STAG2 Mutations Research Articles

Clinicopathological characteristics and genetic features of young and senior Ewing sarcoma patients

BackgroundEwing sarcoma (EwS) is a highly malignant and heterogeneous tumor. Exploring clinicopathological characteristics and genetic features of EwS is critical for prognosis and treatment regimen.MethodsClinicopathological characteristics and genetic features of young (≤ 30y) and senior (> 30y) EwS patients were analyzed based on histology, phenotype, and next-generation sequencing (NGS) detection.ResultsThe young group (18/36) presented nontypical EwS histological morphology, whereas the senior group (18/36) presented typical morphology. The prognosis of the young group was found to be worse compared with the senior group for patients without metastasis at the initial diagnosis. DNA- and RNA-based NGS was conducted on 20 extraosseous EwS patients. 16/20 samples demonstrated EWSR1-FLI1 fusion and 4/20 demonstrated EWSR1-ERG fusion. However, 13/16 EWSR1-FLI1fusions were detected both in DNA- and RNA-based NGS, 1/16 was detected only at the DNA level, and 2/16 were detected only at the RNA level. An analysis of the genetic profiles of the EWSR1-FLI1 cases revealed that the young group was inclined to couple with more copy number variations (CNV), such as CCND1, CDK4 amplification, and fusion variations, such as CHEK1-EWSR1, SLIT2-EWSR1, and EWSR1-FAM76B fusion. The senior group was more likely to have SNV or Indel mutations, such as EPHA3 and STAG2 mutations. Moreover, patients with more CNV abnormalities had a worse prognosis than those with predominantly SNP variants. In addition, compared with the senior group, the young group had significantly higher CyclinD1 protein expression.ConclusionClinicopathological characteristics and genetic features in young and senior EwS patients differed significantly. Targeting cell cycle dysregulation based on age subgroup may be a potential therapeutic strategy for Ewing sarcoma.

The clinical implications of BCOR mutations in a large cohort of acute myeloid leukemia patients: a 5-year single-center retrospective study

To elucidate the effect of BCOR mutation (BCOR mut) on clinical outcomes, we included a total of 899 consecutive AML patients in a single-center during July 2016 to December 2021. Fifty cases (5.6%) had BCOR mutations, which co-occurred with mutations of RUNX1, DNMT3A, IDH2, BCORL1, STAG2, SF3B1 and U2AF1, but were exclusive with KIT and CEBPA mutations. BCOR mut was also found to be exclusive with t(8;21)(q22;q22.1) AML in all patients and MLL rearrangements in the European Leukemia Net (ELN) adverse group. In those receiving intensive chemotherapy regimens, BCOR mut was associated with lower complete remission (CR) rates and worse prognosis. Subgroup analysis showed that BCOR mut mainly conferred a poor prognosis in the intermediate and adverse groups of the ELN2017 risk. These results suggest that BCOR mutation is an independent prognostic parameter in AML, implying BCOR mutation as a novel marker for chemorefractory disease and inferior prognosis.

ETV6::ABL1 fusion: from overlooked minor clone in myeloproliferative neoplasm to major player in leukemic transformation.

The ETV6::ABL1 fusion defines a subgroup of myeloid/lymphoid neoplasms with eosinophilia and tyrosine kinase gene fusions. We report a case of extramedullary involvement and leukemic transformation in myeloproliferative neoplasm (MPN), where ETV6::ABL1 was initially overlooked but later detected in the blast phase. ETV6::ABL1 burden was very low during the MPN phase but increased substantially during the blast phase. This correlation between ETV6::ABL1 burden and disease phenotype indicated that an immature leukemic clone is the sole carrier of ETV6::ABL1, suggesting that ETV6::ABL1 is not the primary driver of the MPN phase. Moreover, only the blast phase revealed somatic mutations in RUNX1 and STAG2, or complex karyotype, while the MPN phase revealed no molecular and cytogenetic abnormalities. Therefore, it remains uncertain whether the small clone of ETV6::ABL1 influenced the manifestation of MPN or if another underlying driver was responsible for the MPN phase, necessitating further research.

Subunit-specific analysis of cohesin-mutant myeloid malignancies reveals distinct ontogeny and outcomes

Mutations in the cohesin complex components (STAG2, RAD21, SMC1A, SMC3, and PDS5B) are recurrent genetic drivers in myelodysplastic neoplasm (MDS) and acute myeloid leukemia (AML). Whether the different cohesin subunit mutations share clinical characteristics and prognostic significance is not known. We analyzed 790 cohesin-mutant patients from the Dana-Farber Cancer Institute (DFCI) and the Munich Leukemia Laboratory (MLL), 390 of which had available outcome data, and identified subunit-specific clinical, prognostic, and genetic characteristics suggestive of distinct ontogenies. We found that STAG2 mutations are acquired at MDS stage and are associated with secondary AML, adverse prognosis, and co-occurrence of secondary AML-type mutations. In contrast, mutations in RAD21, SMC1A and SMC3 share features with de novo AML with better prognosis, and co-occurrence with de novo AML-type lesions. The findings show the heterogeneous nature of cohesin complex mutations, and inform clinical and prognostic classification, as well as distinct biology of the cohesin complex.

Real-world outcomes of newly diagnosed AML treated with venetoclax and azacitidine or low-dose cytarabine in the UK NHS

AbstractVenetoclax with azacitidine is the standard of care for patients with acute myeloid leukemia (AML) who are unfit for intensive chemotherapy; however, uncertainties remain regarding the treatment schedule, accurate prognostication, and outcomes for patients treated outside clinical trials. The option of venetoclax with low-dose cytarabine (LDAC) is also available; however, it is not clear for which patients it may be a useful alternative. Here, we report a large real-world cohort of 654 patients treated in 53 UK hospitals with either venetoclax and azacitidine (n = 587) or LDAC (n = 67). The median age was 73 years, and 59% had de novo AML. Most patients received 100 mg of venetoclax with an azole antifungal. In cycle 1, patients spent a median of 14 days in the hospital, and 85% required red cell transfusion, 59% platelet transfusion, and 63% required IV antibiotics. Supportive care requirements significantly reduced after the first cycle. Patients receiving venetoclax-azacitidine had a complete remission (CR)/CR with incomplete hematological recovery rate of 67%, day 30 and day 60 mortality of 5% and 8%, respectively, and median overall survival of 13.6 months. Mutations in NPM1, RUNX1, STAG2, and IDH2 were associated with improved survival, whereas age, secondary and therapy-related AML, +8, MECOM rearrangements, complex karyotype, ASXL1, and KIT mutations were associated with poorer survival. Prognostic systems derived specifically for patients treated with venetoclax-azacitidine performed better than the European LeukemiaNet and Medical Research Council classifications; however, improved risk classifications are still required. In the 149 patients with NPM1 mutated AML, outcomes were similar for those treated with venetoclax-azacitidine and venetoclax-LDAC.

STAG2 mutations regulate 3D genome organization, chromatin loops, and Polycomb signaling in glioblastoma multiforme

Inactivating mutations of genes encoding the cohesin complex are common in a wide range of human cancers. STAG2 is the most commonly mutated subunit. Here we report the impact of stable correction of endogenous, naturally occurring STAG2 mutations on gene expression, 3D genome organization, chromatin loops, and Polycomb signaling in glioblastoma multiforme (GBM). In two GBM cell lines, correction of their STAG2 mutations significantly altered the expression of ∼10% of all expressed genes. Virtually all the most highly regulated genes were negatively regulated by STAG2 (i.e., expressed higher in STAG2-mutant cells), and one of them-HEPH-was regulated by STAG2 in uncultured GBM tumors as well. While STAG2 correction had little effect on large-scale features of 3D genome organization (A/B compartments, TADs), STAG2 correction did alter thousands of individual chromatin loops, some of which controlled the expression of adjacent genes. Loops specific to STAG2-mutant cells, which were regulated by STAG1-containing cohesin complexes, were very large, supporting prior findings that STAG1-containing cohesin complexes have greater loop extrusion processivity than STAG2-containing cohesin complexes and suggesting that long loops may be a general feature of STAG2-mutant cancers. Finally, STAG2 mutation activated Polycomb activity leading to increased H3K27me3 marks, identifying Polycomb signaling as a potential target for therapeutic intervention in STAG2-mutant GBM tumors. Together, these findings illuminate the landscape of STAG2-regulated genes, A/B compartments, chromatin loops, and pathways in GBM, providing important clues into the largely still unknown mechanism of STAG2 tumor suppression.

Clinical characteristics of myeloid tumors combined with the proliferation of large granular lymphocytes

Myeloid neoplasms (MNs) belong to a group of hematological malignancies characterized by the abnormal biological functions of hematopoietic stem progenitor cells. The abnormal immune and hematopoietic microenvironment of patients with MN interact with malignant clonal hematopoietic stem cells, promoting the occurrence and development of their diseases. MN large granular lymphocyte proliferation (MN-LGLP) is a special and rare clinical phenomenon in this type of disease. Currently, research on this disease in domestic and international cohorts is limited. This study analyzes the clinical and laboratory characteristics of this type of patient and explores the impact of LGLP on the clinical characteristics and survival of patients with MN. Patients with MN-LGLP are prone to neutropenia and splenomegaly. The presence of LGLP is not a risk factor affecting the survival of patients with MN-LGLP. STAG, ASXL1, and TET2 are the most common accompanying gene mutations in MN-LGLP, and patients with MN-LGLP and STAG2 mutations have poor prognoses.

Synthetic Lethality between Cohesin and WNT Signaling Pathways in Diverse Cancer Contexts.

Cohesin is a highly conserved ring-shaped complex involved in topologically embracing chromatids, gene expression regulation, genome compartmentalization, and genome stability maintenance. Genomic analyses have detected mutations in the cohesin complex in a wide array of human tumors. These findings have led to increased interest in cohesin as a potential target in cancer therapy. Synthetic lethality has been suggested as an approach to exploit genetic differences in cancer cells to influence their selective killing. In this study, we show that mutations in ESCO1, NIPBL, PDS5B, RAD21, SMC1A, SMC3, STAG2, and WAPL genes are synthetically lethal with stimulation of WNT signaling obtained following LY2090314 treatment, a GSK3 inhibitor, in several cancer cell lines. Moreover, treatment led to the stabilization of β-catenin and affected the expression of c-MYC, probably due to the occupancy decrease in cohesin at the c-MYC promoter. Finally, LY2090314 caused gene expression dysregulation mainly involving pathways related to transcription regulation, cell proliferation, and chromatin remodeling. For the first time, our work provides the underlying molecular basis for synthetic lethality due to cohesin mutations and suggests that targeting the WNT may be a promising therapeutic approach for tumors carrying mutated cohesin.

Abstract 4358: Genomic profiling of residual kidney structures in dialysis patients

Abstract Background: Chronic kidney disease is frequently associated with persistent inflammation, which results in fibrosis in the stroma, a reduced number of renal tubules, the formation of multiple cystic lesions, ultimately terminating in renal failure and hemodialysis. The high incidence of renal cell carcinoma (RCC) in hemodialysis patients suggests a relationship between tissue remodeling by chronic inflammation and carcinogenesis. However, little is known about the genetic background of cancer development from remaining tubules and cystic lesions in hemodialysis patients. Methods: We enrolled 5 patients under hemodialysis who were accompanied by acquired cystic kidney disease and who underwent total nephrectomy for renal cancer. Surgical specimens were fixed with alcohol-based solution and paraffin-embedded, and after H&E staining, subjected to laser capture microdissection (LCM) to collect remaining tubules and cysts containing approximately 200 cells. DNA was extracted and analyzed for somatic mutations and copy number alteration by whole-exome sequencing. Results: In total, we collected 161 LCM samples, including 118 from proximal tubules, 17 from collecting ducts, and 26 from cysts. The median variant allele frequencies of detected mutations were 0.237 in proximal tubules, 0.133 in collecting duct, and 0.381 in cysts, indicating larger clonal expansion in proximal tubules and cysts than in collecting ducts. Proximal tubules and cysts contained recurrent mutations in FAT1 (11% and 8%, respectively), STAG2 (5% and 8%), and PTEN (3% and 4%), whereas no recurrent driver mutations were identified in collecting ducts. In copy number analysis, 26% of proximal tubules, 35% of collecting ducts, and 80% of cysts had copy number alterations. Of note, samples from cysts had more copy number alterations compared to remaining tubules (on average, 2.3 vs. 1.1). Proximal tubules had recurrent copy number gains of chromosomes 3, 7, 10, 18, and 20, and loss of chromosome 22 and samples from collecting ducts showed gains of chromosome 7 and loss of chromosome 18. In cysts, gains of chromosomes 2, 3, 7, 10, 12, and 16 and loss of chromosomes 15, 16, 21, and 22 were frequently observed. Copy number profile in cysts was similar to that of papillary RCC and acquired cystic disease-associated RCC. Conclusion: In the end-stage cystic kidney, both proximal tubules and cysts exhibited an enrichment of driver mutations commonly found in papillary RCC and RCC with acquired cystic disease, reflecting the fact that the incidence of these two types of RCC increases as the duration of dialysis becomes longer. In addition, clear cell RCC drivers, such as VHL mutation and loss of chromosome 3, were not observed, possibly explaining the rare occurrence of clear cell RCC in hemodialysis patients. Since cysts had more frequent copy number alterations than remaining tubules, cysts in the end-stage kidney might be precursor lesions of RCC. Citation Format: Kosuke Ieiri, Nobuyuki Kakiuchi, Tomonori Hirano, Koichi Watanabe, Hirona Maeda, Hiroko Tanaka, Satoru Miyano, Dai Takamatsu, Takashi Matsumoto, Keisuke Monji, Masaki Shiota, Junichi Inokuchi, Hideki Makishima, Masatoshi Eto, Seishi Ogawa. Genomic profiling of residual kidney structures in dialysis patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4358.

Hematopoietic stem cells with granulo-monocytic differentiation state overcome venetoclax sensitivity in patients with myelodysplastic syndromes

The molecular mechanisms of venetoclax-based therapy failure in patients with acute myeloid leukemia were recently clarified, but the mechanisms by which patients with myelodysplastic syndromes (MDS) acquire secondary resistance to venetoclax after an initial response remain to be elucidated. Here, we show an expansion of MDS hematopoietic stem cells (HSCs) with a granulo-monocytic-biased transcriptional differentiation state in MDS patients who initially responded to venetoclax but eventually relapsed. While MDS HSCs in an undifferentiated cellular state are sensitive to venetoclax treatment, differentiation towards a granulo-monocytic-biased transcriptional state, through the acquisition or expansion of clones with STAG2 or RUNX1 mutations, affects HSCs’ survival dependence from BCL2-mediated anti-apoptotic pathways to TNFα-induced pro-survival NF-κB signaling and drives resistance to venetoclax-mediated cytotoxicity. Our findings reveal how hematopoietic stem and progenitor cell (HSPC) can eventually overcome therapy-induced depletion and underscore the importance of using close molecular monitoring to prevent HSPC hierarchical change in MDS patients enrolled in clinical trials of venetoclax.

Mapping of DDX11 genetic interactions defines sister chromatid cohesion as the major dependency.

DDX11/Chl1R is a conserved DNA helicase with roles in genome maintenance, DNA replication, and chromatid cohesion. Loss of DDX11 in humans leads to the rare cohesinopathy Warsaw breakage syndrome. DDX11 has also been implicated in human cancer where it has been proposed to have an oncogenic role and possibly to constitute a therapeutic target. Given the multiple roles of DDX11 in genome stability and its potential as an anticancer target, we set out to define a complete genetic interaction profile of DDX11 loss in human cell lines. Screening the human genome with clustered regularly interspaced short palindromic repeats (CRISPR) guide RNA drop out screens in DDX11-wildtype (WT) or DDX11-deficient cells revealed a strong enrichment of genes with functions related to sister chromatid cohesion. We confirm synthetic lethal relationships between DDX11 and the tumor suppressor cohesin subunit STAG2, which is frequently mutated in several cancer types and the kinase HASPIN. This screen highlights the importance of cohesion in cells lacking DDX11 and suggests DDX11 may be a therapeutic target for tumors with mutations in STAG2.

Clinical and prognostic characteristics of pediatric acute myeloid leukemia with myelodysplasia-related changes under different diagnostic criteria

Objective: To evaluate the clinical and prognostic differences in acute myeloid leukemia with myelodysplasia-related changes (AML-MRC) children under different diagnostic criteria (World Health Organization (WHO) 2016 and WHO 2022 criteria). Methods: In this retrospective cohort study, clinical characteristics and prognosis information of 260 acute myeloid leukemia (AML) children admitted to Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences from August 2017 to August 2021 were analyzed retrospectively. According to WHO 2016 and WHO 2022 diagnostic criteria, patients were divided into AML-MRC group and non-AML-MRC group, the prognostic and genetic differences between two groups were compared respectively. Meanwhile, the characteristics of children with 8 MRC-related genes defined in WHO 2022 diagnostic criteria were described. Mann-Whitney U test, chi-square test were used for comparison between groups. Survival curve was plotted by Kaplan-Meier method, and comparison between groups was performed by Log-Rank method. Results: Among the 260 children, there were 148 males and 112 females. The follow-up time was 26 (16, 38) months. A total of 28 children (10.8%) were diagnosed with AML-MRC according to the WHO 2016 diagnostic criteria. Compared with non-AML-MRC children, the frequency of PTPN11, RUNX11, SH2B3, MPL and STAG2 mutations was higher in AML-MRC children (25.0% (7/28) vs.4.3% (10/232), 14.3% (4/28) vs.3.9% (9/232), 10.7% (3/28) vs.2.2% (5/232), 10.7% (3/28) vs.2.2% (5/232), 10.7% (3/28) vs.0.9% (2/232), all P<0.05). The 2-year overall survival (OS) and events free survival (EFS) rate of 28 AML-MRC children under WHO 2016 diagnostic criteria were worse than those of 232 non-AML-MRC children ((62.1±10.8)% vs. (94.5±1.6)%, χ2=22.1,P<0.001;(48.0±10.6)% vs. (70.9±3.2)%, χ2=6.33,P=0.012). Twenty-seven children (10.4%) were eventually diagnosed with AML-MRC according to WHO 2022 criteria, their 2-year OS rate were worse than 233 non-AML-MRC children ((60.8±11.1)% vs. (94.5±1.6)%, χ2=24.49,P<0.001), and there was no statistically significant difference in EFS rate between two groups at 2 years ((55.1±10.8)% vs. (70.1±3.2)%, χ2=2.44, P=0.119). Conclusions: Compared with the 2022 WHO diagnostic criteria, the survival rates of children with AML-MRC under the 2016 WHO diagnostic criteria were worse than that of children without MRC.The new version of the AML-MRC diagnostic criteria emphasizes the importance of genes.

Nine-Gene Prognostic Signature for Myelodysplastic Syndrome

Abstract Introduction/Objective Myelodysplastic Syndrome (MDS) is a family of clonal hematopoietic malignancies found frequently in the seventh and eight decades, supporting that aging and acquired somatic mutations drive development of the disease. Without a cure, the prognosis is poor. Patient consideration for bone marrow transplantation remains low (&amp;lt;5%), and enrollment in clinical trials is slightly better (25%). Information regarding MDS-specific whole genome sequencing, a prognostic prediction system, and overall survival is limited and may be beneficial in developing curative therapies. Hence, we aimed to analyze the genomic profile, epidemiology, and overall survival of MDS. Methods/Case Report We utilized cBioPortal cancer genomics [The Cancer Genome Atlas (TCGA) PanCancer Atlas, TCGA Firehose Legacy, and TCGA Nature 2013] to study the mutations associated with MDS. Epidemiological characteristics and genetic profiles available on cBioportal were evaluated. Gene mutations with the most statistically significant, shortest overall survival and survival in days were used for the gene query, and survival rate with the common mutations was calculated. Logrank test and Kaplan–Meier estimators were used in analyzing the survival function. Patients with two or more overlapping mutations were excluded. Results (if a Case Study enter NA) We identified 7,554 patients with MDS out of which 2,852 had a primary MDS. There were 3,323 patients who had gender and age data available. 26.5% were male, and most patients (600) were between the ages of 70-75 years. 1573 (20.8%) were alive and 1600 (21.2%) were deceased. The common mutations associated with reduced survival were ASXL1, NPM1, FLT3, TET2, SF3B1, SRSF2, STAG2, RUNX1, TP53. Median survival of patients with these mutations was 32.02, 27.32, 25.97, 64.21, 80.94, 46.82, 44.28, 16.21, and 10.52 months respectively in comparison with the unaltered mutation group (68.68) (p &amp;lt; 0.0001). Survival was lowest amongst TP53 10.52 months and RUNX1 16.21 months. Leukemia free survival with ASXL1, NPM1, FLT3, TET2, SF3B1, SRSF2, STAG2, RUNX1, and TP53 mutations was 27.88, 13.02, 23.44, 56.52, 79.96, 37.32, 24.89, 14.86, and 9.44 months respectfully in comparison to the unaltered mutation group (68.68) (p &amp;lt; 0.0001). Conclusion Our study found that TP53 and RUNX1 genes were associated with the worst prognosis in MDS with median survival of 10.52 and 16.21 months, respectively. This study may provide insight for genetic predictors and targeted therapies for MDS, as well as provide better understanding of patient prognosis.

Subunit-Specific Analysis of Cohesin-Mutant Myeloid Malignancies Reveals Distinct Ontogeny and Outcomes

Introduction:Loss of function mutations in the cohesin complex ring components and modulators STAG2, RAD21, SMC1A, SMC3, and PDS5B are recurrent genetic drivers in myelodysplastic syndromes (MDS), acute myeloid leukemia (AML), and MDS/myeloproliferative neoplasm (MPN) overlap syndromes. However, whether different cohesin subunit mutations share disease characteristics and prognostic impact is not well understood. Methods: We assembled a cohort of 4,439 patients with hematologic neoplasms at the Dana-Farber Cancer Institute (DFCI) and the Munich Leukemia Laboratory (MLL), and identified a subset of 790 cohesin-mutant patients, the largest cohesin-mutant cohort to date. We performed a retrospective analysis of the incidence, clinical presentation, genomic landscape, and clinical outcomes in a cohesin subunit-specific way. Results: STAG2 mutations were most common and present in 610 cases (diagnosed as MDS (50%), AML (36%), MDS/MPN (10%)), followed by RAD21 in 104 (20% MDS, 64% AML, 2% MDS/MPN), SMC3 in 26 (35% MDS, 42% AML, no MDS/MPN), SMC1A in 22 (27% MDS, 55% AML, 5% MDS/MPN), PDS5B in 16 (13% MDS, 38% AML and 6% MDS/MPN), and 12 cases with more than one mutated cohesin gene (50% MDS, 33% AML, 8% MDS/MPN). Within the DFCI cohort, 256 (82%) patients were diagnosed with a myeloid malignancy and 55 (18%) patients with a non-myeloid hematologic malignancy. We focused our subsequent analysis on 735 patients diagnosed with MDS, MDS/MPN or AML, and compared them to 3,649 cohesin-wildtype (WT) patients in the DFCI and MLL cohorts. We found that STAG2 mutations were acquired at the MDS stage and were associated with MDS with increased blasts (75% cases with MDS-IB1 or IB2) and secondary AML. We also noted their co-occurrence with secondary AML-type mutations, such as ASXL1 (64%, OR=5.5, FDR=5e-29), SRSF2 (45%, OR=7.4, FDR=5-e31) and RUNX1 (37%, OR=3.5, FDR=2e-13), and trisomy 8 (OR=10.6, FDR= 2.2e-50). In contrast, mutations in RAD21, SMC1A, SMC3 and PDS5B shared features with de novo AML, including co-occurrence with NPM1 (32%, OR 4.3, FDR=1e-6) and FLT3 (23%, OR= 2.8, FDR= 0.01), and association of RAD21 and SMC1A with t(8;21) AML (OR= 131;134; FDR= 3.8e-5;4.1e-19). Of note, both STAG2 and RAD21 mutations shared a mutational exclusivity with TP53 mutations (OR=0.04-0.06, FDR &amp;lt; 0.001, Figure 1A). We next assessed the impact of different cohesin mutations on clinical outcomes. We conducted independent analyses of overall survival (OS) and progression free survival (PFS) in MDS and AML. Given our observations that cohesin mutations were mutually exclusive with TP53 mutations, and the established prognostic impact of TP53 mutations, we compared the overall survival (OS) and AML-free survival (PFS) of patients with STAG2-mutant MDS (n=119) to TP53-mutant MDS (n=280) and cohesin/ TP53-WT MDS (n=1,023). With a median follow-up (FU) of 51.1 months we observed a significantly worse OS of STAG2-mutant MDS compared to cohesin and TP53-WT MDS (HR 1.44, CI= 1.10-1.89, p=0.007) and a similar risk of leukemic transformation as TP53-mutant MDS cases (median AML-PFS of 15.4 months for STAG2, and 12.1 months for TP53, p=0.3). Furthermore, STAG2-mutant AML (n=148) had significantly worse OS than AML without myelodysplasia related changes (MR) (n=1384) (HR= 0.62, 95% CI=0.5-0.76, p&amp;lt;0.001, median FU 42.8 months), and similar outcomes as AML-MR without TP53 mutations (n=567), (HR=1.25, 95% CI= 1.01-1.55, p=0.04). Importantly, this pattern was distinct from outcomes of RAD21-mutant AML (n=39), which was almost identical to AML-non-MR and significantly better than STAG2-mutant AML OS (HR= 0.56, 95% CI= 0.34-0.93, p=0.024) ( Figure 1B). The effects of STAG2 and RAD21 mutations on OS remained significant when censored for allogeneic stem cell transplantation. Our findings suggest that only STAG2 mutations confer a negative impact on MDS and AML, and this is attributed to secondary ontogeny. Conclusions: In summary, our study establishes a role for different cohesin subunit mutations in distinct subtypes of MDS and AML, which has significant prognostic implications and expands our current understanding of this important group of driver genes. The findings from our subunit-specific analysis demonstrate that while STAG2 mutations are characterized by secondary AML ontogeny arising from MDS and associated with a worse prognosis, RAD21 mutations are associated with de novo AML and better survival.

Stag2-Cohesin Loss Attenuates Flt3 ITD Myeloid Blast Expansion Yet Preserves Mutant HSC

FLT3 is mutated through an internal tandem duplication (ITD) in 20-25% of acute myeloid leukemia (AML), driving aberrant STAT5/AKT signaling and leukemogenesis. Murine modelling of ITD showed marked myeloid progenitor expansion and hematopoietic stem cell (HSC) exhaustion in various co-mutant settings. Here we present a Stag2 Δ Flt3 ITD model with stark reversal of these two aforementioned features. STAG2, a cohesin complex member, maintains the integrity of the 3D genome partitioning structure known as topologically structural domains. Loss of Stag2 impairs the access and engagement of key hematopoietic transcription factors such as PU.1 to their target genes. sAML is diagnosed when patients present leukemia with known history of hematological malignancies or chemotherapy/radiotherapy treatment. Comparing to de novo AML, sAML often arises in older patients and harbors a poor prognosis with a 5-year overall survival rate of &amp;lt;30%. Advances in genomic studies found various epigenetic mutations, such as STAG2, are often associated with sAML and AML-myelodysplastic related changes (MRC) subtype. STAG2 mutations are found in 14-20% of sAML cases and is suggested to reside within a dominant clone during the pre-leukemia phase, MDS to sAML transformation, such as with FLT3 ITD acquisition and persists during remission. To understand the mechanistic contribution of STAG2-cohesin loss with FLT3 ITD, we generated sequential mutagenesis murine models where the order of Stag2 and Flt3 ITD mutation is set as either ITD 1st Stag2 2nd ( de novo like) or Stag2 1stITD 2nd (sAML like) using tamoxifen-inducible Cre/Flpo recombinase or pIpC-inducible Mx1Cre. In the de novo like model, ITD is constitutively active then Stag2 is deleted when mice reach 6-8 weeks of age. Surprisingly, loss of Stag2 attenuates LSK to MP transition at 4 weeks post deletion, while MPP3 remains elevated, suggesting aberrant remodeling of myeloid differentiation. In the sAML like model, Stag2 is deleted via Mx1Cre and waited for 4 months to mimic the MDS phase, which is then followed by activation of ITD mutation via Flpo, which represents the MDS to sAML transformation. After activating both mutations, mice were followed for another 4 months before analyzing the hematopoietic stem and progenitor compartment. In contrast to the de novo like model, sequential Stag2 1stITD 2nd preserves the HSC population defined by either immunophenotyping or transcriptome via scRNAseq ( Figure 1). The mutant HSC is more quiescent but retains the capacity to reconstitute lethally irradiated recipients in the short term. Similar to the de novo like model, sequential Stag2 1stITD 2nd mice also exhibits a blocked myeloid differentiation. Comparing to ITD mutant, Stag2 1stITD 2nd LSK cells have decreased expression of Socs2 and Cish. While functionally determining the role of mutant HSC, we are performing RNA-seq during at early timepoints post ITD activation to determine how preceding Stag2 mutation could have altered the stem cell fate decision. Targeted therapy with inhibitors of FLT3 have had an overall survival benefit in FLT3-mutant AML, though the magnitude of effect has been modest. STAG2 mutations are more likely to be identified in poor responders to FLT3 inhibition as both reported by us with Pexidartinib treatment, as well as in the setting of Crenolanib treatment where expansion of the STAG2-mutant clone was observed during treatment. Thus, remodeling of the chromatin landscape though altered CTCF binding or cohesin function might impact leukemia identity in FLT3-mutant AML. Our data highlights an important regulatory role of Stag2-cohesin in Flt3 ITD mediated leukemogenesis, while generating a model that mimics the genetic evolution of sAML. This model will not only shed light on the sAML pathogenesis but also with creates a pre-clinical testing platform with potential therapeutic relevance.

A Large Cohort Study of 412 Patients with SRSF2/TET2 Co-Mutated Myeloid Neoplasms: The Molecular Landscape and Clinical Outcomes

Introduction: Serine and arginine-rich splicing factor 2 ( SRSF2) and tet methylcytosine dioxygenase 2 ( TET2) are early mutations that drive the development of myeloid neoplasms and monocytosis. SRSF2/ TET2 co-mutations are most common in chronic myelomonocytic leukemia (CMML). However, they can also be seen in myelodysplastic syndrome (MDS), acute myeloid leukemia from CMML (AML-CMML), other AML (AML-Other, mostly de novo AML), and myeloproliferative neoplasms (MPN). Previous studies have investigated these co-mutations in myeloid diseases separately and as a subset (CMML) or small subset (MDS or AML) of the patients. Additionally, these studies mainly compared the clinical difference between patients with and without these double mutations. A large cohort study of patients with both mutations, irrespective of the morphologic diagnosis, has not been reported. Methods: Out of the Moffitt NextGen sequencing database of more than 8000 patients, we identified 412 patients with both SRSF2 and TET2 mutations and with diagnosed or suspected myeloid neoplasms. The demographics and clinical parameters were collected. Overall survival (OS) was defined as the time from sequencing to the last visit at Moffitt or death. Two experienced hematopathologists confirmed the final diagnosis according to the 5 th edition of the World Health Organization classification of hematological malignancies. Chi-squared tests of independence were used to compare the association between gene mutation and diagnosis, and a post hoc test based on adjusted standardized residuals was used. Cox proportional hazards models were used to compare the OS within and across diagnoses and included gender, age, gene mutation, and diagnosis (when comparing across diagnoses) as covariates. Results: Of the 412 patients, 284 (69%) were male, 128 (31%) were female, and the average age was 75 years. The five most common diagnoses, in descending order, were CMML (41%), AML-Others (23%), MDS (12%), AML-CMML (9%), and MPN (6%). The ten most common additional mutated genes, in descending order, were ASXL1 (44%), RUNX1 (28%), CUX1 (13%), JAK2 (13%), CBL (11%), TP53 (10%), SETBP1 (9%), KRAS (9%), STAG2 (9%), and NRAS (9%). A comparison of the top 5 diagnoses and the top 10 additional gene mutations showed an association between diagnosis and gene mutation (chi2 = 131, 36 df, p=.000). A post hoc test showed CBL mutations were less frequent in patients with AML-Others (p=.029), STAG2 mutations were less common in CMML patients (p=.007), and STAG2 mutations were more frequent in patients with MDS (p=.000). Among all patients, RUNX1 mutation (HR=2.4, 95% CI [1.3, 4.4], p=.005), ASXL1 mutation (HR=2.3, 95% CI [1.3, 4.2], p=.005), and CBL mutation (HR=2.0, 95% CI [1.0, 3.8], p=.048) were associated with lower OS. Among patients diagnosed with CMML, KRAS mutation (HR=4.1, 95% CI [1.5, 11.3], p=.006) and ASXL1 mutation (HR=3.3, 95% CI [1.4, 8.3], p=.009]) were associated with lower OS. Among patients with low-grade myeloid diseases (CMML and MDS), ASXL1 mutation (HR=2.6, 95% CI [1.2, 5.9], p=.021) was associated with lower OS. For the five most frequently co-mutated genes ( ASXL1, RUNX1, CUX1, JAK2, and CBL), no difference in OS was found between patients with CMML vs MDS, or AML-CMML vs AML-Others. Conclusions: SRSF2 and TET2 co-mutations occurred in various myeloid diseases, including CMML, AML transformed from CMML, other types of AML, MDS, and MPN. RUNX1, ASXL1, and CBL, were commonly mutated and associated with lower OS compared to patients with only SRSF2 and TET2 mutations. When comparing OS for patients diagnosed with low-grade diseases (CMML or MDS), ASXL1 mutation was associated with an increased risk of death. No difference in OS was found between CMML vs MDS, or AML-CMML vs AML-Others when co-mutation with ASXL1, RUNX1, CUX1, JAK2, or CBL was present.

Genetic Evolution from Chronic Myeloproliferative Neoplasms to Acute Myeloid Leukemia: An Analysis of Forty-Six Paired Samples

Background: Secondary acute myeloid leukemia (sAML) may arise from chronic myeloproliferative neoplasm (MPN). The genetic evolution pattern may be understood by paired sample analysis. Knowledge of genetic change in MPN/sAML is still limited and more extensive studies should be done. Patients and Methods: Forty-six paired samples (27 males) at diagnosis of MPN (12 polycythemia vera, 6 essential thrombocythemia, 25 primary myelofibrosis and 3 MPN-unclassified) and sAML transformation were available. Mutational analyses of 27 genes ( JAK2V617F, CALR, MPL, ASXL1, IDH1, IDH2, TET2, DNMT3A, EZH2, SRSF2, U2AF1, SF3B1, ZRSR2, SMC1, STAG2, SMC3, RUNX1, SETBP1, IKZF1, WT1, K-RAS, N-RAS, C-CBL, TP53, RAD21, BCOR and BCORL1) were performed. Mutations and their variant allele frequencies (VAF) were measured by next generation sequencing. Results: At baseline (MPN), the mutation number was 2 (maximal 5). Forty-five samples harbored driver gene mutations (31 JAK2V617F, 13 CALR and 1 MPL). Twenty-eight samples harbored at least one epigenetic regulator mutations (11 TET2, 8 DNMT3A,7 ASXL1, 5 EZH2, 2 IDH2, 1 IDH1). Twelve samples harbored spliceosome mutations which were mutually exclusive (6 SRSF2, 3 SF3B1, 2 U2AF1 1 ZRSR2). Other mutations were RUNX1, BCORL1 (n=2 each), CBL and BCOR (n=1 each). In sAML, the median mutation number was 3 (maximal 7). Loss of mutation was found for JAK2V617F (9/31), TET2 (1/11) and SRSF2 (1/6). Acquisition was most common for RUNX1 (n=9), followed by TP53, ASXL1 (n=5 each), K-RAS (n=4) , ZRSR2, STAG2 (n=3 each). The median number of acquired mutation was 1 (maximal 5). The frequencies of gene mutations are summarized in Figure 1A. The baseline VAF of JAK2V617F was high (&amp;gt;35%) in 80.6% (25/31). In progression to sAML, VAF was constant in 29.0% (9/31, VAF changes &amp;lt;10%), increased in 20.0% (9/31, increased VAF&amp;gt; 10%), decreased in 41.9% (13/31, decreased VAF&amp;gt;10%) (Figure 1B). The baseline VAF in CALR mutation was high (&amp;gt;35%) in 91.3% (12/13). VAF remained stable in 76.9% (10/13), and loss of CALR mutation was not observed (Figure 1B). TET2 mutations tended to be stable (7/16), but clonal expansion (5/16 of all mutation events at MPN), or acquisition (n=2) could be found during transformation to sAML. DNMT3A mutations remained stable (5/8), exhibited clonal expansion (2/8), or acquisition (n=1) in sAML progression. ASXL1 mutations remained stable (6/7), with clonal expansion (1/7), or acquisition (n=5) during MPN/sAML progression. All EZH2 mutants had clonal expansion (5/5) and one acquired in sAML (Figure 1B). We found that CALR mutationwas often the founding clone with high VAF at MPN phase, stable clone during sAML, and might acquire mutations in signaling pathways (1 CBL, 1 KRAS), epigenetic regulators (2 ASXL1, 1 IDH2), transcription factors (2 RUNX1, 1 BCOR), spliceosome (2 ZRSR2, 1 SF3B1), and cohesin complex (1 STAG2). JAK2 mutationwas often preceded by other ancestral mutations such as TET2, ASXL1, DNMT3A, EZH2, IDH2, SRSF2 or ZRSR2. During evolution, leukemia arose from non- JAK2 mutated clones with mutations in EZH2, DNMT3A, RUNX1, EZH2, SETBP1, or acquisition of TP53, SF3B1, BCOR and STAG2 mutations) in sAML. In outcome, the median time from MPN to sAML was 82 (range 3.7 to 338.5) months. Female gender, loss of JAK2V617F, presence of U2AF1 and absence of IDH1 were associated with shorter time to sAML transformation. No other genetic mutation in our gene panel or the number of mutations harbored by patients in our cohort had significant impact on time to sAML. Marked increase of VAF was observed for JAK2 (7/22) , DNMT3A (1/7) , IDH1 (2/3), IDH2 (1/3), TET2 (3/10) , EZH2 (4/5), C-CBL (1/1) and SRSF2 (1/4). Marked decrease of VAF was observed for JAK2 (4/22), MPL (1/1), DNMT3A (1/7) , ASXL1 (1/8), SF3B1 (2/3), SRSF2 (1/4) and U2AF1 (1/2). Multiple mutational clones were detected for TET2 (two clones in 4 samples and 3 clones in 1). Clonal expansion and reduction were observed in two pairs of samples upon sAML transformation. Conclusions: At the MPN stage, most patients had driver mutations with frequent co-mutations of epigenetic modifier or spliceosome genes. CALR mutant clones were stable while for JAK2, sAML often arose from clones without JAK2V617F which acquired RUNX1, TP53, ASXL1 and K-RAS. Research funding:Ministryof Science and Technology Council,Taiwan (NSTC 112-2314-B-182-055) and Ministry of Health and Welfare, Taiwan (112-TDU-B-222-124001)

What Is the Optimal Treatment Modality in Molecularly Defined Secondary AML? a Multicenter Cohort Study

Introduction Secondary ontogeny acute myeloid leukemia (AML), defined by the presence of mutations in ASXL1, BCOR, EZH2, SF2B1, SRSF2, STAG2, U2AF1 or ZRSR2 was recently integrated into both the ICC and WHO diagnostic criteria, as well as into the ELN 2022 risk classification as adverse risk. However, it is unknown whether cytarabine + anthracycline (7+3), liposomal cytarabine and daunorubicin (CPX-351) or hypomethylating agent + venetoclax (HMA+VEN) is the optimal frontline treatment for these patients (pts). We performed the largest multicenter retrospective cohort study to date, dedicated to pts with molecular-defined secondary ontogeny AML, comparing treatment modalities and assessing the impact of clinical and molecular characteristics on response and survival. Methods We included pts with newly diagnosed (ND) AML who were treated at 4 large academical centers with 7+3, CPX-351 or HMA+VEN. Secondary ontogeny was defined as absence of TP53 mutation and presence of at least one of the aforementioned mutations. Composite complete response (cCR) was defined as complete response (CR) + CR with incomplete count recovery (CRi). Logistic regression was fitted to evaluate odds ratio (OR) for cCR. Overall survival (OS) was compared between groups by log-rank test. COX regression for OS were fitted to evaluate effect of secondary/co-mutations within each treatment group, as well as the effect of treatment and allogeneic stem cell transplantation (SCT) as a time-varying covariate. Results Out of 1132 ND AML pts in the entire cohort, 401 (35%) were molecularly defined as secondary ontogeny and included in the final analysis. Initial treatment was 7+3 in 173 (43%), HMA+VEN in 162 (40%) and CPX-351 in 66 pts (17%). Pts in the HMA+VEN group were older (median age 74 years[yrs]; CPX351 66 yrs; 7+3 63 yrs, p&amp;lt;0.001), while pts in the CPX351 group were more likely to have prior myeloid neoplasm (n=52 [79%]; HMA+VEN n=72 [44%]; 7+3 n=48 [28%], p&amp;lt;0.001) and prior HMA exposure (n=27 [41%]; HMA+VEN n=23 [14%]; 7+3 n=28 [16%], p&amp;lt;0.001). The cCR rates were 56% (97/173), 56% (90/162) and 44% (29/66) in 7+3, HMA+VEN and CPX-351, respectively (p=0.21). In the 7+3 group, the presence of RUNX1 co-mutation was associated with lower cCR rate (OR 0.8, 95% confidence interval [CI] 0.7-0.95, p=0.01), while PTPN11 was associated with higher cCR rate (OR 1.4, 95% CI 1.1-1.8, p=0.011). In the HMA+VEN group, monosomal karyotype (OR 0.7, 95% CI 0.5-0.9, p=0.002), NRAS co-mutation (OR 0.6, 95% CI 0.5-0.8, p&amp;lt;.001) and SF3B1 mutation (OR 0.76, 95% CI 0.6-0.9, p=0.008) were associated with lower cCR rate and FLT3-TKD with higher cCR rate (OR 1.5, 95% CI 1.1-2.1, p=0.01). In the CPX-351 group, NRAS co-mutation was associated with lower cCR rate (OR 0.65, 95% CI 0.5-0.9, p=0.005). As most younger pts (aged ≤ 60 yrs, n=85) were treated with 7+3 (n=64) or CPX-351 (n=13) and almost exclusively older pts (age &amp;gt;75, n=78) were treated with HMA+VEN (n=74), we performed age-group based analyses. In pts aged &amp;gt; 60 yrs (n=318), the median OS (mOS) was comparable between groups (7+3: 16 months [mo], 95% CI 13-27; HMA+VEN 15 mo, 95% CI 13-19; CPX-351 11 mo, 95% CI 9-28 p=0.57). Similar results were seen in pts 60-75 yrs (n=238): 7+3 mOS 16 mo, 95% CI 13-27; HMA+VEN mOS 16 mo, 95% CI 13-26; CPX-351 mOS 10 mo, 95% CI 8-28, p=0.74. The effect of secondary/co-mutations on survival differ between groups: For 7+3 splicing mutations were associated with worse OS, whereas IDH1/2 were associated with improved OS ( Figure). Conversely, in HMA+VEN and CPX351 groups K/NRAS co-mutations were associated with worse survival. NPM1 co-mutation did not affect survival in any treatment group. In multivariable analysis, age, prior myeloid disease, K/NRAS co-mutations and monosomal karyotype were associated with worse OS ( Table). Conversely, BCOR mutation, IDH1/2 co-mutation and SCT were associated with improved OS. Treatment with HMA+VEN or CPX351 were not statistically different vs 7+3, although there was a trend for better OS with HMA+VEN vs 7+3 (HR 0.68, 95% CI 0.44-1.03, p=0.069). Conclusion In pts with ND secondary ontogeny AML the OS with HMA+VEN was at least comparable to 7+3 or CPX351 when adjusted for multiple covariates. The effect of co-mutations on response and OS differed between treatment modalities and may aid in optimal treatment selection in this population. Prospective trials should evaluate the potential superiority of HMA+VEN and effect of co-mutations in secondary ontogeny AML.

Pre-Transplant Somatic Co-Occurring Mutations (by next generation sequencing) in Acute Myeloid Leukemia: Frequency and Impact on Clinical Outcomes after Allogeneic Hematopoietic Cell Transplantation - a Large Study on Behalf of the EBMT Acute Leukemia Working Party

Background: Acute myeloid leukemia (AML) is a very heterogeneous hematological malignancy, which includes numerous genetically defined subsets. The genomic classification of AML with the identification of mutations in transcription factors, epigenetic modifiers, spliceosome, cohesin complex, and signaling pathways has led to a more accurate risk stratification model. The main genetic aberrations included in the European LeukemiaNet (ELN) 2022 classification are NPM1 (risk group according to karyotype and FLT3-ITD status), FLT3-ITD (intermediate risk), bZIP in-frame mutated CEBPA (favorable risk), and RUNX1, ASXL1, BCOR, EZH2, RUNX1, SF3B1, SRSF2, STAG2, U2AF1, ZRSR2 and TP53 mutations (all belonging to the adverse risk group). In the context of allogeneic hematopoietic stem cell transplantation (allo-HSCT), the frequency and prognostic value of different gene-gene interactions has not been studied and may differ from that of patients treated with chemotherapy alone. We aimed at evaluating, through the European Society for Blood and Marrow Transplantation (EBMT) database, the frequency and impact of different recurrent somatic mutations, either alone or in association, on prediction of relapse and survival in patients receiving allo-HSCT. Methods: This is a retrospective, registry-based, multicenter analysis from the EBMT with the approval of the EBMT Acute Leukemia Working Party. Adult patients aged more than 18 years with a diagnosis ofAML who received an allo-HSCT between 2013-2022, with an available genetic profile determined at diagnosis by next generation sequencing (NGS) were included. Results: We identified 836 allografted AML patients who had NGS performed at diagnosis. Most of these patients had de novo AML (88%), with a median age of 53 years (range: 18-78 years). Karyotype was favorable in 7%, intermediate in 69% and adverse in 24% of patients. At transplant, 74% of patients were in first remission (CR1) and 13% in CR2. The most frequent detectable mutations by frequency were DNMT3A (33%), FLT3 (29%), NPM1 (29%), TET2 (28%), NRAS (23%), RUNX1 (22%), WT1 (22%), BCOR (19%), ASXL1 (17%), IDH2 (17%), IDH1 (15%), SRSF2 (13%), STAG2 (12%), CEBPA (11%), TP53 (10%), KRAS (10%), and PTPN11 (10%) . By multiple correspondence analysis, two independent groups of co-occurring mutations were identified, the first group included DNMT3A, NPM1 and FLT3, the second group included ASXL1, SRSF2 and RUNX1. Outcome analysis was performed on the subset of 298 patients allografted in CR1 with available data for the aforementioned six genes ( DNMT3A, NPM1, FLT3, ASXL1, SRSF2 and RUNX1). Most of these patients had de novo AML (90%), with a median age of 53 years (range: 19-75 years). Patients received primarily reduced intensity conditioning (58%) and peripheral blood stem cells (93%) from matched sibling donors (35%), matched unrelated (28%), and haploidentical donors (21%). Seventy percent of these patients had intermediate-risk cytogenetics, while 27% were classified as adverse-risk. Median follow up calculated by the reverse Kaplan-Meier method was 2.5 years. Overall, the 2-year relapse incidence (RI), leukemia-free survival (LFS) and overall survival (OS) were 24%, 62% and 69%, respectively. When outcome analysis was performed according to the presence or absence of single mutations, none of the six mutations significantly affected RI or LFS. The 2-year OS was positively affected by the presence of NPM1 mutation (78% vs 66%; p=0.02) and FLT3 (79% vs 65%, p=0.01) but not significantly affected by the other 4 mutations. When mutations were investigated in groups, the 2-year RI, LFS and OS were 24%, 70% and 78%, respectively, for patients with NPM1 mutation regardless of other co-mutations, 35%, 56% and 69% for patients with FLT3-ITDand/or DNMT3A mutation, wild type NPM1, regardless of other co-mutations, 17%, 70% and 74% for patients with RUNX1 and/or ASXL1 and/or SRSF2 mutation without FLT3-ITD and with wild type NPM1 and wild type DNMT3A and 20%, 56% and 61% for patients with all six genes unmutated. Conclusion: NGS at diagnosis can be extremely useful in risk stratification of AML patients undergoing allo-HSCT, potentially allowing adequate post-transplant interventions. Notably, the 2-year LFS of 70% for patients harboring RUNX1 and/or ASXL1 and/or SRSF2 mutation indicates that allo-HSCT can overcome the adverse risk associated with these somatic mutations at diagnosis.

NGS Profile and the Mathematical Prediction Model for Venetoclax Combination Therapy in HM-Screen-Japan 02 Study

[Introduction] Azacitidine and venetoclax combination therapy (Aza/Ven) is a novel strategy for acute myeloid leukemia (AML). Although this regimen is widely used as a first line treatment not only for unfit/elderly patients but also for fit/young patients in the real-world situation, appropriate patient selection is an important issue. HM-SCREEN-Japan 02 (UMIN-CTR UMIN000046371) is a Japanese multicenter prospective observational study to evaluate the clinical utility of targeted sequencing. In this study, we performed the sub-analysis of newly diagnosed AML patients who received Aza/Ven as a 1 st line treatment to elucidate the genetic background of AML. Furthermore, we proposed a novel mathematical model to predict the response of Aza/Ven. [Methods] AmoyDx® Myeloid Blood Cancer Panel for acute myeloid leukemia was used for the targeted sequencing. We performed linear discriminant analysis to predict complete response patients by Aza/Ven based on clinical information before treatment. We utilized three clinical quantities for the analysis: Wilms Tumor-1 (WT1) mRNA expression level, the number of “favorable mutations”, and that of “unfavorable mutations”. Favorable and unfavorable mutations were defined as IDH1, IDH2, NPM1, and CEBPA mutations, and ASXL1, BCOR, EZH2, RUNX1, SF3B1, SRSF2, STAG2, U2AF1, ZRSR2 and TP53 mutations, respectively, based on the previous reports (NEJM 2019, Blood 2022). The data were standardized and utilized for the linear discriminant analysis. Statistical analyses were performed using R version 4.2.3 software (R Foundation for Statistical Computation, Vienna, Austria). [Results] Total 158 patients were enrolled in our study. Among 48 patients who received Aza/Ven as a 1 st line therapy, NGS analyses were performed prior to treatment in 38 patients. Their median age was 70.5 (39-92) years old. AML with myelodysplasia-related changes was the major subtype (71%) and 37 percent of the cases had high risk cytogenetic abnormalities at diagnosis. After 1 st line Aza/Ven treatment, complete remission (CR)/ CR with incomplete blood count recovery (CRi) was achieved in 63% of the cases while the remaining 37% were non-CR. There was a trend that patients with NPM1 and IDH1/2 mutations achieved CR/CRi, while patients with RUNX1 mutation were not tended to achieve CR (Figure 1). Next, we performed linear discriminant analysis of treatment response using three pretreatment clinical factors. Linear discriminant analysis found a linear combination of prognostic factors that best separates two classes in the group of patients. Thirty-seven patients were employed to determine the discriminant function D, given by D = 0.638 × x − 0.76 × y + 0.68 × z + 0.145. Here x, y, and z represented the WT1 quantity in peripheral blood, the number of “favorable mutations”, and that of “unfavorable mutations” after standardization, respectively. Using this model, 81.1% of cases were correctly classified, and so were 75.7% of cases with leave-one-out cross validation method (Table 1). [Discussions] As previously reported (NEJM 2019, Blood adv 2020), IDH1/2 and NPM1 mutations tended to be sensitive to Aza/Ven in our cohort. However, it would be hard to predict the response of Aza/Ven by a single gene mutation because multiple gene mutations were co-existed in most of the cases (Figure 1) and clinical factors including tumor markers might also affect the outcome. Our mathematical model, involving gene mutations and WT1, could efficiently predict the response of Aza/Ven, which may support the selection of 1 st line treatment. In conclusion, our study revealed the genetic landscape of real-world Aza/Ven therapy and provided a potential prognostic model.