWT was completed by 91% of patients. The most common reasons for not completing the baseline 6MWT were: patient refusal (50%, 3/6), patient not physically present (33%, 2/6), and unable to complete due to fatigue (17%, 1/6). The 3-month 6MWT was completed by 66% (40/61) of patients, with the most common reasons for missingness being: patient not physically present (38%, 8/21) and unable to complete due to fatigue (14%, 3/21). When considering the days when Fitbit was used, the median wear time was 21.3 hours (IQR 18.9-22.5) per day. The proportion of compliant days (>10 hours of wear time during waking hours) was 53% (IQR 20-84). The median of participants' average compliant days per week was 5.4 (IQR 4.3-6.1) days/week after enrollment, with a slight downward trend over time (-0.017 compliant days per week [95% CI: -0.021, -0.012, p <0.001] over each consecutive week in the study). The exit survey was completed by 39 (59%) patients. Most participants (85%) indicated they did not find the ePRO surveys burdensome to complete. Using the Fitbit (charging and syncing) was found to be manageable by most patients (87% and 84%, respectively). 60.8% of patients did not find the wearable bothersome to use, while the main themes reported by the remaining patients were related to the operation of the wearable itself (functions, small text size, forgetting login information) or discomfort (band material, wearing at night). Conclusion: Multi-modal assessment of PF with PRO, ClinRo, PerfO and wearable sensor data in patients with lymphoma undergoing treatment is feasible. Designing lymphoma therapeutic trials that incorporate at least one PF assessment modality, or assessment with a parsimonious combination of modalities, is achievable and may yield valuable insights into treatment tolerability for clinical and regulatory purposes.