Articles de revues sur le sujet « CML, NGS, aCML, SETBP1 »

Abstract Atypical Chronic Myeloid Leukemia (aCML) is a clonal disorder belonging to the myelodisplastic-myeloproliferative neoplasms, according to the WHO-2008 classification. From a clinical point of view it closely resembles the classical Chronic Myeloid Leukemia (CML), however it lacks the presence of the Philadelphia chromosome and of the BCR-ABL1 fusion gene. In recent works, we and others characterized the somatic lesions present in the aCML genome, mainly by using Next Generation Sequencing (NGS) technologies, demonstrating the presence of a large set of recurrent somatic mutations involving, among the others, SETBP1, ETNK1, ASXL1, EZH2, CBL, TET2, NRAS and U2AF1 genes. The identification of somatic variants occurring in a large number of genes clearly indicates that the genetic bases of aCML are very heterogeneous, in striking contrast with classical CML. This heterogeneity poses a great challenge to the dissection of the molecular steps required for aCML leukemogenesis. The hierarchical reconstruction of the different mutations occurring in a clonal disorder can have important biological, prognostic and therapeutic repercussions; therefore we started a project focused on the dissection of the aCML clonal evolution steps through the analysis of individual leukemic clones by methylcellulose assays in samples whose mutational status has been previously characterized by matched whole-exome sequencing. Patient CMLPh-019 was characterized by the presence of a complex mutational status, with somatic variants occurring in SETBP1, ETNK1, ASXL1 and CBL genes (Fig. 1a). Targeted resequencing analysis of individual clones revealed the presence of all the 4 variants in 44/60 (73.3%) clones; in 15/60 (25%) we detected the presence of mutated ETNK1, ASXL1 and CBL and wild-type (WT) SETBP1. Of these 15 clones, 33% carried heterozygous and 67% homozygous CBL mutations. In one clone (1.7%) we detected heterozygous ETNK1, homozygous CBL and WT sequences for ASXL1 and SETBP1, suggesting a strong selective pressure towards the acquisition of homozygous CBL mutations. Identification of homozygous CBL mutations in all the main clonal phases suggests that a significant positive selective pressure is associated with this event. Allelic imbalance analysis of CMLPh-019 exome using CEQer revealed that CBL homozygosity is caused by a somatic uniparental disomy event occurring in the telomeric region of the long arm of chromosome 11. Patient CMLPh-005 (Fig. 1b) was mutated in ASXL1, CBL and SETBP1. Targeted analysis done on 68 clones revealed a complex, branching evolution, with 63 clones carrying all the 3 variants. Of them, 47 (74.6%) had a heterozygous and 16 (25.4%) a homozygous CBL variant. Four clones (4.2%) carried ASXL1 and SETBP1 but not CBL mutations, while 1 clone was mutated in ASXL1 and CBL in absence of SETBP1 mutations, which suggests that CBL mutations occurred independently in two different subclones. Also in this case, allelic imbalance analysis of exome data revealed that CBL homozygosity was caused by a telomeric somatic uniparental disomy event. According to exome sequencing, patient CMLPh-003 carried SETBP1 mutation G870S and NRAS variant G12R. Clonal analysis confirmed the presence of SETBP1 G870S in all the clones analyzed, while heterozygous NRAS G12R mutation was detected in 67% (Fig. 1c). Notably in the remaining 33% another heterozygous NRAS variant, G12D, was detected. Retrospective reanalysis of exome data confirmed the presence of the newly identified variant, which had been previously filtered-out from exome data because of the low frequency. Patient CMLPh-013 was mutated in ASXL1, ETNK1, NRAS and SETBP1. Of the 39 clones analyzed, 34 (82.9%) showed the coexistence of ASXL1, ETNK1, NRAS and SETBP1, 4 were mutated in ASXL1, ETNK1 and NRAS and 1 in ETNK1 and NRAS, suggesting that ETNK1 and NRAS were early events, ASXL1 an intermediate one and SETBP1 a late variant (Fig. 1d). Taken globally, these data indicate that ETNK1 variants occur very early in the clonal evolution history of aCML, while ASXL1 represents an early/intermediate event and SETBP1 is often a late event. They also suggest that, in the context of aCML, there is a strong selective pressure towards the accumulation of homozygous CBL variants, as already shown in other leukemias. Figure 1. Clonal analysis of four aCML cases. The asterisks indicate hypothetical clones. Figure 1. Clonal analysis of four aCML cases. The asterisks indicate hypothetical clones. Disclosures Rea: Novartis: Honoraria; Bristol-Myers Squibb: Honoraria; Pfizer: Honoraria; Ariad: Honoraria.

Abstract Introduction: Recently, next-generation sequencing (NGS) has revolutionized the molecular characterization and understanding of several hematologic entities, including myeloproliferative neoplasms (MPN) and myelodysplastic syndrome (MDS)/MPN overlap syndromes. Nevertheless, the frequency and clinical impact of the mutations detected by NGS, remain largely unclear, especially in rare MPN which were analyzed in this study. Methods: Thus, we established a novel amplicon-based NGS panel, comprising genes that are known to be recurrently mutated in MPN and/or MDS/MPN. Hot spot regions or all exons of the following 32 genes were chosen: ABL, ASXL1, BARD, CALR, CBL, CEBPA, CHEK2, CSF3R, DNMT3A, ETNK1, ETV6, EZH2, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NFE2, NRAS, PDGFRA, PTPN11, RUNX1, SETBP1, SF3A1, SF3B1, SH3B2 (LNK), SRSF2, TCF12, TET2, TP53, U2AF1. After establishing this panel, peripheral blood samples of 19 patients, which were diagnosed with CMML(10), aCML(2), MPNu(1), MDS/MPNu or other MPN(6), were analyzed on a MiSeq® illumina sequencer. Variants were only analyzed if the absolute coverage at each SNV site was >50 reads, and the absolute coverage of the mutant allele was 10 or more reads and its relative coverage exceeded 10%. Results: Mean coverage of the run was 1516 reads with good Phred-score quality parameters (>84% of called bases with Q-score >= 30). In 300 bidirectional cycles, a yield of nearly seven gigabases of sequencing data was reached. One out of 19 analyzed patients was excluded from analysis due to insufficient DNA quality. In 89% of the samples(16/18), mutations were detected which had not previously been known to be present in these patients. TET2 (50%, 9/18) and SETBP1 mutations were the most common (44%, 8/18). As expected, TET2 mutations were spread over the entire gene and SETBP1 mutations were restricted to the known hot spot region (exon 4, c.2602-c.2620). Additionally, CSF3R mutations were detected in 22% (4/18) of patients. Epigenetic regulator genes were also affected as EZH2 mutations were detected in 17% (3/18), ASXL1 mutations in 39% (7/18) and IDH1/2 mutations were found in 6% (1/18) of all samples, whereas DNMT3A mutations were not present. Further mutations were found in the following genes: CBL (11%), ETV6 (6%), JAK2V617F (6%), KRAS (11%), NRAS (11%), PTPN11 (6%), SH2B3 (6%) and SRSF2 (11%). Besides previously known mutations, several novel variants could be detected. All but one patient harbored more than one of these mutations. Furthermore, clinical correlates and morphologic and cytogenetic subtypes of each patient were available to associate with the NGS data of individual patients. For example, the one patient with a solitary NRAS c.35G>A (amino acid: p.G12D) mutation showed the most aggressive clinical course in our cohort with transformation to AML only 7 months after first diagnosis of CMML. Moreover, CSF3R mutations have been shown to confer sensitivity to ruxolitinib and may thus open up new avenues of treatment for our patients. Conclusion: In a cohort of unclassified MPN and rare MDS/MPN subtypes, NGS is a powerful tool to characterize samples more extensively. Our data suggests that a more comprehensive understanding of the mutational spectrum may have important clinical impact in individual patients, including diagnosis, prognosis, and more specific treatment. Disclosures Isfort: Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel; Ariad: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel; BMS: Honoraria; Mundipharma: Other: Travel; Amgen: Other: Travel; Hexal: Other: Travel. Brümmendorf:Novartis: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Ariad: Consultancy, Honoraria; Patent on the use of imatinib and hypusination inhibitors: Patents & Royalties. Koschmieder:Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Atypical Chronic Myeloid Leukemia (aCML) is a clonal disorder belonging to the group of myelodysplastic/myeloproliferative (MDS/MPN) syndromes. In aCML many clinical features suggest the diagnosis of CML, however the lack of the BCR-ABL1 fusion point to a different pathogenetic process. Recently, we identified the presence of clonal somatic mutations occurring in the SETBP1 gene in approximately 25% of aCML samples (Piazza R. et al., Nat Genet. 2013 Jan;45(1):18-24). A subsequent study (Maxson J. et al., N Engl J Med. 2013 May 9;368(19):1781-90) demonstrated the presence of somatic mutations of the CSF3R gene in Chronic Neutrophilic Leukemia (CNL) and, with lower frequency, in aCML. In a recent follow-up of the first study (Gotlib J. et al., Blood. 2013 Jul 29), the presence of both CSF3R and SETBP1 variants was tested in a cohort of 9 CNL and 20 aCML cases, demonstrating the presence of CSF3R somatic mutations in 40% of the aCML patients. Of these mutations, 20% were membrane, 5% truncating and 15% compound variants. Interestingly, 5% of the aCML patients showed coexistence of CSF3R and SETBP1 mutations, suggesting that variants occurring in these genes are not mutually exclusive. To gain further insight into the relationship between CSF3R and SETBP1 in aCML, we extended our initial study by analyzing an expanded cohort of 65 aCML plus a total of 230 AML, ALL, CLL, CML, PV, TE, MMM, CMML and MDS cases for the presence of CSF3R and SETBP1 mutations. In line with previous findings (Piazza R. et al., Nat Genet. 2013 Jan;45(1):18-24; Maxson J. et al., N Engl J Med. 2013 May 9;368(19):1781-90), we found evidence of SETBP1 and/or CSF3R mutations only in MDS/MPN disorders. In aCML we identified a total of 18 (27.7%) mutations occurring in SETBP1 and 8 (12.3%) in the CSF3R gene. A large fraction (94.4 %) of the SETBP1 mutations was clustered in a 14 amino acid stretch that is also mutated in the Schinzel-Giedion syndrome, as previously reported (Piazza R. et al., Nat Genet. 2013 Jan;45(1):18-24). Of the 8 CSF3R mutations 5 were membrane proximal (4 T618I and 1 T615A) and 3 were truncating (2 Q776X and 1 Q781X). In 2 aCML samples we detected the coexistence of CSF3R and SETBP1 mutations. In both cases the CSF3R variant was a membrane proximal mutation; CSF3R and SETBP1 mutations were at comparable levels at the time of detection, therefore no conclusion can be drawn about the timing of the two mutational events. Taken globally these data indicate that somatic mutations occurring in SETBP1 and CSF3R are present in aCML and can coexist. Interestingly, the frequency of the CSF3R mutations in our aCML cohort is largely different from that of Maxson and colleagues (12.3 vs 40%), although the frequency of the combined CSF3R/SETBP1 mutations is similar (3.1 vs 5%): the reasons for this discrepancy are actually unclear. Previously we demonstrated that the presence of SETBP1 mutations in aCML is an independent negative prognostic factor (Piazza R. et al., Nat Genet. 2013 Jan;45(1):18-24). Further studies with larger cohorts will be required to assess the prognostic impact of concurrent SETBP1 and CSF3R mutations. Disclosures: Cross: Novartis: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria. Gambacorti-Passerini:Pfizer, BMS: Consultancy, Consultancy Other; Pfizer: Research Funding.

Abstract Introduction Chronic neutrophilic leukemia (CNL) and atypical chronic myeloid leukemia (aCML) are rare myeloproliferative and myelodysplastic/myeloproliferative neoplasms. So far, the diagnosis of CNL and aCML has been based on cytomorphology and the absence of JAK2V617F and PDGFR rearrangements. Recently, mutations in CSF3R and SETBP1 were identified and associated with CNL and aCML, respectively. Chronic myelomonocytic leukemia (CMML) and aCML also share several characteristics and need to be discriminated especially by the absolute number of monocytes in the peripheral blood. Aim To determine the frequency of CSF3R mutations (CSF3Rmut) in CNL, aCML, and CMML and to investigate a mutation pattern, cytogenetics and clinical data in all three entities. Patients and Methods To first delineate patients with potential CNL, we investigated blood and bone marrow smears and depicted patients with a white blood cell count >25x109/L, neutrophils >80%, immature granulocytes <10%, <1% myeloblasts and hypercellular bone marrow (according to WHO 2008). BCR-ABL1 fusion transcript, JAK2 and MPL mutations were excluded in all cases by RT-PCR and melting curve analyses. Indication for PDGFR rearrangements was precluded by over-expression analyses of PDGFRA and PDGFRB by quantitative real-time PCR, resulting in a final cohort of 20 cases declared as CNL patients. Additional 60 aCML and 252 CMML patients were included. Cytogenetics was available in 330/332 cases. Mutations in CSF3R exons 14 and 17 (n=332), in ASXL1 exon 13 (n=321), and the mutational hot spots in SETBP1 (n=331) and SRSF2 (n=320) were analyzed by Sanger sequencing. Results In the total cohort of 332 patients we detected CSF3R mutations in 11 cases (3.3%). 8/11 cases showed a p.Thr618Ile mutation in exon 14, four of them carried an additional nonsense/frame-shift mutation in exon 17. One additional patient was mutated in p.Thr615Ala and showed a nonsense mutation in exon 17. Two cases showed a mutation in exon 17 only, one a nonsense the other a frame-shift mutation, respectively. Analyzing the mutation frequencies within the different entities revealed a clustering of CSF3Rmut within CNL cases with 7 of 20 (35%) mutated cases in contrast to 2 of 60 (3.3%; p=0.001) aCML and 2 of 252 (0.8%; p<0.001) CMML cases. Cytogenetics in CSF3Rmut cases showed that 9/11 cases had a normal karyotype and only one aCML patient harbored a del(3q) and one CMML patient a complex karyotype. Mutations in the three other analyzed genes ASXL1, SETBP1 and SRSF2 were detected in the total cohort in 156/321 (49%), 34/331 (10%), and 149/330 (45%) patients, respectively. Analyses regarding concomitant mutations of CSF3R with ASXL1, SETBP1 or SRSF2 revealed no additional mutation in two cases. In 8 of 11 parallel analyzed CSF3Rmut patients an ASXL1mut was identified, SETBP1 as well as SRSF2 were mutated in 3 of the 11 cases. Notably, the 7 CSF3Rmut within the CNL group had no mutation in SETBP1. Analysis of mutational loads in CNL showed that 6/7 CSF3Rmut had a higher mutational load than the second mutated gene (range: 25-50% vs. 10-30%). In one case both mutated genes had equal mutational loads (40%). In contrast, in CMML and aCML 3/4 patients had lower mutational loads in CSF3Rmut than in the additional mutated genes (20-50% vs. 40-50%), while also one case showed equal mutational loads in the mutated genes (50%). Combining the mutational results of these four genes indicate a specific and individual molecular pattern for these three different entities. While ASXL1 is frequently mutated in all entities (CNL: 8/11 (73%); aCML: 38/59 (64%); CMML: 110/251 (44%)), SRSF2 shows the highest mutation frequency in CMML cases (121/251; 48%), followed by aCML (24/60; 40%) and CNL (4/19; 21%). In contrast, SETBP1 is often mutated in aCML (19/60; 32%) and rarely in CMML (13/252; 5%) and CNL (2/19; 10.5%) patients. In addition, CSF3R is much more associated with the CNL cases (35%) and less frequently found in aCML (2%) and CMML (1%). Conclusion 1) CNL, aCML and CMML are related diseases and difficult to distinguish by cytomorphology alone and therefore require additional diagnostic criteria, i.e. molecular mutations. 2) ASXL1 is the most frequently mutated gene in these entities and thus can help to prove clonality. 3) SETBP1 much more closely relates to aCML and SRSF2 to CMML. 4) Mutations in the novel marker CSF3R are closely related to CNL and thus qualify as a new molecular marker for diagnosis of CNL. Disclosures: Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schrauder:MLL Munich Leukemia Laboratory: Employment. Konietschke:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Abstract Abstract LBA-2 The SETBP1 gene codes for a predominantly nuclear protein with a predicted MW of 170 kD. Germline mutations of SETBP1 were described in patients affected by the Schinzel-Giedion syndrome (SGS), a rare disease characterized by bone, muscle and cardiac abnormalities, and presenting neuroepithelial neoplasms. In an effort to investigate the molecular pathogenesis of myeloid malignancies we applied a HTS strategy, including both exome sequencing and RNA-SEQ, to atypical Chronic Myeloid Leukemia (aCML), as defined by WHO criteria, with the aim of identifying novel recurrent driver mutations. aCML shares clinical and laboratory features with CML, but it lacks the pathognomonic BCR-ABL1fusion. Since no specific recurrent genomic or karyotypic abnormalities have been identified in aCML, the molecular pathogenesis of this disease has remained elusive and the outcome dismal (median survival 37 months) with no improvement over the last 20 years. This sharply contrasts with the outcome for CML, for which the prognosis was dramatically improved by the development of imatinib as a specific inhibitor of the BCR/ABL protein. Whole-exome sequencing of 9 aCML patients revealed the presence of 62 unique mutations (range 5–14 per patient), including a recurrent alteration of SETBP1 (G870S and D868N) in three cases. Targeted resequencing performed in 70 aCMLs, 574 patients with different hematological malignancies and 344 cell lines, identified SETBP1 mutations in 17 of 70 aCML patients (24.3%; 95% CI: 16–35%), 4 of 30 (13%) MDS/MPN-u and 3 of 82 (3.6%) CMML patients. Patients with mutations had higher white blood cell counts (p=0.008) and worse prognosis (p=0.01) when tested in multivariate analysis. TF1 cells transfected with SETBP1G870S showed increased SET levels, decreased PP2A activity and increased proliferation rates. The vast majority of mutations (85%) was located between residues 858 and 871, in the SKI homologous region of SETBP1, and were identical to germline changes seen in patients with SGS. This region may be critical for ubiquitin binding and for subsequent protein degradation, since the Eukaryotic Linear Motif (ELM) identified with high probability score a putative functional site (aa. 868–873) for beta-TrCP, the substrate recognition subunit of the E3 ubiquitin ligase. This prediction was experimentally validated using biotinylated, phosphorylated peptides encompassing this region (aa 859–879): while the wild type peptide could efficiently bind beta-TrCP as predicted, a peptide presenting the G870S mutation was incapable of binding this E3 ligase subunit, indicating a possible alteration in SETBP1 protein stability caused by this mutation. In agreement with these findings, cells transfected with SETBP1G870Sshowed increased levels of SETBP1 protein when compared to cells with similar expression levels of the wild type gene. Finally, RNA-SEQ yielded gene expression profiles with overrepresentation of genes under the control of Transforming Growth Factor Beta 1 (TGFβ1) among genes differentially expressed between SETBP1-mutated and unmutated aCML patients. Mutated SETBP1 represents a novel type of oncogene which is specifically present in aCML and closely related diseases. These data allow for a better understanding of the molecular pathogenesis of this disease; they provide evidence that SETBP1 mutations might be a new biomarker for future diagnosis and classification of aCML and related diseases, and indicate a potential strategy to develop new treatment modalities for malignancies caused by mutated SETBP1. Disclosures: Schnittger: MLL Munich Leukemia Laboratory: Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Equity Ownership.

Abstract Atypical chronic myeloid leukemia (aCML) and chronic neutrophilic leukemia (CNL) are rare myeloid neoplasms defined largely by morphologic criteria. The discovery of CSF3R mutations in aCML and CNL have prompted a more comprehensive genetic profiling of these disorders. These studies have revealed aCML to be a genetically more heterogeneous disease than CNL, however, several groups have reported that SETBP1 and ASXL1 mutations occur at a high frequency and carry prognostic value in both diseases. We also report a novel finding—our study reveals a high frequency of U2AF1 mutations at codon Q157 associated with CSF3R mutant myeloid neoplasms. Collectively, these findings will refine the WHO diagnostic criteria of aCML and CNL and help us understand the genetic lesions and dysregulated signaling pathways contributing to disease development. Novel therapies that emerge from these genetic findings will need to be investigated in the setting of a clinical trial to determine the safety and efficacy of targeting various oncogenic drivers, such as JAK1/2 inhibition in CSF3R-T618I–positive aCML and CNL. In summary, recent advances in the genetic characterization of CNL and aCML are instrumental toward the development of new lines of therapy for these rare leukemias that lack an established standard of care and are historically associated with a poor prognosis.

Abstract INTRODUCTION: Atypical Chronic Myeloid Leukemia (aCML) is a heterogeneous disorder belonging to the group of myelodysplastic/myeloproliferative syndromes, characterized by a poor prognosis with a median survival time of 37 months. In 2013, by applying Next Generation Sequencing (NGS) technologies on 8 aCML cases, we demonstrated the presence of a recurrent somatic mutations in the SETBP1 gene (Piazza et al, Nat Gen 2013). SETBP1 mutations were identified in approximately 30% of aCML cases. AIM: To further characterize the molecular pathogenesis of aCML and to possibly identify other recurrent lesions responsible for SETBP1 unmutated cases, we extended our initial NGS effort: we applied whole-exome and transcriptome sequencing to a total of 16 matched samples taken at onset of the disease. MATERIAL and METHODS: Whole-exome and transcriptome sequencing data were generated using an Illumina Genome Analyzer IIx following standard library-preparation protocols. Alignment to the reference GRCh37/hg19 genome was performed using BWA. Alignment data were processed using Samtools. Single nucleotide and small indel detection was performed using in-house software. Copy number analyses from whole-exome data were generated using CEQer (Piazza et al, PLoS One 2013) and gene fusions transcriptome data were screened using FusionAnalyser (Piazza et al, Nucleic Acids Res. 2012). RESULTS: The application of NGS techniques to the cohort of aCML cases led to the identification of a somatic, non-synonymous single-nucleotide mutation (chr4:g.55599321A>T) in the KIT gene in 1/16 (6%) cases. At protein level this mutation translated into the D816V variant that has been already described in several clonal disorders, such as systemic mastocytosis, gastrointestinal stromal tumors and acute myeloid leukemia. To assess whether the mutation identified by NGS was recurrent, we extended our analysis by targeted resequencing on a larger cohort of 68 aCML cases. This analysis revealed the presence of KIT mutations in 3 additional patients, thus confirming the recurrence of KIT variants in aCML. All the KIT mutations identified correspond to the D816V that is responsible for the constitutive activation of the tyrosine kinase. This finding suggests that the activation of the KIT tyrosine kinase signaling may play an important role in this subset of aCML patients. It is known from the literature that KIT D816V is highly sensitive to the tyrosine kinase inhibitor dasatinib (Schittenhelm MM, Cancer Res 2006). To test whether dasatinib is able to affect the growth of the leukemic clone in KIT mutated aCML cases, we performed ex vivo tritiated thymidine proliferation assays on bone marrow (BM) cells from one of the KIT D816V positive aCML patients in presence of either dasatinib, imatinib or vehicle alone: the proliferation assay showed that dasatinib was able to inhibit the proliferation of the leukemic clone with an IC50 of 1nM, while, as expected, neither imatinib nor vehicle alone were able to significantly impair cell growth. In line with these data, western blot with an anti- Phospho-KIT antibody on KIT+ lysates after treatment with increasing concentration of dasatinib showed that the drug was highly effective in inhibiting KIT autophosphorylation. To further confirm the inhibitory activity of dasatinib, we performed a colony assay on peripheral blood cells from a KIT D816V positive aCML patient grown in presence of increasing concentrations of the drug: treatment with 100nM dasatinib was able to completely inhibit cell growth, leading to a virtually complete absence of colonies in the D816V-positive plates. CONCLUSION: These data indicate that KIT D816V is a pro-oncogenic lesion recurrently present in aCML, albeit with low frequency (5/84, 6%) and that aCML cells bearing this mutation are highly sensitive to dasatinib, at least ex vivo. Given the very poor prognosis of this disorder, these findings suggest a new, highly efficient targeted treatment for a subset of aCML patients. Disclosures Schnittger: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Meggendorfer:MLL Munich Leukemia Laboratory: Employment.

Abstract BCR-ABL1 negative myeloproliferative neoplasms not only include atypical chronic myeloid leukemia (aCML), but also chronic myelomonocytic leukemia (CMML), chronic neutrophilic leukemia (CNL), and myelodysplastic/myeloproliferative neoplasm, unclassifiable (MDS/MPN, U). Despite the recent advances in characterizing aCML more specifically, based on next generation sequencing data, the differential diagnosis and subsequent treatment decisions remain difficult. Therefore, we analyzed the transcriptome and performed whole genome sequencing (WGS) in a cohort of morphologically defined 231 patients (pts): 49 aCML, 30 CNL, 50 MDS/MPN, U, and 102 CMML all diagnosed according to WHO classification. WGS libraries were prepared with the TruSeq PCR free library prep kit and sequenced on a NovaSeq 6000 or HiSeqX instrument with 100x coverage (Illumina, San Diego, CA). The Illumina tumor/unmatched normal workflow was used for variant calling. To remove potential germline variants, each variant was queried against the gnomAD database, variants with global population frequencies >1% where excluded. For transcriptome analysis total RNA was sequenced on the NovaSeq 6000 with a median of 50 mio. reads per sample. The obtained estimated gene counts were normalized and the resulting log2 counts per million (CPMs) were used as a proxy of gene expression. Unsupervised exploratory analysis techniques, such as principal component analysis (PCA) and hierarchical clustering (HC) were used to identify groups of samples with similar expression profiles. We observed a high similarity between the different entities with CMML being the most distant entity, followed by CNL. MDS/MPN, U and aCML were the most similar entities. Due to high within-group heterogeneity, we found that it was impossible to identify a gene expression signature that separated aCMLs reliably from the other MDS/MPN overlap entities. Surprisingly, PCA as well as HC indicated the existence of two subgroups within the aCMLs. Therefore, we searched for genes with a bimodal-like expression profile. We found that FOS expression levels strongly separated aCMLs into two groups of 16 pts (FOSlow) and 33 pts (FOShi), respectively. Interestingly, FOShi correlated with mutations in SETBP1 (12/33, 36% vs. 3/16, 19%), a known marker typically mutated in aCML (Figure 1a). Addressing the mutational landscape of these two groups (FOShivs.FOSlow) we found that ASXL1 (88% vs. 100%), TET2 (33% vs. 50%), SRSF2 (45% vs. 56%), EZH2 (27% vs. 31%), and NRAS (21% vs. 25%) showed rather similar mutation frequencies. GATA2 (15% vs. 31%) and RUNX1 (18% vs. 38%) mutations were less frequent in FOShi, whereas SETBP1 and CBL (18% vs. 6%) were more frequent in this group. Consistent with known features of SETBP1 mutation this group showed a higher white blood cell count (78 x109/L vs. 52 x109/L) and platelet count (158x109/L vs. 90x109/L), although none of these differences were significant. The two groups were further analyzed for gene expression differences and we found 16 genes with synchronized upregulation within the FOShi group that were differentially expressed (FDR < 0.05, absolute logFC > 1.5) compared to FOSlow. Functional enrichment analysis linked those genes with regulation of cell proliferation (p<0.001), negative regulation of cell death (p<0.001), and the AP-1 complex (p<0.001). Those 16 genes included the transcription factors JUN, FOSB, EGR3, and KLF4, the cancer-related genes DUSP1, RHOB, OSM, TNFRSF10C, and CXCR2, and the FDA approved drug targets JUN, COX-2, and FCGR3B (Figure 1b). JUN/FOS are the main components of the AP-1 complex, a regulator of cell life and death. The upregulation of these genes results in increased proliferation as clinically observed in aCML pts. Furthermore, for these pts a treatment with INFα might result in an anti-proliferative effect by modulation of FOS transcript levels. Further, COX-2 inhibitors might also suppress proliferation and differentiation of leukemia cells. However, for the FOSlow pts these treatments might not be as effective due to the already low expression levels of the respective genes. Since the expression levels of FOShi equal those of MDS/MPN overlap, whereas FOSlow levels are closer to the ones of a healthy control cohort, SETBP1 mutation might be a marker and indicator for pts with high FOS expression and therefore providing further treatment options by targeting specifically the FOS mediated pathways. Disclosures Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Walter:MLL Munich Leukemia Laboratory: Employment. Hutter:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Abstract Background: Atypical chronic myeloid leukemia (aCML) is a rare disorder classified as one of the MPN/MDS overlap syndromes. aCML usually presents like CML but lacks the pathognomonic BCR-ABL fusion found in CML. Most patients progress to acute myeloid leukemia (AML) with a median time to AML of 11.2 months and have a median overall survival of only 12.4 months (Wang et al. Blood 2014). Recurrently mutated genes found in aCML patients include SETBP1 , CSF3R, NRAS, EZH2, ASXL1, ETNK1, and U2AF1. The pathogenesis of aCML is poorly understood and neither specific nor effective treatments besides hematopoietic stem cell transplantation are available. We therefore aimed at developing a patient derived xenotransplantation model that allows serial transplantation and expansion of human leukemic cells and evaluation of novel treatments and drugs in vivo. Patient and Methods: Bone marrow cells were harvested from a patient diagnosed with atypical CML based on persistent leukocytosis, immature circulating myeloid precursors (16% metamyelocytes, 8% myelocytes, 9% blasts), marked dysgranulopoiesis, minimal monocytosis and basophilia, hypercellular bone marrow with high myeloid/erythroid ratio and 6% myeloid blasts, dysplasia in megakaryocytes and erythroid progenitors, and absence of BCR-ABL and mutated JAK2. The patient had moderate anemia and normal platelet counts and cytogenetic analysis showed a normal karyotype. Eight hundred thousand bone marrow cells were injected intravenously in NOD/SCID IL-2 receptor γ (NSG) deficient mice. We monitored these mice for human cell engraftment by regular eye bleeds every 4 weeks. Bone marrow and spleen cells from engrafted mice were retransplanted in secondary and tertiary mice of the NSG strain transgenic for SCF, IL3 and GM-CSF (NSGS). Patient cells were analyzed for mutations in fifty four genes by next generation sequencing and mutations were confirmed by Sanger sequencing in primary patient cells and cells from tertiary mice. Results: Human CD45+ cells from the aCML patient showed increasing engraftment over time in the NSG mouse reaching 16% in peripheral blood and 35% in spleen at 26 weeks after transplantation. In secondary (n=2) and tertiary (n=4) mice we used NSGS recipient mice and observed considerably accelerated engraftment kinetics leading to 19, 21 and 73% human cells in peripheral blood, spleen and bone marrow, respectively, between 12 and 15 weeks after transplantation. The myeloid marker CD33 was expressed in 86% of human bone marrow cells, while lymphoid markers CD3 and CD19 were absent. The stem and progenitor phenotype CD34+CD38- was found in 11% of human cells. The progenitor marker CD123 was expressed in 42% of cells, while the myeloid marker CD14 was expressed in 6% of cells. Hemoglobin levels and platelet counts were considerably lower in secondary and tertiary recipients of aCML cells compared to control animals. Spleens were enlarged at time of sacrifice with an average spleen weight of 150 mg. Morphological evaluation of bone marrow cells in tertiary recipients revealed a characteristic picture for aCML with 39% neutrophils, 8% blasts and 53% myeloid progenitors and monocytes. Molecular analysis identified mutations in ASXL1, RUNX1 and EZH2 with variant allele frequencies of 49, 48 and 46 percent, respectively that were confirmed in human cells from tertiary recipient mice. Thus, we show that primary aCML cells can be expanded and serially transplanted in immunodeficient mice and suggest clonal stability of this model. Conclusion: We provide the first patient derived xenotransplantation model for atypical CML, which preserves the phenotypic and molecular characteristics of the primary disease and allows serial transplantation and expansion of aCML cells. This model will serve to better understand the pathogenesis of aCML and to test urgently needed novel treatment approaches. Disclosures No relevant conflicts of interest to declare.

Abstract Introduction The identification of mutations (mut) in SETBP1 recently shed light on a molecular marker in atypical chronic myeloid leukemia (aCML), a disease previously defined by exclusion criteria. SETBP1mut have been identified in different myeloid malignancies. We previously reported mutation frequencies in the range of 5-10% in MPN and MDS/MPN overlap, 32% in aCML, while we found SETBP1 less frequently mutated in AML (3%). SETBP1mut has been shown to associate with ASXL1, CBL and SRSF2 mutations, as well as the cytogenetic abnormalities -7 and i(17)(q10). Aim To investigate the mutation frequency of ASXL1, SETBP1, and SRSF2 in different myeloid entities in correlation to the cytogenetic abnormalities -7 and i(17)(q10). Patients and Methods A cohort of 451 patients (pts) with different myeloid entities was analyzed. Diagnoses according to cytomorphology followed the WHO classification from 2008 (n=439, for n=12 cases no cytomorphology was available): AML (n=29), aCML (n=62), MDS/MPN overlap (n=16), CMML (n=283), MDS (n=5), MPN (n=43), CML (n=1). The cohort consisted of 303 males and 148 females; cytogenetics was available in 445 cases. Patients were grouped by normal karyotype (n=291), i(17)(q10) (n=16), -7 (n=22), and other cytogenetic aberrations (n=117); one case carried both a i(17)(q10) and a -7. ASXL1 exon 13, the mutational hotspot regions of SETBP1 and SRSF2 were analyzed by Sanger sequencing in all cases. Results In the total cohort ASXL1 was mutated in 222/451 (49%), SETBP1 in 61/451 (14%), and SRSF2 in 209/451 (46%) cases. 137 pts showed no mutation in any of these three genes. 171 pts carried one mutation, thereof 84 a sole ASXL1mut, 82 a sole SRSF2mut and only 5 cases showed sole SETBP1mut. In 108 pts two, and in 35 pts all three analyzed genes were mutated. The most frequent combination within the group with two mutations was ASXL1 and SRSF2 (n=78), followed by ASXL1 and SETBP1 (n=16), only 5 cases were mutated in SRSF2 and SETBP1. Addressing the association with cytogenetics revealed that in cases with only one mutation SRSF2mut associated as sole mutation with a normal karyotype (68/124 (55%) SRSF2mut in the normal karyotype group vs. 12/42 (28%) SRSF2mut in all other karyotypes; p=0.003). In contrast, ASXL1mut and SETBP1mut as sole mutations showed no correlation to any addressed karyotype. However, addressing the cases with two mutations the combination of SRSF2mut and ASXL1mut correlated with a normal karyotype (67/291 (23%) SRSF2mut/ASXL1mut in the normal karyotype group vs. 19/154 (12%) SRSF2mut/ASXL1mut in all other karyotypes; p=0.008), while SRSF2mut and SETBP1mut occurred more frequently in i(17)(q10) pts (2/16 (13%) SRSF2mut/SETBP1mut in i(17)(q10) vs. 2/429 (1%) SRSF2mut/SETBP1mut in all other karyotypes; p=0.007). Remarkably, cases with mutations in all three analyzed genes (ASXL1mut, SETBP1mut, and SRSF2mut) highly associated with i(17)(q10) and -7. 11 of 16 cases with i(17)(q10) (69%) showed all three mutations (vs. 24/429 (6%) in all other karyotypes; p<0.001). Furthermore, 6 of 22 cases with -7 (27%) showed mutations in all three genes (vs. 29/423 (7%); p=0.005). Therefore, 15 pts carried all three mutated genes as well as i(17)(q10) or -7. Interestingly, there was no case with only i(17)(q10) and no additional mutation, and only one case with i(17)(q10) and only one additional molecular mutation, 4 cases with two additional molecular mutations and 11 cases carrying all three mutations, possibly indicating that i(17)(q10) appear during clonal evolution. Therefore one might assume that this represents a specific genetic phenotype that is driven by the accumulation of molecular events, since addition of SETBP1mut shifts the association from a normal karyotype to i(17)(q10) or -7. Analyzing the distribution of these cases for mutations in all three analyzed genes +/- additional cytogenetic aberration i(17)(q10) or -7 in the different myeloid entities showed that AML, aCML, CMML, MDS as well as MPN showed this genetic phenotype (AML: n=7 (24%); atypical CML: n=12 (19%); CMML: n=8 (3%); MDS: n=1 (20%); MPN: n=6 (14%)). Conclusions Mutations in SETBP1 associate with ASXL1mut and SRSF2mut and are frequently found in patients with i(17)(q10) or -7. This combination of genetic lesions occurs in different myeloid entities and might therefore define a specific genetically defined subtype of myeloid malignancy. Disclosures: Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Sirch:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Abstract Background. The Atypical Chronic Myeloid Leukemia (aCML) and Chronic Neutrophilic Leukemia (CNL) had put in separate sections of myeloid neoplasms classification but have common entity and bone marrow changes. aCML and CNL hard to differentiate from each other. The main differential criterion is the proportion of immature white blood cells in blood, but it is not strong due to its instability. The achievement of recent years is discovering of aCML and CNL molecular factors: mutations in SETBP1 and CSFR3R genes gave the basis for the diagnosis confirmation in part of patients but could not differentiate between two nosologies. In addition, the access to the "uncommon" molecular diagnostic is complicated in routine clinical practice. Aim. At the abstract we would like to report the first, as we known, diagnosis of aCNL in Russia, that had been confirmed by molecular markers and is treating with target therapy. Materials and methods. The patient, female 51-year old has presented severe fatigue, pain, weight loss and burden under the left costal margin since Sep-2017. Results. The initial assessment has revealed massive splenomegaly (200x130x248 mm) with high WBC (133.9x109/L with left shift: blasts 1%, promyelocytes 6%, myelocytes 14%, metamylocytes 16%, bands 14%, segments 45%, lymphocytes 2%, monocytes 0%), mild anemia (10.4 g/dL) and normal platelets (223x109/L). There was neutrophil hyperplasia without eosinophilia and basophilia in myelogram. Initial diagnosis of typical CML was made but cytogenetic was normal and BCR-ABL (p190, p210) was negative. Atypical CML was suspected by bone marrow histology that demonstrated hypercellularity, granulocytic hyperplasia and mild megakaryocytic atypia and only mild reticuline fibrosis (MF-1). There were no MPN-driver markers (JAK2, CALR, MPL) revealed. Initial therapy with Hydroxyurea 2 g/day was started in Nov-2017. The re-work-up (morphological, cytogenetic, FISH and molecular) has been done in federal referral center in Nov-2017 but no signs of typical CML or Ph-MPN was detected. Mutation in exon 12 of ASXL1 gene was revealed in Jan-2018. After initial cytoreduction at follow-up in Feb-2018 mild leukocytosis (10.0-25.0x109/L) with shift to myelocytes and splenomegaly (+3 cm) was noted, severe fatigue and night sweats were still presented. Given the molecular results the target therapy with Ruxolitinib 15 mg BID was started since Feb-2018. The Ruxolitinib has given results with rapid resolution of constitutional symptoms, weight gain and complete CBC normalization during first month of therapy. At 3 months of treatment follow-up bone marrow histology showed hypocellularity and myeloid swelling. The first assessment of CSF3R gene in Russia on May-2018 has revealed the T618I mutation. Thus, the final diagnosis of aCML has been made (revealed mutation more related to CNL but WBC profile is consistent to aCML). The patient is still receiving Ruxolitinib therapy with complete clinical and hematologic response up to date. The search of unrelated donor was started. Conclusions. Nowadays diagnosis of aCML or CNL need to be established on thorough complex investigation. There is a need to get a widespread consensus guideline of aCML and CNL diagnosis and management and reclassification of these diseases in one common group. Disclosures No relevant conflicts of interest to declare.

Introduction: Germline RUNX1 mutations/deletions result in a Familial Platelet Disorder with propensity to Myeloid Malignancy (FPDMM); an autosomal dominant condition characterized by thrombocytopenia, qualitative platelet defects, and myeloid clonal evolution (MDS and AML). The advent of next generation sequencing (NGS) has allowed detection of clonal cytopenias of unclear significance (CCUS) prior to bone marrow (BM) morphological changes. Somatic RUNX1 mutations (RUNX1MT) can be seen in myeloid malignances, including MDS/MPN overlap syndromes, with an indeterminate prognostic impact. We carried out this study to define the landscape of clonal evolution in FPDMM patients and to compare germline RUNX1MT with somatic mutations. Methods After IRB approval, families with RUNX1MT FPDMM (detected by germline sequencing and deletion/duplication assays) and patients with 2016, WHO-defined MDS/MPN overlap syndromes (except JMML) were included in the study. Index patients with FPDMM underwent BM biopsies and in select cases NGS at diagnosis and then as indicated for follow up, or at disease progression. All MDS/MPN overlap syndrome patients underwent a 29-gene panel NGS assay on BM samples obtained at diagnosis by previously described methods (Patnaik et al., BCJ 2016). Results Eight index patients with FPDMM were included; median age at diagnosis 58 (range, 0-71) years, 3 (38%) males (Figure A). Four (50%) had intragenic deletions involving multiple exons in 3 cases and 2 nucleotides in 1 case, 1 (13%) each had missense, frameshift and splice site mutations, while 1 (13%) patient had a whole gene deletion (Figure C). Notably, in 4 (100%) of 4 patients with large deletions, NGS testing was negative for RUNX1 abnormalities. Four (50%) index patients presented with a myeloid neoplasm; JAK2, SRSF2, ASXL1 mutant CMML, MDS/MPN-U with trisomy 8, AML with del7q and normal karyotype AML (negative NGS). Three (38%) index patients had CCUS at diagnosis with TET2 (67%) being the most common acquired mutation, and others including SRSF2, EZH2, and SF3B1. Cumulatively, myeloid clonal evolution was seen in 7 (88%) patients. Three (38%) index patients (AML-2, CMML-1) underwent allogeneic HCT, and at last follow up were in remission. Median age at myeloid clonal evolution was 61 (range, 4-71) years; median overall survival (OS) from date of myeloid clonal evolution was 12 (range, 7-53) months. For the comparative analysis, 499 patients with MDS/MPN overlap syndromes were included; 382 (77%) with CMML, 48 (10%) with MDS/MPN-RS-T (MDS/MPN with ring sideroblasts and thrombocytosis), 17 (3%) with aCML (atypical CML), and 52 (10%) with MDS-MPN-U (unclassifiable). Median age at diagnosis was 71 (range, 18-99) years, and 329 (66%) were male. RUNX1MT were detected in 57 (11%) patients; 43 (11%) with CMML, 5 (30%) with aCML, and 9 (17%) with MDS-MPN-U. No RUNX1MT were found in MDS-MPN-RS-T. Overall, 62 RUNX1MT were identified in 57 patients, with 52 (39 CMML, 4 aCML, 9 MDS-MPN-U) and 5 (4 CMML, 1 aCML) patients harboring 1 and 2 RUNX1MT, respectively. RUNX1MT spanned the entire coding sequence without specific hotspots (Figure B): 27 (44%) were missense, 2 (3%) involved the splicing sites, 5 (8%) were nonsense and 28 (45%) were frameshift. There was only one RUNX1MT (R273K), seen in both germline and somatic patients (Figures B and C). Compared to wild type patients, RUNX1MT patients with MDS/MPN overlap syndromes had significantly lower platelet counts (median 72 vs 117 x109/L, p<0.0001), without any other phenotypic differences. In the somatic RUNX1MT cohort, co-occurring mutations included ASXL1 (54%), SRSF2 (54%), TET2 (49%), and NRAS (28%), with NRAS (28% vs 13%, p=0.0028), and SRSF2 (54% vs 39%, p=0.0218) mutations clustering with RUNX1MT. Median OS of the entire cohort was 29 (range, 0-170) months. On univariate analysis, while there was a trend for an inferior OS in RUNX1MTvs wild type patients (20 vs 29 months, p=0.0523), the leukemia-free survival was clearly inferior (p=0.0175, Figure D). Conclusion RUNX1 MT FPDMM is a germline predisposition syndrome with a high rate of myeloid clonal evolution (88%), including clonal cytopenias (38%). Germline RUNX1MT have minimal overlap with somatic mutations seen in myeloid malignancies, with NGS testing often missing RUNX1 deletions. Somatic RUNX1MT in myeloid malignancies are significantly associated with thrombocytopenia and an inferior leukemia-free survival. Figure Disclosures Patnaik: Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees.

Abstract INTRODUCTION: The management of myelodysplastic syndrome/myeloproliferative overlap neoplasms (MDS/MPN) remains challenging due to their molecular complexity. Hypo-methylating agents (HMA) have been used for cytoreduction and preparation of patients for allogeneic blood or marrow transplantation (BMT). However, less than 50% patients have a meaningful response to HMA and predictive factors for response remain unknown. The aim of our study is to examine molecular predictors of response to HMA in patients with MDS/MPN. PATIENTS AND METHODS: We performed a retrospective analysis of 150 patients evaluated at our center for chronic myelomonocytic leukemia (CMML), atypical chronic myeloid leukemia (aCML) and unclassifiable MDS/MPN (MDS/MPN-U) between 1/1/2010 and 12/31/2020. Forty-three individuals who were treated with HMA during chronic phase and had next generation sequencing (NGS) using the established 63-genes panel were identified. Complete and partial remission (CR and PR), and marrow response (MR) were assessed based on the MDS/MPN International Working Group response criteria. Univariate logistic regression analysis was used to associate the number of somatic mutations or high-risk (HR) mutations (NRAS, SETBP1, RUNX1, EZH2, TP53, ASXL1, STAG2), and other disease specific factors at the time of the initiation of HMA with response categories. Multivariable analysis for modeling response were conducted via Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression approach, where the predictors were selected based on 5-fold cross validation with turning parameter selected to minimize deviance of logistic regression model. Kaplan-Meier was used to assess the overall survival based on the CR/PR status at 6 months from the initiation of HMA in landmark analysis. Cox-regression analysis considering the occurrence of CR/PR as a time-varying covariate was used to assess the impact of CR/PR on overall survival. RESULTS: Fifteen women and 28 men with a median age 67 years (range: 45 - 85 years) and a median follow up of 1.5 years (range: 91 days - 5.2 years) were included. Twenty five (58.1%) had CMML, 15 (34.9%) had MDS/MPN-U and 3 (7%) had aCML. Thirty-four patients (79.1%) received azacitidine (median number of cycles: 4.5, range: 1 - 65) and 9 patients (20.9%) received decitabine (median number of cycles: 4, range: 3 - 21). Seventeen patients (39.5%) underwent BMT following HMA therapy. The incidence of AML transformation was 16%. No patients had CR while 56% achieved a PR and 42% had an MR. Univariate analysis showed that ≥2 HR mutations (OR 0.19, 95% CI 0.05-0.67), SETBP1 mutation (OR 0.16, 95% CI 0.02-0.76), RUNX1 mutation (OR 0.1, 95% CI 0.01-0.48) and a mutation in at least one out of the SETBP1, RUNX1 and EZH2 genes (OR 0.05, 95% CI 0.01-0.21) were associated with absence of PR. ≥2 HR mutations (OR 0.23, 95% CI 0.05-0.9), and the presence of a mutation in one out of the SETBP1, RUNX1 and EZH2 genes (OR 0.16, 95% CI 0.03-0.62) were associated with absence of MR on univariate analysis. Finally, older age as a continuous variable was associated with PR (OR 1.09, 95% CI 1.01-1.19) and MR (OR 1.12, 95% CI 1.03-1.24). Presence of a mutation in one of the SETBP1, RUNX1 and EZH2 genes with age adjusted was selected from LASSO approach and significantly predicted the absence of PR (OR 0.05, 95% CI 0.01-0.27), and MR (OR 0.19, 95% CI 0.04-0.91) (Table 1). Using the landmark of 6 months after the initiation of treatment, Kaplan-Meier analysis showed that PR at 6 months was associated with superior overall survival (P=0.010) compared to patients with no response (Figure 1). Similarly, Cox-regression analysis revealed that the occurrence of PR following the initiation of treatment was associated with better overall survival (HR 0.26, 95% CI 0.9-0.13, P=0.010). CONCLUSIONS: Mutations in SETBP1, RUNX1 or EZH2 genes predicted absence of response to HMA among patients with MDS/MPN independent of other factors including karyotype, blast percentage and R-IPSS. These findings suggest that the molecular profile of MDS/MPN patients can potentially identify patients with HMA-refractory phenotype. Multi-institutional studies of larger cohorts are required to verify these results and develop novel treatment strategies especially for patients with high-risk mutations in MDS/MPN. Figure 1. Kaplan-Meier estimates of OS by PR status at 6 months in landmark analysis. P-value was based on log-rank test. Figure 1 Figure 1. Disclosures Levis: BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Jazz: Consultancy, Honoraria; Amgen, Astellas Pharma, Daiichi-Sankyo, FujiFilm, and Menarini: Honoraria; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Astellas and FujiFilm: Research Funding; Pfizer: Consultancy, Honoraria; Takeda: Honoraria. Jain: Syneos Health: Research Funding; CTI Biopharma: Research Funding; CareDx: Other: for advisory board participation; Bristol Myers Squibb: Other: for advisory board participation; Targeted Healthcare Communications: Consultancy.

Background Atypical CML (aCML) is a rare myeloid neoplasm with molecular heterogeneity and overlapping features of MDS and MPN. Distinction from unclassified MDS/MPNu based on WHO criteria remains difficult, and the management of these closely related entities remains ill-codified. Most patients (pts) are managed with cytoreductive agents, but small series have reported responses to hypomethylating agents or tyrosine kinase inhibitors (TKI), notably ruxolitinib. Allogeneic stem cell transplantation (SCT) is considered the only curative option. To instruct clinical trials with novel agents in this rare and heterogeneous population, real-life cohorts must i) provide prognostic factors and molecular characterization able to stratify patients, and ii) benchmark outcomes with current treatment options. Methods The French National observational study of rare MDS/MPNs performed a retrospective analysis of adult patients with MDS/MPN from 35 centers. Cases were centrally reclassified according to the 2016 WHO criteria to exclude CMML, classical MPNs and CNL. All statistical analyses were done without dichotomizing continuous clinical or biological variables. The prognostic influence of treatments was analyzed considering onset of treatment as a time-dependent covariate (Mantel-Byar method). Results The study population included 136 pts (M/F 83/53), with a median age of 72 years. Only 43 (31.6%) met WHO 2016 criteria for aCML while the remaining 93 were classified as MDS/MPNu. At diagnosis, spleen enlargement or other tumor symptoms were present in 36% of pts, while 32% had constitutional symptoms. Mutations in ASXL1, splice genes (U2AF1, SF3B1, SRSF2 or ZRSR2), SETBP1, EZH2, CSF3R, JAK2 and ETNK1 were present in 68.8%, 50.0%, 30.3%, 15.9%, 12.7%, 12.6% and 7.4% of 63 tested cases, respectively. 25 pts had an AML transformation. With a median follow-up of 29.8 months (0.5-276.4) median overall survival (OS) and AML-free survival (AMLFS) were 25.6 and 20.6 months, resp. Median OS was 20.2 versus (vs) 29.7 months in aCML vs MDS/MPNu, resp (log rank test p=0.2) and median AMLFS was 16.6 vs 27.4 months, resp (p=0.09). In univariate analysis, higher WBC (p=0.003) and lower Hb level (p<10-5) predicted significantly shorter OS, while presence of splenomegaly or other tumor symptoms (p=0.08), higher proportion of IMC (p=0.06), lower platelet count (p=0.08) and dyserythropoieisis (p=0.05) tended to shorten OS. Age, gender, presence of constitutional symptoms, bone marrow or peripheral blast percentage or dysmegakaryopoiesis had no significant impact (all p>0.1). Patients with EZH2 mutations had shorter OS (median 9.9 vs 20.6 months in EZH2 wt pts, p=0.03), while other gene mutations had no significant prognostic impact (all p>0.1). All variables with p <0.1 in univariate analyses were included in a multivariate Cox model. After backward selection, only Hb levels (HR= 0.81, p<10-5) and dyserythropoiesis (HR=2.4, p=0.04) retained independent prognostic value. At any time during follow-up, 89 (65.4%) pts received cytoreductive agents (mostly hydroxyurea), while 23 (16.9%) received TKI (ruxolitinib in 12, imatinib in 8, dasatinib in 3 pts) and 18 (13.2%) HMA, resp. Of note, 8/18 pts received HMA at transformation to AML, while all pts received TKIs prior to AML. Finally, 19 pts (14.0%) received an SCT and 35.3% received ≥2 of the above-mentioned types of treatment. Median time to SCT, HMA and TKI were 10.2, 11.9 and 4.7 months, resp. In multivariate Cox models adjusting for baseline Hb level and dyserythropoieisis, neither cytoreduction (p=0.6) nor SCT (p=0.5) were associated with a significant OS improvement. Treatment with HMA was associated with a significantly worse OS (HR=3.0, p=0.001), but this effect was confounded when transformation to AML, as a time-dependent event, was included in the model (HMA: HR= 1.1, p=0.7, AML: HR=5.1, p<10-6). Finally, treatment with TKIs was also associated with significantly worse OS (HR=2.3, p=0.02). This TKI's detrimental effect was confirmed in a model also accounting for baseline WHO, (log-transformed) WBC count, platelet levels and bone marrow blast percentage. Conclusions Anemia and dyserythropoiesis are important prognostic factors in aCML and MDS/MPNu that should be used to stratify pts included in clinical trials. There is currently no standard of care for these overlap syndromes. Treatment with HMAs and TKIs should be restricted to clinical trials. Disclosures Rea: Incyte Biosciences: Honoraria; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria. Roy:Incyte Biosciences: Consultancy. Caers:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Nicolini:Incyte Biosciences: Honoraria, Research Funding, Speakers Bureau; Novartis: Research Funding, Speakers Bureau; Sun Pharma Ltd: Consultancy. Legros:Novartis: Honoraria; BMS: Honoraria; Incyte Biosciences: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding.

Background: Acquired somatic mutations are crucial for the development of the majority of cancers. In hematological malignancies, some molecular mutations are very specific for certain entities (e.g. BRAF in HCL, MYD88 in LPL), while others were detected in a variety of malignancies (e.g. mutations in TP53, TET2, DNMT3A, RUNX1). Moreover, mutations in genes related to CHIP (clonal haematopoiesis of indeterminate potential; ASXL1, TET2,DNMT3A) were detected in an age-related manner. Aim: (1) Analysis/comparison of mutation frequencies of 122 selected genes in 3096 cases with 28 different hematological malignancies for identification of "mutation-driven" entities. (2) Correlation of CHIP-related mutations with mutational landscapes. Methods: Whole-genome sequencing (WGS) was performed for all 3096 patients. For this, 151bp paired-end reads were generated on NovaSeq 6000 and HiSeqX machines (Illumina, San Diego, CA). The Illumina tumor/unmatched normal workflow was used for variant calling. All reported p-values are two-sided and were considered significant at p&lt;0.05. Results: Entities with the highest numbers of mutations (median n=4) and thus potentially with the largest impact of mutations on pathogenesis comprised aCML (range: 1-7), CMML (1-6), MDS/MPN-U (2-5) and s-AML (2-8), whereas the lowest numbers (median n=0) were observed for CML (0-3), MGUS (0-2), MLN_eo (0-3), NK cell neoplasm (0-3) and PPBL (0-2). In the total cohort of 3096 cases, the most frequently mutated genes were TET2 (14%), ASXL1 (13%), TP53 (10%), SF3B1 (9%), DNMT3A (9%) and SRSF2 (9%). Entities with high frequencies of specific mutations (&gt; 50%) comprised: aCML (ASXL1, 86%), BPDCN (TET2, 67%), BL (TP53, 60%), CMML (TET2, 67%; ASXL1, 58%), FL (KMT2D, 87% and CREBBP, 73%), HCL (BRAF, 100%), LPL (MYD88, 98%; CXCR4, 51%), MDS/MPN-U (ASXL1, 60%), MPN (JAK2, 68%), B-NHL (TP53, 50%) and T-NHL (STAT3, 52%). Mutations enriched in distinct entities included SETBP1 (26% in MDS/MPN overlaps), CSF3R (30% in MDS/MPN-U), STAT3 (only in T-NHL and NK cell neoplasm, 52% and 23%), NOTCH1 and PHF6 (T-ALL, 38% and 30%) and MYC and ID3 (almost exclusively in BL, 30% each). Genes predominantly mutated in myeloid neoplasms comprised e.g. SF3B1 (with the exception of CLL), JAK2, NPM1, RUNX1, IDH2, CEBPA, STAG2, NF1 and GATA2. By contrast, mutations in KMT2D, MYD88, ARID1A, ATM, CXCR4, BIRC3 and CD79B were detected almost exclusively in lymphoid malignancies. A broad distribution across entities was observed for mutations in TET2, ASXL1,DNMT3A, TP53, BCOR and ETV6. Thus, the first three, i.e. CHIP-related genes were also mutated with a high frequency in lymphoid neoplasms. In line with this, gene mutations found in the largest number of entities comprise DNMT3A (n=23 entities), TET2 (n=21), ASXL1, TP53, NRAS (n=19, respectively), KRAS and BCOR (n=17, respectively). Further, we compared the mutational patterns of cases with at least one CHIP-associated mutation (n=920 cases in the total cohort, "CHIP+") with cases without such mutations (n=2176, "CHIP-") to decipher CHIP-correlated mutation patterns. Significant differences with respect to accompanying mutations were mainly detected for myeloid neoplasms (MDS, mutations in n=12 genes significantly different in CHIP+ vs. CHIP- without CHIP genes themselves; AML, n=7; MPN, n=4; aCML, n=2; CMML, n=1) but also for MPAL (n=3), T-ALL (n=2), B-ALL, FL and LPL (n=1, respectively). Mutations in TP53 were found significantly enriched in CHIP- cases in 4 different entities, moreover mutations in KRAS, WT1 and SF3B1 were more abundant in CHIP- cases (in CMML, AML and aCML, respectively). By contrast, CHIP+ cases were characterized by high frequencies of mutations in RUNX1 (in n=4 entities), SRSF2, IDH2, NRAS (n=3) and EZH2 (n=2). Conclusions: (1) Certain mutations showed a broad distribution within or even across the myeloid/lymphoid lineage, including CHIP-related mutations frequently detected also in lymphoid malignancies. (2) The median numbers of mutations were low in entities that are defined by chromosomal fusions (CML, MLN_eo) or in entities that are regarded as "pre-malignant" (MGUS, PPBL), while especially MDS/MPN overlap cases seem to be mutation-driven (high number of mutations). (3) We deciphered different mutation patterns in CHIP+ (RUNX1, SRSF2, IDH2, NRAS, EZH2) and CHIP- (TP53, KRAS, WT1, SF3B1) cases across all entities, suggesting differences in pathophysiology. Disclosures No relevant conflicts of interest to declare.

INTRODUCTION: Atypical chronic myeloid leukemia (aCML) is a rare subtype of myelodysplastic/myeloproliferative neoplasms (MDS/MPN) associated with shorter survival and higher risk of transformation to acute myeloid leukemia (AML) than other MDS/MPNs. However, the clonal mechanisms underlying transformation to leukemia remain unclear. There is a need to develop predictive models and identify the optimal therapeutic management of these pts. METHODS: We evaluated all consecutive pts with aCML treated at the University of Texas MD Anderson Cancer Center from 2005 to 2020. Whole bone marrow (BM) DNA was subject to 28 or 81 gene targeted next-generation sequencing (NGS) analysis in a subset of pts. Variant allele frequency (VAF) estimates were used to evaluate clonal relationships within each sample using Pearson goodness-of-fit tests and VAF differences. Response to therapy was assessed following MDS/MPN IWG response criteria. Cox proportional hazards regression was used to study association of variables with survival. RESULTS: A total of 65 pts were identified. Median age was 67 years (range 46-89). Median WBC, Hgb and platelets were 44.5x109/L (5.9-474.9x109/L) 10.0g/dL (5.7-14.7g/dL) 93x109/L (12-560x109/L), respectively. Median neutrophil, promyelocyte, myelocyte and metamyelocyte percentages were 64%, 0%, 0% and 16%. Forty-one (63%) pts had normal karyotype, 5 (8%) trisomy 8, 2 (3%) i(17q) and 2 (3%) del(20q). Splenomegaly was observed in 26 (40%) pts and 7 (11%) had extramedullary disease. NGS data was available in 35 (54%) pts. The most frequently mutated genes included ASXL1 in 83%, SRSF2 in 68% and SETBP1 in 58%. Frequency and VAF of identified mutations is shown in Figure 1A. Mutations in SETBP1, SRSF2, TET2 and GATA2 tended to appear within dominant clones while other RAS pathway mutations were more likely to appear as minor clones. SRSF2 and SETBP1 tended to be co-dominant while ASXL1 appeared within minor clones in up to 50% of pts (Figure 1B). Therapy consisted of single agent hypomethylating agent (HMA) in 19 (29%), hydroxyurea in 8 (12%), HMA in combination with ruxolitinib in 7 (11%), other HMA combinations in 5 (8%), ruxolitinib single agent in 5 (8), induction chemotherapy in 3 (5%) and other investigational agents in 1 (2%) pts. Response outcomes by therapy are detailed in Figure 1C. With a median follow up of 35.6 months (95% CI 28.2-43.1) 18 (28%) of pts experienced transformation to AML within a median of 18 months (1-123 months). Median survival after transformation of 8.3 months (95% CI 5.5-11.0 months). NGS at the time of transformation was available in 12 (67%) pts with matched NGS at diagnosis of aCML and AML in 8 (44%) pts. Acquisition of new previously undetectable mutations was observed in 5 pts the most common involving signaling pathway mutations (Figure 1D). Acquisition of new cytogenetic abnormalities was observed in 9/14 pts (Figure 1D) the most frequent involving i(17q). The median OS was 25 months (95% CI 20.0-30.0) with pts who received intensive chemotherapy having significantly worse OS than those receiving HMA-based therapy or other agents such as ruxolitinib or hydroxyurea (p=0.012, Figure 1E). By multivariate analysis for survival, age, platelet count, BM blast percentage and serum LDH levels influenced prognosis. Based on these factors we developed a multivariable Cox model to generate a nomogram which assigned a score to each of the prognostic variables and allowed to predict 1-year and 3-year OS based on the total score among all prognostic variables (Figure 1F). CONCLUSIONS: aCML is characterized by high frequency of co-dominant SRSF2 and SETBP1 mutations. HMA therapy is associated with the best response outcomes. Clinicopathological features can help predict outcomes of these pts. Figure 1 Disclosures Sasaki: Daiichi Sankyo: Consultancy; Novartis: Consultancy, Research Funding; Pfizer Japan: Consultancy; Otsuka: Honoraria. Jabbour:Genentech: Other: Advisory role, Research Funding; Amgen: Other: Advisory role, Research Funding; Adaptive Biotechnologies: Other: Advisory role, Research Funding; AbbVie: Other: Advisory role, Research Funding; Pfizer: Other: Advisory role, Research Funding; Takeda: Other: Advisory role, Research Funding; BMS: Other: Advisory role, Research Funding. DiNardo:Agios: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Notable Labs: Membership on an entity's Board of Directors or advisory committees; ImmuneOnc: Honoraria; Novartis: Consultancy; MedImmune: Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Syros: Honoraria; Daiichi Sankyo: Consultancy, Honoraria, Research Funding; Calithera: Research Funding; Jazz: Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Konopleva:F. Hoffmann La-Roche: Consultancy, Research Funding; Ablynx: Research Funding; Eli Lilly: Research Funding; Kisoji: Consultancy; Sanofi: Research Funding; Stemline Therapeutics: Consultancy, Research Funding; Agios: Research Funding; Genentech: Consultancy, Research Funding; Rafael Pharmaceutical: Research Funding; AbbVie: Consultancy, Research Funding; Forty-Seven: Consultancy, Research Funding; Calithera: Research Funding; Reata Pharmaceutical Inc.;: Patents & Royalties: patents and royalties with patent US 7,795,305 B2 on CDDO-compounds and combination therapies, licensed to Reata Pharmaceutical; Ascentage: Research Funding; Amgen: Consultancy; AstraZeneca: Research Funding; Cellectis: Research Funding. Pemmaraju:MustangBio: Honoraria; Incyte Corporation: Honoraria; Blueprint Medicines: Honoraria; Roche Diagnostics: Honoraria; LFB Biotechnologies: Honoraria; Stemline Therapeutics: Honoraria, Research Funding; Celgene: Honoraria; AbbVie: Honoraria, Research Funding; Pacylex Pharmaceuticals: Consultancy; Daiichi Sankyo: Research Funding; Affymetrix: Other: Grant Support, Research Funding; Plexxikon: Research Funding; Novartis: Honoraria, Research Funding; Samus Therapeutics: Research Funding; Cellectis: Research Funding; SagerStrong Foundation: Other: Grant Support; DAVA Oncology: Honoraria. Short:Takeda Oncology: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy; Amgen: Honoraria; Astellas: Research Funding. Issa:Novartis: Membership on an entity's Board of Directors or advisory committees; Syndax: Research Funding; Celegene: Research Funding. Kadia:Celgene: Research Funding; Abbvie: Honoraria, Research Funding; Novartis: Honoraria; Genentech: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Amgen: Research Funding; Incyte: Research Funding; Cellenkos: Research Funding; BMS: Honoraria, Research Funding; Ascentage: Research Funding; Astra Zeneca: Research Funding; Cyclacel: Research Funding; Pulmotec: Research Funding; Astellas: Research Funding; JAZZ: Honoraria, Research Funding. Ravandi:Amgen: Consultancy, Honoraria, Research Funding; Orsenix: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria, Research Funding; Xencor: Consultancy, Honoraria, Research Funding; Macrogenics: Research Funding; AstraZeneca: Consultancy, Honoraria; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria. Daver:Bristol-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Research Funding; Servier: Research Funding; Genentech: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novimmune: Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Trovagene: Research Funding; Fate Therapeutics: Research Funding; ImmunoGen: Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Trillium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Syndax: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Borthakur:AstraZeneca: Research Funding; PTC Therapeutics: Consultancy; Nkarta Therapeutics: Consultancy; Treadwell Therapeutics: Consultancy; Jannsen: Research Funding; Curio Science LLC: Consultancy; Novartis: Research Funding; Argenx: Consultancy; BioTherix: Consultancy; Polaris: Research Funding; BioLine Rx: Consultancy; Incyte: Research Funding; PTC Therapeutics: Research Funding; BioLine Rx: Research Funding; BMS: Research Funding; Cyclacel: Research Funding; Oncoceutics: Research Funding; Xbiotech USA: Research Funding; FTC Therapeutics: Consultancy; Abbvie: Research Funding; GSK: Research Funding. Verstovsek:Gilead: Research Funding; NS Pharma: Research Funding; Celgene: Consultancy, Research Funding; Genentech: Research Funding; Blueprint Medicines Corp: Research Funding; CTI Biopharma Corp: Research Funding; Protagonist Therapeutics: Research Funding; ItalPharma: Research Funding; Novartis: Consultancy, Research Funding; Incyte Corporation: Consultancy, Research Funding; Promedior: Research Funding; Roche: Research Funding; Sierra Oncology: Consultancy, Research Funding; PharmaEssentia: Research Funding; AstraZeneca: Research Funding. Kantarjian:Adaptive biotechnologies: Honoraria; Novartis: Honoraria, Research Funding; BioAscend: Honoraria; Daiichi-Sankyo: Honoraria, Research Funding; Immunogen: Research Funding; Jazz: Research Funding; Delta Fly: Honoraria; Janssen: Honoraria; Pfizer: Honoraria, Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Research Funding; Aptitute Health: Honoraria; BMS: Research Funding; Ascentage: Research Funding; Amgen: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; Oxford Biomedical: Honoraria. Bose:Blueprint Medicines Corporation: Honoraria, Research Funding; NS Pharma: Research Funding; Kartos Therapeutics: Honoraria, Research Funding; CTI BioPharma: Honoraria, Research Funding; Celgene Corporation: Honoraria, Research Funding; Astellas Pharmaceuticals: Research Funding; Incyte Corporation: Consultancy, Honoraria, Research Funding, Speakers Bureau; Pfizer, Inc.: Research Funding; Constellation Pharmaceuticals: Research Funding; Promedior, Inc.: Research Funding. Garcia-Manero:Celgene: Consultancy, Honoraria, Research Funding; H3 Biomedicine: Research Funding; Novartis: Research Funding; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astex Pharmaceuticals: Consultancy, Honoraria, Research Funding; AbbVie: Honoraria, Research Funding; Helsinn Therapeutics: Consultancy, Honoraria, Research Funding; Onconova: Research Funding; Acceleron Pharmaceuticals: Consultancy, Honoraria; Merck: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy; Amphivena Therapeutics: Research Funding.

Introduction NPM1mutation is considered a founder genetic event of acute myeloid leukemia withNPM1mutation (NPM1mut-AML). Nonetheless, growing evidence of pre-existing genetic mutations and clonal hematopoiesis (clonal response) after intensive AML treatment in many patients is being generated, although the precise clinical impact of this genetic background is mostly unknown. Thus, the emergence of a wild-typeNPM1myeloid neoplasm (NPM1wt-MN) after intensive chemotherapy treatment forNPM1mut-AML is a well-known phenomenon, but poorly described in long-term follow-up. Sequential genetic analysis with next generation sequencing (NGS) has the potential to elucidate the clonal origin of diverse emerging clinical scenarios occurring during clinical follow-up based on tracking of genetic evolution of clonal hematopoiesis status after AML treatment, as recently proposed (Hasserjian et al, Blood 2020). We aimed to analyze the incidence and clinico-biological characteristics ofNPM1wt-MN emerging after treatment forNPM1mut-AML in a long-term follow-up series from a single institution. Patients and Methods We included in the study 62 patients diagnosed withNPM1mutAML patients and treated with intensive chemotherapy according to two consecutive protocols of the Spanish CETLAM cooperative group (CETLAM-2003 and -2012). Patients were diagnosed between 2005 and May 2019.NPM1wt-MN has been classified according to recent criteria proposed by Hasserjian et al, Blood 2020. Statistical analyses were performed using Rv3.1 and SPSS v20. Next generation targeted sequencing (NGS) was performed with Ion Ampliseq AML Research and Oncomine Myeloid Research Assay panel. Results The cohort included 62 patients (median age, 53 years, 25-73) with a median follow-up of alive patients of 44 months. After induction therapy, 58 patients (pt) achieved complete remission (CR) and 21 pt relapsed asNPM1mut-AML. Additionally, 9 pts (15%) developed aNPM1wt-MN: 4 (7%) presented aNPM1wt-AML relapse and 5 (8%) developed otherNPM1wt-MN (non-AMLNPM1wt-MN) that would be classified as residual myeloid neoplasm according to proposed criteria: 1 myelodysplastic syndrome, 3 myeloproliferative/myelodysplastic syndrome [2 CMML and 1 atypical chronic myeloid leukemiaBCR-ABLnegative (aCML)] and 1 polycythemia vera (PV) Characteristics of the 3 groups (NPM1mut-AML,NPM1wt-AML, non-AMLNPM1wt-MN) are shown in the Table. Median time from CR achievement to progression was longer in the group who developed a non-AMLNPM1wt(24 vs 8 months; p=0.016), and an statistical trend of younger ager in pts with AML-NPM1mutgroup (48 vs 69 vs 60 years-old, respectively, p=0.056) and lower leucocyte count in pt presenting a non-AMLNPM1wt-MN (5.5 vs 29 vs 50 x109/L, respectively, p=0.065) were observed. Moreover, among 19 pts with available NGS at diagnosis,DNMT3Amutation was more frequently comutated inNPM1mut-AML (71% vs 0%vs 40%, respectively p=0.034) andSRSF2was more frequently mutated in non-AMLNPM1wt-MN (60% vs others (0%), p=0.01). Interestingly, outcome of patients presenting with AML relapse did not differ according to NPM1 status at relapse (NPM1mut-AML vs.NPM1wt-AML), with a similar response rate after salvage chemotherapy (80% vs 75%, p=NS) and OS (5-year OS: 75±40% vs 60±20%; p=NS). NGS analysis of paired samples at diagnosis and emergentNPM1wt-MN in pts who lostNPM1mutation at progression is detailed in Figure. Frequently persisting mutations were those usually found in clonal hematopoiesis such as DNA methylation (TET2, DNMT3A, IDH1, IDH2), chromatin remodeling ASXL1, and splicing factor SRSF2, whereasFLT3mutation was the most frequently lost at relapse.TP53, PTPN11,SETBP1, JAK2, IDH1oASXL1were mutations gained at time of NPM1wt-MN emergence. Conclusions A proportion of pts withNPM1mut-AML will develop an NPM1 wild-type myeloid neoplasm after intensive chemotherapy-induced CR, emerging from preleukemic clonal hematopoiesis. Given this possible evolution, which can not be predicted byNPM1mutmeasurable residual disease monitoring, an active surveillance of these pts is recommended, including genetic re-testing at time of disease relapse or progression. Acknowledgement:PI16/01027 (JE; MDB), PI19/01476 (JE; MDB) Table:Characteristics at diagnosis depending on type of progression. Figure:Mutations in paired samples (diagnosis/relapse) of patients who developed aNMPwt-MN. Figure Disclosures No relevant conflicts of interest to declare.

Abstract Introduction: Using next generation sequencing (NGS) in monitoring residual disease in patients with myeloid neoplasms is complicated by the significant heterogeneity in these diseases and the frequent presence of CHIP (clonal hematopoiesis of indeterminate potential) in patients with hematologic neoplasms on which these neoplasms arise. This is particularly relevant post hematopoietic stem cell transplant (HSCT). We explored the ability of using plasma cell-free DNA (cfDNA) in monitoring patients after HSCT and evaluated the potential of using liquid biopsy as a replacement for bone marrow biopsy. Method: cfDNA was isolated from 204 peripheral blood samples obtained from 75 patients, collected at various time points ranging from 27 days to 650 days (median 178 days) post-transplant. DNA from 102 bone marrow (BM) samples was extracted and sequenced using the same panel and approach as cfDNA. Diagnoses included 30 acute myeloid leukemia (AML), 2 chronic myelogenous leukemia (CML), 5 chronic myelomonocytic leukemia (CMML), 4 lymphoma, 10 myelodysplastic syndrome (MDS), 2 multiple myeloma (MM), 9 myeloproliferative neoplasm (MPN), 1 aplastic anemia, and 11 acute lymphoblastic leukemia. cfDNA was sequenced by NGS using 177 gene panel on Illumina platform. Single primer extension (SPE) approach with UMI was used. Sequencing depth was increased to more than 2000X after removing duplicates. Low-level mutations were confirmed by inspecting BAM file. Results: 156 cfDNA samples (76%) tested negative and 48 samples from 30 different patients were positive. The negative samples were collected from 28 days to 650 days post-transplant (median 277 days). The positive samples were collected from 27 days to 650 days post-transplant (median 188 days). One of these positive patients was in full clinical relapse at the time of testing. No negative patient who remained negative had clinical relapse. Five patients converted from negative to positive and 12 from positive to negative with subsequent testing. Three from the converted to positive patients developed clinical relapse. Patients who were positive without clinical relapse had median variant allele frequency (VAF) of 0.85% (range: 0.01-13.25) and typically one mutated gene. The mutated genes in this group were: JAK2, IDH2, ASXL1, TET2, DNMT3A, ASXL1, PTPN11, SF3B1, MPL, CEBPA1. Patients who had clinical relapse (#4) had median VAF of 16.33% (0.4%-57.63%) with multiple mutated genes. The mutated genes in this group were: TP53, FLT3, ASXL1, CEBPA, EZH1, NRAS, SETBP1, TET2. To evaluate relevance to BM testing, we compared BM samples with cfDNA samples collected within 120 days of each other. This showed 17 pairs with concordant negative results, 10 with concordant positive results, 5 pairs with positive by cfDNA but negative by BM cells, and one pair with positive by BM but negative by cfDNA. This BM positive sample was performed at 78 days after the cfDNA sample and showed mutation in DNMT3A gene at VAF of 0.63%. Four of the 5 pairs with positive cfDNA but negative BM were collected approximately 3 months after bone marrow and the 5th case was one month prior to BM sample. Conclusion: These data suggest that monitoring residual disease after HSCT using cfDNA and NGS is a reliable approach and may replace the need of bone marrow biopsy. However, low-level mutations should not be used as the sole criterion for determining relapse. Variant allele frequency and the mutated gene should be considered in evaluating actionable findings. Disclosures Pecora: Genetic testing cooperative: Membership on an entity's Board of Directors or advisory committees; Genetic testing cooperative: Other: equity investor. Rowley: ReAlta Life Sciences: Consultancy.

Abstract Acute erythroid leukemia (AEL) is a distinct subtype of acute myeloid leukemia (AML) characterized by predominant erythropoiesis. Currently, only few studies using next-generation sequencing were reported in AEL. To decipher the somatic mutation spectrum and discover disease-driving genes responsible for the pathogenesis of AEL, we performed whole exome-sequencing (WES) in 6 AEL and validating using targeted next generation sequencing (NGS) and Sanger sequencing in 58 AEL. From August 2003 to October 2014, a total of 158 patients fulfilling the WHO criteria for AEL were identified, comprising 91 males and 67 females. Median age was 50 years. These patients were further subclassified into 3 groups: 37 AEL after MDS, 108 de novo AEL, and 13 AML with myelodysplasia-related changes. In total, we identified 52 genes with somatic mutations in at least 2 patients, including CEBPA in 4 patients and GATA2 in 2 patients. We identified high frequencies of mutations in CEBPA (40.0%, 22/55; about 1/4 are biallelic mutations), GATA2 (22.4%, 13/58), NPM1 (15.5%, 9/58), SETBP1 (12.1%, 7/58), and U2AF1 (12.1%, 7/58), followed by TP53 (5.2%, 3/58), RUNX1 (3.5%, 2/58), TET2 (3.5%,2/58), ASXL1 (3.5%, 2/58), DNMT3A (3.5%, 2/58), SRSF2 (1.7%, 1/58) and FLT3 (1.7%, 1/58). We did not detect alterations of some of commonly mutated genes associated with AML, including IDH1, IDH2 and RAS. The results are summarized in Figure 1. To further identify the prevalence of GATA2 mutations in hematologic malignancies, we amplified and sequenced the entire coding region of GATA2 gene in 253 non-AEL AML, 40 chronic myeloid leukemia in blast crisis (CML-BC), 55 B-cell acute lymphoblastic leukemia (B-ALL), and 38 T-cell acute lymphoblastic leukemia (T-ALL). We detected GATA2 mutations in 5.5% of non-AEL AML, 15% of CML-BC, and none of B-ALL or T-ALL. The GATA2 mutations in AEL are mainly localized in ZF1 domain (P304H, D309E, A318V/T, G320S/D, L321P, and R330X) and TAD domain (Q20H). To find out the implications of GATA2 mutations in the leukemogenesis of AEL, we overexpressed the mutants of GATA2 (P304H, L321P, and R330X) in 293T cells and demonstrate that GATA2 mutant led to reduced transcriptional activity. Whereas overexpression of GATA2 mutants in mouse myeloid progenitor cell line, 32D, has no effect on the proliferative or colony formation abilities, it caused increased expression of erythroid-related antigen Ter-119 (Figure 2), b-globin and bh1-globin. Furthermore, 32D cells transfected with GATA2 mutants showed increased positivity than control cells by Benzidine staining. Taken together, our findings demonstrate that the mutatome of AEL is different from other types of AML. AEL is associated with a high frequency of mutations in GATA2 and CEBPA. GATA2 mutations resulted in a decrease of transcriptional activity and erythroid development of mouse myeloid progenitors, suggest an important role of GATA2 mutations in AEL. Figure 1. Figure 1. Figure 2. Figure 2. Disclosures No relevant conflicts of interest to declare.

Abstract Aims: The onset of blast crisis (BC) in initially chronic phase (CP) CML patients that entered treatment-free remission (TFR) after TKI is an exceptional event, however, there is emerging evidence that this may occur in such patients (pts), although the pathogenesis remains unclear to date. Methods: Anonymous clinical case retrospective data collection from patients' datafiles, after written agreement of living patients, centralisation of available frozen nucleic acid collection from diagnosis and from blast crisis and reanalysis by Next-Generation Sequencing of samples (ASXL1, ASXL2, BCOR, CALR, CBL, CEBP alpha , CSF3R, DNMT3A, EP300, ETNK1, ETV6, EZH2, FLT3, GATA2, IDH1, IDH2 JAK2, KIT, , KRAS,MPL, NPM1, NRAS, PHF6, PTPN11 , RAD2, RUNX1, SETBP1, SF3B1, SH2B3, SMC1A, SMC3, SRSF2, STAG1, STAG2, TET2, TP53, U2AF1, WT1 and ZRSR2 genes analysed) on Illumina platform. CNV analysis were performed using VisCAp or in-house pipelines and/or by Multiplex Ligation Dependant Probe Amplification (MLPA). ABL1 tyrosine kinase domain mutations were screened by NGS on cDNA or directly on DNA. BCR-ABL1 transcripts are expressed in % (IS) with at least 32,000 copies of ABL1 as control. All patients discontinued their TKI after 2 years of MR4.5 and a TKI was resumed in case of MMR loss. Results: Along 15-year experience of TFR in our country and ≥ ~800 patients experiencing a TKI cessation attempt, informations from 4 (~0.5%) TFR CML patients entering BC have been collected. All patients harboured Major BCR transcripts. The chronic phase characteristics are mentioned in Table 1. All these long-lasting CP CML pts were ELTS risk score low, and 1 was harbouring ACA at diagnosis. One pt was mutated for ASXL2 and 2 mutations for EP300, found again at BC. Three pts had IFN-a prior to imatinib for all. Three out of 4 lost their MMR after a first cessation attempt at 12, 10 and 3 months after cessation. Pt #1 experienced a 2 nd cessation attempt 52 months after re-initiation of TKIs and entered lymphoid BC 6 months after a second resumption of TKI for a 2 nd MMR loss. The BC characteristics are mentioned in Table 2. Three out of 4 BC were lymphoid, one had ACA different from those at CP diagnosis. Two pts explored had multiple mutations in Runx1, U2AF1, EP300 and ASXL2 genes, not present at CP diagnosis, in addition to multiple ABL1 mutations in 2 out of 4 pts (2 T315I, 3 P-Loop mutations). All pts underwent chemotherapy + various TKI leading to complete remission (CR) in all and 3 out of 4 pts could be allotransplanted in CR, one relapsed shortly after transplant, and a second one 34 months after transplant. Overall 3 pts are alive with 1 in controlled relapse. Conclusions: The onset of BC after TFR for sustained deep molecular response remains an exceptional event and is probably not induced by this therapeutic procedure. These 4 cases underline the need for a sustained long-lasting molecular follow-up of pts in TFR, although the majority of these BC seem sudden. Figure 1 Figure 1. Disclosures Bauduer: Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Rea: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees. Nicolini: Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel, accommodations, expenses, Research Funding; Sun Pharma Ltd.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kartos Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Incyte Biosciences: Honoraria, Other: travel, accommodations, expenses, Research Funding, Speakers Bureau; BMS: Honoraria.

Abstract Background: In a subset of CML patients treated with tyrosine kinase inhibitors (TKI) primary or secondary resistance has been observed. Depending on disease state and treatment, in around 30-90% of these cases secondary mutations in the ABL1 part of the BCR-ABL1 fusion gene have been described which became clear indicators for change of therapy. In addition, also cytogenetic evolution is correlated to TKI resistance. However, in a high percentage of cases the reason for TKI resistance remains unclear, yet. Aim: We hypothesized that mutations in genes frequently involved in myeloid malignancies may contribute to resistance to TKI. Methods: We investigated 34 CML patients with no response or loss of response to TKI defined by clinical parameters and a BCR-ABL1 level >10%. Median age of patients was 54 years (range: 33-88 years), 22 were male and 12 female. At the time point of analysis 9 patients had received imatinib only, 16 patients had received 2 TKIs, 7 had 3 TKIs, and 2 even 4 TKIs (one of those in addition had undergone stem cell transplantation, SCT). In 24 cases primary resistance and in 10 cases secondary resistance after initial response to imatinib was observed. Samples for subsequent analyses were from the time point of BCR-ABL1 mutation analysis performed upon clinically suspected TKI resistance and in none any BCR-ABL1 mutation was identified by Sanger sequencing at a sensitivity level of 10-20%. For these samples we applied a pan-myeloid panel of 32 genes: ASXL1, BCOR, BRAF, CALR, CBL, CSF3R, DNMT3A, ETV6, EZH2, FLT3-TKD, GATA1, GATA2, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NPM1, NRAS, PHF6, PTPN11, SETBP1, SF1, SF3B1, SRSF2, TET2, TP53, U2AF1, WT1, ZRSR2. Either complete coding regions or hotspots were first amplified by a microdroplet-based assay (RainDance, Billerica, MA) and subsequently sequenced with a MiSeq instrument (Illumina, San Diego, CA). In addition, RUNX1 was sequenced on the 454 NGS platform (454 Life Sciences, Branford, CT). For backtracking of mutations also deep sequencing by 454 technology was performed. Results: In 18 of the 34 patients (52.9%) mutations were detected. In a large subset of 12 cases (66.7%) ASXL1 was the only mutated gene. The other 6 cases had mutations in 1) RUNX1, 2) IDH1, 3) DNMT3A, 4) BCOR, 5) DNMT3A and WT1, and 6) NRAS, PTPN11, RUNX1 and WT1, respectively. Median mutation loads were 25% (range 4-53%). In order to assess the kinetics and onset of these mutations backtracking in 91 prior samples was performed. 11 of the 12 ASXL1 mutations were detected in cases with primary TKI resistance. In 7 of these patients samples from diagnosis of CML were available and ASXL1 mutations were already present at high levels in all of them. The pattern obtained from the backtracking analysis clearly showed that the ASXL1 mutation load closely correlates with the BCR-ABL1 expression (3 examples are shown in the figure). In only one patient with secondary resistance the ASXL1 mutation was gained after 40 months of imatinib treatment. Results of the other 6 patients are as listed in the following (numbering as indicated above). 1) A RUNX1 mutation with 40% load was detected after 6 months of dasatinib treatment. This case was negative for this mutation before and during 2 years of imatinib treatment. 2) An IDH1 mutation was gained 1 year after start of nilotinib treatment. 3) and 4) Backtracking is ongoing in patients. 5) DNMT3A and WT1 mutations both were gained after 34 months of imatinib treatment. 6) The 4 mutations in this patient were not present at diagnosis and detected for the first time after 22 months of treatment with 3 consecutive TKIs and upon non-response to allogeneic SCT. These results show that mutations can occur during any kind of TKI treatment, but also are frequently present already at the time of CML diagnosis. These gene mutations are considered to contribute to TKI resistance in both scenarios. Conclusions: 1) Mutations known from other myeloid malignancies are frequently present in CML patients that do not respond to or lost response to TKI treatment and lack BCR-ABL1 resistance mutations. 2) The courses of these mutations clearly parallelize with the courses of the BCR-ABL1 positive clones. 3) ASXL1 is the most frequently mutated gene. 4) These mutations are additional genetic hits that point to a more aggressive and treatment resistant biology of the BCR-ABL1 positive clone and 5) may indicate that alternative therapies besides TKI inhibitors are needed in these cases. Figure 1 Figure 1. Disclosures Schnittger: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Fasan:MLL Munich Leukemia Laboratory: Employment. Rose:MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.