Mangaonkar, Abhishek A.

Abstract Background: Integrin αE (CD103) has been thought to mediate gut-homing Treg retention during GVHD by facilitating E-cadherin interaction on intestinal epithelial cells. However, only a small percentage of natural Tregs express CD103 in peripheral blood (PB). To leverage this mechanism and potentially enhance Treg therapeutic efficacy, we hypothesized that Tregs overexpressing CD103 (CD103high) would show improved gut-homing and GVHD mitigation. Methods: Murine CD4 Tregs were isolated from C57BL/6 (B6) mice via flow sorting and were retrovirally transduced with murine CD103 or truncated epidermal growth factor receptor as a control. Transduced Tregs were then tested in a murine acute GVHD model (B6 → BALB/c). Mouse organs, including small intestine (SI), colon, spleen, PB, axillary (aLN) and mesentric lymph nodes (mLN) were harvested on day 10 post-transplant and analyzed by flow cytometry, multiplex cytokine assay, histopathology, and single-cell RNA sequencing (scRNA-seq). Ex vivo expanded Tregs were subjected to 13C-glucose tracing assay to evaluate glycolytic flux, TCA cycle, and lipid biosynthesis. Results: Despite comparable FoxP3 expression at the end of ex vivo expansion, CD103high Tregs had significantly higher in vitro suppression compared to control Tregs (54% vs. 33% at Treg:Tcon ratio of 1:8, p=0.004). Upon re-stimulation, CD103high Tregs demonstrated increased proliferation compared to control Tregs (3.8 vs 2.8 fold expansion, p <0.0001). Bulk RNA seq on ex vivo expanded CD103high showed upregulation of immuneregulatory and metabolic programs including GTPase signaling and oxidative stress control. These transcriptomic changes suggest that CD103 intrinsically promotes a regulatory phenotype, stress tolerance and metabolic fitness. In vivo, CD103highTregs significantly decreased the severity and mortality of GVHD, compared to control Tregs, as measured by clinical scores, weight loss, and survival (50% vs 0% on day +60, p<0.0001 for three independent experiments combined; n = 24/group). Day 20 histopathology revealed significantly improved colitis scores in mice treated with CD103high Tregs vs controls (9.5 vs. 14.6, p=0.02). While these findings could be partially attributed to CD103 gut-homing function, we observed that CD103high Treg absolute number and frequency were higher not only in the the GI organs and mLN, but also in the spleen, PB, and aLN with similar distribution ratios across different organs (~5-fold higher). In vivo CFSE suppression assay, where CFSE labeled donor T cells were cotransferred with Tregs into B6 Rag1ko mice, demonstrated enhanced suppressive function of CD103high Tregs in the spleen (p=0.02), an effect that could not be accounted for by the conventional gut-homing mechanism attributed to CD103. Plasma cytokine analysis showed significantly elevated IL-10 levels in mice treated with CD103high Tregs (p<0.0001), consistent with increased Treg number and frequency. 13C-glucose tracing assay showed lower palmitate levels in CD103high Tregs, indicating lower de novo lipid synthesis, while glycolysis and TCA cycle tracing were similar. Day 10 scRNA-seq on colon samples revealed seven distinct immune clusters. The neutrophil cluster was absent in CD103high Treg group, suggesting reduced inflammation. Donor-derived dendritic cells (DCs) upregulated genes such as Cstb, and Slamf7, while pro-inflammatory genes including Cd52 and Cd74 were downregulated. STAT5 signaling was upregulated, indicating reprograming of myeloid cells toward an immunoregulatory state. Colon epithelial cells from CD103high Treg-treated mice displayed enhanced stress tolerance, with increased oxidative phosphorylation, fatty acid metabolism, and epithelial repair pathways. CellChat analysis revealed that CD103high Tregs reshaped the intestinal communication landscape, with DCs acting as key signaling hubs through interactions such as Ccl6–Ccr2 and Lgals3–Cd44. Enhanced DC-to-DC and DC-to-T cell communication suggest that CD103high Tregs promote a tolerogenic DC network that modulates downstream immune responses and supports epithelial recovery. Conclusion: Tregs overexpressing CD103 via retroviral transduction significantly improve overall survival and GVHD clinical scores in a murine transplant model. CD103High Tregs orchestrate broad remodeling of cell-cell communication across immune and stromal compartments, promoting an immunoregulatory microenvironment that underlies their protective effects in GVHD.

Abstract Background: Clonal cytopenia of undetermined significance (CCUS) is defined as clonal hematopoiesis in the absence of a hematologic neoplasm, along with unexplained cytopenia. While several studies have identified risk factors and developed scores to predict progression to overt myeloid neoplasms, the clinical and molecular features during the progression process remain poorly understood. Aim: Evaluate the clinical and clonal characteristics of patients with CCUS, with a focus on the longitudinal evolution of clonal and clinical parameters over time. Methods: After IRB approval, we retrospectively reviewed charts of patients with unexplained cytopenia (2015-2024), recording data at the time of CCUS diagnosis (WHO 2022 diagnostic criteria) and at time of follow-up bone marrow biopsy after diagnosis. Follow-up CBC and karyotype data were recorded for patients who had repeat bone marrow biopsies (n= 111), while follow-up clonal parameters and risk scores were calculated for those who underwent repeat NGS (n= 74). A reduction or expansion in clone size was defined as a change exceeding 5% (CE5%), or change exceeding 10% (CE10%) from the baseline value. Overall survival (OS) was calculated from diagnosis to last follow-up. For statistical analysis, we used BlueSky Statistics V10.3.1. Results: 214 CCUS patients (median age 73, 68% males) were included. At baseline, 30% of patients had abnormal cytogenetics, with del (20q) being the most common one (8%; n= 18), followed by trisomy 8 (6%; n= 13), and loss of chromosome Y (5%; n= 10). The median number of mutations was 2 (range, 1-5), with the most common mutations TET2 (38%), SRSF2 (21.5%), ASXL1 (21%), ZRSR2 (18.5%), DNMT3A (9.5%), and U2AF1 (9%). Most patients had high risk CHRS (60%), followed by intermediate (30%), and low risk (10%). On the other hand, 41% had high risk CCRS, 29% had intermediate risk, and 30% had low risk. After a median follow-up of 46 months, 62 patients died (median OS not reached). A decrease in the white blood cell (WBC) count from the time of diagnosis to follow-up was more frequently seen among CCUS patients who progressed to MN (70% vs 50%, p= 0.04), however, changes in hemoglobin and platelets did not differ between those who progressed and those who did not (p> 0.05). Although the frequency of abnormal karyotypes at diagnosis was similar between patients who eventually progressed (28%) and those who did not (31%) (p= 0.6), 4 (2%) patients with initially normal karyotypes acquired chromosomal abnormalities during follow-up, and all progressed to MDS. Among the 74 patients who had follow-up NGS, 31% acquired new mutations, clonal expansion of pre-existing mutations were seen in 54% using CE5% and 19% per CE10%, and 16% developed new variants of uncertain significance (VUS). Acquiring new pathogenic mutations was similar in patients who progressed to MN compared to those who did not progress (34% vs 28%, p= 0.6). On the other hand, clonal expansion was significantly more observed in patients who progressed compared to those who did not, using both CE5% (73% vs 31%, p = <0.001) and CE10% (27% vs 9%, p= 0.03). At follow-up, ASXL1 was the most commonly acquired mutation among patients who did not progress (4 cases), followed by TET2 (2 cases), and U2AF1, GATA2, DNMT3A, SF3B1, ZRSR2, TP53, and CBL (1 case each). On the other hand, SRSF2, SETBP1, CBL, JAK2, TET2, and RUNX1 were more frequently acquired among those who progressed to myeloid neoplasms (each appeared in 2 patients). When recalculating CCRS, CHRS, IPSS-M, and IPSS-R at follow-up for patients who had repeat NGS, there was no significant difference in score changes - either upward or downward - between those who progressed and those who did not (p> 0.05). Conclusion: In CCUS patients who progressed to myeloid neoplasms, WBC decline, clonal expansion (more frequent), and evolving chromosomal aberrations (less frequent) were observed, supporting the value of longitudinal genomic and clinical monitoring in CCUS.

Abstract Introduction: Protein truncating somatic ASXL1 mutations in CMML are associated with high-risk features and poor outcomes. We have previously demonstrated that ASXL1-mutant (mt) CMML is characterized by permissive chromatin states and overexpression of leukemia stemness genes (Binder et al. Nat Commun; 2022). DLK1 (delta-like homolog 1) is a pseudo-NOTCH like ligand that is maternally imprinted and paternally expressed and is physiologically not expressed beyond embryogenesis. Aberrant DLK1 expression has been associated with poor outcomes in solid tumors and we have shown differential overexpression in ASXL1mt versus wild-type (wt) CMML. Both the promoter and the last exon of DLK1 contain CpG islands that play a role in regulating DLK1. The CpG island within the fifth exon of DLK1, known as the DLK1-differentially methylated region (DMR) [chr14:100,726,892-100,738,224] is completely unmethylated on the maternal allele and partially methylated on the paternal allele. Previous work (Developmental Cell; 2021) has also identified a DLK1 imprinting control region (ICR) known as the IG-DMR [chr14:100,811,001–100,811,037]. DNA methylation state of the IG-DMR has been shown to impact the expression of MEG3 mRNA (lncRNA) which functions as a cofactor to direct PRC2 to the DLK1 promoter, suppressing DLK1 expression. Since the regulation of DLK1 in ASXL1mt CMML is not well understood, we conducted this multiomic analyses to define epigenetic mechanisms of DLK1 overexpression in ASXL1mt CMML. Methods: After IRB approval, we performed bulk RNA-seq, ChIP-seq (H3K4me1/me3, H3K27ac, H3K27me3) and Illumina MethylationEPIC array on bone marrow (BM) mononuclear cells of 40 CMML patients (19 ASXL1mt, 21 wt). scRNA-seq was conducted on 5 ASXL1mt and 3 wt cases. All libraries were sequenced on an Illumina NovaSeq instrument. We assessed these samples for differential gene expression (RNA-seq) and changes in histone modifications (ChIP-seq) between ASXL1mt and wt CMML, specifically at the DLK1-DMR and IG-DMRregulatory loci. We conducted ddPCR (digital droplet PCR) to determine allelic status of DLK1 in ASXL1mtand wt cases. Global and allele/sequence specific DNA methylation changes were determined using Biomodal's duet EvoC methodology (6 base sequencing, including 5mC and 5hmC) in 5 ASXL1mt and 5 wt CMML cases. Results: We validated the overexpression of DLK1 in 19 ASXL1mt versus 21 wt (log2 fold change +4.85, FDR 4.67e-13) CMML BM samples. scRNA-seq on 5 ASXL1mt versus 3 wt samples demonstrated that DLK1 is only expressed in mutant cases, with the expression being limited to HSPCs. ChIP-seq analysis at the DLK1 regulatory loci validated (a) reduced occupancy of H3K27me3, correlating with ASXL1mt associated disruption of the PRC2-complex, and (b) increased co-occupancy of H3K4me1 and H3K27ac in mt cases, validating a permissive chromatin state in ASXL1mt cases at the DLK1 regulatory regions. Through correlation analysis of RNA-seq and ChIP-seq, we defined the promoter for DLK1, characterized by high Pearson correlation coefficients (R > 0.5) and enrichment of H3K27ac and H3K4me3. Differential methylation analysis identified global hypomethylation around the DLK1-DMR and promoter regions. We observed a mean reduction of ~40% in methylation status at the DLK1 promoter in ASXL1mt versus wt cases, suggesting a loss of epigenetic silencing at this locus. This was corroborated by significant enrichment of 5hmC at the fifth exon of DLK1 indicating active DNA demethylation. Conversely, we observed a gain in methylation at the IG-DMR, suggesting loss of imprinting control through MEG3 silencing and DLK1 overexpression. To further determine the impact of imprinting deregulation on overexpression of DLK1 in ASXL1mt CMML, allele-specific methylation was profiled using the Biomodal whole genome methylation data. This demonstrated that the methylation patterns in ASXL1mt CMML cases were significantly deregulated at the DLK1-DMR, with >30% loss of methylation compared to GRCh38 reference alleles. Furthermore, ddPCR was able to confirm bi-allelic expression of DLK1 in ASXL1mt CMML, suggesting that the observed methylation dysregulation leads to loss of imprinting of the maternal allele. Conclusion: In summary, we demonstrate that ASXL1 mutations in CMML disrupt epigenetic pathways, promoting DNA demethylation, resulting in permissive chromatin states and an aberrant and oncogenic re-expression of maternal DLK1, due to loss of imprinting control.

Abstract Introduction Chronic myelomonocytic leukemia (CMML) is a myeloid neoplasm with overlapping features of myelodysplastic syndromes (MDS) and myeloproliferative neoplasms (MPN). Blast transformation (BT) is a frequent complication of CMML with a 3-year risk of approximately 31%. MPN driver mutations (i.e., JAK2, CALR, MPL) are known to occur in CMML but their impact on overall survival (OS) or BT remains uncertain. Methods The current study was conducted under institutional review board approved minimum risk protocols that allowed retrospective collection and analysis of patient data. Diagnostic criteria were according to the International Consensus Classification (Blood 2022; 140:1200). For survival analysis, patients were censored at the time of allogeneic stem cell transplant (ASCT). All statistical analyses were conducted using JMP Pro 17.0.0 software (SAS Institute, Cary, NC, USA) and Bluesky Statistics Software (Worldwide Headquarters, Chicago, IL, USA). Results A total of 612 CMML patients were considered (median age 71 years; 68% males). MPN driver mutations (MPNMUT) were detected in 56 (9%) patients, including 43 (77%) with JAK2, 10 (18%) MPL, and 3 (5%) CALR. The median variant allele frequencies were 44% for JAK2 (range, 0.3–100%), 49% for MPL (range, 0.3–97%), and 50% for CALR (range, 20–80%). Age and sex distributions and CMML-1 vs. CMML-2 representation were similar between CMML patients with and without MPNMUT. On the other hand, CMML patients with MPNMUT were more likely to display higher hemoglobin level (p <0.01), platelet count (p <0.01), absolute neutrophil count (p = 0.02) and leukocytosis (≥13 ×109/L; p <0.01); they were also less likely to be red blood transfusion dependent (p <0.01), display platelet counts of <100 ×109/L (p <0.01) or abnormal karyotype (p= 0.03), present with severe anemia (p= 0.03) or harbor NRAS mutation (p = 0.02). Higher Mutational frequencies of SRSF2 (median 53% vs. 41%; p = 0.01), TP53 (median 8% vs. 2%; p = 0.02) and IDH2 (median 13% vs. 4%; p = 0.01) were noted in CMML patients with MPNMUT. During a median follow-up of 23 months (inter-quantile range 11-51 months) for all 612 CMML patients, 402 (67%) deaths, 118 (19%) BT and 108 (18%) ASCT were documented. Of these, 36 (9%) deaths, 18 (15%) BT and 13 (12%) ASCT occurred in patients with MPNMUT. Median OS for the entire group (N=612) was 32 months with 1-, 2- and 3-year OS rates of 78%, 58% and 47%, respectively. There was no significant difference in OS between CMML patients with or without MPNMUT (median 41 vs 31 months; p = 0.27). Thrombotic events were reported in 53 (9%) patients after diagnosis of CMML, including 48 venous and 5 arterial events. There was no significant difference in arterial (p = 0.10) or venous (p = 0.76) thrombosis-free survival between CMML patients with or without MPNMUT. Among all 612 patients with CMML, followed for a median of 18 months for living patients, 118 (19%) experienced BT, with 1-, 3-, and 5-year BT rates of 10.8%, 23.1%, and 31%, respectively. Cumulative incidence analysis function (CIF) was calculated in order to assess the BT-free survival while accounting for death as a competing risk; 3-year CIF was 30% for CMML patients with vs. 18% for those without MPNMUT (Gray's test; p = 0.01). This observation was confirmed in univariate analysis of time to BT (HR 1.7; p=0.03) as well as the corresponding multivariable analysis involving other mutations and clinical risk factors: MPNMUT (HR 1.8; 0.036), ASXL1MUT (HR 2.3; p<0.01), DNMT3AMUT (HR 2.6; p<0.01), CMML-2 vs. CMML-1 (HR 3.4; p<0.01), and leukocyte count ≥13 ×109/L (HR 2.0; p<0.01). SRSF2, IDH2, and TP53 mutations did not impact BT. Notably, the aforementioned risk factors for BT, including ASXL1MUT and DNMT3AMUT, were no longer significant when analysis was restricted to patients with MPNMUT. Conclusions The current study suggests a higher risk of BT in CMML patients with MPNMUT, independent of other molecular or clinical risk factors for BT. On the other hand, overall and thrombosis-free survival did not appear to be similarly influenced. The differential impact of previously recognized risk factors for BT in CMML (e.g., ASXL1MUT, DNMT3AMUT, CMML-2, CMML-MP), in the presence (lost significance) vs. absence (remained significant) of MPNMUT was intriguingly noted.

Abstract The importance of bone marrow (BM) microenvironment and its immune interactions within and their role in chronic myelomonocytic leukemia (CMML) disease progression have not been well studied. Our previous work in CMML identified type 1 helper T cell (Th1) and CD4 terminal effector cell suppression in peripheral blood from untreated patients, in comparison to age-matched normal controls (Mangaonkar A et al. Blood Adv 2020). Furthermore, clonal dendritic cell (DC) aggregates in CMML are present in approximately 20-30% patients at diagnosis, display significant cell heterogeneity (plasmacytoid DCs + myeloid DCs and other myeloid/immune cells), express indoleamine 2,3-dioxygenase-1 (IDO), associate with T regulatory cell (Treg) expansion, and transformation to AML [blast transformation or BT, Lucas N et al. Leukemia 2019, Mangaonkar A et al. Blood Adv 2020, and Mangaonkar A et al. Blood 2023 (abstract)]. The purpose of this study was to define the myeloid-immune cell interactions within the BM microenvironment critical for CMML progression to AML. To phenotypically identify cell types and their interactions within the CMML BM, we used single-cell type spatial omics through two distinct modalities on archival formalin-fixed paraffin-embedded (FFPE) BM biopsy specimens. Ten serial CMML samples at chronic phase [CP, n=5, median BM blast% 5 (2-15)] and at BT [n=5, median BM blast% 60 (25-74)] were used for both techniques. Spatial transcriptomics was conducted through GeoMx Digital Spatial Profiler (DSP) platform that uses UV-photocleavable, spatial-barcoded oligo probes to profile the whole transcriptome in defined regions of interest (ROI). CD123 (marker for DC-myeloid aggregates) immunofluorescence antibody was used to identify and segment ROI. 16-color flow cytometry was done to validate cell-specific expression. Spatial cellular phenotyping of immune cells on the same samples (serial cuts) was done through multiplex imaging by co-detection by indexing (CODEX) using 27 markers: CD31, Ki67, CD11b, CD20, CD44, Ecad, CD123, CD107a, CD8, CD11c, CD45RO, FoxP3, CD14, PDL1, CD56, CD68, CD163, PD-1, CD38, HLA-DR, CD4, IDO, CD45, PanCK, Na/K/ATPase, CD3e, and DAPI. CD8T+ cell anergy was demonstrated through CFSE cell proliferation assay. Benjamini-Hochberg correction was used to adjust for multiple hypotheses. After filtering poor quality ROIs [ROIs with total read count < 1000 were removed, ROIs with trim, stitch, alignment < 80% or saturation < 50% were removed], 3rd-quartile normalization [BiocGenerics (v. 0.48.1)] and batch correction [limma (v. 3.58.1)], we compared transcriptomics signatures between CD123+ and CD123- ROIs in all samples. Results showed that LIPA, SLC4A1, HBA2, TIMD4 and HMOX1 werethe top five genes upregulated in CD123+ areas. Among all gene transcripts, TIMD4 expression increased the most (Log2FC=0.6, P-value=8.79E-10, FC=1.52, FDR=1.68E-07) when CD123+ ROIs were compared between CMML-CP and CMML-BT serial samples, suggesting a biological relevance in disease progression. Previous work in metastatic peritoneal cancer has established that TIM-4 expressing macrophages suppress Th1/Th2 ratios and impair CD8+ T cell function (Chow A et al. Cancer Cell 2021). To confirm expression at the protein level, we used a multicolor flow cytometry panel and confirmed that TIM4 is expressed on macrophages (Lineage-negative, HLA-DR+, CD68+ cells) in independent CMML BM aspirate samples (n=3). Next, we conducted spatial phenotyping using CODEX on serial cuts from the same serial samples used for spatial transcriptomics. Anatomical co-localization of macrophages with leukemic cells, monocytes and T cells was visually inspected and confirmed. Cell-interaction analysis (after Benjamini-Hochberg correction) indicated that macrophages-monocyte, macrophage-leukemic cells, and macrophage-memory CD4+T cells were significantly (P<0.05) increased in CMML-BT versus CMML-CP. CD8T+ cell anergy was confirmed through a CFSE cell proliferation assay in untreated CMML PBMC samples. In conclusion, our data suggests that TIM4-expressing macrophages and their interactions with monocytes/monocyte precursors and immune cells within a DC aggregate create a protective leukemic stem cell niche and T cell tolerance, promoting blast transformation in CMML.

Abstract Background Blast transformation (BT) occurs in approximately 15-30% of patients with chronic myelomonocytic leukemia (CMML) and remains a leading cause of death. Allogeneic stem cell transplantation (ASCT) is currently the only treatment modality with the potential to cure the disease or prolong survival. Optimal timing of ASCT is critical for maximizing benefit while minimizing risks. To that end, contemporary risk models have focused on the prognostic relevance of individual, as opposed to concurrent mutations. In the current study, we looked into the possibility of prognostic prominence from concurrent mutations in predicting BT in CMML. Methods CMML diagnostic criteria were according to the International Consensus Classification (Arber et al. Blood 2022; 140:1200). A machine-learning hierarchical clustering algorithm was developed and tailored for patient stratification using survival outcomes and co-expression of genomic alterations. To reduce complexity and improve interpretability, we generalized each cluster using existing rule induction algorithms, including the in Trees framework and JRip. The final output was a set of mutation-based cluster definitions, each representing a distinct patient subgroup with similar survival trajectories. Competing risk analysis and cumulative incidence functions were used in downstream evaluation to validate the clinical distinctiveness of the clusters. For all survival analysis, patients were censored at the time of ASCT. Time-to-BT was calculated from the date of diagnosis to the date of BT or ASCT or last contact. BT-free-survival was calculated from the date of diagnosis to the date of BT, ASCT, death, or last contact. Results The core study cohort included 605 patients from the Mayo Clinic, USA, and the external validation cohort 501 patients from Humanitas Cancer Center, Milan, Italy. Using the patient cohort from the Mayo Clinic, machine-learning algorithms identified five molecular clusters with 3-year blast transformation (BT) rates ranging from 0% to 100% (AUC at 3 years 0.78): the order of molecular signature assignment (probability of BT/death from another cause) was i) PHF6MUT/ASXL1WT (0%/17% at 3 years; N=32), ii) NPM1MUT OR BCORMUT/ASXL1MUT OR SETBP1MUT/NRASMUT (48%/30% at 1 year; N=24), iii) RUNX1MUT/ASXL1MUT OR SRSF2MUT/NRASMUT OR EZH2MUT/ASXL1MUT OR SETBP1MUT OR BCORMUT (31%/55% at 3 years; N=132), iv) ASXL1MUT/TET2MUT OR DNMT3AMUT OR JAK2MUT (24%/28% at 3 years; N=123), and v) all other permutations (10%/40% at 3 years; N=294) [Figure 1]. Additional analysis confirmed significant differences in survival between RUNX1MUT/ASXL1MUT vs. RUNX1MUT/ASXL1WT (p<0.01) OR RUNX1WT/ASXL1WT (p<0.01) OR RUNX1WT/ASXL1MUT (p=0.038) [Figure 2]. Similar patterns of differences in survival were also documented for NRAS/SETBP1, ASXL1/EZH2, and NRAS/SRSF2 mutation combinations (Figure 2). A subsequent Cox regression analysis confirmed independent prognostic contributions from “PHF6MUT/ASXL1WT” (HR 5.43e-10; p<0.01), NPM1MUT (HR 26.7; p<0.01), “SETBP1MUT/NRASMUT” (HR 12.7; p<0.01), BCORMUT(HR 5.8; p<0.01), “RUNX1MUT/ASXL1MUT” (HR 2.3, p<0.01), JAK2MUT (HR 2.1; p<0.01), and “ASXL1MUT/TET2MUT” (HR 1.7; p=0.02). The prognostic relevance of “SETBP1MUT/NRASMUT”, “RUNX1MUT/ASXL1MUT”, NPM1MUT, and BCORMUT was validated in the external cohort from Italy (N=501). In the Mayo Clinic cohort, presence of any of the latter mutations was associated with 1-, 3-, and 5-year BT (death from other cause) rates of 27% (21%), 44% (49%), and 44% (51%), respectively (Figure 3). The corresponding values in the absence of high risk mutations were 7% (15%), 15% (37%), and 18% (52%) [Gray's p value <0.01 for both BT and death from another cause; Figure 3]. Similarly, the 1-, 3-, and 5-year BT (death from another cause) rates in the Italian cohort were 21% (19%), 37% (47%), and 42% (54%) in the presence and 8% (14%), 20% (35%), and 24% (45%) in the absence of high-risk mutations (Gray's p value <0.01 for BT and 0.18 for death from another cause; Figure 4). Conclusions In the current study, machine-learning algorithms enabled the discovery of concurrent mutations in CMML that were shown to be prognostically more significant than their individual constituents. Such prognostic interaction might have contributed to some of the discrepancies noted in current literature regarding the prognostic relevance of certain mutations in CMML and should be accounted for in the development of future risk models.

Abstract Recent updates to the monocyte count thresholds for diagnosing chronic myelomonocytic leukemia (CMML) have recognized oligomonocytic CMML (OM-CMML) as an early stage within the CMML spectrum. However, the clinical validity of these revised criteria remains uncertain without considering biological factors and might misclassify myelodysplastic syndromes (MDS) with mild monocytosis as CMML. To characterize the genomic landscape of OM-CMML, we evaluated OM-CMML (n=249), MDS (n=304) and myelodysplastic CMML (MD-CMML, n=358) patients (pts) treated at three academic institutions. Targeted next-generation sequencing was performed on bone marrow (BM) at initial diagnosis or first referral. OM-CMML was characterized by lower frequencies of biallelic TET2 (biTET2) and RAS pathway (RASp) gene mutations (BRAF, CBL, KRAS, NF1, NRAS and PTPN11) compared to MD-CMML (p<0.001) but higher frequencies than MDS (p<0.001). BM monocyte frequencies, assessed morphologically, were higher in OM-CMML than in MDS (p<0.001) but lower than in MD-CMML (p<0.001), indicating that OM-CMML is a heterogenous group including true CMML and distinct MDS subsets. Unsupervised hierarchical clustering based on genomic alterations across all cases (n=911) identified three distinct clusters: 1) TP53 alterations (predominantly multihit TP53) and complex karyotype (TP53-complex); 2) biTET2 or TET2-SRSF2 co-mutation (biTET2/SRSF2); 3) a heterogenous group lacking these features (not otherwise specifiable [NOS]). Among OM-CMML pts, 11%, 34% and 55% belonged to these clusters, respectively. Model-based unsupervised clustering further identified 9 unique clusters that could be consolidated into 6 groups: 1) TP53-complex; 2) biTET2/SRSF2; 3) SF3B1 (without biTET2 or SRSF2); 4) SRSF2 without TET2 and frequent IDH2 mutations (SRSF2-IDH2); 5) ASXL1 and U2AF1 mutations and copy number alterations (CNA-ASXL1/U2AF1); 6) no somatic mutations (No mutation). biTET2/SRSF2 group exhibited monocytic bias with higher AMC, PB and BM monocyte % even among OM-CMML cases. This bias was not attributed to higher RAS pathway mutation frequencies, as biTET2/SRSF2 cases had similar RASp mutation frequencies but lower median variant allele frequencies for RASp mutations compared to NOS cases (9% vs. 21%, p=0.029). PB monocyte partitioning using flow cytometry (FC) in a subset of OM-CMML pts (n=50) demonstrated higher frequency of classical monocytosis (>94% CD14+/CD16- monocytes) in biTET2/SRSF2 vs other OM-CMML. To further determine if biTET2/SRSF2 genotype defines a distinct biological subgroup, we performed RNA-sequencing of BM CD34+ cells from healthy donors (n=15) and pts with OM-CMML (n=12), MD-CMML (n=14) and MDS (n=55). Unsupervised clustering based on gene expression profiles revealed that biTET2/SRSF2 clustered irrespective of their diagnostic group with greater dispersion being observed based on diagnosis. MDS and CMML with biTET2/SRSF2 had less differentially expressed genes compared to MDS and CMML with biTET2/SRSF2 relative to other MDS and CMML genotypes. Among 138 OM-CMML pts in whom progression to overt CMML was evaluable, 37 (27%) progressed to overt CMML of which 26 (70%) belonged to the biTET2/SRSF2 group. Competing risk analysis confirmed higher cumulative incidence and shorter time to CMML progression among biTET2/SRSF2 OM-CMML. Using ElasticNet regression we identified BM monocytosis and 14 genomic variables (including biTET2 and TET2-SRSF2) as predictors of overt CMML progression among OM-CMML. We developed a score-based model able to predict progression with high reliability (AUC 0.805, sensitivity 0.70, specificity 0.76). Model accuracy was confirmed by optimism-corrected bootstrap internal validation (AUC 0.668). Monocytic bias, BM classical monocytosis (>94% CD16- monocytes) and higher overt CMML progression in biTET2/SRSF2 was confirmed in a validation cohort (28, 66 and 22 pts with OM-CMML, MDS and MD-CMML, respectively). BM monocytosis of biTET2/SRSF2 was confirmed in this cohort with morphologic and FC monocyte frequency quantification having high concordance (r=0.737, p<0.001). Genomic subgroup analysis discriminated survival outcomes more reliably than diagnostic categories alone. Our findings suggest that the presence of biTET2 or TET2-SRSF2 co-mutations, combined with BM monocytosis, can more reliably identify true CMML cases within the OM-CMML spectrum. Integrating genomic determinants into the CMML diagnostic framework enhances diagnostic accuracy.

Abstract Background and Significance: CMML is a myeloid neoplasm characterized by hematopoietic stem and progenitor cell (HSPCs) monocytic bias, leading to downstream monocyte expansion that plays a key role in disease maintenance and progression. Monocytes in CMML express high surface expression of the homing C-C chemokine receptor 2 (CCR2), which promotes malignant monocyte survival. Expansion of CCR2+ monocytic progenitors drives acute transformation in CMML and contributes to venetoclax resistance in AML. For these reasons, CCR2 is a potential novel therapeutic target in CMML and monocytic AML. The CyTAC platform was designed to enable targeting of cell surface antigens that demonstrate limited or ineffective binding to conventional therapeutic antibodies. A CyTAC is a heterobivalent small molecule that binds to both a target of choice and to a fully humanized monoclonal antibody. STX-0712 comprises a CCR2 CyTAC which potently binds to CCR2 on malignant cells, and a CyTAC humanized ADCC-enabling monoclonal antibody, which when combined eliminates target cells via enhanced effector-mediated killing in the presence of NK cells. We have demonstrated that treatment with STX-0712 ex vivo results in human target engagement and pharmacodynamic activity, and in vivo leads to depletion of CCR2 MO1 monocytes in a potent and dose-dependent manner in CMML and AML (ASH 2024). Therapeutic depletion of CCR2+ malignant monocytes presents a novel opportunity to develop a potential disease-modifying targeted therapeutic agent. We have designed a first-in-human, phase 1 clinical trial to evaluate the effect of CCR2 CyTAC in patients with refractory/resistant CMML, and relapsed/refractory monocytic or monocytic predominant AML. Study Design and Methods This is a phase 1, first-in-human, open-label, multicenter clinical trial based in the USA to evaluate STX-0712 as a monotherapy in patients with CMML and AML who have no remaining treatment options known to confer clinical benefit. STX-0712 will be administered as a single intravenous (IV) infusion every 3 weeks (additional regimen schedules may be explored) until evidence of disease progression, death, intolerance to study medication, or withdrawal of consent. The study consists of a dose-escalation and dose-expansion part and includes two cohorts: Cohort 1 (refractory/resistant CMML) and Cohort 2 (relapsed/refractory monocytic or monocytic predominant AML). Dose escalation will begin in participants with CMML using the Bayesian Optimal Interval (BOIN) design, with a minimum of three patients enrolled at each dose level. Backfilling of up to two cleared dose levels will be initiated once efficacious exposure levels are reached and at least one CMML participant has achieved a complete remission (CR) or a partial remission (PR), marrow response, or clinical benefit as defined by the MDS/MPN IWG 2015 criteria. In the AML cohort, backfilling may begin once at least one participant has achieved a response defined by ELN 2022 criteria. Dose expansion will occur upon completion of dose escalation in each cohort, using a Simon 2-stage adaptive design. Approximately 47 CMML and 58 AML patients may be enrolled in this phase 1 study. The primary objectives of the study are to evaluate the safety and tolerability of STX-0712 and to determine the minimal safe and biologically effective dose, recommended phase 2 dose (RP2D), and/or maximum tolerated dose (MTD), and to characterize dose-limiting toxicities (DLTs). Secondary objectives include evaluation of preliminary antitumor activity, pharmacokinetic (PK) parameters, and pharmacodynamic effects of STX-0712 on CCR2+ malignant cells in blood and bone marrow. Key exploratory endpoints include: (1) assessment of changes in CCR2+ tumor cells following STX-0712 dosing, (2) evaluation of candidate biomarkers, (3) characterization of T cells, B cells and NK cells at baseline and over the course of treatment, and (4) to explore the effects of STX-0712 on patient-reported outcomes using the CMML Symptoms Assessment Tool (MPN-SAF-TSS scoring system) and the EuroQoL 5 Dimension 5 level (EQ-5D-5L) for AML. Enrollment for Cohort 1 (CMML) began in March 2025, and the study is ongoing. Clinical Trial Information: NCT06950034

Abstract Background: TP53-mutated (TP53mut) myeloid neoplasms (MN) are a biologically and clinically distinct subgroup of blood cancers associated with extremely poor outcomes and limited response to conventional therapies. In some patients, MN are preceded by clonal cytopenia of undetermined significance (CCUS). Prior cytotoxic exposure (treatment related, TR) is an independent predictor for survival in CCUS (Li et al, Blood Adv. 2024). As TP53mut CCUS and MN are enriched in TR cases, the interaction between cytotoxic exposure and TP53mut status on the risk of progression and survival remains unclear. Methods: Adult patients with CCUS who were evaluated at the Mayo Clinic or South Australian myelodysplastic syndrome (MDS) Registry (Adelaide, Australia) were included. CCUS and MDS were defined according to the 5th edition of the WHO classification for MN (Khoury et al, 2022), except for the exclusion of cases harboring MDS-defining cytogenetics. Next-generation sequencing was performed using a targeted panel covering genes commonly mutated in MN. In cases with >1 TP53mut, VAFs were summed. Survival outcomes were assessed by Kaplan-Meier with log-rank testing. Univariate and multivariate analyses were estimated using Cox proportional hazards regression. Results: Of 320 CCUS cases, 50 (15.6%) harbored TP53mut (TP53mut CCUS), whereas 270 (84.4%) were wild-type (TP53wt CCUS). Median age at diagnosis was 71 years (range 16-99). TP53mut CCUS had a greater proportion of females (60% vs 33.7%, p<0.001) and TR (66% vs 23%, p<0.001) compared to TP53wt. Hematologic parameters including hemoglobin, red cell distribution width, mean corpuscular volume, white blood count, absolute neutrophil count, platelets, and bone marrow blasts were comparable between the two groups. Almost all TP53mut (n=48, 96%) were located in the DNA-binding domain and the median variant allele frequency (VAF) was 9% (range 2-46%). Five (10%) cases harbored 2 TP53mut. The distribution of TP53mut VAF among patients was as follows: ≤2.5% (n=2), 2.5-5% (n=10), 5-10% (n=19), 10-20% (n=11), and ≥20% (n=7). The proportion of cases with cytogenetic abnormalities was smaller in TP53mut compared to TP53wt CCUS(12% vs 25.9%, p=0.035). Both cohorts had a comparable median number of mutations: 2 (range 0-7) in TP53mut and 2 (range 0-5) in TP53wt. The most common co-mutations in TP53mut CCUS were TET2 (n=8, 17.8%), PPMD1 (n=7, 15.6%), DNMT3A (n=6, 13.3%), ASXL1 (n=6, 13.3%), and SRSF2 (n=4, 8.9%). At last follow up, the rate of progression was comparable between TP53mut and TP53wt CCUS (12% vs 22%, p=0.13). Median time to MN progression was not reached in TP53mut and 6.25 months in TP53wt CCUS (p=0.5197). A significantly higher proportion of TP53mut cases acquired complex cytogenetics compared to TP53wt cases (33% vs 2%, p=0.024) at MN progression. Of 20 deaths observed in the TP53mut cohort, non-myeloid hematologic malignancies (n=6, 30%), infections (n=5, 25%), and TP53mut MN (n=4, 20%) were the 3 most common causes. With a median follow-up of 4 years (IQR 1.2-4.8), median OS was longer in de novo (dn) cases (8.7 years for dn TP53wt; not reached for dn TP53mut) and shorter in TR cases (3.3 years for TR TP53wt; 4.8 years for TR TP53mut). Notably, TP53mut showed no independent prognostic impact in the entire cohort, or when stratified by TR vs dn CCUS. On multivariate analysis that included TP53mut status, factors independently associated with inferior OS included prior therapy (HR 2.21, 95% CI 1.41-3.45, p<0.001), anemia (HR 4.1, 95% CI 1.88-8.99, p<0.001), and thrombocytopenia (HR 2.38, 95% CI 1.43-3.95, p<0.001). Similarly, TR CCUS (HR 1.6, 95% CI 1.06-2.4, p=0.03) and anemia (HR 2.15, 95% CI 1.25-3.7, p=0.006) were independently associated with inferior progression free survival. Conclusion: TP53 mut in CCUS did not independently predict inferior survival or increase leukemic transformation. While TP53mut CCUS were less likely to harbor cytogenetic abnormalities at diagnosis, significantly more cases harbored genomic instability at leukemic transformation. The poor outcomes attributed to TP53mut CCUS were driven by prior cytotoxic exposure, cytopenia – particularly anemia, and non-leukemic causes of death. These findings suggest risk stratification in CCUS should prioritize clinical context over TP53mut status alone.

Abstract Introduction: Somatic mutations in splicing factors (SF) - SF3B1, SRSF2, U2AF1, and ZRSR2 – represent one of the most common drivers of premalignant clonal hematopoesis. While SF mutations are potent drivers of clonal expansion (Fabre et al., Nature 2022), multiple SF mutations are rarely observed in the same individual (negative epistasis). Prior studies have identified rare cases of concurrent SF mutations (<4%) and described specific hotspot combinations that escape negative epistasis (Taylor et al., Blood 2020). We conducted this study to further characterize the frequency and clonal relationship between concurrent SF mutations using a larger patient cohort. Methods: After IRB approval, we assessed 3,369 myeloid next generation sequencing (NGS) results that identified somatic variants in SF3B1, SRSF2, U2AF1, or ZRSR2, in 2,500 adult patients from 08/2015 to 07/2025. Patient demographics, ICD-9/10 codes, and complete blood counts with differentials were obtained, retaining only those datapoints assigned 30 days before or after NGS testing. To allow comparison of clone size between autosomal and the X-linked SF ZRSR2, VAFs were multiplied by two to estimate the cancer cell fraction (CCF), except for ZRSR2 mutations in males. For patients harboring concurrent SF mutations, we categorized them as co-dominant if the difference in respective CCFs was < 10% of the greater CCF. Specific SF variants were categorized into common hotspots (n=13), except for ZRSR2 variants, which do not occur in defined hotspots. Fisher's exact testing was used to assess the enrichment of SF hotspot variants in patients with concurrent SF mutations, as well as combinations of SF variants in patients with co-dominant SF mutations. Results: We identified 2,331 patients with at least 1 pathogenic SF mutation, of which 6.7% (n=156) had > 1 SF mutation (multi-SF MT). The total cohort comprised cases of AML (n=549, 24%), MDS (n=977, 42%), MDS/MPN (n=233, 10%), MPN (n=228,10%), and uncategorized ICD codes (“Other”, n=326), of which the largest category was clonal cytopenia(s). Notably, the prevalence of multi-SF cases was higher than previously described and our cohort included 5 patients with 3 SF mutations and 1 with 4 SF mutations. Of the multi-SF MT patients, we identified 42 (27%) with co-dominant CCFs among their respective SF mutations. Thirty-three multi-SF MT patients had multiple NGS sampling timepoints (median 2, range 2-4) spanning a median of 0.97 years (range 0.06-5.69 years); we found that 17 of these 33 demonstrated correlative SF CCFs over multiple timepoints, suggesting their SF mutations occurred in the same clone (“co-clonal”). Of these 17 patients, 82% had co-dominant CCFs at the single-timepoint level, whereas none of the 16 non-co-clonal demonstrated co-dominance. Thus, we used SF co-dominance as a surrogate for cases likely to be co-clonal. ZRSR2 (p=8.8x10-29), U2AF1Q157 (p=9.4x10-9), SF3B1K666 (p=1.4x10-4) and infrequent SF3B1 (“SF3B1-Other”, p=.0029) mutations were overrepresented in the multi-SF MT cohort compared to patients with a single SF mutation. Within the multi-SF MT cohort, 3 SF mutation combinations showed overrepresentation in codominant cases – SRSF2P95R/H/L+ ZRSR2 (p=0.014), SRSF2P95R/H/L+ SF3B1K666 (p=0.044), and U2AF1S34 + U2AF1Q157 (p=0.024), although not significant after multiple hypothesis correction. Dual ZRSR2 mutations were the most common combination seen in the multi-SF MT cohort but were underrepresented in codominant cases (p=0.025). Although there was no disease subtype uniquely associated with total or co-dominant multi-SF MT cases, occurrence of multiple SF mutations was more common in males (8% vs. 3% in females), an effect driven by ZRSR2 mutations. Hemoglobin and WBC were lower in multi-SF MT cases, with the lower hemoglobin strongly driven by the codominant multi-SF MT cases (median 8.3 g/dL vs 9.4 g/dL, p=0.00046). Conclusions: These findings suggest that SF mutation co-occurrence in myeloid neoplasms is more prevalent than previously estimated (~7%). Furthermore, we identified 6 individuals harboring > 2 SF mutations, which has not been previously described. We validate specific SF variant pairs that appear to exist in the same clone and are working to confirm the clonal architecture and characterize global splicing aberration in selected cases with single-cell studies to fully uncover the mechanism by which negative epistasis is overcome.