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INTRODUCTION: The Stromal Antigen 2 ( STAG2), on Xq25, is the most common cohesin complex gene mutated in myeloid neoplasms (MN) (5-10%). STAG2 mutations ( STAG2m) were incorporated in the ELN2022 as AML-MDS defining genetic mutations inferring poor prognosis and is a genetic marker in IPSS-M risk stratification. The PHD-finger protein 6 ( PHF6) gene, on Xq26.3, is a tumor suppressor gene, mutated in 3% of MN, and is more common in T-ALL. PHF6m is believed to be a late event in MN with little data on its prognostic implications in MN. Both STAG2m and PHF6m are more prevalent in males, but their implications on the clinical presentation of MN have not been compared prior. METHOD: Our study is a multicenter study at Mayo Clinic (Rochester, Florida, Arizona). After IRB approval, we retrospectively analyzed charts of 7935 patients who had NGS between 2016-2022. STAG2m was found in 96 patients, and PHF6m in 116 (including 3 with concurrent STAG2m and PHF6m). We excluded 4 PHF6m patients who had T-ALL. Data was captured at time of NGS. MDS risk stratification was by IPSS-M and AML by ELN2022. Overall survival (OS) was calculated from date of NGS to date of last follow-up. BlueSky Software was used for statistical analysis. RESULTS: Characteristics: We compared 96 STAG2m vs 112 PHF6m MN patients. Of STAG2m cases, 78% were male vs 76% in PHF6m MN. Median age was 72 vs 73 years, respectively. Diagnoses included AML (29% of STAG2m vs 34% of PHF6m MN), MDS (54% vs 28%), MDS/MPN (10% vs 21%) and MPN (3% vs 9%). MDS was more common among STAG2m MN (p<.001) while MDS/MPN was more common among PHF6m MN (=.05). MDS-IB was the most common subtype in both (69% vs 52% in STAG2m vs PHF6m MDS). MDS-LB and 5q subtypes were only found in PHF6m MDS, and there was more PHF6m MDS-RS (13% vs 2%). Median IPSS-M score was 0.9 vs 0.8 in STAG2m vs PHF6m MDS (both high-risk). Majority of STAG2m AML were adverse risk (96%) while PHF6m AML were intermediate (79%) (p<.001). AML cases included 43% vs 30% secondary AML (sAML) in STAG2m vs PHF6m AML. Among STAG2m and PHF6m MN, 17% of each were tMN. Cytogenetic abnormalities were more common in PHF6m MN (50% vs 31%, p=.005). The median bone marrow (BM) blasts count among STAG2m MN was 7% vs 4% in PHF6m MN (p=.03). Genetic characteristics: STAG2m were nonsense, frameshift and splice site (54%, 36% and 11%). PHF6m were nonsense, frameshift, splice site, missense and start loss variant mutations (44%, 33%, 12%, 10% and 1%). The median variant allele frequency (VAF) of STAG2m MN was 50% compared to 32% in PHF6m MN (p=.008). Co-mutations: The median number of co-mutations was 3 in STAG2m and 4 in PHF6m MN (p=.04). The most common were TET2m (37% in STAG2m MN vs 45% in PHF6m MN), RUNX1m (31% in both), SRSF2m (39% vs 20%), ASXL1m (66% vs 38%), BCORm (19% vs 6%), U2AF1m (13% vs 14%) and IDH2m (18% vs 7%). ASXL1m, SRSF2m, BCORm, IDH2m and SF3B1m were more common among STAG2m MN (p=<.001, .003, .006, .02, .09). JAK2m, IDH1m are more common among PHF6m MN (p=.02, .06). Survival: Of STAG2m and PHF6m MN, 70% and 72% of patients received treatment. HSCT was performed in 23 (24%) and 23 (21%) of STAG2m and PHF6m patients, including AML (n=9, n=10), MDS (n=12, n=8), MDS/MPN (n=2, n=2). OS among STAG2m and PHF6m MN was 20.5 and 22.1 months, respectively. OS among AML cases was 13.5 vs 21 months (p=.6) in STAG2m vs PHF6m, was NR vs 22 months (p=.4) in MDS, 11.7 vs 17.6 months in MDS/MPN (p=.4), and 10.4 vs 27.4 months (p=.5) in MPN. There was no difference between males and females in either STAG2m or PHF6m MN. HSCT led to longer OS among both STAG2m (NR vs 19.9 months, p=.01) and PHF6m MN patients (NR vs 17.6 months, p=.07). Among AML patients, HSCT did not significantly impact OS (18 vs 9.6 months, p=.3 and 25.1 vs 21 months, p=.2, in STAG2m and PHF6m). HSCT improved OS in STAG2m MDS (NR vs 20.5 months, p=.03). In PHF6m MDS, OS was 22.1 vs 13.1 months in HSCT vs non-HSCT (p=.3). CONCLUSION: STAG2m and PHF6m are 2 X-linked mutations that occur in MN. Both commonly occur in elderly males. MDS was the most common diagnosis in STAG2m MN. STAG2m co-occurred particularly with SRSF2m ASXL1m and BCORm, which are associated with poor prognosis. In our cohort, STAG2m AML carried a poorer prognosis than PHF6m AML. Our study confirms the ELN2022 AML risk stratification. MDS risk classification and OS did not differ between STAG2m and PHF6m in our cohort. A larger cohort is required to confirm our findings and may provide stronger validation.

Introduction The advent of venetoclax (VEN) based chemotherapy has revolutionized the treatment of elderly acute myeloid leukemia (AML), with improvement in remission rates from historical 10%-20% to 60%-70%. However, remission duration is short-lived in patients (pts) with high-risk AML with consequent dismal outcome. As our knowledge of genomic landscape of AML expands and more immunotherapies become available, exploration of the immune tumor microenvironment (TME) of AML may allow identification of subsets of pts that may benefit from immune based therapy. We conducted an investigator initiated prospective study to evaluate TME of pts receiving VEN plus hypomethylating agent (HMA; azacitidine or decitabine) combination. We hypothesize that these pts will cluster into immune-infiltrated vs. immune-depleted sub-types by high-definition immune cell profiling. Methods In 26 newly diagnosed AML pts, who were planned to receive VEN plus HMA therapy, we isolated bone marrow (BM) and peripheral blood (PB) derived mononuclear cells (MC) by density gradient centrifugation and cryopreserved. We performed CyTOF (cytometry time-of-flight) analysis to study their immune signatures. Thawed cells were labeled with metal-conjugated antibodies that bind CD33, CD196, CD19, CD127, CD11b, CD4, IgD, CD11c, CD14, CD56, CD123, TCRgd, CD185/CXCR5, CD45RA, CD27, CD28, CD66b, CD183 (CXCR3), CD161, CD45RO, CD197 (CCR7), CD8a, CD25, CD3, CD20, CD38, HLA-DR, CD194 (CCR4), CD57, CD16 and CD45. We performed a Rphenograph clustering on 25 paired BMMC and PBMC samples (one patient only had PBMC) to create 35 unique clusters for each ( Figure 1). Then we broke down the distribution of cluster by two different groupings: pts with TP53 mutation (m) and those who achieve complete remission. Statistical significance of clusters calculated using t-test. We performed Pearson correlation test on the paired BMMC and PBMC samples to assess correlation between BMMC and PBMC samples. Results Baseline characteristics The median age of the pts was 74 years (range, 53-88), and 17 (65%) pts were male. Ten (37%) pts had secondary AML, and 12 (46%) pts had ELN adverse risk disease (n=6; TP53m). There was no significant difference in median age (p= >0.99), proportion of pts with secondary AML (p= 0.64), acute myelomonocytic leukemia (p= 0.14) white blood cell count (WBC) ≥ 100 (10 9/L) (p= >0.99), and frequency of commonly occurring co-mutations ( ASXL1 [p=0.35]), FLT3 ITD [p=0.54], splicing [p=0.29], IDH1/2 [p=0.28], DNMT3A [p=0.29], NPM1 [p=0.29], TET2 [p=0.35]) in TP53m and TP53 wild-type group. Response 12/20 (60%) evaluable pts achieved complete remission with or without count recovery (CR/CRi). There was no significant difference in median age (p= 0.06), proportion of pts with secondary AML (p= 0.16), therapy related AML (p= 0.60) WBC ≥ 100 (10 9/L) (p= 0.40), and frequency of commonly occurring mutations ( TP53 [p=0.60], ASXL1 [p > 0.99]), FLT3 ITD [p=0.54], splicing [p > 0.99], IDH1/2 [p=0.60], DNMT3A [p=>0.99], NPM1 [p=0.61], TET2 [p >0.99]) in CR/CRi and no-CR/CRi group. CyTOF analysis and Rphenograph clustering on 25 paired BMMC and PBMC samples We found significant clustering with high expression of B-cell activated (cluster 2; p= 0.005), NK cell rich (cluster 1; p= 0.005, cluster 35; p= 0.0009), CD8 T-cells (cluster 31; p= 0.01) and CD4 effector cells (cluster 17; p= 0.005) phenotype among TP53m AML ( Table 1). Among pts who achieved CR/CRi, significant clustering with low expression of B-cell activated (cluster 29; p= 0.01), CD8 cytotoxic (cluster 14; p= 0.01) CD4 activated (cluster 21; p= 0.03) phenotypes observed. Correlation between BMMC and PBMC clustering Among clusters which showed significance for a particular phenotype, we performed Pearson correlation (R 2) and observed strong correlation between BMMC and PBMC samples clustering in cluster 1 (R 2 = 0.99), cluster 2 (R 2 = 0.95), cluster 17 (R 2 = 0.96), cluster 21 (R 2 = 0.99) and cluster 29 (R 2 = 0.93). Conclusion In this single institutional study using CyTOF analysis we have identified novel clustering with immune- infiltrated phenotype among pts with TP53m AML and conversely immune-depleted phenotype among AML pts who responded to VEN plus HMA. Moreover, we found strong correlation in CyTOF analysis conducted from BMMC and PBMC samples. Future studies with larger sample size needed to validate our findings.

Introduction Chronic myelomonocytic leukemia (CMML) can be classified into dysplastic (dCMML) and proliferative (pCMML) subtypes based on a white blood cell count (WBC) ≥ 13 x 10 9/L for pCMML. Though this cutoff may seem arbitrary, there is evidence that pCMML is a unique biological entity with a distinct molecular profile and worse outcomes (Carr RM, et al. Nat Commun. 2021). We hypothesized that contemporary CMML prognostic scoring systems - such as the Mayo Molecular Model (MMM; Patnaik MM, et al. Leukemia. 2014) and the CPSS-Molecular Model (CMM; Elena C, et al. Blood. 2016) - would not adequately risk-stratify pCMML patients. Moreover, while truncating ASXL1 mutations are considered a high-risk feature in CMML, their prognostic relevance in pCMML is unknown. Methods After IRB approval, we compiled a large (n = 888), molecularly-annotated database of CMML patients seen at two US medical centers (Mayo Clinic and MD Anderson) via retrospective chart review. All statistical analyses considered the clinical and laboratory parameters obtained at the time of presentation. The cohort was divided into dCMML and pCMML subgroups, which were analyzed independently alongside the entire cohort. Categorical variables were compared by Fisher exact or Pearson χ 2 tests and continuous variables by Mann-Whitney U tests. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Survival was assessed via the Kaplan-Meier method. P-values < 0.05 were considered significant. Calculations were performed using the BlueSky Statistics (v10.3.1) interface for R. Results We identified 474 (54%) dCMML cases and 410 (46%) pCMML cases with median age 71 years and 67% males. Patients with pCMML were more likely to have higher AMC (5.1 vs 1.5 x 10 9/L, p < 0.0001), circulating immature myeloid cells (IMC; 65% vs 36%, p < 0.0001) and abnormal karyotypes (37% vs 30%, p = 0.0187). They were also overrepresented in higher-risk categories of the MMM and CMM compared to dCMML (p < 0.0001 for each model). The number of somatic mutations was higher in pCMML than dCMML (mean 3.0 vs 2.6, p = 0.0050). Mutations in ASXL1 (53% vs 39%), NRAS (21% vs 11%), CBL (18% vs 12%), SETBP1 (14% vs 7%), JAK2 (10% vs 3%), CEBPA (5% vs 2%), GATA2 (3% vs 0%), and FLT3 (3% vs 1%) were more frequent while mutations in TET2 (38% vs 48%), SF3B1 (2% vs 8%), ZRSR2 (2% vs 8%), and NPM1 (1% vs 3%) were less frequent in pCMML compared to dCMML, respectively (p < 0.05 for all). Though the MMM and CMM effectively stratified the dCMML group, they did not provide meaningful risk stratification in the pCMML group (MMM p < 0.05 overall but could not distinguish between low and intermediate-1/2 or intermediate-1 and high risks; CMM p > 0.05). Likewise, there was no difference in the median overall survival (OS) or leukemia free survival (LFS) when pCMML patients were stratified by truncating ASXL1 mutations( Figure 1A). We then sought to better risk stratify pCMML. Univariate analysis identified increasing age, male gender, abnormal karyotype, and elevated WBC, ANC, and AMC as adverse predictors for OS. In addition, the presence of IMC and peripheral blood (PB) blast % were adverse factors for LFS, while age was not significant for LFS. None of the aforementioned mutations were significant in the univariate model for OS, whereas GATA2 and NPM1 mutations were significant for LFS. In multivariate analysis for OS, only male gender and AMC ≥ 10 x 10 9/L retained significance. In multivariate analysis for LFS, male gender, AMC ≥ 10 x 10 9/L, and peripheral blasts ≥ 5% remained significant; GATA2 and NPM1 mutations were not significant. These variables risk-stratified pCMML patients based on the presence of 0, 1, or ≥ 2 risk factors ( Figure 1B). In comparison, OS was 40.7 months (95% CI 35.2 - 50.1 mo.) for dCMML patients, 20.1 months (95% CI 18.2 - 22.7 mo.) for pCMML patients, and 31.8 months (95% CI 28.4 - 33.5 mo.) for the entire cohort. At last follow up, 586 deaths (66%) and 168 AML transformations (19%) were recorded in the cohort. Deaths in dCMML vs pCMML were 294 (62%) vs 291 (71%; p = 0.0067), with AML transformations in 83 (18%) vs 84 (21%; p = 0.2055) patients, respectively. Conclusions Truncating ASXL1 mutations, along with ASXL1-mutation weighted CMML prognostic models failed to effectively risk stratify pCMML patients. In pCMML, male gender and AMC ≥ 10 x 10 9/L, effectively risk stratified for OS, while these factors along with PB blasts ≥ 5% effectively risk stratified for LFS.

BACKGROUND: Recent World Health Organization (WHO) classifications (5 th edition), International Consensus Classification (ICC) recognized TP53-mutated ( TP53mut) myeloid neoplasms (MNs) as a distinct subcategory, acknowledging their uniformly poor outcomes. However, there are critical differences between the two guidelines in how TP53 allelic status is assigned. Both WHO-5 and ICC acknowledged the poor outcome of multi-hit TP53mut but excluded single-hit TP53mut. These changes are driven by a pivotal study demonstrating favourable outcome of single-hit TP53mut, however this study predominantly included de novo myelodysplastic syndromes (MDS) cases (Bernard et al. Nat Med 2020). In contrast, we previously reported poor outcome of TP53mut therapy-related myeloid neoplasm (t-MN) irrespective of the allelic status of TP53 (Hiwase et al Blood 2022andShah et al BCJ 2023). Finally, the ICC removed the subcategory of “therapy-related,” substituting it with diagnostic qualifiers instead. The WHO has grouped t-MN with secondary MN and renamed it as “myeloid neoplasm post cytotoxic therapy,” with the assertion that only multi-hit T P53mut MDS occurring post-cytotoxic therapy have poor outcome compared with single-hit. METHODS: We analyzed one of the largest international cohorts of TP53mut MN (n=544) with full characterization of TP53mut allele status utilizing uniform ICC criteria and similar large numbers of de novo and t-MN cases managed at Mayo Clinic Enterprise (USA) and South Australian MDS Registry, Adelaide (Australia) with clinical, integrated genomic profiling, and long-term follow-up. RESULTS: In our cohort of TP53mut MN (n=544), 475 (87.3%) MN had TP53mut variant allele frequency (VAF) of ≥10% and thus satisfied ICC criteria for TP53mut MN. Majority of TP53mut t-MN presented with MDS (bone marrow (BM) blasts 0-9%) compared de novo MN (62% vs. 48%; P=0.0012). While acute myeloid leukemia (AML) (BM blasts ≥20%) were more prevalent in TP53mutde novo MN compared to t-MN (38% vs. 24%; P= 0.001) and there was no difference in frequency of MDS/AML (BM blasts 10-19%) between the two cohorts (14% vs. 14%; P=0.8) ( Figure 1A). Majority of TP53mut were observed in the DNA-binding domain in t-MN and de novo MN (95% vs. 96.2%; P=0.48). However, mutations in Tetramer Domain were more frequent in t-MN (4.3% vs. 0.3%; P=0.002), whereas those in the TAD2 domain were more frequent in de novo TP53mut MN (2.4 vs. 0%; P =0.006). Integrating the mutation, conventional G-banding cytogenetic, copy number variation (CNV), FISH, and SNP array analysis, TP53mut MDS (BM blast 0-9%; n=260) were classified as multi-hit (n=179, 68.9%) or multi-equivalent (n=35, 13.5%) and single-hit (n=46, 17.7%) (Arber et al. Blood 2022). Striking enrichment of multi-hit/multi-hit equivalent was observed in TP53mut t-MDS compared to de novo MDS (91% vs. 72%; P<0.0001). While single-hit TP53mut were prevalent in de novo MDS compared to t-MDS (28% vs. 9%; P<0.0001). Importantly, median overall survival (OS) of single-hit was significantly longer than multi-hit de novo MDS (25.4 vs. 7.2 months; P=0.0002). In contrast to this we did not observe OS difference between single-hit and multi-hit TP53mut t-MDS (11.6 vs. 10.9 months; P =0.73) ( Figure 1B). CONCLUSION: Our study based on a large international cohort of T53mut MN provides compelling evidence that in contrast to de novo MDS, single hit TP53mut t-MDS is associated with poor outcome. Our data supports the consideration of single hit t-MDS as a multi-hit equivalent.

Background: Ph-like ALL is a high-risk subset of B-lineage ALL that responds poorly to standard chemotherapy regimens. While allogeneic hematopoietic cell transplantation (HCT) is routinely recommended for patients with Ph-like ALL, large multicenter data addressing its role is limited. Here, we conducted a multicenter study to evaluate the role of HCT in adolescent and young adult (AYA) and adult patients (pts) with Ph-like ALL and compare their outcomes to pts with Ph-pos and Ph-neg (non-Ph-like) ALL. Methods: The study included pts (age ≥18) with B-lineage ALL who received HCT in first complete remission (CR1) at 3 academic centers (MD Anderson Cancer Center, City of Hope and Mayo Clinic) between 2006 and 2021. Pts were divided into 3 main subgroups: Ph-like, Ph-pos and Ph-neg ALL. Ph-like ALL cases were identified using cumulative data obtained by targeted RNA sequencing, conventional cytogenetics, FISH studies, whole genome chromosomal microarray and flow cytometry. Measurable residual disease (MRD) prior to HCT was measured using flow cytometry with a sensitivity of 0.01% for Ph-neg and Ph-like ALL, and with a PCR assay for BCR::ABL1 for Ph-pos ALL. MRD-negativity was defined as <0.01%. Predictors of relapse were evaluated in univariate and multivariate analysis using Fine-Gray sub-distribution hazard models considering non-relapse mortality (NRM) as a competing risk. Results: 673 patients were identified, 83 (12.3%) had Ph-like ALL, of which 73% had CRLF2-alterations. The remaining patients were classified either as Ph-pos (N=271, 40.3%) or Ph-neg ALL (N=319, 47.4%). Patients with Ph-like ALL were younger (median age 40 years vs 48 and 46 years for Ph-pos and Ph-neg ALL, respectively, p=0.01), more likely to be of Hispanic ethnicity (69% vs 32% and 48% for Ph-pos and Ph-neg ALL respectively, p<0.001). Patients with Ph-like ALL were also more likely to have induction failure (24% vs 2% and 11% for Ph-pos and Ph-neg ALL, respectively, p=0.001). A summary of pts characteristics for each subgroup can be found in Table 1. The median follow-up was 30, 52 and 48 months for patients with Ph-like, Ph-pos and Ph-neg ALL, respectively. In univariate analysis, 3-yr OS and PFS did not differ significantly (66% and 59% vs 59% and 54%, p=0.1) between patients with Ph-like and Ph-neg ALL, respectively. Similarly, the cumulative incidence of relapse was comparable between patients with Ph-like and Ph-neg ALL (22% vs 20%, respectively, p=0.7). In contrast, the 3-yr OS (75%, p<0.001) and PFS (70%, p=0.001) were significantly higher and relapse rate significantly lower (12%, p=0.003) in pts with Ph-pos ALL compared with Ph-like or Ph-neg ALL (Figure 1). The inferior survival in patients with Ph-like and Ph-neg ALL was likely attributable to higher relapse rates (22% and 20% vs 12%, respectively, p=0.003) compared to Ph-pos ALL. Finally, the 3-yr NRM rate in patients with Ph-like ALL was comparable (20% vs 18% and 23%, respectively, p>0.1) to Ph-pos and Ph-neg ALL. We confirmed that the relapse rate in patients with Ph-like ALL was comparable to the rate in pts with Ph-neg ALL (HR=1.02, 95% CI 0.6-1.8, p=0.9) on multivariate analysis (MVA). Ph-pos ALL was associated with a significantly lower relapse rate compared with Ph-neg ALL (HR=0.4, 95% CI 0.3-0.7, p<0.001). MRD positivity prior to allo-HCT was the only additional significant predictor for relapse on MVA (HR=2.9, 95% CI 1.8-4.7, p<0.001). Conclusions: HCT appears to overcome the poor prognosis of patients with Ph-like ALL. Despite higher induction failure rates, patients with Ph-like ALL undergoing HCT in CR1 had similar outcomes to other Ph-neg ALL subsets. The impact of effective salvage therapy leading to MRD-negativity in CR1 in this group is under investigation and will be reported. Further studies are needed to assess the impact of different Ph-like alterations on HCT outcomes. Outcomes for patients with Ph-pos ALL are significantly better than other groups, likely due to the use of TKIs pre- and post-HCT.

Introduction While chimeric antigen receptor (CAR)-T cell therapy has transformed the management of hematologic malignancies, it requires frequent monitoring for acute toxicities, almost universally achieved through mandatory hospitalizations, therefore utilizing a significant amount of healthcare resources. At Mayo Clinic in Rochester, MN, our standard practice is administering CAR-T cell therapy in the outpatient setting through a multi-disciplinary hospital-based outpatient (HBO) unit and remote patient monitoring (RPM) program. Our CAR-T RPM program consists of in-home, electronic health record-integrated technology to monitor vital signs and neurologic symptoms for 30 days post CAR-T infusion. Here we report the healthcare utilization outcomes of CAR-T patients managed in the outpatient setting enrolled in the RPM program. Methods Patients undergoing FDA-approved CAR-T cell treatment in the outpatient setting and participating in the CAR-T RPM program at Mayo Clinic Rochester were included in this IRB-approved study. Patient characteristics, healthcare utilization metrics, inpatient interventions, and patient satisfaction data regarding the RPM program were reviewed. Length of stay (LOS) includes any hospitalizations for which the admission date falls within the RPM monitoring period (CAR-T cell infusion to day +30), even if the hospitalization continued past day +30. Results A total of 123 patients participated in the CAR-T RPM program and underwent treatment in the outpatient setting. Median age at CAR-T infusion was 63 years (range 22 - 83), and most patients were male (n=78, 63%). Non-Hodgkin lymphoma was the most common diagnosis (n=74, 60%), followed by multiple myeloma (n=47, 38%), ALL (n=1, 1%) and other (n=1, 1%). During the PRM monitoring period, 19 (16%) patients were managed entirely in the outpatient setting. The remaining 104 (84%) patients required at least one hospitalization, with most patients (n=70, 57%) hospitalized only once [26 (21%) patients were hospitalized twice, and 7 (6%) patients were hospitalized 3 times, and 1 (1%) patient hospitalized 4 times during the monitoring period]. When considering the first hospitalization post CAR-T infusion, the median LOS was 6 days (range 2 - 47). When considering all hospitalizations post CAR-T, the median LOS was 8 days (range 2 - 47). Only 7 (6%) patients required an ICU stay, with a mean ICU stay of 0.2 days (standard deviation 0.9). Cytokine release syndrome (CRS) was noted in 92 (75%) of patients at a median of 3 days (range 0 - 18) post CAR-T infusion. All patients with CRS received tocilizumab, at a median of 4 days post CAR-T infusion. Steroids for CRS were administered in 63 (68%) of these patients. Neurotoxicity was reported in 45 (37%) patients at a median of 7 days (range 1 - 19) post CAR-T infusion. During the RPM monitoring period, patients were seen in our HBO unit with a median of 18 outpatient visits (range 4 - 30). Patient survey data, obtained at the end of the RPM monitoring period, were available from 37 patients. The majority of patients felt that the RPM program helped them feel comfortable managing their health at home, were able to reach a team member, and receive an appropriate response promptly. The majority of patients felt comfortable using the RPM equipment and interacting with providers virtually. Overall, 83% of patients were satisfied with the RPM program and 6% were neither satisfied nor dissatisfied. When asked about the reason for disappointment, technical difficulties/issues with the devices were the themes mentioned by the few patients (11%) who were unsatisfied with the RPM program. Conclusion: Despite the complexities and frequent monitoring associated with CAR-T cell therapy, outpatient CAR-T cell treatment is a feasible model of care. As the standard practice at our institution, the CAR-T RPM program was part of the management of nearly all patients undergoing an FDA-approved CAR-T product in the outpatient setting. RPM in the acute setting post CAR-T infusion is a well-received practice initiative by the majority of patients, including a high level of comfort utilizing the RPM equipment and virtual interaction with the RPM providers.

Background: Obe-cel is an autologous chimeric antigen receptor (CAR) T cell product with a novel CD19 binding domain CAT conferring a fast antigen off-rate designed to mitigate safety concerns and improve persistence over approved CD19 CAR T therapies. Early results from the pivotal FELIX study Phase IIA cohort (N=94) were recently presented (Roddie C et al. J Clin Oncol 2023;41[16 Suppl]:7000). We report findings from a pooled analysis of all patients (pts) treated to date with obe-cel in the FELIX Phase Ib/II study (NCT04404660), with a focus on pts with low leukemia burden prior to obe-cel infusion. Methods: The FELIX study enrolled adults with R/R B-ALL at screening with either morphological disease ≥5% bone marrow (BM) blasts (Cohort A), or in ≥2 nd complete remission (CR)/CR with incomplete hematologic recovery (CRi) with measurable residual disease (MRD) (Cohort B), or with isolated extramedullary disease (EMD) (Cohort C). The Phase Ib part of the study enrolled Cohorts A and B; the Phase II part enrolled Cohorts A, B, and C. CAR T products were generated from leukapheresis material using an automated process. Pts received bridging therapy as needed and lymphodepletion with fludarabine (4 × 30mg/m 2) and cyclophosphamide (2 × 500mg/m 2). A target dose of 410 × 10 6 CAR T cells was infused as a split dose on Days 1 and 10 based on pre-lymphodepletion BM blast burden. The primary endpoint was overall remission rate (best response of CR/CRi by independent review). Secondary endpoints included duration of remission (DoR), MRD negative remission rate, safety, and CAR T expansion/persistence. This pooled analysis included data from pts treated with obe-cel across all cohorts in the Phase Ib/II parts of the study. Low leukemia burden was defined as morphological remission per investigator assessment (<5% BM blasts without EMD) as measured at screening or at the start of lymphodepletion. Results: Between September 2020 and December 2022, 152 pts were enrolled and underwent leukapheresis. As of 16 March 2023, obe-cel was successfully administered to 126/152 (83%) pts (Phase Ib: Cohort A n=13, B n=3; Phase II: Cohort A n=94, B n=9, C n=7). Baseline characteristics at screening (n=126): median age 46.5 (range 20-81) yrs; Philadelphia positive B-ALL 27%; median 2 (range 1-6) prior lines of therapy; prior blinatumomab/inotuzumab 42%/32%; median BM blast burden 37% (range 0-100) including 23% pts with EMD; prior allogeneic stem cell transplant 44%. At a median follow up of 11.0 (range 0.9-30.6) months, the CR/CRi rate was 77% (95/124 response evaluable pts) with CR rate 57% (71/124). Among MRD evaluable responders, 96% achieved MRD negative status by central flow cytometry analysis. Median DoR was not reached at the current follow up. Low rates of Grade (Gr) ≥3 cytokine release syndrome (CRS; 2.4%) and/or Gr ≥3 immune effector cell associated neurotoxicity syndrome (ICANS; 7.1%) were observed. CAR T expansion was similar across the Phase Ib/II cohorts and CAR T persistence was ongoing in the majority of responders at the current follow up. Preliminary data indicate favorable efficacy and safety in pts with low leukemia burden prior to obe-cel infusion. Among 12 pts with MRD at screening (Cohort B), two pts were not evaluable and 9/10 evaluable pts achieved CR/CRi, with 100% achieving MRD negative status by central flow cytometry analysis post obe-cel. Median DoR was not reached at the current follow up. In this subset, no Gr ≥3 CRS was observed; one pt had Gr ≥3 ICANS. In a subset of 28 pts (across all cohorts) in morphological remission at the time of lymphodepletion, 24/27 (89%) response evaluable pts achieved CR/CRi and 100% of MRD evaluable responders achieved MRD negative CR/CRi by central flow cytometry analysis post obe-cel. Median DoR was not reached at the current follow up. In this subset, no pts experienced Gr ≥3 CRS/ICANS. Conclusions:This pooled analysis of data from all pts treated to date in the FELIX study demonstrates high rates of CR/CRi after obe-cel treatment, durable responses (median DoR not reached), and a favorable safety profile. Preliminary data suggest better outcomes in pts with low leukemia burden at screening/lymphodepletion, with higher rates of deep MRD negative complete remission, median DoR not reached at the current follow up, no Gr ≥3 CRS and one Gr ≥3 ICANS. These data support further exploration of CAR T therapy earlier in the treatment algorithm for adults with ALL.

Background: Clonal cytopenia of undetermined significance (CCUS) is characterized by the presence of a clone with somatic mutations in genes associated with myeloid neoplasms (MN) or abnormal cytogenetics, along with unexplained and persistent cytopenias in the absence of significant marrow dysplasia. CCUS is considered a premalignant state with a risk of progression to MN. The clinical outcomes of patients (pts) with high risk CCUS (Weeks et al, NEJM Evidence 2023) may be similar that of some patients with myelodysplastic syndromes (MDS). This study aims to predict the outcomes of CCUS patients using the molecular international prognostic scoring system (IPSS-M) developed for MDS. Methods: A retrospective analysis was conducted in patients diagnosed with CCUS between 2015 and 2023, we included patients harboring pathogenic mutations (MUT) identified through next-generation sequencing (NGS) testing at two institutions: Mayo Clinic and the University of Texas Southwestern Medical Center, Dallas, TX, USA were included. Progression was considered present if patients with CCUS progressed into myeloid neoplasm at follow up. Statistical analysis was performed using JMP® 17.1.0 Software. IPSS-M risk scores were calculated via the IPSS-M Risk Calculator (mds-risk-model.com). Results: A total of 103 patients were included in the study. The median age was 72 years, the majority were male patients (73%), and the median bone marrow blast % at the time of NGS was 1%. Forty-five % had an isolated mutation in a single gene, and 55% had co-mutations in ≥1 gene. The median number of mutations was 2 (range 1 - 5), occurring across 43 different genes. The most common mutations were in TET2 (N=28; 27%), ASXL1 (N=21; 20%), SRSF2 (N=21; 20%), U2AF1 (N=18; 17%), DNMT3A (N=16; 16%), and TP53 (N=12; 12%). Additionally, 25% of patients had an abnormal karyotype. Hematologic and genetic characteristics are summarized in (Table 1A). The median IPSS-M score was -0.9 (-3 to +2.34) and the median IPSS- Revised (R) score was 2 (0 - 6). The majority of patients had low (L) IPSS-M risk category (53%), followed by moderate low (ML) (19%) and very low (VL) (17%). Per IPSS-R, the majority had low-risk category (47%), followed by VL (38%) and intermediate (14%). Overall, 26 (25%) pt died after a median follow-up of 34 months and 21% progressed to MN (MDS 14 & CMML 8), and 1 patient with MDS and 1 with CMML progressed to secondary AML (2%). The median overall survival (mOS) was not reached, with a 2-year estimated (YE) OS and leukemia-free survival (LFS) of 80%. Predictive Power: When utilizing the IPSS-M risk category ( L, M, H) * by combining the risk categories into L *(L+VL), M * (ML+MH), and H *(H+VH) to overcome the low sample size limitation, it significantly predicted OS (p < .0001) ( Figure 1A) and median MN-free survival (FS) (p < .0001) ( Figure 1B). The 2YE-OS rates by IPSS-M risk category were as follows: VL - 93%, L - 87%, ML - 75%, high (H) - 25%, very high (VH) - 0% and the 2YE-OS rates by IPSS-M ( L, M, H) are summarized in Table 1B. IPSS-M hazard ratio (HR) for OS was 1.6 for ( M*) compared to 25 for ( H *) risk category (p < .0001). The ( L *) category, being the largest, was used as the reference level. Conclusion: This study provides the first real-world experience of using the IPSS-M and a modified version of the IPSS-M ( L, M, H) * risk category model to predict survival and progression into MN in CCUS (MUT) pt. The IPSS-M risk category was found to be a significant predictor of OS and MN-free survival. We propose that larger cohorts are needed to validate our findings.

Background: Venetoclax (Ven) in combination with hypomethylating agent (HMA) is the preferred treatment for elderly/unfit patients with newly-diagnosed acute myeloid leukemia (AML). Current prognostication for AML is based on European LeukemiaNet (ELN) genetic risk stratification which has limited applicability in patients treated with Ven-HMA ( Blood, 2022). Accordingly, our primary objective was to determine predictors of treatment response and survival outcomes in treatment-naïve AML patients receiving Ven-HMA. Methods: Our study population was recruited from Mayo Clinic (MN, FL, AZ), after institutional review board approval and based on documentation of newly-diagnosed AML treated with Ven-HMA outside of clinical trials between November 2018 and April 2023. Cytogenetic and molecular studies were performed by conventional karyotype, and next-generation sequencing, respectively. Response was assessed according to the 2022 ELN criteria Results: Patient characteristics A total of 301 newly-diagnosed AML patients (median age 73 years, 66% male, 62% de novo) received a median of 3 cycles (range 1-48) of azacitidine 75 mg/m2 days 1-7 ( n=100) or decitabine 20 mg/m2 days 1-5 ( n=201) with Ven. ELN 2022 cytogenetic risk included favorable (1%, n=4), intermediate (61%, n=184) or adverse (38%, n=113). Mutations involved TP53 in 77/301 (25%), ASXL1 in 54/279 (19%), RUNX1 in 54/296 (18%), NPM1 in 44/299 (15%), DNMT3A in 40/296 (13%), K/NRAS in 41/296 (14%), IDH1 in 20/301 (6%), IDH2 in 30/301 (10%), FLT3-ITD in 25/301 (8%) and DDX41 in 9/247 (4%) of informative cases. Predictors of response Complete remission, with (CR) or without (CRi), count recovery, was documented in 182 (60%) patients, including CR in 36% and measurable residual disease (MRD) negative by flow cytometry in 77% of 105 informative cases that achieved CR/CRi. Median time to CR/CRi was 1.4 months. In univariate analysis, CR/CRi was more likely to occur in the presence of NPM1 mutation, (86% vs. 56%; p < .01), IDH2 mutation, (80% vs. 58%; p = .02), DNMT3A mutation, (78% vs. 57%; p = .01), or DDX41 mutation, (100% vs. 58%; p <.01), and in the absence of adverse karyotype, (71% vs. 42%; p < .01), TP53 mutation, (67% vs. 40%; p <.01), FLT3-ITD mutation, (63% vs. 36%; p = .01), or RUNX1 mutation, (64% vs. 44%; p = .01); in multivariable analysis, adverse karyotype, ( p < .01), FLT3-ITD ( p < .01), RUNX1 ( p < .01), NPM1 ( p = .03), IDH2 ( p = .04), and DDX41, ( p = .01) mutations remained significant. Predictors of survival After a median follow-up of 8.5 months (range 0.5-56), 13.2 months for living patients, 174 (58%) deaths, 73 relapses (40% of those achieving CR/CRi), and 41 (14%; including 35 in CR/CRi) allogeneic hematopoietic stem cell tranplants (AHSCT) were documented. In univariate analysis of pre-treatment variables, thrombocytopenia < 100 x 10 9/l, (HR 1.5, 95% CI 1.03-2.2; p = .03), adverse karyotype, (HR 2.8, 95% CI 2.1-3.8; p < .01) TP53 mutation, (HR 2.5, 95% CI 1.8-3.5; p < .01), or absence of IDH2 mutation, (HR 3.5, 95% CI 1.7-7.6; p < .01) predicted inferior survival. Failure to achieve CR/CRi (HR 4.5, 95% CI 3.3-6.1; p < .01) was also associated with inferior survival and in multivariable analysis, failure to achieve CR/CRi, (HR 3.4, 95% CI 2.5-4.8; p< .01), presence of adverse karyotype, (HR 1.6, 95% CI 1.1-2.6; p = .02), TP53 mutation, (HR 1.6, 95% CI 1.002-2.4; p = .04), and absence of IDH2 mutation (HR 2.2, 95% CI 1.004-4.7; p = .04) were identified as risk factors for survival. Subsequent HR-weighted scoring resulted in three-tiered risk stratification: low (0-1 point; n= 130), intermediate (2-3 points; n= 105), and high (4-5 points; n= 66), with respective median survival (3-year rate) of 28.9 (48%), 9.6 (6%), and 3.1 (0%) months ( p < .01) (Figure). AHSCT had an independent favorable impact on survival (HR 0.3, 95% CI 0.1-0.6; p < .01), most apparent in low ( p =0.04), and intermediate ( p <.01), as opposed to high ( p = .06) risk. Conclusions: In the current single institutional series of Ven-HMA treated newly-diagnosed AML, response to Ven-HMA was the foremost predictor of survival. Additional risk factors for survival included adverse karyotype, presence of TP53 and absence of IDH2 mutations. These observations allowed for a three-tiered genetics-enhanced survival model with CR/CRi as a backbone, and also confirmed survival advantage from AHSCT, regardless of risk category.

Introduction Atrial fibrillation/flutter (Afib) contributes independently to the hematopoietic cell transplant comorbidity index (HCTCI) and is a known complication of allogeneic hematopoietic transplantation (AlloHCT) which has been linked to inferior outcomes, particularly in older patients. An electrocardiogram (ECG)-based artificial intelligence (AI) algorithm to predict Afib and cardiac contractile dysfunction risk has been validated (Lancet 394:861, 2019). We hypothesized that assessment of pre-transplant Afib risk using the AI algorithm may predict future development of Afib and help identify patients at higher risk for this complication. Methods 191 consecutive MDS patients undergoing AlloHCT with curative intent using myeloablative (28.3%) or reduced intensity conditioning (62.3%) in the Mayo Clinic Comprehensive Cancer Center (Rochester, Jacksonville, Phoenix) between November 2015 and January 2022 were included in this retrospective analysis. Primary outcome was Afib within 100 days and 365 days of transplantation, and we also assessed the outcomes of Death and Relapse. Revised IPSS (IPSS-R) and HCTCI scores were included for all patients. Elevated Afib risk score using the AI algorithm was calculated from pre-transplant ECG, performed during vital organ testing at AlloHCT clearance. In addition to left ventricular (LV) ejection fraction (EF) we evaluated detailed echocardiographic (Echo) parameters including LV volume and mass indices, left atrial volume index (LAVI), maximum trans mitral flow velocities during LV filling (E velocity) and during the diastolic phase due to atrial contraction (A velocity), the velocity of the annulus away from the apex during the protodiastolic phase (e' velocity), E/A and E/e' ratios, the presence of valvular disease, and right ventricular systolic pressure (RVSP). We performed an analysis using a Cox proportional hazards regression models (adjusting for age and sex) to evaluate associations with Afib risk, Relapse, and Overall Survival. Results The median age was 64 years (18-75), 58.6% were male, 6.9% non-white race, and 3.7% Hispanic/Latino ethnicity. Most patients had an HCTCI score of 0-3 (76.3%). GVHD prophylaxis was predominantly with calcineurin inhibitor-based regimes plus/minus methotrexate or mycophenolate mofetil (83.8%). 5.2% of patients had a history of Afib before transplant. Non-relapse mortality was 7.9% at 100 days, and 18.3% at 365 days. N=25 patients (13.1%) developed Afib within 100 days, and n=28 (14.7%) within 1-year after AlloHCT. On multivariable analysis, Age [Hazard Ratio (HR) 2.83, 95% Confidence Interval (CI) 1.36-5.89, p=0.0055] and Echo parameters [including LAVI (HR 2.10, CI 1.23-3.58, p=0.0067), E velocity (HR 3.28, CI 1.29-8.80, p=0.013), E/A ratio (HR 3.74, CI 1.75-7.97, p=0.0006), E/e ' ratio (HR 1.81, CI 1.07-3.07, p=0.026) and RVSP (HR 1.68, CI 1.04-2.70, p=0.032)] were significantly associated with Afib risk; elevated AI risk score was significant in the univariate model (HR 2.74, CI 1.15-6.53, p=0.023) but was borderline in the multivariate model (HR 2.34, CI 0.98-5.60, p=0.056) ( Table 1). Based on previous observations we evaluated the association of AI and Echo parameters with Relapse and Death after AlloHCT ( Table 1). Age (HR 1.32, CI 1.01-1.71, p=0.041) and IPSS-R (HR 1.20, CI 1.08-1.33, p=0.0009) were significantly associated with Death after AlloHCT, while HCTCI (HR 1.10, CI 1.00-1.22, p=0.052) and higher LV EF (HR 0.63, CI 0.38-1.06, p=0.084) were borderline. For Relapse, only IPSS-R (HR 1.52, CI 1.31-1.75, p=1.22E-08) was significant, while increase Echo E velocity was of borderline significance (HR 0.45, CI 0.20-1.02, p=0.057). Conclusions Afib is a common post-AlloHCT complication and is more frequent with increasing Age. Echo parameters (specifically E/A ratio) predict significantly higher Afib risk, while the baseline ECG AI algorithm was of borderline significance. The selection of patients with lower HCTCI scores, and the low background prevalence of Afib in this cohort (i.e., selection of patients with lower baseline cardiac morbidity) are possible explanations for non-significance of the AI algorithm. As anticipated Age and IPSS-R are the greatest predictors of Death after AlloHCT, although the suggestion of an association with baseline Echo parameters highlights the importance of identifying those who may benefit from preemptive Cardiology intervention.