Tolosa, Ezequiel J.

Carcinoma-associated fibroblasts (CAFs) play an important role in the progression of multiple malignancies. Secretion of cytokines and growth factors underlies the pro-tumoral effect of CAFs. Although this paracrine function has been extensively documented, the molecular mechanisms controlling the expression of these factors remain elusive. In this study, we provide evidence of a novel CAF transcriptional axis regulating the expression of SDF1, a major driver of cancer cell migration, involving the transcription factor GLI1 and histone acetyltransferase p300. We demonstrate that conditioned media from CAFs overexpressing GLI1 induce the migration of pancreatic cancer cells, and this effect is impaired by an SDF1-neutralizing antibody. Using a combination of co-immunoprecipitation, proximity ligation assay and chromatin immunoprecipitation assay, we further demonstrate that GLI1 and p300 physically interact in CAFs to co-occupy and drive SDF1 promoter activity. Mapping experiments highlight the requirement of GLI1 N-terminal for the interaction with p300. Importantly, knockdowns of both GLI1 and p300 reduce SDF1 expression. Further analysis shows that knockdown of GLI1 decreases SDF1 promoter activity, p300 recruitment, and levels of its associated histone marks (H4ac, H3K27ac, and H3K14ac). Finally, we show that the integrity of two GLI binding sites in the SDF1 promoter is required for p300 recruitment. Our findings define a new role for the p300–GLI1 complex in the regulation of SDF1, providing new mechanistic insight into the molecular events controlling pancreatic cancer cells migration.

Abstract Pancreatic ductal adenocarcinoma (PDAC) affects many older adults in the United States. This aggressive type of pancreatic cancer is resistant to many chemotherapies, resulting in a poor prognosis and a five-year survival rate of less than ten percent. To study PDAC progression and develop novel therapies, it is important to better understand the tumor microenvironment (TME) and the contributing cell populations and molecular mechanisms. Despite the well-described role of soluble Type I collagen in the regulation of pancreatic cancer TME, the molecular events modulating its expression/activity remain elusive. Here, we describe a novel mechanism controlling the levels of soluble collagen in cancer associated fibroblasts (CAFs), a major producer of Type I collagen in pancreatic cancer TME. Specifically, we provide evidence that the transcription factor GLI2 is required for the expression of COL1A1, a key component of the Type I collagen fiber, stimulated by the transforming growth factor β (TGFβ). Our methodology included expression studies from patient samples, ChIP-qPCR, qPCR, RNA-seq analysis, gene set enrichment analysis, biological assays, and gene ontology analysis. Our results confirm that the TGFβ-GLI2 axis in CAFs is able to activate EGR1-proliferative signaling downstream of collagen signaling in pancreatic cancer cells contributing to our understanding of the molecular underpinnings of pancreatic cancer TME. Further studies that define the complete role of EGR1 in PDAC may lead to the development of novel therapies targeting EGR1 or CAFs to promote enhanced quality of life following a PDAC diagnosis.

BACKGROUND A patient-derived organoid (PDO) platform may serve as a promising tool for translational cancer research. In this study, we evaluated PDO’s ability to predict clinical response to gastrointestinal (GI) cancers. METHODS We generated PDOs from primary and metastatic lesions of patients with GI cancers, including pancreatic ductal adenocarcinoma, colorectal adenocarcinoma, and cholangiocarcinoma. We compared PDO response with the observed clinical response for donor patients to the same treatments. RESULTS We report an approximately 80% concordance rate between PDO and donor tumor response. Importantly, we found a profound influence of culture media on PDO phenotype, where we showed a significant difference in response to standard-of-care chemotherapies, distinct morphologies, and transcriptomes between media within the same PDO cultures. CONCLUSION While we demonstrate a high concordance rate between donor tumor and PDO, these studies also showed the important role of culture media when using PDOs to inform treatment selection and predict response across a spectrum of GI cancers. TRIAL REGISTRATION Not applicable. FUNDING The Joan F. & Richard A. Abdoo Family Fund in Colorectal Cancer Research, GI Cancer program of the Mayo Clinic Cancer Center, Mayo Clinic SPORE in Pancreatic Cancer, Center of Individualized Medicine (Mayo Clinic), Department of Laboratory Medicine and Pathology (Mayo Clinic), Incyte Pharmaceuticals and Mayo Clinic Hepatobiliary SPORE, University of Minnesota-Mayo Clinic Partnership, and the Early Therapeutic program (Department of Oncology, Mayo Clinic).

Abstract Despite development of personalized treatments GI cancer like pancreatic ductal adenocarcinoma (PDAC) and colorectal cancer (CRC) remain dismal outcomes. While some patients are potentially curable with surgery and chemotherapy, most unresectable cases are invariably lethal. To advance patient care, we rely on clinical trials to test new therapeutic approaches. Here, we assume that the highest dose of a drug that does not cause severe toxicities is optimal for cancer treatment. However, this treatment strategy, in many cases, may be more harmful for the patient. Adopting principles from the field of evolutionary biology and pest management could offer more effective strategies that can be used for patients with metastatic PDAC and CRC. Resistance mechanisms are assumed to come with an energy cost, making the organism/cell less fit than others in the population. When high doses of treatment are applied, it results in a significant selection gradient by eliminating sensitive populations, freeing resources and facilitating resistant population growth. Such evolutionary dynamics and interactions within the tumor microenvironment can be modeled and exploited, in the form of adaptive strategies, for treatment of CRC and PDAC. It is our central hypothesis that integration of evolutionary dynamics and into PDAC and CRC treatment will delay emergence of resistance, enhance quality of life, and improve clinical outcomes. Our preliminary observations in co-cultured drug sensitive and resistant cell containing spheroids show that a higher proportion of drug sensitive cells inhibits the proliferation of drug resistant cells over time, in the presence of chemotherapeutic agents 5-FU and Oxaliplatin. We also demonstrate a role for the MLL family of histone methyltransferases in the epigenetic regulation of genes involved in chemoresistance. RNA-seq data has shown differential gene expression in metabolic genes regulated by histone methyltransferase KMT2A, KM2TB and KMT2D knockout (KO) cells including Gstt1, CYP26B1 and PYGL. In addition to this, KMT2A, KM2TB and KMT2D KOs show differential sensitivity to chemotherapeutic agents Gemcitabine, SN-38, 5-FU and Oxaliplatin. Further, analysis of KMT2A, KM2TB and KMT2D KO cells will provide mechanistic insight of the epigenetic regulation of metabolic patterns in drug resistant cells. This strategy would provide an approach for reducing exposure to toxic drugs, improving patient quality of life and renewing hope for prolonged control of metastatic PDAC and CRC. This proposal represents a bedside-to-bench-to-bedside project; identifying a shortcoming in how we currently treat PDAC and CRC patients, developing solutions in the lab and ultimately translating such strategies to benefit patients. Citation Format: Glancis Luzeena Raja Arul, Ezequiel Tolosa, Ryan M. Carr, Martin E. Fernandez-Zapico. Modeling evolutionary therapy for GI malignancies [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B002.

Changes in nuclear shape have been extensively associated with the dynamics and functionality of cancer cells. In most normal cells, nuclei have a regular ellipsoid shape and minimal variation in nuclear size; however, an irregular nuclear contour and abnormal nuclear size is often observed in cancer, including pancreatic cancer. Furthermore, alterations in nuclear morphology have become the ‘gold standard’ for tumor staging and grading. Beyond the utility of altered nuclear morphology as a diagnostic tool in cancer, the implications of altered nuclear structure for the biology and behavior of cancer cells are profound as changes in nuclear morphology could impact cellular responses to physical strain, adaptation during migration, chromatin organization, and gene expression. Here, we aim to highlight and discuss the factors that regulate nuclear dynamics and their implications for pancreatic cancer biology.

Polycystic kidney disease (PKD) has been linked to abnormal structure/function of ciliary proteins, leading to renal dysfunction. Recently, attention has been focused in the significant vascular abnormalities associated with PKD, but the mechanisms underlying this phenomenon remain elusive. Here, we seek to define the molecular events regulating the angiogenic imbalance observed in PKD. Using micro computed tomography (n=7) and protein expression analysis (n=5), we assessed the vascular density and the angiogenic profile of noncystic organs in a well-established PKD rat model (Polycystic Kidney-PCK rat). Heart and lungs of PCK rats have reduced vascular density and decreased expression of angiogenic factors compared with wild type. Similarly, PCK-vascular smooth muscle cells (VSMCs; n=4) exhibited lower levels of vascular markers. Then, using small interfering RNA (n=4), we determined the role of the ciliary protein fibrocystin in wild type-VSMCs, a critical component/regulator of vascular structure and function. Reduction of fibrocystin in wild type-VSMCs (n=4) led to an abnormal angiogenic potential similar to that observed in PCK-VSMCs. Furthermore, we investigated the involvement of the hedgehog signaling, a pathway closely linked to the primary cilium and associated with vascular development, in PKD. Mechanistically, we demonstrated that impairment of the hedgehog signaling mediates, in part, this abnormal angiogenic phenotype. Lastly, overexpression of Gli1 in PCK-VSMCs (n=4) restored the expression levels of proangiogenic molecules. Our data support a critical role of fibrocystin in the abnormal vascular phenotype of PKD and indicate that a dysregulation of hedgehog may be responsible, at least in part, for these vascular deficiencies.

The Hedgehog-regulated transcription factors GLI1 and GLI2 play overlapping roles in development and disease; however, the mechanisms underlying their interplay remain elusive. We report for the first time that GLI1 and GLI2 physically and functionally interact in cancer cells. GLI1 and GLI2 were shown to co-immunoprecipitate in PANC1 pancreatic cancer cells and RMS13 rhabdomyosarcoma cells. Mapping analysis demonstrated that the zinc finger domains of both proteins are required for their heteromerization. RNAi knockdown of either GLI1 or GLI2 inhibited expression of many well-characterized GLI target genes (BCL2, MYCN, PTCH2, IL7 and CCND1) in PANC1 cells, whereas PTCH1 expression was only inhibited by GLI1 depletion. qPCR screening of a large set of putative canonical and non-canonical Hedgehog/GLI targets identified further genes (e.g. E2F1, BMP1, CDK2) strongly down-regulated by GLI1 and/or GLI2 depletion in PANC1 cells, and demonstrated that ANO1, AQP1 and SOCS1 are up-regulated by knockdown of either GLI1 or GLI2. Chromatin immunoprecipitation showed that GLI1 and GLI2 occupied the same regions at the BCL2, MYCN and CCND1 promoters. Furthermore, depletion of GLI1 inhibited GLI2 occupancy at these promoters, suggesting that GLI1/GLI2 interaction is required for the recruitment of GLI2 to these sites. Together, these findings indicate that GLI1 and GLI2 co-ordinately regulate the transcription of some genes, and provide mechanistic insight into the roles of GLI proteins in carcinogenesis.

Abstract Background : The 2016 revision to the World Health Organization classification of myeloid neoplasms has recommended distinction between "proliferative" (WBC ≥ 13 x 10(9)/L) and "dysplastic" (WBC < 13 X 10(9)/L) subtypes of chronic myelomonocytic leukemia (CMML). In addition, CMML is characterized by a spectrum of cytogenetic and molecular abnormalities (Patnaik Leukemia 2014). In the current study, we looked for correlations between gene expression profiles (GEP) and morphologic or molecular categories of previously untreated patients with CMML. Methods : 35 patients with CMML were included in the study. Targeted capture assays were carried out on BM DNA specimens obtained at diagnosis for 28 myeloid-relevant genes (Patnaik Blood C. J.). RNA sequencing (Stranded Total RNA- Illumina, San Diego, CA), was performed on 9 normal BM controls, and 35 CMML samples (25 peripheral blood (PB) and 10 BM). The RNA-Seq data was analyzed using MAPRSeq v.2.0. Normalization and differential expression analysis was performed using edgeR 2.6.2. We selected genes that were differentially expressed with a False Discovery Rate (FDR) <0.1 and a fold change bigger than 2. Pathway enrichment analysis was performed using Ingenuity Pathway Analysis (IPA). Results: Among the 35 study patients, 75% were males and median age was 71 years (range, 55-87). 21 (60%), 9 (25%) and 5 (15%) patients were classified as CMML-0, 1 and 2, respectively. 16 (45%) had a dysplastic while 19 (55%) had a proliferative phenotype. At a median follow-up of 16 months, 5 (14%) deaths and 4 (14%) leukemic transformations were documented. Mutational frequencies included; TET2 45%, ASXL1 45%, SRSF2 40%, NRAS 14%, SETBP1 13%, CBL 10%, JAK2 7%, RUNX1 6%, DNMT3A 6%, U2AF1 6%, SF3B1 5%, ZRSR2 4%, Tp53 4%, and IDH2 4%. Abnormal cytogenetics (n=9, 35%) included; -Y 8%, trisomy 8 6%, monosomy 7 3%, del(13q) 3% and monosomal karyotype 3%. i) Differential GEP in PB samples: 25 PB CMML samples were analyzed. Unsupervised GEP demonstrated two unique clusters (figure one); cluster one was enriched with dysplastic CMML (90%) and cluster two with proliferative CMML (64%). Consistent with the difference in the distribution of morphologic categories, in comparison to cluster one, patients in cluster two had a higher white blood count (p=0.003), higher monocyte count (p=0.02) and higher risk prognostication by the Mayo Model (p=0.016); there was no significant difference between the two clusters in terms of age and gender distribution, hemoglobin level, neutrophil and platelet counts, PB or BM blast content, cytogenetic risk stratification, ASXL1, TET2, RAS, CBL and SETBP1 mutational status. Genes significantly upregulated (FDR<1e-5 and fold change ≥ 16x); in cluster two (proliferative CMML) in comparison to cluster one included; PRG2, CTSG, BEX1, CD34, CRISP2, while those significantly down-regulated included (FDR<1e-15 and fold change ≥ 5x); IL2RB, PRF1, GNLY, PDGFRB. IPA analysis identified the following pathways preferentially expressed in cluster two (proliferative CMML) 1) mitotic roles of polo-like kinase (KIF23, WEE-1, PLK1, PLK4), 2) Cell cycle: G2/M checkpoint regulation (CDC25C, WEE-1, AURKA, CDK1), 3) Cell cycle: chromosomal replication (CDC45, RPA3, MCM2, CDC7), and 4) BRCA1 in DNA damage response (BARD1, RBBP8, PLK1, RAD51). Whereas in the cluster one (dysplastic CMML), preferentially expressed pathways included; 1) T-cell receptor signalling (CD247 PRKCQ, CD4, PLCG1, CD28) and 2) STAT3 signalling (SOCS3, MAP3K9). ii) Differential GEP in BM samples: 10 BM CMML samples were analyzed along with 10 normal controls. Samples and controls clustered separately and within the CMML samples two clusters were identified (figure two). These clusters had equal representations of dysplastic (n=5) and proliferative (n=5) CMML sub-types. Additional samples are being processed. Conclusions: Differential gene expression profiling in patients with CMML identifies two unique clusters, clinically demarcated, at least in PB samples, by "proliferative" and "dysplastic" CMML subtypes. The proliferative cluster is enriched in genes involved in cell cycle regulation and DNA damage response; whereas the dysplastic cluster is enriched in T-cell receptor and STAT3 signalling. The prognostic and therapeutic impact of these gene clusters remains to be assessed in a larger group of informative patients. Figure 1. Figure 1. Figure 2. Figure 2. Disclosures Al-Kali: Novartis: Research Funding; Celgene: Research Funding.

Introduction: Chronic myelomonocytic leukemia (CMML), an aggressive myeloid malignancy, can be categorized into two subtypes, proliferative CMML (pCMML) and dysplastic (dCMML), based on a white blood cell (WBC) count of ≥ 13 x 109/L for the former (Arber et al. Blood 2016). While this WBC cut off is somewhat arbitrary, patients with pCMML have unique phenotypic features and a shorter survival. We carried out this study to assess the genomic, transcriptomic and epigenetic landscapes of these two CMML subtypes. Methods: Peripheral blood (PB) and bone marrow (BM) mononuclear cells (MNC) were obtained from WHO-defined CMML patients. Next generation sequencing (NGS) using a 36-gene panel was performed on 350 patients with Illumina HiSeq4000 platform with median read depth of 400X. RNA sequencing (RNA-seq) was performed on 25 patients by bulk whole transcriptome sequencing using Illumina TruSeq. DNA immunoprecipitation sequencing (DIP-seq) was performed on 18 patients using 5-methylcystocine (5mC), 5-hydroxymethylcytosine (5hmC) and bridging monoclonal antibodies with subsequent paired-end sequencing using HiSeq4000. Chromatin immunoprecipitation sequencing (ChIP-seq) was performed on 30 patients with Illumina HiSeq2500 to a depth of 25 million for histone 3 lysine 4 monomethylation (H3K4me1) and histone 3 lysine 4 trimethylation (H3K4me3) and 50 million reads for histone 3 lysine 27 trimethylation (H3K27me3) and Input per sample. Results: Five hundred and seventy-three patients with WHO defined CMML were included; median age 71 years (range 18-95 years), 67% males. 282 patients had pCMML (49%), while 291 (51%) had dCMML. As pre-defined, patients with pCMML were more likely to have higher absolute monocyte counts (p<0.0001), circulating immature myeloid cells (p<0.0001), PB blasts (p<0.0001), and higher lactate dehydrogenase levels (p=0.03). At last follow up 234 (41%) deaths and 70 (20%) leukemic transformations were documented. The median OS for pCMML vs dCMML in this cohort was 19 months vs 30 months (p<0.0001, Figure 1A) and validated in an independent Austrian cohort (p=0.02). Genomic profiling: NGS performed on 350 patients (BM MNC) revealed a higher frequency of NRAS (35 vs 17%, p=0.004), cumulative RAS pathway (NRAS, KRAS, CBL and PTPN11) (73 vs 47%, p=0.001), ASXL1 (p=0.003) and JAK2V617F (p=0.04) mutations in pCMML relative to dCMML (Figure 1B); while dCMML had a higher frequency of SF3B1 mutations (p=0.02). There were no differences in distribution of TET2 and SRSF2Transcriptomic analysis: RNA-seq was performed on PB MNC from RAS pathway mutant pCMML patients (n=12) and RAS pathway wildtype dCMML patients (n=13). Unsupervised clustering analysis resulted in appropriate segregation revealing distinct expression profiles between disease subtypes (Figure 1C). Compared to dCMML, 3729 genes were significantly differentially upregulated and 2658 genes were differentially downregulated in pCMML. Among genes most highly upregulated were mitotic checkpoint kinases including AURBK, PLK1, PLK2, PLK4 andEpigenetic profiling: ChIP-seq of PB and BM MNC from pCMML (n=18) and dCMML (n=12) patients and healthy, age-matched controls (n=10) revealed a global increase in H3K4me1, without significant differences in H3K4me3 or H3K27me3 occupancies (regardless of stratification by ASXL1 mutational status; 40% ASXL1mt in pCMML, 30% dCMML) in pCMML vs dCMML (Figure 1D). H3K4me1 occupancy was also increased in a sequence-specific manner at the transcription start sites of the aforementioned mitotic kinases (PLK1 and WEE1). DIP-seq was performed on PB MNC to assess global differences in 5-mC and 5-hmC levels, between pCMML (n=9) and dCMML (n=9), with no differences seen between the two subtypes (regardless of TET2 mutational status, 40% TET2mt in each subtype) (Figure 1E). Conclusions: Despite the somewhat arbitrary WBC distinction between pCMML and dCMML, clear phenotypic, genetic, transcriptomic, epigenetic and survival differences exist between the two subtypes, providing strong biological rationale for this distinction. pCMML patients have a higher frequency of oncogenic RAS pathway mutations, a unique transcriptomic profile enriched in mitotic check point kinases and a unique chromatin configuration with global and sequence specific enrichment in H3K4me1, with no significant global differences in 5mC, 5hmC, or H3K4me3 and H3K27me3 occupancy. Figure 1 Disclosures Geissler: AOP: Honoraria; Pfizer: Honoraria; AstraZeneca: Honoraria; Novartis: Honoraria; Celgene: Honoraria; Roche: Honoraria; Abbvie: Honoraria; Ratiopharm: Honoraria; Amgen: Honoraria. Al-Kali:Astex Pharmaceuticals, Inc.: Research Funding. Patnaik:Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees.

Abstract Background : TET2, located on chromosome 4q24, is frequently mutated in the majority of patients with chronic myelomonocytic leukemia (CMML). TET2 has 11 exons, and variations, especially in exon 3 have been described as a part of age related clonal hematopoiesis (Jaiswal NEJM 2015). In CMML, somatic TET2 mutations in the absence of ASXL1 mutations (ASXL1wt/TET2mt) were previously shown to impart a favorable outcome on survival (Patnaik BCJ 2015). In the current larger CMML patient cohort, we describe the number and type of TET2 mutations and examine their phenotypic and prognostic effects. Methods : 261 patients with CMML were included in the study. All patients had bone marrow (BM) biopsies and cytogenetics performed at diagnosis. Targeted capture assays were carried out on BM DNA specimens obtained at diagnosis for the following genes; TET2, DNMT3A, IDH1, IDH2, ASXL1, EZH2, SUZ12, SRSF2, SF3B1, ZRSR2, U2AF1, PTPN11, Tp53, SH2B3, RUNX1, CBL, NRAS, KRAS, JAK2, CSF3R, FLT3, KIT, CALR, MPL, NPM1, CEBPA, IKZF, and SETBP1. TET2 (NM_001127208.2) coverage extended from exons 3-11, with frame shift, non-sense, and missense variations considered pathogenic. Previously annotated single nucleotide polymorphisms (http//www.hapmap.org) were considered non-pathogenic. Results: Among the 261 study patients, 65% were males and median age was 70 years (range, 28-91). 154 (59%), 64 (25%) and 43 (16%) patients were classified as CMML-0, 1 and 2, respectively. At a median follow-up of 23 months, 174 (67%) deaths and 37 (14%) leukemic transformations were documented. Mutational frequencies ≥4% were encountered in; ASXL1 45%, TET2 42%, SRSF2 40%, NRAS 14%, SETBP1 13%, CBL 10%, JAK2 7%, RUNX1 6%, DNMT3A 6%, U2AF1 6%, SF3B1 5%, ZRSR2 4%, Tp53 4% and IDH2 4%. i) TET2 mutations type, number and phenotypic correlates: TET2 mutations were seen in 109 (42%) patients; these included frameshift 33 (30%), nonsense 29 (27%) and missense 11 (10%) variants whereas 36 (33%) had more than one type of mutation. Overall, 57 (52%) patients had more than 1 TET2 mutations: 52 (48%) patients had 1, 46 (42%) 2 and 11 (10%) ≥3 TET2 mutations. Among all 109 TET2 mutated patients, 65% were male, and median age was 71 years with no significant difference in age and gender distribution between mutated and un-mutated cases, or type of TET2 mutations; however, older patients were more likely to carry multiple TET2 mutations (p=0.01). Compared to their un-mutated counterparts, TET2 mutated cases were less likely to have a low hemoglobin (p<0.001), circulating immature myeloid cells (IMC) (p=0.001), peripheral blood (PB) (p=0.009) and BM blasts (p=0.009), and have high-risk stratification per Mayo Molecular Model (p<0.001); these differences were not affected by the type or number of TET2 mutations. TET2 mutated cases were more likely to have a higher frequency of SRSF2 (p=0.004) and lower frequency of ASXL1 (p=0.03), Tp53 (p=0.04) and IDH1/2 mutations (p<0.001); these associations were also not affected by the type or number of TET2 mutations. ii) Impact on survival: Median survival for the entire cohort (n=261) was 24 months. In univariate analysis, survival was superior in TET2 mutated (median 33 months) versus wild-type (median 21 months) patients [p=0.03; HR 1.3 95% CI 1.12-1.86] (figure 1A). This survival difference remained significant after adjustment for age (p=0.04), leukocyte count (p=0.017), absolute monocyte count (p=0.02), absolute lymphocyte count (p=0.02), platelet count (p=0.015), circulating IMC (p=0.03), DNMT3A (p=0.02) and ASXL1 (p=0.045) mutations; however, significance was lost after adjustment for abnormal karyotype (p=0.32) and the Mayo Molecular Model (p=0.0003). These observations were not affected by the type or number of TET2 mutations. Finally, our previous observation regarding the survival advantage of ASXL1wt/TET2mt versus other genotypes was most apparent for patients with multiple TET2 mutations (p=0.02) (figure 1B). Conclusions: TET2 mutations are common in CMML and constitute approximately equal proportions of frameshift and non-sense mutations, while missense mutations are less frequent. Majority of TET2 mutated CMML cases harbor more than one mutant variant. Regardless, the relevance of type and number of TET2 mutations in CMML was limited to an association between older age and number of mutations and the latter with possibly improved survival in the absence of clonal ASXL1 mutations. Disclosures No relevant conflicts of interest to declare.