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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 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 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.

Abstract Background: Germline predisposition states (GPS), including inherited bone marrow failure syndromes (IBMFS) are seen in 5-10% of individuals with myeloid neoplasms (MN). Given overlap with somatic driver genes, blood, saliva, and buccal swabs are suboptimal specimens for GPS testing in MN; the latter two due to contamination with blood cells(Jerez, 2024). Skin biopsy with fibroblast culture-derived DNA remains the gold standard, but the process is expensive, takes 6-8 weeks to complete, and fibroblast culture failure can occur in some patients with telomere biology disorders. Given the need to rapidly screen donors for HSCT and adjust therapy/conditioning in certain IBMFS, we developed a rapid hematologic germline testing algorithm using hair follicle-derived DNA. Methods The study was conducted after IRB approval through the Mayo Clinic GPS/IBMFS clinic. To perform PCR-based hair follicle testing, we obtained 15-25 hair follicles (bulbs) per patient. The bulbs were placed in a microcentrifuge tube and subjected to a 24-hour digestion and extraction protocol using a modified version of the QIAGEN DNA Purification from Dried Blood Spots protocol. DNA quality was assessed by Nanodrop and Qubit.Testing included either validation of known or suspected germline variants (e.g., RUNX1, DDX41, ETV6), or panel testing (e.g., GPS or IBMFS). Pathogenic variants were validated by repeat testing in a CAP/CLIA certified lab prior to medical decision making. 23 patients underwent whole exome sequencing (WES) in a CAP/CLIA lab, and 13 patients had concurrent germline testing using alternate DNA sources (8 skin biopsies, 1 saliva, 4 buccal swabs). Results Ninety-three patients (49 male, 53%) underwent hair follicle-derived germline DNA testing (median age 63 years). Indications for germline testing included the presence of a suspected variant on somatic testing with variant allele frequency (VAF) between 35%-60% ( n= 66, 71%), patient age <50 years (n=26, 28%), antecedent thrombocytopenia (n=15, 16%), presence of syndromic features (n=4, 4%), patient history of multiple malignancies (n=4, 4%), and positive family history (n=15, 16%). Time to reporting variants after receipt of hair follicle-derived DNA was <14 days. There were zero complications associated with the procedure. DNA quality as assessed by Nanodrop revealed a median nucleic acid concentration of 25.64 ng/μL. The median A260/A280 ratio was 1.86 (range 0.701-2.133) and the median A260/A230 ratio was 1.27 (range -8.193-9.223). DNA quality was insufficient for chromosomal microarray (CMA) assessments. Of 93 patients evaluated, 67 (72%) had ≥1 germline variant, with 3 having >1 germline variant for a total of 72 variants. Pathogenic/likely pathogenic variants identified included: DDX41 (30, 41.7%), TP53 (4, 5.6%), ANKRD26 (4, 5.6%), RUNX1 (4, 5.6%), GATA2 (3, 4.2%), TERT (3, 4.2%), JAK3 (2, 2.8%), SAMD9/SAMD9L (2, 2.8%), ATM (2, 2.8%), and 1 each (1.4%) in BCL2, BCOR, BPGM, CDKN2A, CEBPA, CHEK2, CSF3R, CXCR4, DNMT3A, ETV6, GATA1, MPL, MPO, POT1, PTPN11, RPL5, and SH2B3. In the 13 patients that had concurrent germline testing, results were identical in all cases, except for 1 false negative in a buccal specimen (PTPN11) and 1 case of germline mosaicism, where the TP53 variant was identified in the blood and hair follicle DNA but not in skin fibroblast DNA. After testing, 30 (44.7%) patients had a change in their management plan: 8 (27%) with DDX41-GPS were observed due to known latency of DDX41-mutant MN, 6 (20%) were referred for HSCT based on the germline variant (CEBPA, DDX41, GATA1, GATA2, RPL5, TP53), 6 (20%) were placed on an enhanced surveillance plan for cancer screening (1 ANKRD26, 3 TERT, 2 TP53), 4 (13%) patients undergoing HSCT had related donors removed from consideration as they were carriers (2 DDX41, 1 ANKRD26, and 1 SAMD9), 2 (7%) patients with neutropenia and underlying germline variants (1 ATM, 1 DDX41) had G-CSF therapy discontinued due to concerns for clonal stimulation, and 1 (3%) patient with a germline CDKN2A mutation (hematological diagnosis- CMML) was recommended to avoid radiation therapy for prostate cancer. Conclusion In summary, we validate a rapid and simple hair follicle-derived DNA based germline assessment for patients with hematological disorders and demonstrate a positive impact on clinical care in 44% of patients. We are currently optimizing DNA quality so that germline copy number alterations can be better detected using CMA.

Abstract Heterozygous germline variants of DDX41 occur in 2-4% of adult Myelodysplastic Syndrome (MDS) and Acute Myeloid Leukemia (AML) cases, making them the most prevalent cause of inherited predisposition to these diseases. Homozygous deleterious variants are never observed in the germline, and loss of both DDX41 alleles causes apoptosis of proliferative cells, consistent with essentiality. Most disease-associated germline variants cause loss of full-length protein expression (truncating). However, 30-40% are missense (non-truncating) and their role in disease risk compared to truncating variants remains in question. Previous reports have shown that both truncating and non-truncating Pathogenic/Likely Pathogenic (P/LP) variants (defined by ACMG scoring) are associated with DDX41-specific disease features, including co-mutation of the contralateral allele of DDX41. In contrast, variants of unknown significance (VUS) are less associated with these features. Acquired co-mutations of DDX41, of which p.R525H accounts for 50-70%, are restricted to DDX41-mutated patients and are always missense. Our previous studies indicated that p.R525H lacks the essential DDX41 function and cannot support hematopoietic progenitor proliferation. However, the frequency with which this mutation occurs and the absence of acquired truncating mutations suggest that p.R525H has a specific effect on DDX41 function that is distinct from complete loss and promotes pathogenesis specifically in the context of existing P/LP DDX41 mutation. To understand how germline non-truncating variants predispose to disease, we characterized the effect of six recurrent non-truncating P/LP variants (p.G173R, p.R219H, p.P258L, p.Y259C, p.K331del, and p.I396T) and three VUS (p.K9E, p.Y33H, and p.M155H) on DDX41 function. We utilized a genetic complementation approach in murine lineage-negative (Linneg) bone marrow cells with inducible deletion of DDX41. We found that all non-truncating P/LP and VUS forms of DDX41 could fully rescue the colony forming potential of Ddx41-deficient cells to a similar level as wild-type protein, whereas the p.R525H variant completely failed to rescue. To determine the effect of the non-truncating variants on DDX41 function at endogenous expression levels, we utilized CRISPR to modify the DDX41 alleles in MOLM13 human AML cells. We produced viable, proliferating cell lines with homozygous mutations for all 3 VUS and 4/6 P/LP variants. For p.P258L and p.K331del, like p.R525H, we could not produce homozygous mutant cell lines despite screening hundreds of clones and finding several with heterozygosity. To further study the P/LP variants that were functional in the cell line, we generated C57Bl/6 mouse lines harboring p.G173R, p.Y259C, and p.I396T mutations in the endogenous Ddx41 alleles. Heterozygous mutant mice were phenotypically normal in all three strains. However, we could not obtain homozygous mutant mice for p.G173R or p.Y259C, indicating these cannot support embryonic/fetal development. In contrast, p.I396T-homozygous mutant mice were born at Mendelian ratios and were phenotypically normal until at least 15 months of age. Since p.R525H mutation is common in patients with non-truncating P/LP variants, we sought to model the combined effect of these mutations. We utilized the Linneg cells with inducible knockout of Ddx41, co-expressed each non-truncating variant with p.R525H by viral transduction, and monitored the colony formation potential. Remarkably, cultures expressing P/LP variants or M155I combined with p.R525H had dramatically reduced colony formation, while wild-type DDX41 and the other 2 VUS supported normal colony formation when co-expressed with p.R525H. Thus, we conclude p.R525H has a dominant-negative effect on certain non-truncating DDX41 variants. This is consistent with the emerging idea that the presence of an acquired hotspot DDX41 co-mutation is sufficient to classify a non-truncating DDX41 variant as pathogenic.Our results demonstrate that many DDX41 missense variants retain protein function when overexpressed. However, at endogenous expression levels, some P/LP variants are unable to support cell proliferation, indicative of hypomorphic effects on protein function. In patients, acquisition of the p.R525H mutation in the contralateral allele disrupts the functionality of P/LP variants through dominant-negative effects, leading to hematopoietic progenitor defects that are hallmark of the DDX41 pathogenesis.

Abstract Introduction: TERT promoter (pTERT) variants are among the most frequent genetic alterations in human cancers, where they drive oncogenesis through telomerase reactivation. However, somatic, pathogenic pTERT variants have also been seen in non-cancerous conditions such as telomere biology disorders (TBD), where they attempt to rescue the bone marrow failure phenotype (adaptive compensation). We conducted this study to assess the phenotype and outcomes of pTERT mutations in TBD patients. Methods: After IRB approval, the Mayo Clinic institutional TBD database was queried to identify all patients with somatic pTERT mutations. We have designed a customized error corrected sequencing panel that covers somatic mutations (52 genes) associated with adaptive and maladaptive outcomes in TBD patients. This covers the promoter region for TERT and can detect variants down to 0.5% variant allele fraction (VAF) with 10,000 X sequencing depth. Clinical data was retrospectively abstracted. Results: We identified 7 pTERT variants (3 hotspots) in 6 (two females (33%), mean age 61 years, 4 alive). The three hotspots were: (1) c.-57A>C (2 individuals, mean VAF 17.1%; range 11.6%-22.6%), (2) c.-124C>T (4 individuals, mean VAF 12.9%; range 1.9%-41.3%), and (3) c.-146C>T (1 individual, VAF 1.2%). One individual had both the c.-124C>T (VAF 41.3%) and the c.-146C>T somatic pTERT variants, occurring in the context of a germline TERT variant. The median VAF for all 7 pTERT variants was 6.1% (range 1.2%-41.3%). The hotspot, c.-57A>C, occurred in the context of pathogenic germline TERT (VAF 49.9%) variants with pathogenic somatic co-variants in PPM1D (avg. VAF 1.5%). The second hotspot, c.-124C>T, occurred in the context of germline TERT (avg. VAF 49.6%) and RTEL1 (VAF 47.3%) variants with pathogenic somatic co-variants including ASXL1 (VAF 1%), DNMT3A (VAF 8%), and PPM1D (VAF 4%). Five of six assessable patients with pTERT variants had shortened telomere lengths (TL), with results pending for one individual. Among those with the c.-57A>C variant, granulocyte TLs were at or below the 10th percentile, while lymphocyte TLs were below the 10th percentile in one patient and below the 1st percentile in another. For those with the c.-124C>T variant, all granulocyte TLs were below the 1st percentile. Lymphocyte TLs in this group included one at the 10th percentile and two at or below the 1st percentile. The median follow up for all patients was 2 years. Hotspot 1 (c.-57A>C) variants were associated with normocellular bone marrow biopsies with one patient having normal blood counts and the other having chronic macrocytic anemia (grade 2) and thrombocytopenia (< grade 1). In patients with hotspot 2 and 3 somatic variants, bone marrow cellularity ranged from 15–50% (1 patient had grade 2-3 hypocellularity), with normal bone marrow morphology, except for polytypic plasma cells (10–15%) identified in a patient with IgG kappa multiple myeloma (currently MRD negative on maintenance therapy). This patient also had a history of head and neck cancer and follicular lymphoma. Of these four patients, only one had normal blood counts (co-occurring c.-146C>T variant); the rest had cytopenias (n=3, the worst being grade 2 thrombocytopenia), progressive macrocytosis (n=3), or eosinophilia (n=1). Comorbidities encountered in these patients included myasthenia gravis (1), hypogonadism (1), and sarcoidosis (1). Moreover, four patients (2 each for hotspots 1 and 2) presented with idiopathic pulmonary fibrosis, while liver fibrosis was seen in 4 patients (also 2 each for hotspots 1 and 2). At last follow up, none of these patients had documented progression to myelodysplastic syndrome or acute myeloid leukemia. Conclusions: We describe the spectrum and clinical features of somatic pTERT mutations in TBD patients. pTERT mutations involved the following hotspot regions, c.-124C>T, c.-146C>T, and c.-57A>C, and co-occurred with other somatic variants (i.e., PPM1D and DNMT3A). None of the 6 patients with pTERT mutations had a severe bone marrow failure phenotype or developed myeloid neoplasms at last follow up, exemplifying a unique mechanism of adaptive somatic rescue.

Abstract Introduction: VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) is an aggressive auto-inflammatory disorder defined by somatic UBA1 mutations. UBA1 mutations arise in hematopoietic stem cells and bias differentiation toward myeloid lineages. Clonal involvement of monocytes and neutrophils in VEXAS is frequent. Recently, natural killer (NK) cells have been recognized within the UBA1 mutant clone; mutated NK cells have an exhausted phenotype and impaired cytotoxicity (Ganesan BioRxiv 2025; Breillat et al, Blood 2025). A unique NK-like T cell type (CD3+CD16+[CD56-] T cells) has a role in the immunopathogenesis of severe COVID-19, resulting in heightened cytotoxicity and tissue damage (Georg et all, Cell 2022). As NK cells do not typically express CD3, and as the activation of inflammatory pathways is not restricted to myeloid cells in VEXAS, (Mizumaki et al, Nat Comm 2025) we sought to assess the CD3+ cell populations for co-expression of CD16 using single-cell (sc) multiomic data from VEXAS patients. Methods: After IRB approval, we performed sc-proteogenomic sequencing using a custom-made gene panel (Tapestri, MissionBio) in 2 VEXAS patients. Libraries were sequenced on an Illumina NovaSeq instrument. In one case, we performed in parallel CITE-Seq in parallel and used canonical correlation analysis (CCA) to integrate these immunophenotypic and transcriptomic data with matching cell populations identified from proteogenomic sequencing. We used pathway analysis (IPA) and gene ontology enrichment (gProfiler), as well as differential gene expression (RNA-seq) to identify significant gene signatures. T-tests with Welch's correction were performed for statistical significance on surface markers from proteogenomic data which were transformed by center log ratio. Our observations were then validated in sc-proteogenomic data from two additional VEXAS patients profiled at the NIH. Results: We used a sc-multiomic strategy to study CD3+ T cell subsets in VEXAS patients. In the first UBA1 mutant (mt) sample, using clusters defined by UMAP overlay of CITE-Seq/proteogenomic data, we defined positive expression of CD3 expression in the non-UBA1mt T cell cluster. We then examined the proteogenomic data (n=700 cells) to identify CD3+ cells (n=89 UBA1mt, n=42 UBA1wt). We then divided the CD3+ fraction into CD56+ vs CD56- to obtain CD3+CD56+ (n=25 UBA1mt, n=12 UBA1wt) and CD3+CD56- (n=64 UBA1mt, n=0 UBA1wt) cells. The CD3+CD56- cells were not only entirely UBA1mt, but also co-expressed CD16, significantly elevated from CD3+CD56+ UBA1wt cells (p<0.0001; and no significance from granulocyte populations): 10% of UBA1mt cells were CD3+CD16+CD56-. This cell subset was detected in an additional 3 VEXAS samples, and, in each case, there was no significant difference between UBA1mt/UBA1wt CD3 expression (both were T cell subsets) and no significant difference in CD56 expression. There was a significant increase in CD16+ expression in UBA1mt over UBA1wt (p<0.0001) cells, but not between UBA1mt cells and other granulocytes. Finally, we assessed the CITEseq data from the first UBA1mt case and focussed on gene expression and pathway differences between CD3+ and CD3+CD16+(CD56-) cell populations. Using IPA, we found top differentially expressed pathways included neutrophil degranulation, inflammation, cell killing, and IL-8 activity. Differentially expressed genes included FCGR3B, TLR2, IL1R2, FCGR2A, CCR1, CXCL8, and CXCR1, some of these overlapping with what was reported in similar cells (CD3+CD16+) detected in COVID-19 (Georg et all, Cell 2022). Conclusion: We identify a unique NK-T cell like [CD3+CD16+(CD56] subset of cells within UBA1mt cells in patients with VEXAS. This cell type has been reported in patients with severe COVID-19 as having increased cytotoxic functions and associated with fatal outcomes. Rare or aberrant cell clusters defined by standard clustering analysis may mis-identify some cell types, especially if they aberrantly express CD3+CD16+, as either marker could be used to pre-gate cells into larger clusters of lymphoid or myeloid cells. Prospective and functional profiling of this cell type in VEXAS patients is ongoing.

Abstract RAS pathway (RASp) mutations induce proliferative features, and promote transformation in chronic myelomonocytic leukemia (CMML). However, the unique clonal landscape and hierarchy of distinct RASp mutations remain unexplored. To characterize the landscape, architecture, and implications of unique RASp mutations in CMML, we evaluated a cohort of 814 patients with CMML. We identified 461 RASp mutations among 342 patients (42%). N/KRAS and CBL mutations were the most common, frequently involved the P-loop or RING domains, respectively, and frequently appeared as dominant events (63% and 65%, respectively). BRAF, NF1, and PTPN11 mutations spanned throughout the gene structure, and frequently appeared as subclonal events (75%, 64%, and 59%, respectively). CBL mutations frequently occurred in codominance with SRSF2 and multihit TET2, and were enriched for KIT mutations. PTPN11 mutations more frequently co-occurred with SETBP1 and DNMT3A mutations, and were infrequently codominant with TET2 or ASXL1. RASp mutations predicted for shorter overall survival (hazard ratio [HR], 1.55; 95% confidence interval [CI], 1.15-2.07; P = .0075) and leukemia-free survival (LFS; HR, 1.67; 95% CI, 1.26-2.20; P = .0011), influenced outcomes of myelodysplastic and TET2 mutant CMML, and cooperated with IDH2 and RUNX1 mutations to induce shorter LFS. These data set the bases for refined genomic classifications of CMML, and underscore the need to develop RAS-directed therapies for patients with CMML.

6579 Background: Treatment strategies in chronic myelomonocytic leukemia (CMML) are not standardized and include hydroxyurea (HU) and hypomethylating agents (HMA). In a phase 3 study comparing HU and decitabine, in proliferative CMML, response rates were higher for decitabine (56% vs 31%; p<0.01) but overall survival was similar (p=0.67) between the two groups (Itzykson, R. JCO, 2023. 41:1888). In the current retrospective study, we examined the survival impact of different treatment strategies among 457 Mayo Clinic patients with CMML. Methods: The current study was conducted under institutional review board approved minimum risk protocols allowing retrospective patient data collection and analysis. Diagnostic criteria were according to the International Consensus Classification (Arber et al. Blood 2022. 140:1200). All statistical analyses were conducted using JMP 17 software. For survival analysis, patients were censored at time of allogeneic stem cell transplant (ASCT). Results: A total of 457 patients were considered (median age 72 years; 68% males). 209 patients received CMML-directed therapy: HU (N=102), HMA (N=78; azacitidine 32 and decitabine 46). Responses were adjudicated separately for leukocytosis and anemia; normalization of leukocyte count was achieved in 21% vs. 16 % (p<0.01) for HU vs. HMA and overall response in anemia in 1% vs. 9% (p=0.02), respectively. Overall survival did not appear to be impacted by different treatment strategies at any stage of CMML; (i) treated vs. untreated (p=0.3), (ii) HU vs. HMA for first-line therapy (p=0.3), and (iii) HU/HMAs vs. other drugs as first-line therapy (p=0.1). Blast transformation-free survival (BTFS) was also similar between HU vs. HMA as well as HU/HMA vs. other drugs. In univariate analysis, BTFS was inferior in patients receiving CMML-directed therapy (p<0.01); the particular association (HR 2; 95% CI 1.2-3.3) retained its significance in multivariable analysis that also included other risk factors for BTFS: bone marrow blast ≥10% (HR 4.3), circulating blast ≥2% (HR 2.7), WBC ≥13 x 10 9 /L (HR 1.8), and ASXL1 mutation (HR 1.7). Conclusions: In the current retrospective study that included a large number of patients with CMML, chemotherapy with HU or HMA did not appear to affect overall survival but might have increased the risk of blast transformation. The study also suggests superiority of HU for the treatment of leukocytosis and HMA for anemia. Predictors of blast transformation-free survival (BTFS) in 457 patients diagnosed with chronic myelomonocytic leukemia (CMML). BTFS Univariable analysis p-value (HR) Multivariable analysis p-value (HR) CMML-directed therapy <0.01 (2.9; 1.8-4.7) <0.01 (2; 1.2-3.3) Bone marrow blasts ≥10% <0.01 (12.4) 0.01 (4.3) Circulating blasts ≥2% <0.01 (5.2) <0.01 (2.7) WBC ≥13 x 10 9 /L <0.01 (2.9) 0.02 (1.8) ASXL1 mut <0.01 (2.1) 0.02 (1.7)