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Background. Some patients who present with clinical features consistent with idiopathic hypereosinophilic syndrome (HES; absolute eosinophil count (AEC) ≥1.5 x 10 9/L with related end organ damage) are ultimately diagnosed with a myeloid neoplasm. Although FIP1L1::PDGFRA is the most common molecular abnormality in this setting, many other fusion genes, point mutations and cytogenetic abnormalities have been implicated in driving primary (neoplastic) eosinophilia. Given the poor prognosis of these disorders in the absence of treatment and the availability of targeted therapies for many of the driver mutations, it is becoming increasingly important to rapidly identify the underlying genetic alteration. In this regard, the expense and variable sensitivity of molecular diagnostic tests remains problematic. Although clinical features have been reported to distinguish between PDGFRA-associated myeloid neoplasms and D816V KIT-positive systemic mastocytosis with hypereosinophilia, little is known about the clinical phenotypes of other subsets of patients. This multicenter retrospective study aimed to assemble a large cohort of patients with HES secondary to a myeloid neoplasm to explore the utility of clinical and laboratory features in predicting the underlying molecular abnormality. Methods. Retrospective, de-identified data from 16 centers were collected via an online Research Electronic Data Capture repository. Patients and associated data were obtained from in-house research databases and/or electronic medical record searches at each site. Clinical and laboratory data were entered in accordance with local Institutional Review Boards. Inclusion criteria were peripheral blood hypereosinophilia (AEC >1.5 x 10 9/L) on at least two occasions and one of the following: ≥1 confirmed genetic abnormality recurrently associated with primary myeloid neoplasms, other evidence of clonal eosinophilia, or increased blasts (≥2% in the blood or >5% but <20% in the marrow). Patients with acute myeloid leukemia were excluded. Results. A total of 277 patients followed between 1990 and 2022 were included in the analysis. Median length of follow up was 31 months (range <1-356), and 217/277 (78%) were alive at last follow up. The most common genetic abnormality was FIP1L1::PDGFRA (n=131) followed by D816V KIT mutations (n=39) and alterations involving JAK2 (n=22) (Figure 1). Five patients had genetic abnormalities involving two distinct genes recurrently associated with eosinophilic myeloid neoplasms. The overall median age at diagnosis was 55 years (range 12-89) and 79% of the patients were male. When patients with abnormalities involving PDGFRA and PDGFRB were excluded from the analysis, the male predominance was significantly lower at 62% (p<0.001, Fisher's exact test as compared to the data set as a whole). The overall pattern of organ system involvement was similar irrespective of the underlying genetic abnormality with a few notable exceptions. Cardiac involvement was most common in patients with FIP1L1:: PDGFRA, abnormalities involving JAK2 or without pathologic alterations identified (reported in 22%, 32% and 30%, respectively); whereas skin and gastrointestinal involvement, lymphadenopathy and splenomegaly were most frequent in patients with KIT D816V. Laboratory abnormalities also differed between groups. Whereas anemia was the most common blood abnormality (reported in >50% of patients), erythrocytosis was noted primarily in patients with abnormalities involving JAK2. In contrast, circulating blasts were identified in 70% of patient with BCR::ABL1 and 29% of patients with chromosomal abnormalities or KIT D816V, but in <15% of patients in any of the other groups. Whereas peak AEC alone did not discriminate between the different patient groups, the AEC/tryptase ratio was increased in patients with PDGFRA-associated myeloid neoplasms, molecular abnormalities involving JAK2, or chromosomal abnormalities as compared to those with KIT mutations (Figure 2). Conclusions. Despite the limitations of retrospective data analysis, the data from this large multicenter cohort of patients with HES due to a chronic myeloid neoplasm suggest that routine demographic, clinical and laboratory features vary depending on the underlying molecular abnormality. This approach could ultimately help guide empiric therapy when molecular studies are negative or unavailable.

Primary Myelofibrosis (PMF) is an aggressive myeloproliferative neoplasm (MPN) characterized by constitutional symptoms, cytopenias, splenomegaly, extramedullary hematopoiesis, bone marrow (BM) fibrosis, and a propensity to transform to acute myeloid leukemia (AML). Despite advances in understanding the underlying genetic abnormalities in MPN and the development of JAK2 inhibitors to treat MF, there is an urgent need to devise new treatment strategies, particularly for triple negative myelofibrosis (TN-MF) cases that lack mutations in the JAK2 kinase pathway and who have inferior outcomes. To identify potential oncogenic drivers in TN-MF, we performed cytogenetic analyses and targeted exome sequencing of 98 genes commonly mutated in myeloid malignancies in 584 MF patients identified from the Total Cancer Care database at Moffitt Cancer Center. Notably, there were no significant differences in the somatic mutation profiles (other than JAK2 activating mutations) between TN vs. JAK2/CALR/MPL mutant MF patients. However, trisomy of chromosome 8 occurs more frequently in TN-MF vs. other subtypes (26.7% vs. 6.2%, p=0.0001). To identify oncogenic drivers in trisomy 8+ TN-MF, we performed scRNA-seq analysis from 18,651 cells ( n=15,850 from 3 normal donors and n=2,801 from a trisomy 8+ TN-MF patient) and identified a total of 1,260 genes that are differentially regulated in hematopoietic stem cells (HSCs) of trisomy 8+ TN-MF compared to normal donors. Among these, 131 genes were located on chromosome 8 and MYC was one of the top 5 genes that are significantly upregulated in trisomy 8+ HSCs. Additional immunohistochemistry staining demonstrated that MYC protein levels in BM cells were significantly higher in trisomy 8+ TN-MF patients vs. trisomy 8- patients. To assess whether MYC might be a driver of MPN, we established an Mx1-Cre +/-;Rosa26 LSL-MYC/LSL-MYC transgenic mouse model that inducibly overexpresses MYC in HSCs following treatment of polyinosinic-polycytidylic acid (pIpC). Forced MYC expression induced profound anemia, monocytosis, megakaryocytic atypia, splenomegaly, increased BM collagen deposition/fibrosis, extramedullary hematopoiesis in spleen and liver, and significantly reduced OS vs. Mx1-Cre +/- wild type controls (median OS 258 days vs. not reached (NR), p<0.0001). MYC also promoted expansion of HSCs, myeloid progenitors, and Gr-1 +/CD11b + mature myeloid cells in BM and spleen; thus, MYC was sufficient to provoke MF-like disease independent of JAK2 pathway mutations. Subsequent scRNA-seq analysis of 25,232 cells ( n=13,552 from control and n=11,680 from a MYC transgenic mouse) revealed that S100a9 mRNA levels were increased by MYC in most major hematopoietic cell types. Supporting oncogenic roles of S100A9 in MYC-driven MF, deletion of S100a9 in Mx1-Cre +/-;Rosa26 LSL-MYC/LSL-MYC;S100a9 -/- mice abolished MYC-induced MF phenotypes and significantly improved OS (median OS NR vs. 225 days, p=0.0345). To test whether inhibition of MYC can suppress MF disease progression in vivo, lethally irradiated CD45.1 +/CD45.2 + WT mice were transplanted with BM cells harvested from CD45.2 + Mx1-Cre +/-;Rosa26 LSL-MYC/LSL-MYC mice that were treated with pIpC 20 weeks prior to transplant. MYCi975, a small molecule that inhibits MYC, reduced MYC and S100a9 protein levels in BM and spleen cells. Further, MYCi975 effectively suppressed MYC-driven MF phenotypes and disease progression, and significantly improved OS (median OS NR vs. 252 days, p=0.0109). In summary, our studies are the first to describe an oncogenic role of MYC in MF pathogenesis, where MYC provokes an alarmin-driven inflammatory circuit, and where the MYC-S100A9 axis represents a therapeutic vulnerability for TN-MF patients. Accordingly, our results provide a strong rationale for testing agents targeting MYC or S100A9 in early phase clinical trials in MPNs having increased MYC levels or activity.

Abstract Disclosure: S.L. Samson: Consulting Fee; Self; Novartis Pharmaceuticals, Chiasma. M. Bolanowski: Grant Recipient; Self; Amryt, Recordati, Pfizer, Inc., Novartis Pharmaceuticals, Ipsen, IBSA, Teva Pharmaceutical Industries Ltd., Berlin Chemie. Speaker; Self; Amryt, Recordati, Pfizer, Inc., Novartis Pharmaceuticals, Ipsen, IBSA, Teva Pharmaceutical Industries Ltd., Berlin Chemie. S. Zhang: None. Y. Yu: None. P. Witek: Grant Recipient; Self; Novartis Pharmaceuticals, Ipsen, Recordati, Novo Nordisk, Xeris Pharmaceuticals (Strongbridge), Lilly USA, LLC. Speaker; Self; Novartis Pharmaceuticals, Ipsen, Recordati, Novo Nordisk, Xeris Pharmaceuticals (Strongbridge), Lilly USA, LLC. N. Kietsiriroje: None. A. Piacentini: Employee; Self; Recordati. A.M. Pedroncelli: Employee; Self; Recordati. U. Feldt-Rasmussen: Advisory Board Member; Self; Novartis Pharmaceuticals, Recordati, Novo Nordisk, Xeris Pharmaceuticals (Strongbridge). Grant Recipient; Self; Ipsen, Recordati, Novo Nordisk. Speaker; Self; Ipsen, Recordati, Novo Nordisk. Introduction: Pasireotide efficacy and safety in persons with acromegaly or Cushing’s disease (CD) is confirmed in a comprehensive clinical trial program. Pasireotide-induced hyperglycemia events, expected based on the drug’s mechanism of action, are manageable with low rates of treatment discontinuation. To advance knowledge on pasireotide-induced hyperglycemia management, a prospective randomized Phase IV study (B2219, NCT02060383) was conducted. This secondary analysis assessed factors that might predict development of pasireotide-induced hyperglycemia. Methods: In B2219, participants (Pts) with acromegaly or CD who did not need therapy for hyperglycemia or were managed with metformin alone entered the non-randomized observational arm. Pts who developed hyperglycemia not managed with metformin alone were randomized to incretin-based therapy or insulin. This analysis evaluated Pts according to whether therapy for hyperglycemia during pasireotide treatment was needed. Logistic regression analyses evaluated quantitative and qualitative predictive factors associated with pasireotide-induced hyperglycemia. Results: Of 190 Pts with acromegaly and 59 with CD, 88 and 15, respectively, did not need antihyperglycemic medication during pasireotide treatment; Pt characteristics were generally balanced across subgroups at study baseline (BL). Most Pts who did not develop hyperglycemia had a mean age of <40 years (acromegaly 62.5%, CD 86.7%), BL glycated hemoglobin (HbA1c) <6.5% (acromegaly 98.9%, CD 100.0%) and BL fasting plasma glucose (FPG) <100 mg/dL (acromegaly 76.1%, CD 100.0%). Age (odds ratio [OR] 1.0, 95% CI 1.0−1.1), BL HbA1c (OR 3.5, 95% CI 1.3−9.9) and prediabetes or diabetes conditions (OR 3.0, 95% CI 1.2−7.6) were identified as risk factors associated with pasireotide-induced hyperglycemia in Pts with acromegaly. BL FPG (OR 1.2, 95% CI 1.0−1.3) was associated with increased risk of pasireotide-induced hyperglycemia in Pts with CD. Overall, adverse events (AEs) of hyperglycemia and diabetes mellitus (investigator reported) occurred in 21.1% and 14.2% of Pts with acromegaly and 28.8% and 11.9% of Pts with CD, respectively. More Pts who had diabetes or prediabetes conditions at BL had hyperglycemia-related AEs than Pts with normal glucose levels. Hyperglycemia-related AEs were managed with antihyperglycemic medication (acromegaly 26.3%, CD 30.5%); few Pts temporarily interrupted treatment (acromegaly 3.7%, CD 10.2%). Conclusions: These data suggest that age, HbA1c, FPG and having prediabetes or diabetes conditions at BL are associated with increased risk of developing pasireotide-induced hyperglycemia. AEs were manageable with antihyperglycemic medication. Potential risk factors associated with pasireotide-induced hyperglycemia may be used to identify Pts who need vigilant monitoring to ensure optimal outcomes during pasireotide treatment. Presentation: Thursday, June 15, 2023

Abstract Myelodysplastic neoplasms (MDS) are a collection of hematopoietic disorders with widely variable prognoses and treatment options. Accurate pathologic diagnoses present challenges because of interobserver variability in interpreting morphology and quantifying dysplasia. We compared local clinical site diagnoses with central, adjudicated review from 918 participants enrolled in the ongoing National Heart, Lung, and Blood Institute National MDS Natural History Study, a prospective observational cohort study of participants with suspected MDS or MDS/myeloproliferative neoplasms (MPNs). Locally, 264 (29%) were diagnosed as having MDS, 15 (2%) MDS/MPN overlap, 62 (7%) idiopathic cytopenia of undetermined significance (ICUS), 0 (0%) acute myeloid leukemia (AML) with <30% blasts, and 577 (63%) as other. Approximately one-third of cases were reclassified after central review, with 266 (29%) diagnosed as MDS, 45 (5%) MDS/MPN overlap, 49 (5%) ICUS, 15 (2%) AML with <30%, and 543 (59%) as other. Site miscoding errors accounted for more than half (53%) of the local misdiagnoses, leaving a true misdiagnosis rate of 15% overall, 21% for MDS. Therapies were reported in 37% of patients, including 43% of patients with MDS, 49% of patients with MDS/MPN, and 86% of patients with AML with <30% blasts. Treatment rates were lower (25%) in cases with true discordance in diagnosis compared with those for whom local and central diagnoses agreed (40%), and receipt of inappropriate therapy occurred in 7% of misdiagnosed cases. Discordant diagnoses were frequent, which has implications for the accuracy of study-related and national registries and can lead to inappropriate therapy. This trial was registered at www.clinicaltrials.gov as #NCT05074550.

Histiocytic neoplasms are rare hematologic disorders accounting for less than 1% of cancers of the soft tissue and lymph nodes. Clinical presentation and prognosis of these disorders can be highly variable, leading to challenges for diagnosis and optimal management of these patients. Treatment often consists of systemic therapy, and recent studies support use of targeted therapies for patients with these disorders. Observation (“watch and wait”) may be sufficient for select patients with mild disease. These NCCN Guidelines for Histiocytic Neoplasms include recommendations for diagnosis and treatment of adults with the most common histiocytic disorders: Langerhans cell histiocytosis, Erdheim-Chester disease, and Rosai-Dorfman disease.

MYC gene amplification and somatic mutations are frequent in both adult and pediatric AML although how MYC drives and contributes to the development and maintenance of AML has not been resolved. Transcription factor EB (TFEB) is a master regulator of genes that control autophagy and lysosome biogenesis, a central catabolic recycling pathway that regulates cell survival. Given the oncogenic effects of MYC in AML and that the induction of autophagy compromises AML cell growth and survival, we tested if the oncogenic effect of MYC depends on its suppression of TFEB transcription programs in AML. In support of this hypothesis, inducible MYC expression in K562 and THP-1 leukemia cells was sufficient to suppress expression of TFEB and its target genes. Further and conversely, MYC knockdown in NB4 AML cells provoked increased expression of TFEB mRNA and protein, as well as increased expression of TFEB target genes. Notably, dose response studies demonstrated that expression of TFEBS211A, constitutively nuclear form of TFEB that is refractory to control by mTORC1 signaling, dramatically impairs proliferation of HL60, OCI-AML2 and OCI-AML3 AML cells. In addition, induction of TFEBS211A provoked rampant apoptosis. Of important, overexpression of TFEBS211A in HL-60 and OCI-AML3 cells was also sufficient to promote monocytic and granulocytic differentiation, as judged by morphological changes and the acquisition of mature monocytic and granulocytic markers including CD11b, Gr1, and CD15. To identify TFEB targets that might contribute to myeloid/granulocytic differentiation, we performed RNA-seq analysis of HL60 leukemia cells engineered to inducibly express the TFEBS211A transgene. Using a cut-off of fold change>4 with q<0.01, a total of 1152 genes were differentially regulated following the induction of TFEBS211A in HL60 cells. As expected, this included the robust induction of nearly all TFEB target genes associated with the autophagy-lysosome pathway, but also of STAT1, KLF4, KLF6, CEBPB, CSF1 and GATA2 genes that are necessary and/or sufficient to provoke terminal monocytic and granulocytic differentiation of AML cells. Surprisingly, among genes induced by TFEB in HL60 cells is IDH1, which catalyzes the production of α-ketoglutarate (α-KG), a required substrate of the TET family of dioxygenases that convert 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC). In particular, TFEBS211A expression provoked increases in levels of α-KG and significant increases in global levels of 5hmC in genomic DNA of HL60 leukemia cells both ex vivo and in vivo. Furthermore, TFEB-mediated induction of IDH1/2 mRNA and protein, and of IDH1 promoter activity, was antagonized by inducible expression of MYC. To assess the global effects of TFEB on 5mC/5hmC landscapes, we performed paired reduced representation bisulfite (BS)- and oxidation bisulfite (oxBS)-sequencing. As predicted, TFEBS211A induced both loss and gains of 5mC, but there were more losses (n = 722) than gains (n = 459) across all 22 chromosomes. Quite remarkably, and consistent with TFEB-provoked increases of 5hmC signals, TFEBS211A exclusively induced 5hmC gains (in a total of 863 genes), and 37% and 36% of these 5hmC gains occurred in promoter regions and CpG islands, and across all 22 chromosomes. Comparison of BS- and oxBS-seq versus RNA-seq analyses of HL60 cells expressing TFEB revealed significant changes in mRNA levels and concomitant differential changes in 5mC and 5hmC marks in KLF4, KLF6, STAT3, TP73, andFOXO1 that have pivotal roles in controlling myeloid cell differentiation and death. Collectively, these findings demonstrate that MYC suppresses TFEB expression and function in AML cells, and that TFEB functions as a tumor suppressor that provokes AML cell differentiation and death. Strikingly, these responses rely on epigenetic control, where TFEB directly induces the transcription of IDH1 and IDH2 to provoke global hydroxylation of 5-methylcytosine and the expression of genes that drive terminal differentiation and apoptosis. Thus, a MYC-TFEB-IDH1/2-TET2 circuit controls AML cell fate. Disclosures Murphy: Merck: Research Funding; Puma Biotech: Research Funding. Ballabio:CASMA Therapeutics: Other: Co-Founder. Kaufmann:Takeda Pharmaceuticals: Research Funding.

Introduction: The NHLBI National MDS Study (NCT02775383) is a prospective cohort study conducted at 92 community hospitals and 29 academic centers. It enrolls patients undergoing work up for suspected MDS to understand the genetic, epigenetic, and biological factors associated with the initiation and progression of the disease. Previously untreated, cytopenic participants undergo both local and centralized pathology review and are assigned a diagnosis, including MDS, MDS/MPN, AML with blasts < 30%, and "Other". Emerging data suggests that Next Generation Sequencing (NGS), along with cytogenetics and clinical variables, may improve MDS diagnostic precision. Given that our study relies on central review (with additional tertiary pathology review used to adjudicate disagreements), we examined whether targeted gene sequencing data could be used to increase the agreement between local and central pathologic diagnosis of MDS vs. Other. Methods: Peripheral blood and bone marrow (BM) biopsy specimens from cytopenic patients, along with clinical history, CBC, and other results including karyotyping, FISH and pathology reports from local pathologists were reviewed by central pathologists. The updated 2016 WHO classifications were used to diagnose MDS. Targeted exon sequencing of 96 genes was performed using BM specimens. A subset of 648 individuals that were classified as MDS (n=212) or Other (n=436, including 90 CCUS and 89 individuals with other cancers) by pathology assessments were selected. A mean coverage of 1,317X was achieved and variants had a minimum variant allele frequency (VAF) of 2% (except FLT3). Variants for 596 subjects were manually reviewed to retain likely disease-causing variants to build a binary classifier (MDS vs. Other) using the maximum VAF per gene as input (Figure 1). Subjects diagnosed with MDS or Other by both central and local pathology were used for training, validation, and testing, and were considered "gold standard" (GS) cases (n=546). These subjects were split into 4 random groups with equal proportions of MDS cases. 75% of the GS cases were used to train and validate lasso-regularized logistic regression models using 3-fold cross validation. ROC curve analysis was carried out using the remaining 25% of GS cases (Test Set 1) on the best model to identify an optimal probability cut off point for classifying subjects as MDS. Model performance was then tested on 50 subjects for which the central and local pathology diagnosis disagreed (Test Set 2), as well as on 52 additional subjects irrespective of agreement (Test Set 3). Results : The best performing logistic regression model retained 7 genes as most informative in a discriminating diagnosis of MDS from Other based on their VAFs, in order of impact: TP53, SF3B1, U2AF1, ASXL1, TET2,STAG2, and SRSF2. We used this model to assign probabilities for each of the subjects in Test Set 1 and to estimate the performance using ROC analysis (Figure 1), resulting in a high area under the curve (AUC) of 0.89. We chose a probability cut-off of ≥0.17, being associated with a high percentage of correct classification of MDS with a sensitivity and specificity of 0.90 and 0.81, respectively. Among the cohort of 50 subjects with a discordant local and central pathology diagnosis (Test Set 2), the classifier accurately reassigned 37 subjects (accuracy = 74%) from the local to the central pathology. The blinded tertiary pathology reviewer agreed with central in all Test Set 2 cases. This included 24/34 MDS cases that had been labeled as Other by local pathology (positive predictive value [PPV]=0.89). 3/16 final pathology-classified Other cases were mis-classified as MDS by the local pathologist (negative predictive value [NPV] = 0.57). Next, we assessed the ability of the model to predict MDS vs. Other for 52 additional independent subjects using the third pathologist's diagnosis to break any ties (Test Set 3). The classifier correctly predicted 15/21 MDS cases (PPV=0.83) and misclassified 6/31 Others as MDS (NPV=0.82). The overall accuracy was 83%. Conclusions: We identified that VAFs for 7 genes can correctly re-classify subjects as either MDS or Other in 74% of cases that were misclassified between local and central pathology review. Further assessment on an independent cohort showed an accuracy of 83% of the model. Taken together, these data suggest that complementing pathology reviews with targeted sequencing of 7 genes could improve MDS diagnosis. Disclosures Lindsley: MedImmune: Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Bluebird Bio: Consultancy; Takeda Pharmaceuticals: Consultancy. Bejar:Aptose Biosciences: Current Employment; AbbVie/Genentech: Honoraria; Astex/Otsuka: Honoraria; Takeda: Honoraria, Research Funding; Celgene/BMS: Honoraria, Research Funding; Daiichi-Sankyo: Honoraria; Forty-Seven/Gilead: Honoraria; Genoptix/NeoGenomics: Honoraria. DeZern:MEI: Consultancy; Astex: Research Funding; Abbvie: Consultancy; Celgene: Consultancy, Honoraria. Foran:H3Biosciences: Research Funding; Aptose: Research Funding; Kura Oncology: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Revolution Medicine: Consultancy; Xencor: Research Funding; Agios: Honoraria, Research Funding; Aprea: Research Funding; Actinium: Research Funding; Servier: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding. Gore:Abbvie: Consultancy, Honoraria, Research Funding. Komrokji:Acceleron: Honoraria; Incyte: Honoraria; Abbvie: Honoraria; Agios: Speakers Bureau; BMS: Honoraria, Speakers Bureau; Jazz: Honoraria, Speakers Bureau; Geron: Honoraria; Novartis: Honoraria. Maciejewski:Alexion, BMS: Speakers Bureau; Novartis, Roche: Consultancy, Honoraria. Padron:Novartis: Honoraria; BMS: Research Funding; Incyte: Research Funding; Kura: Research Funding. Starczynowski:Captor Therapeutics: Consultancy; Tolero Therapeutics: Research Funding; Kurome Therapeutics: Consultancy, Current equity holder in private company, Research Funding. Sekeres:BMS: Consultancy; Takeda/Millenium: Consultancy; Pfizer: Consultancy.