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

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

Background: Anaplastic large cell lymphomas (ALCLs) represent a heterogeneous group of T-cell lymphomas that currently are classified by the presence or absence of ALK tyrosine kinase (TK) fusion genes (ALK+ or ALK−) and clinical presentation (systemic, cutaneous, or breast implant-associated). Two overarching molecular types of ALCL recently were discovered, defined by the presence (Type I) or absence (Type II) of a gene expression signature highly enriched for JAK-STAT3 activation. Fusions involving non-ALK TK genes occur in some ALK− cases, but the fusion landscape of ALCL remains incompletely characterized. Methods: Expert consensus pathology review was conducted in the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). RNAseq was performed and fusions were identified using FusionCatcher. Here, we focused on recurrent in-frame coding fusions. Previously unreported fusions were validated by RT-PCR. Type I/II was assigned using a previously validated gene expression-based model. Genes with adjusted (adj) P<0.05 were considered differentially expressed. Overall survival (OS) was assessed for systemic ALCL, when available. Results: We evaluated 379 ALCLs (229M/150F; mean age, 56 y). Of 199 candidate fusions (excluding reciprocal events), 28 were recurrent and passed quality metrics. At least 1 of these 28 fusions was present in 150 cases (40%). ALK fusions were present in 106 ALK+ ALCLs (all Type I; P<0.0001). Of these, NPM1::ALK was seen in 68/106 (64%). Alternate partners (X::ALK) included ATIC (N=24) and CTLC, COL1A2, MSN, MYH9, RNF213, SATB1, TFH, TPM3, and TRAF1 (1-3 cases each). X::ALK was associated with older age (mean, 52 y) than NPM1::ALK (32 y; P<0.0001) and showed relative overexpression of 49 genes, including multiple activators of small GTPases such as CGNL1 (FC, 5.6; Padj=2.4×10-6), SRGAP1, ALS2, DOCK1, and NCKAP1. ALK expression was similar in cases with NPM1::ALK and X::ALK and there was no significant difference in OS. Non-ALK TK fusions were seen in 17/273 ALK− cases (6%), including TYK2 (N=9); JAK2 (N=6); and ROS1 (N=2). All were Type I ALCLs (P<0.0001). ALK− cases with non-ALK TK fusions overexpressed 38 genes compared to ALK− cases without TK fusions, including cytokines involved in the IL17 signaling pathway such as CXCL6 (FC, 12.5; Padj=4.2×10-3), CXCL1, and CSF3. We then assessed the relationship between ALK− cases with non-ALK TK fusions and ALK+ cases by separately comparing each subset to ALK− cases without TK fusions. FC values for ALK− cases with non-ALK TK fusions were significantly correlated with FC values for ALK+ ALCLs over the set of expressed genes (R=0.54; P<0.0001). At a median follow-up of 32 months, 0/4 systemic ALCL patients with non-ALK TK fusions had died, while 30% of those with ALK− ALCL without TK fusions had died, but this was not statistically significant (P=0.26). The other 13 ALK− cases with non-ALK TK fusions were either localized ALCLs or did not have outcome data available. Of 20 TP63 fusions, 17 (85%) were TBL1XR1::TP63 and 3 were X::TP63. As previously reported, TP63 fusions were associated with poor OS (median OS, 10 months; not reached for other ALK− ALCLs; P=0.007). Four ALCLs had a novel NCL::UBTF fusion involving genes encoding the nucleolar proteins nucleolin and nucleolar (upstream binding) transcription factor-1. Four cases each had PARG::BMS1 and TNK1::GPS2 (the latter seen only in Type I ALCLs). Conclusions: This large consortium-based analysis of coding fusions further elucidates the molecular distinction between Type I and Type II ALCLs. Both ALK and non-ALK TK fusions were seen exclusively in Type I ALCLs, which we have shown previously are enriched for JAK-STAT3 pathway genes and correlate strongly with pSTAT3Y705 positivity by immunohistochemistry. These fusions were not identified in Type II ALCLs, which previous data suggest are associated with epigenetic alterations. ALK+ ALCLs with NPM1::ALK and X::ALK showed differences in gene expression, suggesting biological differences. Furthermore, ALCLs with non-ALK TK fusions shared gene expression features with ALK+ ALCL. Clinical fusion detection could enhance molecular classification of Type I and Type II ALCLs and may guide precision therapy.

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

Introduction Plasmablastic lymphoma (PBL) is a rare aggressive subtype of lymphoma. It is more common in HIV positive patients, and is often associated with Epstein-Barr virus (EBV) and MYC rearrangements. PBL is characterized by markers of plasmacytic differentiation including CD138 and MUM1/IRF4, and loss of B-cell markers such as CD20, which suggests a cell of origin similar to that of multiple myeloma (MM) or activated B-cell-like (ABC) diffuse large B-cell lymphoma (DLBCL). The standard of care for PBL is CHOP-based chemotherapy but this is frequently not curative. Other than EBV-negative status, which defines a high-risk group, no other biological features have been discovered that are associated with outcomes. Methods Here, we provide a comprehensive analysis of the genomic and transcriptomic landscape of PBL using a collection of 176 exomes and genomes (n=55 new, contributed by Lymphoma/Leukemia Molecular Profiling Project [LLMPP] sites and centrally reviewed by the LLMPP pathology panel [WHO 2016]; n=121 previously published [PMID: 33225311, 33951889, 34465776, 34714908]), 65 transcriptomes (n=44 new; n=21 published) and 37 in situ single cell transcriptomic profiles (CosMx Spatial Molecular Imager) from archival diagnostic tissue biopsies. Somatic mutations (SNVs/Indels) were identified using an ensemble of four variant callers (Strelka2, Lofreq, Mutect2, SAGE). Salmon and DESeq2 were used to identify differentially expressed genes. This multi-omics dataset was compared to other known B-cell malignancies including 92 MM, 238 Burkitt lymphomas (BL), and 208 DLBCLs. Cell segmentation of the CosMx data was performed using Baysor and downstream analyses were conducted using the Seurat workflow. For functional validation, cell viability assays (CellTiter-Glo Luminescent Assay) were conducted in the PBL cell line, PBL-1, and 4 control DLBCL cell lines. Results Within the cohort, 63% (106/169) of primary PBL cases were EBV-positive (EBV+) and 57% (82/144) harbored MYC rearrangements (MYC+). When stratifying patients by EBV and MYC rearrangement status, mutations in different genes were enriched in each group: STAT3 occurred in 55% (29/53) of EBV+/MYC+ PBLs; NOTCH1 in 19% (7/36) of EBV+/MYC-; MYC in 24% (6/25) and TP53 in 40% (10/25) of EBV-/MYC+ tumors; TET2 was mutated in 38% (9/24) and KRAS in 25% (6/24) of EBV-/MYC- PBLs. EBV-/MYC+ tumors represented a subgroup of patients with dismal outcomes. The 2-year overall survival (OS) of these patients was 22% compared to 61%, 78%, and 54% of EBV+/MYC+, EBV+/MYC-, and EBV-/MYC- PBL patients, respectively (log-rank test p-adj. < 0.05). Consistent with previous studies, we observed recurrent mutations affecting JAK-STAT (STAT3, SOCS1, SOCS3, DUSP2) in 41% of cases and RAS-RAF (NRAS, KRAS, BRAF) signaling in 38% of all PBLs. In contrast to ABC-DLBCL, very few mutations occurred in the NF-κB signalling pathway. Accordingly, PBL showed marked downregulation of genes involved in B-cell receptor and NF-κB signaling. Consistent with the lack of reliance on these pathways, functional analyses in PBL-1 showed resistance to treatment to ibrutinib as well as PI3K- and MALT1-inhibitors. Moreover, constitutive expression of the IκBα super-repressor did not affect viability of PBL-1 cells. In situ single cell transcriptomic data analyses showed a sparse tumor microenvironment (TME) in PBL, with the primary non-malignant cell types being, on average, 10% macrophages, 7% NK/T cells, and 4% stromal cells of all represented cell types. EBV+/MYC+ tumors displayed a more abundant immune cell population with higher levels of macrophages (median 12%) and NK/T cells (median 9%), whereas EBV-/MYC- tumors were composed of the lowest levels of immune cells (median 4% macrophages and 1% NK/T cells). With respect to malignant cell phenotypes, we noted a novel population of SPP1-expressing cells that were enriched in EBV+/MYC+ tumors and a population of CD44-expressing cells that were enriched in EBV+/MYC- tumors. Conclusion Here we present novel subgroups of PBL with unique biology and clinical outcomes. We show that PBL does not rely on B-cell receptor signaling, instead relying on potentially targetable vulnerabilities in JAK-STAT, NOTCH, and RAS-RAF signaling according to EBV positivity and MYC rearrangement status. Lastly, we provide insight into the TME of PBL and demonstrate a novel population of SPP1 and CD44 expressing malignant cells in EBV+ tumors.

Introduction: Based on a donor versus no-donor analysis, UKALLXII/E2993 showed a survival benefit for adults with acute lymphoblastic leukemia (ALL) who underwent allogeneic hematopoietic cell transplantation (alloHCT) in first complete remission (CR1) compared to consolidation/maintenance chemotherapy alone. The follow-up phase 3 E1910 trial (NCT02003222) randomized BCR::ABL1-negative B-lineage ALL patients (pts) aged 30-70 years in measurable residual disease (MRD)-negative CR1 after intensification to conventional chemotherapy (CC) +/- blinatumomab (blin) and demonstrated significantly improved overall survival (OS) with blin (Litzow, NEJM 2024). The current exploratory subgroup analysis evaluates outcomes of MRD-negative pts randomized on E1910 who underwent alloHCT on trial. Methods: Among pts enrolled on E1910, pts in MRD-negative CR1 by 6-color flow cytometry after intensification who were randomized to CC +/- blin and subsequently underwent alloHCT were identified. We compared baseline characteristics, MRD status post induction, relapse-free survival (RFS) and OS using the Kaplan-Meier method and the two-sided log-rank test and Cox model. A multivariable analysis was performed with alloHCT included as a time-varying covariate as well as a landmark analysis comparing the outcome of pts with unfavorable risk on the CC + blin arm who underwent alloHCT versus those who did not. Results: Of 224 MRD-negative randomized pts, 44 underwent alloHCT on trial: 22 in each arm. The median time from randomization to transplant was 3.2 months (mos). The median follow-up from initial registration was 57.8 mos. Baseline demographics including age (median 55 years), gender (53% male), race (89% white) and ethnicity (89% non-Hispanic/Latino) were equally distributed. Compared to CC + blin, the median peripheral blood white cell (WBC) count and blast percentage at diagnosis were higher in the CC arm at 6,640 vs 3,740/uL and 55 vs 9%, respectively, while median marrow blast percentage and overall unfavorable risk as defined in E1910 (55% vs 64%) were similar. Of the 44 MRD-negative pts who proceeded to alloHCT on study, 77% in the CC arm and 64% in the CC+ blin arm were MRD-negative after induction. Myeloablative conditioning was given to the majority of pts (68% CC arm and 73% CC+blin arm) and the most common graft versus host disease prophylaxis was tacrolimus-based on both arms. Among the 44 pts who underwent alloHCT, the observed hazard ratio (HR) comparing relative risk of death between pts randomized to CC+blin or CC only was 0.59 (95% CI: 0.12-2.11) with a 3-year OS rate of 82% versus 71% and the HR comparing relative risk of relapse/death was 0.52 (CI: 0.15-1.79) with a 3-year RFS rate of 82% versus 67%. For patients with unfavorable risk, 3-year OS and 3-year RFS in each treatment arm were both 71% versus 65%. Among 50 pts with unfavorable risk in MRD-negative CR after intensification who were randomized to CC + blin, a landmark analysis performed at 5 mos post randomization showed 3-year OS and RFS rates of 71% versus 90% and 71% versus 86% between the 14 pts who underwent alloHCT and those who did not, respectively. Receipt of alloHCT was a time-varying covariate in a multivariable analysis with gender, WBC count, platelets, hemoglobin, peripheral blood blasts, bone marrow blasts, performance status, and combined molecular risk category. Age, CD20 status, rituximab use, and intention to receive alloHCT were used as stratification factors. In the entire cohort of MRD-negative pts who were randomized, there was a significant association between improved OS and the receipt of CC+blin vs CC alone (HR 0.46, 95% CI: 0.26 - 0.82; p=0.009), better performance status of 0-1 vs ≥2 and favorable vs unfavorable risk ALL. In contrast, the receipt of alloHCT had no significant effect on OS (HR 1.00, 95% CI: 0.49 - 2.01). Conclusions: Within the constraints of small numbers, this exploratory subgroup analysis demonstrates that in pts with newly diagnosed BCR::ABL1-negative B-ALL treated on E1910 who achieved MRD-negativity after intensification, alloHCT outcomes did not appear to be different with or without blin in consolidation. In a multivariate analysis of all MRD-negative pts, receipt of blin but not alloHCT was associated with improved OS. Further investigation is warranted to characterize the relative benefit of blinatumomab in pts receiving alloHCT in frontline consolidation.

Background: CD19-directed chimeric antigen receptor T-cell (CAR-T) therapy is an established treatment with high efficacy in treating relapsed or refractory (R/R) mantle cell lymphoma (MCL). However, with CAR-T therapy, refractory disease occurs and a continuous pattern of relapse over time has been observed. Limited data exist about post-CAR-T progression of disease (POD) management and outcomes in MCL. Such data would meaningfully inform practice and set a critical benchmark for future studies in the post-CAR-T setting. We characterized treatment patterns and outcomes for pts with POD after CD19 CAR-T therapy for R/R MCL. Methods: We queried institutional databases to identify pts with R/R MCL who received CD19-directed CAR-T therapy. Treatment may have occurred as standard-of-care or in a clinical trial. We performed chart review to extract variables and categorized therapies by mechanism(s) of action. We used descriptive statistics to characterize patient/disease characteristics and treatment patterns, the reverse Kaplan-Meier method to calculate follow-up, the Kaplan-Meier method to calculate survival, and Cox proportional hazards to associate clinical and disease features with survival outcomes. Results: Across 9 sites, we identified 306 pts who received CD19 CAR-T for R/R MCL, of which 104 (34%) experienced POD and were investigated in detail: pts with POD were mostly men (73%), had a median age of 67 yrs (range 36-86) at infusion, and had received a median of 3 lines of therapy pre-leukapheresis, including a BTK inhibitor (BTKi) in 97% of patients; 36% of BTKi-exposed patients had BTKi-unresponsive disease. High-risk tumor features were common pre-CAR-T: 47/68 (69%) with a TP53 mutation, 66/93 (71%) with Ki67 ≥50%, and 47/102 (46%) with blastoid/pleomorphic MCL. Most pts (75%) received bridging therapy. Pts received brexucabtagene autoleucel (88%) or lisocabtagene maraleucel (12%). Regarding best CAR-T response for pts with POD, 71% had a complete response (CR), 13% partial response (PR), and 15% had no response. The median time from CAR-T infusion to POD was 6 months (IQR 3-12). At time of POD, high-risk MCL features were again common: 55% blastoid/pleomorphic, 42/56 (75%) Ki67 ≥50%, 51/83 (61%) MIPIb high-risk, and 21/35 (60%) TP53-mutated MCL. Among 69 pts with CD19 assessed on a post-POD biopsy, 8 (12%) had CD19-negative disease. 30% of pts had an ECOG performance status of ≥2 at time of POD. After POD occurred, 15 pts received no anti-lymphoma therapy (Tx), 11 pts underwent excision or radiation, and 78 pts received systemic therapy. The most commonly used first-line systemic Tx post-CAR-T progression included: pirtobrutinib in 13 pts [overall response rate (ORR) 31%], chemoimmunotherapy in 12 pts (ORR 25%), venetoclax in 10 patients (ORR 20%), bispecific antibodies (BsAb) in 10 pts (ORR 60%), and small molecule combinations (at least 2 of BTK inhibitor, BCL2 inhibitor, and lenalidomide) in 8 patients with ORR 50%. The ORR to all first systemic Tx post-POD was 42%. The median follow-up from POD is 15.2 months among survivors. The median progression-free and overall survival (OS) from time of POD were 2.3 (95% CI 1.9-3.4) and 5.4 months (95% CI 4.5-9.4), respectively, and 1-year OS rate was 33%. TP53 mutations predicted inferior OS (HR 2.83, 95% CI 1.08-7.43, P = 0.026) as did age ≥65 years at time of POD (HR 1.83, 95% CI 1.07-3.15, P = 0.023), MIPIb high-risk (HR 3.56, 95% CI 1.08-11.7, P = 0.042), and non-response to CAR-T (HR 3.55, 95% CI 1.93-6.53, P < 0.001). Discussion: Our data, the largest reported cohort of pts with POD post-CAR-T with R/R MCL, confirm the poor prognosis in this patient population, with a median OS of 5.4 months. BsAbs showed promise with an overall response rate of 60%. The presence of a TP53 mutation significantly predicted inferior OS, corroborating the prognostic importance of this finding in the post-CAR-T context. Data from pts treated at additional sites and updated analyses will be presented at the meeting.

Background: Polatuzumab vedotin (Pola) is an antibody drug conjugate targeting CD79b that incorporates the microtubule disrupting monomethyl auristatin E payload. Pola was approved in 2023 for the upfront treatment of diffuse large B cell lymphoma (DLBCL) in combination with rituximab, cyclophosphamide, doxorubicin, and prednisone (polaRCHP) based on the POLARIX trial. However, the activity of pola appears to vary based on DLBCL cell of origin (COO) subtype, with greater efficacy in activated B cell (ABC) DLBCL compared to germinal center B cell (GCB) DLBCL (Russler-Germain Blood 2023). When outcomes in POLARIX are stratified by COO, polaRCHP demonstrated progression free survival (PFS) and overall survival (OS) benefits over RCHOP in patients with ABC but not GCB subtype DLBCL (PFS HR 0.34 ABC vs 1.03 GCB, OS HR 0.27 ABC vs 1.64 GCB; Morschhauser ASH 2023 and FDA data). Most prospective studies of pola used gene expression to assess COO, which is not readily clinically available. This study aims to examine if COO subtype by Hans algorithm (based on CD10, BCL6, and MUM1 expression by immunohistochemistry) is predictive of pola responses and outcomes in patients with large B cell lymphoma (LBCL). Methods: We conducted a retrospective, multicenter observational study of adults with LBCL who received pola (monotherapy or in combination) from 2015-2024 with Hans algorithm COO data and response assessment available. Patients were stratified by receipt of pola in the frontline vs relapsed/refractory (R/R) setting. The primary endpoint was overall response rate (ORR) to pola-based treatment in GCB vs non-GCB subtypes. Secondary endpoints included complete response rate (CRR), PFS, and OS. For time to event endpoints, patients responding to pola who received CAR T or stem cell transplantation prior to progression were censored at time of cellular therapy. Demographics were summarized by descriptive statistics. Comparative and survival analyses used Chi squared/Fischer exact tests and Kaplan Meier analysis. Data cutoff was July 1, 2024. Results: 718 patients were included. Median follow-up was 15 months (interquartile range [IQR] 8-32). Median age at LBCL diagnosis was 66 years (IQR 56-74); 62% were men; 69 (10%) had double hit lymphoma (DHL); 129 (18%) had underlying low grade lymphoma. Pola was used in the frontline setting in 293 (41%) patients, of whom 139 (47%) had GCB vs 154 (53%) non-GCB COO. Of the 426 patients receiving pola for R/R LBCL (including one patient receiving pola retreatment), 224 (53%) had GCB vs 202 (47%) non-GCB COO. Among patients receiving pola-based regimens in the R/R setting (GCB vs non-GCB: pola monotherapy = 7% vs 4%, pola + R = 26% vs 26%, pola + BR = 55% vs 61%, pola + other = 12% vs 9%; p = 0.44), the ORR in GCB vs non-GCB LBCL was 36% vs 61% (p < 0.001), while CRR in GCB vs non-GCB was 17% vs 36% (p < 0.001). COO remained a significant component of logistic multivariate regression models of ORR (p < 0.001) and CRR (p < 0.001) when incorporating IPI at original LBCL diagnosis, histology, DHL status, and refractory status to frontline therapy. Despite this, no significant PFS or OS differences by COO were seen, potentially due to approximately 1/4 patients being censored due to receiving subsequent cellular therapy (e.g. CAR T) prior to progression. In patients receiving frontline pola-based regimens (of which 275 [94%] included an anthracycline), ORR and CRR were similar in GCB vs non-GCB (ORR 89% vs 88% p > 0.5; CRR 76% vs 77% p > 0.5). While PFS and OS were similar between COO groups in the frontline cohort, follow-up and cohort size were limited. Conclusion: Based on this real-world evidence, COO classification by Hans algorithm is a strong predictor of the activity of pola-containing therapy in R/R LBCL, with significantly higher ORR and CRR in patients with non-GCB compared to GCB COO LBCL. This aligns with the cumulative existing evidence. ORR and CRR to pola-containing therapy in the frontline setting did not differ significantly by COO subtype, but longer follow-up of larger cohorts is needed to clarify the predictive role of COO by Hans algorithm in this setting, especially considering the PFS advantage with polaRCHP in POLARIX was not associated with significant differences in ORR or CRR. Overall, clinicians should consider factoring COO subtype into treatment decisions regarding pola-containing regimens, and studies of pola-based therapies should stratify patients and report outcomes by COO subtype.

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.

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.