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

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

Introduction: Diffuse large B cell lymphoma (DLBCL) patients experience favorable outcomes following frontline immunochemotherapy, however, 30-40% of patients will exhibit primary refractory disease or relapse (rrDLBCL). Recent studies have expanded upon well-defined characteristics of newly diagnosed DLBCL (ndDLBCL) to elucidate genomic landscapes underlying rrDLBCL; yet, high-throughput examination of resistance and relapse mechanisms within rrDLBCL subtypes, including the newly defined dark zone signature (DZsig) addition to cell of origin (COO), have yet to be described. To expand upon the current tumor etiology and define subtype-specific driving mechanisms, we describe a multi-omic analysis leveraging clinical and biologic variables in rrDLBCL. Methods: Tumor biopsies (N=228) collected at the time of relapse were obtained from n=85 participants in the Mayo Clinic/University of Iowa Lymphoma Molecular Epidemiology Resource (MER), n=73 in the Mayo Clinic Biobank, and n=38 from CC-122-DLBCL-001 or n=32 CC-122-ST-001 trials. Tumor samples were analyzed by WES (n=158) or WGS (n=70) and by RNAseq (n=145). Comparative analysis against ndDLBCL MER samples (N=444) utilized WES (n=404) and RNAseq (n=321). Chi Square or Fisher's exact test was used for enrichment analysis of categorical variables, while Wilcoxon or Kruskal-Wallis test was used for continuous variables. Results: rrDLBCL samples were enriched for ABC (46% vs 33% in ndDLBCL, p=0.01), and fewer GCB (27% vs 40%, p=0.006). Amongst rrDLBCL patients, variance in overall survival (from time of original diagnosis; log-rank p=0.001) was observed between COO subtypes, with poor outcomes in patients with DZsig (median 15.0 mo) and GCB (36.5 mo) compared to ABC tumors (74.4 mo). Patients with progression or relapse within 6 months featured a more even COO distribution (ABC - 22%, GCB - 34%, DZsig - 28%) than patients with early (6-24 mo; 51%, 22%, 22%) or late relapses (>24 mo; 62%, 19%, 4%), which were predominantly ABC. Comparing mutation frequency within subtypes, rrDLBCL GCB tumors were enriched for B2M (41% vs 15% in ndDLBCL, p=0.002), EP300 (19% vs 7%, p=0.059), CIITA (19% vs 5%, p=0.02), PRKCB (11% vs 2%, p=0.035), CD79B (11% vs 0%, p=0.004), and CD83 (8% vs 1%, p=0.049) mutations, and CNV events including gains at 8q24.21 (MYC locus; 48% vs 14%, p<0.001) and 18q21.33 (BCL2, TCF4 locus; 36% vs 15%, p=0.021), and losses at 17p13.1 (TP53 locus; 40% vs 19%, p=0.035). rrDLBCL DZsig tumors featured enrichment for BCL6 (22% vs 3%, p=0.025), and SPEN (17% vs 3%, p=0.062) mutations and 2q22.2 losses (LRP1B locus; 20% vs 0%, p=0.019). Despite differential mutation and CNV profiles, gene expression analysis revealed minimal variance within COO subtypes in rrDLBCL and ndDLBCL, however upregulation of lymphoma driving genes including MYBPC2 (LogFC=1.68, FDR<0.001), MYOM2 (LogFC=1.33, FDR=0.007), MYC (LogFC=0.61, FDR=0.04), and CELSR2 (LogFC=0.53, FDR=0.02) were observed in ABC rrDLBCL. Increased frequency of LymphGen classifier A53 was observed in ABC (43% vs 17%, p=0.005) and GCB (40% vs 14%, p=0.009) rrDLBCL. Using CIBERSORTx to infer lymphoma microenvironment (LME) cell type abundance, an LME-depleted class was evident in rrDLBCL tumors, including reduction of CD8+ T cells (effect size (r)=-0.78, p<0.001) and T follicular helper cells (r=-0.48, p=0.012) in GCB rrDLBCL and reduction of T follicular helper cells (r=-0.43, p=0.023) and Tregs (r=-0.32, p=0.065) in DZsig rrDLBCL. Significance: We present an update to the genomic landscape of rrDLBCL, highlighting GCB and DZsig tumors with differential biology and advanced clinical course. Our data supports increased implementation of sequencing efforts in rrDLBCL to more broadly evaluate relapse mechanisms, with optimism that a more detailed understanding of r/r disease may guide trials for targeted treatment strategies. For example, rrDLBCL patients may be strong candidates for MYC pathway targeting agents (BETi), or a Lenalidomide-based regimen (R2 or Tafa-Len), as Lenalidomide has been shown to reprogram the LME via PD-L1 expression in addition to downregulation of MYC and MYC target genes. Or, due to enrichment of variants affecting anti-apoptotic proteins including BCL6 or BCL2 in DZsig and GCB rrDLBCL, a venetoclax-based therapeutic may be considered. Further targeted strategies should be considered as development of a more personalized approach remains an unmet need.

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.

Background: A donor search prognosis score based on HLA type and race/ethnicity can classify patients into 3 groups based on the likelihood of finding an HLA-matched (8/8) unrelated donor (MUD): Very Likely (44% of the population), Likely (41%) and Very Unlikely (15%). Previous studies showed that >90% of Very Likely, 26% of Likely and <10% of Very Unlikely patients used a MUD for their hematopoietic cell transplants (HCT), with the rest using other donor sources (mismatched unrelated donor, cord blood, or haploidentical relative). For some patients, prolonged efforts to identify a MUD might be futile and delay HCT, leading to increased morbidity, greater chance for relapse and disease resistance, and worse HCT outcomes. BMT CTN 1702 (NCT03904134) was the first national study to track the entire donor search identification process. Designed as a biologic assignment study, the goal was to estimate and compare overall survival between two arms: patients who are Very Likely to find a MUD versus those who are Very Unlikely to find a MUD. It tested whether provision of a donor search prognosis score to centers could prevent prolonged futile searches for the Very Unlikely group and improve their transplant rates and outcomes, compared to the Very Likely group. Methods: Eligible diagnoses included acute leukemia, myelodysplastic syndromes, lymphoma, acquired aplastic anemia and sickle cell disease. Patients could be consented at any time after diagnosis until an unrelated donor search was started. Consented patients became evaluable only after it was determined that no appropriate HLA-identical siblings were available. The primary endpoint was survival time after the patient was declared evaluable, regardless of whether HCT occurred, and was compared between the Very Unlikely and Very Likely groups. The target enrollment was 1732 evaluable patients. Because this was a biologic assignment trial and not a randomized trial, formal comparisons of overall survival between the Very Likely and Very Unlikely groups were done using a covariate-adjusted Cox proportional hazards model. The following covariates were a priori specified for adjustment in the model, according to the statistical analysis plan: sex, age, Karnofsky Performance Score (KPS), race/ethnicity, disease, disease status, and interval from consent to evaluability. Results: 1751 evaluable patients were enrolled at 47 centers: 44% female, median age 59.4 years (range 0.6-81.3 years), 73% were non-Hispanic White, 10% Hispanic White, 8% Black, 5% Asian/Native Hawaiian/Pacific Islander, 0.5% American Indian/Alaska Native. Among the evaluable patients, 1181 received a HCT, 827 died, and 924 are still alive with or without HCT, with a median of 25 months of follow up (range=6-54 months [mos], inter-quartile range [IQR]=25-34 mos). The distribution was: 958 Very Likely, 517 Less Likely, and 276 Very Unlikely. Individuals in the Very Unlikely group were younger and were less likely to be non-Hispanic White. The unadjusted cumulative incidences of undergoing HCT by 6 mos and 2 years [yrs], in the Very Unlikely group were 51% and 61% vs. 60% and 69% in the Very Likely Group; after adjustment, there was not a significant difference in the likelihood of undergoing HCT (Dehn et al, submitted). There was no difference in median time from evaluability to HCT: 3.4 mos Very Unlikely and 3.3 mos Very Likely. Unadjusted survival rates from the time of evaluability for the Very Unlikely and the Very Likely groups were: 6 mos (85% vs 84%), 1 yr (69% vs. 69%) and 2 yrs (55% vs. 56%). In the multivariate Cox model, there was no significant difference in the risk of death (HR = 1.07 for Very Unlikely vs. Very Likely, 95% confidence interval 0.86-1.33, p=0.56) adjusting for significant clinical covariates: age, KPS, disease status, and time from consent to evaluability were all significantly associated with overall survival. There was no significant center effect and no interaction between donor search prognosis group and clinical covariates. Conclusion: In this large multicenter BMT CTN study, using the donor selection strategy described, there was no difference in adjusted time to HCT or survival for patients Very Likely versus Very Unlikely to find an 8/8 MUD. These results suggest that patients Very Unlikely to identify a MUD should proceed to HCT using the best available alternative donor rather than delaying HCT to try to identify a MUD.

Introduction: VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) is an adult-onset autoinflammatory disorder defined by somatic UBA1 mutations in hematopoietic cells. VEXAS is associated with a high frequency of clonal hematopoiesis (CH- 60%); with the clonal landscape being dominated by DNMT3A mutations. In our prior study (Gutierrez-Rodrigues Blood 2023), we showed that DNMT3A mutations in VEXAS associated with increased mortality, but without a higher risk of MDS/AML. As DNMT3A is a critical epigenetic regulator, we conducted this study to define the epigenetic deregulation and impact on mortality of DNMT3Amt (mutant) CH in VEXAS. Methods: After IRB approval, 88 VEXAS patients from the Mayo Clinic and the NIH were retrospectively assessed, including 81 screened for CH by error-corrected DNA sequencing (ECS). DNA methylation changes were identified using the Illumina Infinium MethylationEPIC BeadChip on peripheral blood samples (PB). Cellular indexing of transcriptomes and epitopes (CITE)-seq was performed using the 10x Chromium 3' GEX platform; 16,600 pooled cells were subjected to UMAP dimensionality reduction, followed by Azimuth based cell identification. Genotyping of targeted loci with chromatin accessibility (GoTChA) was conducted on two PB DNMT3Amt samples from CCUS individuals (Izzo et al Nature 2024). Results: Patients' median age was 70 years (range: 56 - 89); 95% were white. Twelve out of 81 patients screened by ECS were found with a DNMT3Amt (15%), with a median variant allele fraction (VAF) of 42% (range: 6-46%). In this cohort, while the presence of any CH mutation did not impact survival, DNMT3Amt CH had an age-independent negative impact on mortality (5.5 years vs 8.7 years, p =0.005), without an increase in risk for MDS/AML. Changes in DNA methylation were profiled in 19 and 9 VEXAS patients without CH (Median Age: 68) or with DNMT3Amt CH (Median Age: 74), respectively. VEXAS samples with DNMT3Amt CH had >4,000 differentially methylated CpGs with 95% of the CpGs being hypomethylated compared to those without CH. Using the Roadmap Epigenomics project, we found that this hypomethylation was enriched at enhancer (Enh) sites and actively transcribed states (TxWk). Pathway analysis revealed that the hypomethylated sites were in or near genes involved in the development and differentiation of leukocytes, with IL-13 and IL-15 being identified as upstream regulators of the methylation changes. Bulk RNA-seq performed on PB of 2 and 3 VEXAS patients with and without DNMT3Amt, respectively, identified >1,500 differentially expressed genes in DNMT3Amt samples, 78% of these being overexpressed. Pathway analysis was enriched in gene pathways involved in the development of leukocytes, with IL-13 and IL-15 once again being identified as upstream regulators. Integration of methylation and transcriptomic data identified upregulation of several genes within the IL-13 and IL-15 pathways, with these regions correlating with a decrease in methylation. To assess if the epigenetic dysregulation is linked to DNMT3A mutations, we performed GoTChA-seq on two DNMT3Amt clonal cytopenia samples (CCUS). The comparison of the number of cutsites in DNMT3A wild type vs mt cells from the same individual demonstrated increased open chromatin within the IL-13 and IL-15 pathways in mt cells, both globally and in a genomic locus specific manner. CITE-seq performed on 3 VEXAS samples (2 DNMT3Amt CH vs 1 no CH) further showed that expression of genes involved in IL-13 and IL-15 pathway is significantly increased in CD4+ and CD8+ T cells from DNMT3Amt samples, suggesting a paracrine regulatory effect of T lymphocytes (mostly UBA1 and DNMT3A wild-type) in VEXAS. Pathway analysis of DEGs in these cells also revealed an enrichment of genes involved in inflammation and lymphocyte proliferation. Conclusions: Our study validates the age-independent, negative prognostic impact of DNMT3Amt CH on survival in VEXAS syndrome. DNMT3Amt mediates epigenetic and transcriptional priming associated with upregulation of IL-13/15 pathway in CD4/CD8 T cells, which are mostly DNMT3A and UBA1 wild-type, suggesting that the contribution of T lymphocytes to inflammation may be secondary to CH in the myeloid compartment.

Introduction: Frailty is known to be an important risk factor for adverse outcomes in multiple myeloma (MM) and is often under-represented in clinical trials. Frail patients are known to have increased toxicity, high rates of treatment discontinuation rates and decreased efficacy including worse overall survival in MM. Teclistamab (TEC) is a bispecific BCMA-CD3 directed T-cell antibody (BsAb) that was approved based upon the pivotal MajesTEC-1 study showing high overall response rates in patients with R/R MM. In MajesTEC-1, the median age was 63, and patients with ECOG ≥ 2 were excluded, suggesting that the vast majority of patients in the trial were fit. There is a paucity of data both in clinical trials as well as in the real-world regarding the outcomes of patients, particularly frail patients, with BsAb. This data is needed to both understand current outcomes of frail patients as well as devise strategies for future optimization with BsAb treatment. We performed a retrospective analysis utilizing the International Myeloma Foundation (IMF) immunotherapy database with the objective of understanding the outcomes of older adults (age ≥ 70) including frail patients treated in the real-world with teclistamab. Methods: Data was collected from 7 individual academic sites for patients aged ≥ 70 years treated with teclistamab in the real-world. Data collected include patient demographics, disease characteristics, as well as efficacy and toxicity associated with teclistamab. Frailty score was retrospectively calculated using the simplified/IFM frailty index which includes chronological age, ECOG PS and Charlson Comorbidity Index categorizing the patients into fit (score 0-1) or frail (≥ score 2). Fisher's exact tests were performed to evaluate differences in outcomes between fit and frail patients. Results: A total of 81 pts were included in our total cohort. The median age was 76 year (range 70-91). Among them, 44 (54%) were > age 75 and 23 (28%) > age 80. Twenty-eight (35%) patients had an ECOG performance status of ≥2. Using the simplified/IFM frailty index, 22 (27%) were classified as fit and 59 (73%) were frail. In the frail subgroup, a high proportion of patients (42%) would be classified as ultra frail (frailty score of ≥3). Selected baseline patient and disease characteristics are as follows: high risk cytogenetics including 1q gain/amp (fit 67% vs frail 43%), median prior lines (fit 7 vs frail 5), triple class refractory (fit 81% vs frail 88%), CrCl <30 (fit 5% vs frail 15%). For patients hospitalized for step-up dosing, median number of hospital days was 8 both in the fit and frail group. All grade CRS was noted in 12 (55%) fit and 28 (47%) frail patients. Among the fit patients, only 1 of the 12 patients (8%) had grade 2 CRS, whereas 8 of 28 (29%) frail patients had grade 2 (p-value=0.23). ICANS was reported in 2 (9%) fit patients and 8 (14%) frail patients (p=0.72). The majority of ICANS was grade 1 in both groups, but among the frail group, there was one grade 3 and two grade 4 ICANS cases reported. Infections were reported in 10 (45%) fit patients and 35 (59%) frail patients (p=0.32), with 2 (9%) and 14 (23%) being grade≥3 (p-value=0.21). IVIG was administered in most patients (fit 50% vs frail 58%, p=0.62). Grade 3/4 neutropenia was reported in 10 (45%) fit patients and 19 (32%) frail patients (p=0.30). The overall dosing interval was changed in 32% of fit patient and 34% of frail patients (p=1.00). The overall response rate was 50% for fit patients versus 66% for frail patient (p=0.61). The type of responses noted in the fit patient were as follows: sCR/CR 18%, VGPR 27%, PR/MR 5%, SD 18%, PD/NE 32% and for frail patients : sCR/CR 18%, VGPR 43%, PR/MR 9%, SD 5%, PD/NE 25%. The median follow-up time was 13.1 months. 12-month PFS for fit pts was 47.6% (95% CI 25.7% - 66.7%) and for frail pts 42.4% (29.0% - 55.3%). 12-months OS for fit pts was 64.9% (95% CI 39.9% - 81.6%) and for frail 61.5% (47.0% -73.1%). Conclusions: This is the first real-world study to evaluate the outcomes of teclistamab in frail older adults. With regards to toxicity, frail older adults showed a trend towards higher rates of ≥ grade 2 CRS, ≥ grade 2 ICANS as well as ≥3 grade infections. Efficacy was maintained in both fit and frail older adults similar to the MajesTEC-1 study. Our study highlights that BCMA BsAb can be safely utilized in older adults including frail older adults; however, additional proactive supportive care may be required to further optimize outcomes.

Introduction: Understanding patient preferences and decision-making processes is crucial in managing relapsed multiple myeloma (RRMM). Shared decision-making has become a key element of patient-centered care, allowing patients to collaborate with healthcare providers in choosing treatments that align with their health and quality of life goals. This study examines how the perceived severity of treatment side effects influences patient decision-making autonomy and communication patterns, providing insights into decision-making practices in hematology. Methods: A survey was conducted with 784 RRMM patients as of January 1, 2024, using HealthTree Cure Hub (PMID: 35271305). Among the participants, 333 experienced a relapse and responded to the question about how side effect severity affected their treatment choices. Of these, 54% (n=181) considered side effects to be very or extremely influential (VE), whereas 46% (n=152) regarded them as somewhat, slightly, or not influential at all (SSN). Participants evaluated these factors on 5-point Likert scales: 1 (very poor) to 5 (very good); 0 (not at all influential) to 4 (extremely influential). The survey assessed patient involvement in final treatment decisions, discussions with fellow patients, family or caregivers, and the time allocated and used for decision-making. Results: Patients in the VE group reported a better understanding of the likely side effects of treatment options compared to the SSN group (VE: 3.9±1.0; SSN: 3.6±1.0, p<0.05), with a higher proportion reporting a very good understanding (VE: 31%, n=45; SSN: 18%, n=29, p=0.036). A weak relationship confirmed VE patients engaged in additional side effect education before making a change in treatment decisions (r=0.164, p=0.004). VE patients also reported a better understanding of the balance between effectiveness and potential side effects of treatments than SSN patients (VE: 3.8±1.0; SSN: 3.5±1.1, p<0.05), with more VE patients reporting a very good understanding (29%, n=41 vs. 15%, n=24, p=0.006). A weak relationship confirmed that VE patients more closely evaluated the trade-offs of treatment options when choosing a new treatment regimen (r=0.197, p<0.001). Likely to achieve a better understanding, more VE patients talked with fellow patients (VE: 19%, n=24; SSN: 7%, n=11, p = 0.003) and rated these conversations as more influential than SSN (VE: 1.5±1.5; SSN: 1.1±1.4, p<0.05). Additionally, VE patients were more likely to discuss treatment options with family or caregivers before making a final decision (VE: 49%, n=61; SSN: 29%, n=43, p<0.05). Moreover, VE patients reported greater involvement in their doctor-patient communication approach (VE: 3.2±0.8; SSN: 2.8±0.8, p<0.05), with scores ranging from 1 (“...follow the doctor's suggestions”) to 4 (“...we discuss my preferences... and I make the final decision”). Furthermore, VE patients reported more self-determination in the treatment decision-making process than SSN patients, with more VE patients making the final treatment decision themselves rather than having their doctor decide (“I made the final decision” - VE: 66%, n=93; SSN: 52%, n=81; “My doctor made the final decision” - VE: 34%, n=47; SSN: 46%, n=72, p=0.013). VE patients reported being provided 1.5 more weeks of time to make a treatment decision than the SSN (4.8±8.9 v. 3.3±6.0 wks, p<0.05). Subsequently, VE patients reported using 79% more time than SSN patients to arrive at a final decision (VE: 2.5±6.0; SSN: 1.4±1.9 wks, p<0.05), likely attributed to time spent gaining a better understanding, having more conversations with patients and family, more shared decision making and self-determination in their treatment decision. Conclusion: The study highlights that RRMM patients who consider side effects to be very or extremely influential in their treatment decisions report being more proactive in understanding and discussing their treatment options. These patients engage more with healthcare providers, peers, and family members and are granted more time to make informed decisions. This emphasis on understanding and communication underscores the importance of personalized patient education and shared decision-making in the treatment of RRMM, especially for patients who are highly influenced by potential side effects. Together, these findings underscore the ongoing need for patient-centered care and education to optimize treatment choices.

Severe COVID-19 is a multisystem condition with thromboinflammation as a significant driver of morbidity and mortality. Cellular components involved in inflammatory and coagulation responses include platelets, endothelium, monocytes, and neutrophils. Thrombotic manifestations, such as arterial thrombosis, venous thromboembolism, and tissue microthrombosis, occur in at least 20% of ICU COVID-19 patients, possibly more based on postmortem studies. This study investigates the presence of prothrombotic antibodies similar to those found in heparin-induced thrombocytopenia (HIT), a condition caused by platelet-activating antibodies targeting platelet factor 4 (PF4) when complexed with heparin (PF4/H). In a study of samples from 130 hospitalized patients collected on average 3.6 days after COVID-19 diagnosis, 80% were found to have IgG antibodies recognizing PF4/H. This percentage is significantly lower than in 22 HIT patients (100%) but higher than in 51 non-COVID-19 patients with acute respiratory symptoms (ARS) (25%) and 12 healthy subjects (0%). Additionally, 41% of the 130 patients had antibodies inducing PF4-dependent P-selectin expression in CpG-treated normal platelets, a rate significantly lower than in 12 HIT patients (100%) but higher than in 51 non-COVID-19 ARS patients (20%) and 12 healthy subjects (0%). Significantly, platelet-activating antibodies in COVID-19 patients were associated with a specific elevation of platelet α-granule proteins in the plasma and correlated with inflammation and tissue damage markers, suggesting these antibodies' functionality in patients. Significantly, unlike HIT, both PF4/H-reactive and platelet-activating antibodies were found in COVID-19 patients regardless of recent heparin exposure, indicating different antigenic stimuli for these antibodies in COVID-19. Notably, certain antibodies against the receptor-binding domain (RBD) of the spike protein of SARS-CoV-2 possessed sequence motifs, RKH and Y5, in the heavy-chain complementarity-determining region 3 (HCDR3) resembling those in pathogenic HIT antibodies identified in our previous studies, suggesting that these antibodies can activate platelets. Introducing exogenous RBD to COVID-19 plasma or IgG purified from COVID-19 plasma significantly reduced their ability to activate platelets. Furthermore, immunodepleting RBD-reactive antibodies from COVID-19 plasma or IgG purified from COVID-19 plasma using RBD-coated beads significantly reduced their ability to activate platelets. These findings demonstrate that some RBD-specific plasma IgG antibodies can activate platelets. To demonstrate the presence of RBD-specific, platelet-activating antibodies at the clonal level, we produced recombinant antibodies from 42 RBD-binding IgG+ B cells, tested their ability to activate platelets, and identified four that could do so. Interestingly, three antibodies possess HCDR3 sequences resembling RKH or Y5 motifs. Additionally, we identified RKH or Y5 motifs in RBD-specific antibodies reported by other groups, produced 15 such antibodies recombinantly, tested their ability to activate platelets, and identified four more that could do so. IgG+ B cells with these HCDR3 motifs were markedly expanded in severe COVID-19 patients, suggesting an expansion of B cells producing platelet-activating antibodies. The demonstration of functional and structural similarities between certain RBD-specific antibodies in COVID-19 patients and pathogenic HIT antibodies suggests a novel mechanism by which RBD-specific antibodies might contribute to thrombosis in COVID-19.