ASXL1 Mutational Status Research Articles

Mutation Analysis of ASXL1 in Normal Karyotype Myelodysplastic Syndromes: Experience From Pakistan

ABSTRACTBackgroundThe challenges in advancing treatment modalities for myelodysplastic syndromes (MDS) may stem from an incomplete understanding of the disease's complex pathophysiology and lack of reliable prognostic molecular markers. Advanced genomic techniques have revolutionized disease prognosis and risk stratification, particularly for cases with a normal karyotype.AimThe present study aimed to analyze ASXL1 mutations in MDS exhibiting a normal karyotype.Methods and ResultsThe study enrolled 41 MDS patients with normal karyotypes. Genomic DNA was extracted from peripheral blood samples, followed by Sanger sequencing. The Chi‐square and Mann–Whitney U tests were applied to assess the association of age and hemogram with the occurrence of mutations. Survival analysis was done via the Kaplan–Meier method. Statistical operations were performed employing the IBM SPSS Statistics version 24. The patients had a median age of 40 years comprising 28 (68.3%) males and 13 (31.7%) females. ASXL1 mutations were identified in 8 (19.5%), particularly stopgain single nucleotide variant (SNV) and frameshift insertion. The median total leucocyte count × 109/L and blast percentage among the patients with ASXL1 mutation were 3.9 and 4.5, respectively. A survival of 85 weeks was recorded for ASXL1‐mutated and nonmutated cases. The association of ASXL1 mutation status with age and studied hematological parameters was found nonsignificant.ConclusionASXL1 mutation plays a pivotal role in MDS prognosis, warranting assessment at diagnosis for risk stratification and treatment decisions. Early identification of ASXL1 mutation, particularly in low‐risk patients or those with normal karyotype, is imminent to identify patients exhibiting unfavorable prognosis. Integrating molecular insights into existing risk assessment holds significance for improved clinical outcomes, reduction in disease progression, and ultimately the improved quality of life and should be identified early in the course of disease even in the developing world.

ASXL1 Truncating Mutations Drive Leukemic Resistance to T Cell Attack

Restoration of graft-versus leukemia activity underlies the efficacy of donor lymphocyte infusion (DLI), a curative immunotherapy for leukemic relapse following allogeneic stem cell transplant (SCT). We found that while specific exhausted T cell subsets defined DLI response, no pattern of T cell dysfunction appeared in nonresponders (NRs) [PMID: 34758319]. We hypothesized that leukemic molecular pathways define DLI resistance (DLIr). We performed whole exome sequencing on bone marrow samples collected before and after DLI from 11 patients (pts) with relapsed chronic myeloid leukemia (CML) at Dana-Farber Cancer Institute. We used MuTect2 to discover somatic alterations using genomic DNA from recipient-derived mesenchymal stromal cells and donor peripheral blood cells as germline sources. The burden of nonsynonymous mutations and mutational spectra was similar between responders (Rs) and non-responders (NRs). Known non-Philadelphia (Ph) chromosome cancer drivers were found in 0/7 Rs and 4/4 NRs (RUNX1 (1/4), IKZF1 (2/4), and truncating exon 12 ASXL1 mutations (ASXL1 m) (3/4)). We profiled 6 more DLI-treated pts with relapsed CML from the MD Anderson Cancer Center with a targeted mutation panel that identified ASXL1 m in 4/5 NRs. Altogether, we found ASXL1 m in 78% (7/9) of NRs and 0% (0/10) of Rs (p=7e-4, two-sided Fisher's test), suggesting ASXL1 m as a driver of DLIr. To discover molecular pathways of DLIr, we interrogated unpublished non T-cell single cell (sc)RNA-seq data in our DLI cohort (8 R, 6 NR). Leukemic cells were identified for patients (n=8) with sex-mismatched SCT by male sex-defining genes, which correlated with Ph chromosomal positivity (Pearson correlation = 0.85). These cells were primarily confined to the myeloid population, so we performed a scRNA myeloid reclustering (138,152 cells) with Harmony batch correction and identified 5 populations enriched in R vs NR; 4 clusters in NR, and 1 monocyte cluster in R (p=0.039, 0.005, 0.038, 0.043, and 0.025, respectively). These NR clusters were enriched in progenitor cell identities, notably the LSC17 [PMID: 27926740] signature (p<2e-16). Interrogation of immune pathways in the LSC cluster showed downregulation of HLA-I and multiple antigen processing/presentation (APP) genes in NRs (p<2e-16), while HLA-II remained unchanged. Thus, ASXL1 m may mediate immune escape through suppression of HLA-I expression and antigen presentation. To directly test this hypothesis, we CRISPR corrected the endogenous ASXL1 m (Y591*) in a BCR-ABL-driven leukemic cell line (K562). This wildtype reversion (ASXL1 c) increased HLA-I expression at the RNA (RNA-seq; HLA-B/C, log2foldchange= -4.77, q=7e-42) and protein level (flow cytometry; 49.0% vs 1.62%, q=2e-4); here too, HLA-II expression remained unaffected by ASXL1 mutation status. Gene-set enrichment analysis also showed increased APP expression in ASXL1 c K562 (NES=-1.75, q=0.01). We then sought to identify whether correction of ASXL1m acted through known regulators of HLA-I. Treatment with IFNɣ or EPZ011989, an inhibitor of enhancer of zeste-homolog 2 (EZH2), resulted in greater HLA-I in K562 ASXL1 c (85.0% vs 50.2% and 89.5% vs 39.3%, respectively, q<0.001) suggesting that ASXL1 cacts orthogonally to IFNɣ or EZH2. ASXL1 c also mediated increased T-cell cytotoxicity towards K562 ASXL1 c vs ASXL1 m without (43% vs 16%, q=2e-4) and with IFNɣ pre-treatment (71% vs 34%, q=1e-6) at 10:1 target to effector ratios. Finally, to study other disease contexts, we examined published sc chromatin accessibility and scRNA-seq data from a chronic myelomonocytic leukemia cohort [PMID: 35301312] and an acute myeloid leukemia cohort [PMID:32649887], respectively. We found both chromatin and transcriptional states enriched in ASXL1m samples to have decreased accessibility and expression, respectively, of HLA-I and APP genes (p<2E-16). In summary, we integrated molecular analyses with immuno-functional studies to define a novel oncogenetic pathway of immune evasion. Specifically, we link DLIr to ASXL1 m that suppresses transcription of HLA-I and antigen presentation machinery in myeloid diseases; moreover, its correction restores anti-leukemic CD8+ T-cell cytotoxicity. Ongoing studies will examine additional clinical contexts and the epigenetic mechanisms by which ASXL1m regulates HLA-I expression.

ASXL1/ TET2 Genotype-Based Risk Stratification Outperforms ASXL1 Mutational Impact and Is Independent of Mutant Variant Allele Fractions (VAF) in CMML

Introduction Truncating ASXL1 mutations in chronic myelomonocytic leukemia (CMML) are associated with inferior overall survival (OS) and leukemia free survival (LFS). Conversely, loss-of-function mutations in TET2 are associated with better outcomes, with the ASXL1wt/ TET2mut genotype being associated with the best OS and LFS-rates (Coltro G, et al. Leukemia. 2020). Contemporary CMML prognostic scoring systems - such as the Mayo Molecular Model (MMM; Patnaik MM, et al. Leukemia. 2014) and the CPSS-Molecular Model (CMM; Elena C, et al. Blood. 2016) - do not consider concomitant ASXL1/ TET2 mutational status or mutational VAF. We hypothesized that the ASXL1/ TET2 genotype would better risk stratify patients in comparison to ASXL1 mutations alone, and that this effect would be proportional to the underlying mutational VAF. Methods After IRB approval, we compiled a large (n = 888), molecularly annotated database of CMML patients seen at two US medical centers (Mayo Clinic and MD Anderson) via retrospective chart review. All statistical analyses considered the clinical and laboratory parameters obtained at the time of presentation to the respective institution. Categorical variables were compared by Fisher exact or Pearson χ 2 tests and continuous variables by Mann-Whitney U tests. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Survival was assessed via the Kaplan-Meier method. P-values < 0.05 were considered significant. All statistical calculations were performed using the BlueSky Statistics (v10.3.1) interface for R. Results The median age of the cohort was 71 years (range 20 - 94), 67% were male, 46% had proliferative CMML (pCMML), and 19% had CMML-2. The distribution of low, intermediate-1, intermediate-2, and high-risk patients was 15%, 11%, 32%, and 42% by the MMM and 9%, 23%, 40%, and 28% by the CMM, respectively. The most frequently mutated genes were ASXL1 (45%), TET2 (43%), SRSF2 (41%), and RUNX1 (17%), while 40% harbored at least one RAS pathway mutation ( NRAS 16%, CBL 15%, KRAS 8%, PTPN11 4%, FLT3 2%). The median OS and LFS of the entire cohort were 31.8 months (95% CI 28.4 - 33.5 months) and 28.4 months (95% CI 24.6 - 32.1 months), respectively. Patients were stratified into ASXL1wt/ TET2wt (28%), ASXL1mut/ TET2wt (29%), ASXL1wt/ TET2mut (26%), and ASXL1mut/ TET2mut (17%) genotypes. Those with isolated TET2 mutations had the longest median OS (53.6 months; p < 0.02 for all comparisons) whereas those with isolated ASXL1 mutations had the shortest median OS (20.9 months; p < 0.04 for all comparisons); mutations in neither or both genes performed similarly (p = 0.9224; Figure 1A). The same trend was seen for LFS. We further hypothesized that the ASXL1 or TET2 mutation VAF would be more predictive of outcomes than a binary metric. The respective median VAFs were 37% (quartiles 28% - 45%) and 45% (quartiles 40% - 49%). When treated as a continuous variable, however, there was no correlation between either VAF and OS or LFS by both Pearson linear regression and Cox proportional hazard modeling. Unlike the overall cohort, the ASXL1/ TET2 genotypes did not further stratify patients with pCMML, CMML-2, or those considered high risk by the CMM in Kaplan-Meier analyses, suggesting that the high-risk features inherent in these subgroups outweigh the benefits of the TET2 mutation. In contrast, patients considered high-risk by the MMM were further stratified by the ASXL1/ TET2 genotypes. Incorporating TET2 mutations into the MMM as a protective factor (worth -1.5 points) improved detection of low- (≤ 1 point) and high-risk (≥ 4 points) patients, while intermediate-1 and intermediate-2 coalesced into a single intermediate risk category ( Figure 1B). A similar phenomenon was observed when TET2 was incorporated into the CMM (worth -1 point, yielding low- (0 points), intermediate- (1-2 points), and high-risk (≥ 3 points) groups with median OS of 83 months (95% CI 66.2 - 104.2), 34.3 months (95% CI 31.6 - 38.7), and 17.7 months (95% CI 15.7 - 20.2), respectively. Conclusions Truncating and hypomorphic TET2 mutations are associated with better outcomes in CMML, with the ASXL1mut/ TET2wt genotype being associated with improved risk stratification in comparison to ASXL1 mutational status alone. Counterintuitively, in our data set, this stratification was not impacted by mutational VAF, supporting binary mutational assessments in prognostic models.

Comprehensive genomic profiling reveals molecular subsets of ASXL1-mutated myeloid neoplasms

A large-scale genomic analysis of patients with ASXL1-mutated myeloid disease has not been performed to date. We reviewed comprehensive genomic profiling results from 6043 adults to characterize clinicopathologic features and co-mutation patterns by ASXL1 mutation status. ASXL1 mutations occurred in 1414 patients (23%). Mutation co-occurrence testing revealed strong co-occurrence (p < 0.01) between mutations in ASXL1 and nine genes (SRSF2, U2AF1, RUNX1, SETBP1, EZH2, STAG2, CUX1, CSF3R, CBL). Further analysis of patients with these co-mutations yielded several novel findings. Co-mutation patterns supported that ASXL1/SF3B1 co-mutation may be biologically distinct from ASXL1/non-SF3B1 spliceosome co-mutation. In AML, ASXL1/SRSF2 co-mutated patients frequently harbored STAG2 mutations (42%), which were dependent on the presence of both ASXL1 and SRSF2 mutation (p < 0.05). STAG2 and SETBP1 mutations were also exclusive in ASXL1/SRSF2 co-mutated patients and associated with divergent chronic myeloid phenotypes. Our findings support that certain multi-mutant genotypes may be biologically relevant in ASXL1-mutated myeloid disease.

Long-Term Follow-up and T Cell Characteristics of Patients with ASXL1-Mutated Relapsed or Refractory MDS or CMML Treated with Guadecitabine and Atezolizumab

Background Treatment of patients with myelodysplastic syndrome (MDS) or chronic myelomonocytic leukemia (CMML) after failure of a hypomethylating agent (HMA) remains an unmet need. We and others demonstrated a modest overall response rate (ORR) to the combination of immune checkpoint inhibition (ICI) and an HMA in such patients; a promising overall survival (OS) compared to historical data (5-6 months) was seen in some, but not all, studies. Our study and that of Daver et al. suggested that patients with ASXL1 mutations, in particular, may benefit from the addition of ICI. We conducted a Phase I/II clinical trial evaluating the addition of a programmed death ligand 1 (PD-L1) inhibitor, atezolizumab, to a subcutaneous prodrug of the HMA decitabine, guadecitabine. We evaluated the presence of common driver mutations in CD3- bone marrow mononuclear cells (BMMC) and CD3+ T lymphocytes. Among 27 tested patients, 12 had the ASXL1 mutations in the myeloid compartment and, of those, 5 patients' T cells carried the exact same mutation at a variant allele frequency (VAF) of &amp;gt;10%. Both patients with complete remission in the study (n=2) carried the mutation in both compartments (co-mutated) and median OS was significantly better for co-mutated patients (not reached) than for those with CD3- BMMC (myeloid) mutations (9.5 months) or wild type ASXL1 (16.5 months). Herein we report long-term follow-up of this cohort of patients, along with T cell programmed death-1 (PD-1) expression analyzed based on mutational status. Methods Details of the trial design and correlative plan are published. In the published study we used a VAF cutoff of 2% (1% for TP53) for BMMC and 10% for CD3+ T lymphocytes for the panel of 40 commonly mutated genes. In the current study we also evaluated patients with a T cell ASXL1 VAF of 5-10%. Patients have been followed for progression and survival every 6 months. Demographic and disease characteristics and outcome data were compared based on ASXL1 mutation status. Previously obtained T lymphocyte PD-1 expression data from samples obtained pre-treatment (PRE), during cycle 2 (EARLY) and after cycle 3 or 4 (LATE) were analyzed based on ASXL1 mutation status. Results Among 27 patients from 4 centers with DNA available for genetic analysis, 15 had no ASXL1 mutation ( ASXL1 WT), 5 had ASXL1 mutations restricted to the myeloid lineage, and 7 had ASXL1 mutations in both the myeloid and T-cell populations ( ASXL1 co-mutated). Two co-mutated patients had T cell VAFs of 5-10% and 5 had VAFs&amp;gt;10% (Figure 1). No baseline characteristic by ASXL1 mutational status was significantly associated with response to study treatment, though 6 of 7 co-mutated patients (vs 3/5 myeloid-only patients) had not responded to first-line HMA (refractory). With a median follow-up time of 64.9 months, median survival times were 48.9 months (15.1, 64.9+) for co-mutated patients with T cell VAF &amp;gt;10%, 34.9 months (8.5, NR) for co-mutated patients including those with T cell VAF of &amp;gt;5%, 16.4 months (3.3, 27.3) for ASXL1 WT patients, and 9.5 months (2.1, 35) for myeloid-only patients (Figure 2). This was statistically significant after adjusting for age and ECOG performance status at study entry, diagnosis, baseline bone marrow blast percentage, and number of prior chemotherapy regimens using the likelihood ratio test from multivariate analysis for overall survival (P = 0.008). Early treatment-induced upregulation of CD8 + T cell PD1 was observed in the ASXL1 WT, before returning to baseline levels. This upregulation was more pronounced in the ASXL1 co-mutated group beginning at a lower baseline and peaking at a higher MFI and was statistically significant (P = 0.0098). No significant treatment-induced change in PD-1 expression was noted in the myeloid-only subset. Discussion In patients with relapsed or refractory MDS or CMML, the presence of an ASXL1 mutation in both myeloid and T lymphocyte compartments, as compared to WT or myeloid-only mutations, was associated with a significantly longer median OS when treated with the combination of ICI and HMA. Significant upregulation of PD-1 was noted in T lymphocytes from both wild-type and co-mutated patients. The effect of mutant ASXL1 on T cell responsiveness to ICI deserves further investigation; patients with ASXL1-mutated HMA-refractory myeloid malignancies may benefit from ICI.

Genomic landscape of patients with FLT3-mutated acute myeloid leukemia (AML) treated within the CALGB 10603/RATIFY trial

The aim of this study was to characterize the mutational landscape of patients with FLT3-mutated acute myeloid leukemia (AML) treated within the randomized CALGB 10603/RATIFY trial evaluating intensive chemotherapy plus the multi-kinase inhibitor midostaurin versus placebo. We performed sequencing of 262 genes in 475 patients: mutations occurring concurrently with the FLT3-mutation were most frequent in NPM1 (61%), DNMT3A (39%), WT1 (21%), TET2 (12%), NRAS (11%), RUNX1 (11%), PTPN11 (10%), and ASXL1 (8%) genes. To assess effects of clinical and genetic features and their possible interactions, we fitted random survival forests and interpreted the resulting variable importance. Highest prognostic impact was found for WT1 and NPM1 mutations, followed by white blood cell count, FLT3 mutation type (internal tandem duplications vs. tyrosine kinase domain mutations), treatment (midostaurin vs. placebo), ASXL1 mutation, and ECOG performance status. When evaluating two-fold variable combinations the most striking effects were found for WT1:NPM1 (with NPM1 mutation abrogating the negative effect of WT1 mutation), and for WT1:treatment (with midostaurin exerting a beneficial effect in WT1-mutated AML). This targeted gene sequencing study provides important, novel insights into the genomic background of FLT3-mutated AML including the prognostic impact of co-mutations, specific gene–gene interactions, and possible treatment effects of midostaurin.

Clinical Characteristics and Outcome of Patients with EZH2- Mutant Myelodysplastic Syndromes

Clinical Characteristics and Outcome of Patients with EZH2- Mutant Myelodysplastic Syndromes

Outcome with Hypomethylating Agent and Venetoclax Combination in Patients with Chronic Myelomonocytic Leukemia

Outcome with Hypomethylating Agent and Venetoclax Combination in Patients with Chronic Myelomonocytic Leukemia

Between a Rux and a Hard Place: Investigating Causes of Ruxolitinib Discontinuation, Salvage Treatment and Outcome in Myelofibrosis

Background: Ruxolitinib (rux) is a JAK1/2 inhibitor approved for the treatment of intermediate and high risk myelofibrosis (MF) patients with constitutional symptoms and/or symptomatic splenomegaly. Unfortunately, many patients discontinue rux due to lack or loss of initial response, or treatment related cytopenias. Optimal management of MF after rux discontinuation is not clear. In this study, we aimed to further investigate rux discontinuation; the causes that lead to it, treatment approaches after, and ultimate clinical outcomes.Methods: We retrospectively reviewed MF patients who presented to our institution between 8/2008 and 3/2016. We included rux-treated patients who discontinued treatment after ≥ 4 consecutive months (mo) of treatment and who had ≥ 5 mo of follow-up after discontinuation. Overall survival (OS) was defined from time of rux discontinuation. Patients who underwent allogeneic transplant (allo-HCT) were censored at time of transplant. Response to rux was defined by IWG criteria.Results: Out of 158 MF patients treated with rux, 23 (14.6%) met inclusion criteria. The median age at rux initiation was 62 years. Sixteen (70%) patients had a JAK2 V617F mutation, 2 (9%) had a CALR mutation, 1 (4%) was triple-negative (negative for JAK2 V617F, MPL and CALR mutations) and 4 (17%) had incomplete analysis to determine driver mutation status. The median exposure to rux prior to discontinuation was 14 mo [5-60 mo]. Median time of follow-up after rux discontinuation was 12 mo [6-43 mo]. Among the 23 patients, 12 responded to rux, 6 had no response and 5 were not evaluable for response. Among the 12 responders, mean duration of rux treatment prior to discontinuation was 29.4 mo compared to 10.4 mo in the 6 non-responders (p = 0.03). The most common reasons for discontinuation were lack of efficacy (26%), decision to undergo allo-HCT (26%), or progression of symptoms after initial response (22%). Less common reasons for discontinuation included development of cytopenias (9%), side effects unrelated to cytopenias (9%), and diagnosis of a non-hematologic malignancy requiring treatment (9%).Of 23 evaluable patients, 100% received a second line of therapy after rux discontinuation. Five patients (28%) received >1 salvage therapy. The most common treatment after rux discontinuation was allo-HCT (n = 10, 43%). Apart from transplant, treatment choices after rux discontinuation included hydroxyurea (26%), lenalidomide (17%), thalidomide (17%), interferon (13%), investigational agents (13%), danazol (4%) and cladribine (4%). Rux was re-initiated in one patient who did not respond. The response rate to subsequent lines of therapy was 23% (n=5). Of five documented responses, two were anemia responses after treatment with thalidomide, one was a spleen response with lenalidomide, one a symptom response with hydroxyurea, and one a spleen response after treatment with an investigational JAK2/FLT3 inhibitor (SB1518).Median OS from rux initiation was 52 mo, whereas median OS after rux discontinuation was 15 mo. Median OS was 52 mo vs. 29 mo in patients who responded to rux compared to non-responders, respectively (p = 0.27). After rux discontinuation, those who underwent allo-HCT had longer OS compared to those who did not (median OS not reached vs 15 mo, OR 0.18 [0.04-0.73]; p = 0.07). Response to subsequent lines of therapy was not associated with improved OS (p = 0.36).Molecular profiling was available for 14/23 patients. In 13 cases, next generation sequencing (NGS) was performed prior to initiation of rux. Thirteen (93%) patients were found to have at least one somatic mutation, while 3 patients had ≥ 3 mutations. In patients with 0-2 somatic mutations, there was an 88% response rate to rux compared with a 67% response rate in patients with ≥ 3 mutations (p = 0.13). ASXL1 mutation was found in 8 (62%) patients. All other mutations occurred with a frequency ≤ 15%. Of the two patients with NGS data who did not respond to rux, both had ASXL1 mutations. ASXL1 mutation status did not correlate with survival; however 5 (63%) patients with ASXL1 mutations underwent allo-HCT.Conclusion: A significant percentage of rux-treated patients discontinue treatment due to lack or loss of response. After rux discontinuation, anemia, spleen and symptom responses are infrequent. Allo-HCT offers the best chance for long-term survival. Outcome after rux failure is poor and represents an unmet need in the treatment of MF. [Display omitted] DisclosuresPadron:Incyte: Honoraria, Research Funding. Sallman:Celgene: Research Funding. Lancet:Erytech: Consultancy; Celgene: Consultancy; Pfizer: Other: Institutional research funding, Research Funding; Jazz Pharmaceuticals: Consultancy; Boehringer Ingelheim: Consultancy; BioSight: Consultancy; Novartis: Consultancy; Bio-Path Holdings: Consultancy; Janssen: Consultancy. Komrokji:Celgene: Honoraria; Novartis: Honoraria, Speakers Bureau.

Predictors of Survival and Time to Progression to Myeloid Neoplasm in Patients with Clonal Cytopenias

Background: Clonal cytopenias of Undetermined Significance (CCUS) have a higher risk of progression to myeloid neoplasm (MN) compared to idiopathic cytopenias of undetermined significance (ICUS) (Malcovati et al., Blood, 2017). The implementation of flow cytometric (FC) immune-phenotyping and next generation sequencing (NGS) in clinical practice has improved the diagnosis of these entities but the clinical significance and interaction of these abnormal results are still unknown. In this study we investigated predictive factors that play role in survival and progression to MN in patients with ICUS/CCUS. Methods: Patients (Pts) who had undergone evaluation for unexplained cytopenia and had undergone FC and bone marrow morphological assessment between 3/2015-3/2020 at Mayo Clinic Rochester were included. Pts were excluded if a malignant hematological disorder was diagnosed prior to the time of FC. FC included evaluation of the following parameters: Abnormal expression of HLA-DR/CD13, CD2, CD7, CD45, and CD56 on blasts; and abnormal CD13/CD16 expression and side scatter on granulocytic cells. NGS panel up to 2018 included 34 genes, ASXL1, BCOR, BRAF, CALR, CBL, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, GATA1, GATA2, IDH1, IDH2, JAK2, KIT, KRAS, MPL, MYD88, NOTCH1, NPM1, NRAS, PHF6, PTPN11, RUNX1, SETBP1, SF3B1, TERT, TET2, TP53, U2AF1, WT1, and ZRSR2; in 2018, BRAF was omitted and 12 genes were added, ANRD26, DDX41, ELANE, ETNK1, KDM6A, MYD88, NOTCH1, RAD21, SH2B3, SRP72, SMC3, and STAG2. Results: Characteristics: Of 490 consecutive pts, 238 (median age 69 years (range 19-92), 66% males) met our inclusion criteria as ICUS. 86 (36%) pts had CCUS (abnormal cytogenetics and/or tested positive for pathogenic mutations on NGS). After a median follow-up of 28 months (95% CI: 20 to 31 months), 21 (25%) patients developed MN and 23 (27%) died during follow-up. Comparing ICUS vs CCUS: upon comparing CCUS pts to ICUS, several factors were found to be significantly different: CCUS pts were older (p= .02); majority male (p= .04), had more abnormal HLA-DR/CD13 (p &amp;lt;.0001), more side-scattered light by FC (p &amp;lt;.0001), more pancytopenia on follow up (p= .02) and more morphologic atypia (&amp;lt;.0001). Overall survival (OS) outcomes in CCUS: Several covariates were significant in univariate models, and model selection was used to generate a risk score based on abnormal CD7, abnormal CD13/CD16, abnormal HLA-DR/CD13, splenomegaly and history of prior chemotherapy or radiotherapy (range: 0 - 4; HR=2.58, [95 CI: 1.69 - 3.94], p&amp;lt;.0001). Risk scores were grouped as low risk (score=0), intermediate risk (score=1), and high risk (score=2+), with estimated 2-yr-OS of 95%, 84%, 40%, respectively (Figure 1). An extended risk score model including NGS factors added ASXL1 and IDH1 mutation status to the previous model (range: 0 - 6; HR=2.72, [95 CI 1.82 - 4.06], p&amp;lt;0.0001). MN-free survival (MNFS) in CCUS: 37 pts either progressed to MN and/or died with a median follow up time for MNFS of 22.4 months. Similar for OS, model selection approaches yielded a composite risk score: splenomegaly, BCOR mutation status, mutation in RAS signaling pathway, abnormal expression of flow markers CD13/CD16, HLA-DR/CD13 or CD7 (HR=3.23, [95 CI: 1.90 - 5.49], p=&amp;lt;0.0001). Risk scores were grouped as low risk (score=0), intermediate risk (score=1), and high risk (score ≥ 2), with estimated 1-yr MNFS of 84%, 74%, and 31%, respectively (Figure 2). Conclusion: CCUS has unique features compared to ICUS. Several factors, including clinical characteristics, immune-phenotyping by FC, and somatic mutations have important impact on risk of progression to MN and on overall survival. Our findings serve as proof-of-concept that such integrated models could help identify CCUS patients at higher risks for progression to MN or death. They can guide treatment accordingly and should be evaluated further. Disclosures Shah: Dren Bio: Consultancy.

Characterization of somatic mutation-associated microenvironment signatures in acute myeloid leukemia patients based on TCGA analysis

Recurrent genetic mutations occur in acute myeloid leukemia (AML) and have been incorporated into risk stratification to predict the prognoses of AML patients. The bone marrow microenvironment plays a critical role in the development and progression of AML. However, the characteristics of the genetic mutation-associated microenvironment have not been comprehensively identified to date. In this study, we obtained the gene expression profiles of 173 AML patients from The Cancer Genome Atlas (TCGA) database and calculated their immune and stromal scores by applying the ESTIMATE algorithm. Immune scores were significantly associated with OS and cytogenetic risk. Next, we categorized the intermediate and poor cytogenetic risk patients into individual-mutation and wild-type groups according to RUNX1, ASXL1, TP53, FLT3-ITD, NPM1 and biallelic CEBPA mutation status. The relationships between the immune microenvironment and each genetic mutation were investigated by identifying differentially expressed genes (DEGs) and conducting functional enrichment analyses of them. Significant immune- and stromal-relevant DEGs associated with each mutation were identified, and most of the DEGs (from the FLT3-ITD, NPM1 and biallelic CEBPA mutation groups) were validated in the GSE14468 cohort downloaded from the Gene Expression Omnibus (GEO) database. In summary, we identified key immune- and stromal-relevant gene signatures associated with genetic mutations in AML, which may provide new biomarkers for risk stratification and personalized immunotherapy.

ASXL1 mutation as a surrogate marker in acute myeloid leukemia with myelodysplasia-related changes and normal karyotype.

Acute myeloid leukemia with myelodysplasia‐related changes (AML‐MRC) are poor outcome leukemias. Its diagnosis is based on clinical, cytogenetic, and cytomorphologic criteria, last criterion being sometimes difficult to assess. A high frequency of ASXL1 mutations have been described in this leukemia. We sequenced ASXL1 gene mutations in 61 patients with AML‐MRC and 46 controls with acute myeloid leukemia without other specifications (AML‐NOS) to identify clinical, cytomorphologic, and cytogenetic characteristics associated with ASXL1 mutational status. Mutated ASXL1 (ASXL1+) was observed in 31% of patients with AML‐MRC compared to 4.3% in AML‐NOS. Its presence in AML‐MRC was associated with older age, a previous history of myelodysplastic syndrome (MDS) or myelodysplastic/myeloproliferative neoplasms (MDS/MPN), leukocytosis, presence of micromegakaryocytes in bone marrow, lower number of blasts in bone marrow, myelomonocytic/monocytic morphological features and normal karyotype. ASXL1 mutation was not observed in patients with myelodysplastic syndrome‐related cytogenetic abnormalities or TP53 mutations. Differences in terms of overall survival were found only in AML‐MRC patients without prior MDS or MDS/MPN and with intermediate‐risk karyotype, having ASXL1+ patients a worst outcome than ASXL1−. We conclude that the ASXL1 mutation frequency is high in AML‐MRC patients being its presence associated with specific characteristics including morphological signs of dysplasia. This association raises the possible role of ASXL1 as a surrogate marker in AML‐MRC, which could facilitate the diagnosis of patients within this group when the karyotype is normal, and especially when the assessment of multilineage dysplasia morphologically is difficult. This mutation could be used as a worst outcome marker in de novo AML‐MRC with intermediate‐risk karyotype.

Clinical Categorization of Chronic Myelomonocytic Leukemia into Proliferative and Dysplastic Subtypes Correlates with Distinct Genomic, Transcriptomic and Epigenomic Signatures

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

Response to Erythropoiesis Stimulating Agents in Patients with WHO-Defined Myelodysplastic Syndrome/Myeloproliferative Neoplasm with Ring Sideroblasts and Thrombocytosis (MDS/MPN-RS-T)

Background: Myelodysplastic syndrome (MDS)/myeloproliferative neoplasm (MPN) with ring sideroblasts and thrombocytosis (MDS/MPN-RS-T) was formally included as a unique WHO-defined entity in the 2016, iteration of the classification of hematological neoplasms (under MDS/MPN overlap syndromes). Patients with MDS/MPN-RS-T have features of MDS-RS-single lineage dysplasia (SLD), persistent thrombocytosis (platelet count ≥450x109/L), with proliferation of large atypical megakaryocytes. Anemia, including red blood cell transfusion dependency (RBC-TD) is a major problem. While extensive studies have documented erythroid response rates (ERR) to erythropoiesis stimulating agents (ESA) in MDS and MDS-RS-SLD, the data in MDS/MPN-RS-T is less clear. We carried out this study to asses ERR in ESA treated patients with MDS/MPN-RS-T. Methods: After approval by the IRB, patients with 2016, WHO-defined MDS/MPN-RS-T were included in the study. The bone marrow (BM) morphology, cytogenetics and BM RS% were retrospectively reviewed. All study patients underwent next generation sequencing for 29 myeloid-relevant genes, obtained on BM mononuclear cells, at diagnosis, or at first referral, by previously described methods (Patnaik et al., BCJ 2016). Treatment details, including the type of ESA used, dose administered, side effects and reason for discontinuation were retrospectively abstracted. Erythroid responses were assessed using the 2006, international working group (IWG) MDS and the 2015, IWG MDS/MPN response criteria. Results: Forty seven patients with MDS/MPN-RS-T were identified, of which 37 (79%) patients received ESA treatment at any time point during their disease course; median age 73 years (range, 52-93), 46% male.The hemoglobin at diagnosis (HB) and baseline erythropoietin (EPO) levels were 9.1 gm/dL (range, 6.6-12.1) and 39 IU/L (range, 8-500), respectively. Ten (29%) patients were RBC-TD at baseline. None of the 37, ESA-treated patients were on concomitant cyto-reductive therapy for thrombocytosis. Twenty (54%) patients were treated with erythropoietin-a, 13 (35%) with darbepoetin, and 4 (11%) with both sequentially. Median doses were 40,000 IU weekly (range, 20,000-80,000) for erythropoietin-a and 200 mcg every 2 weeks (range, 100-500), for darbepoetin. Median treatment duration was 14 months (range, 1-173) and causes for discontinuation included; ESA failure/loss of response in 20 (54%), sustained HB rise in 1 (3%) and other causes, including adverse events in 4 (11%) patients. With regards to safety, the following events were considered potentially ESA related; treatment emergent hypertension in 2 (5%), venous thromboembolism, ischemic stroke and splenic infarction in 1 (3%) patient each, respectively. All patients with thrombotic/ischemic events had been on low dose aspirin prophylaxis. Erythroid responses by the IWG MDS and MDS/MPN response criteria were assessable in 35 (95%) patients: with 16 (46%) meeting criteria for an erythroid response, by both assessment systems. The median duration of ER was 20 months (range, 2-172). In comparison to ESA non-responders, those that responded were more likely to have baseline EPO levels ≤44 IU/L (ROC analysis; median, 28 vs 112 IU/L; p=0.0080), while there was a trend for inferior responses associated with RBC-TD (p=0.0857). Age, gender, baseline white blood cell and platelet counts, type of ESA used, BM RS %, JAK2V617F, SF3B1, DNMT3A, TET2 and ASXL1 mutational status did not impact ESA response (Table 1). On a univariate survival analysis (OS), survival was not significantly different between ESA responders vs non-responder (median OS, 76 vs 45 months; p=0.2929). After ESA failure, 7 (19%) patients received hypomethylating agents (HMA), while 5 (14%) received lenalidomide. There were no erythroid responses to HMA, while 1 of 3 (33%) assessable lenalidomide treated patients achieved a morphological complete response. Conclusion: Erythropoiesis stimulating agents are effective first line therapies for the management of anemia in patients with MDS/MPN-RS-T, with 46% achieving an erythroid response (median duration of response of 20 months). Low baseline endogenous EPO level (&lt;44 IU/L) was the best predictor of response, with a trend towards an inferior response in the presence of RBC-TD. In the context of clonal thrombocytosis, potentially related thrombotic/ischemic events were documented in 8% of patients. Disclosures Al-Kali: Astex Pharmaceuticals, Inc.: Research Funding. Patnaik:Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees.

Comprehensive Clinical-Molecular Transplant Risk Model for Myelofibrosis Undergoing Allogeneic Stem Cell Transplantation

Background The Dynamic International Prognostic Scoring System (DIPSS) is commonly applied to predict survival among patients with primary myelofibrosis (PMF) but has been shown to perform less precisely in secondary myelofibrosis (SMF) and after transplantation. Furthermore, the prognostic relevance of mutation profile resulted in the mutation-enhanced IPSS (MIPSS70) in PMF, as well as in a model specific to SMF (MYSEC-PM). We aimed to develop a comprehensive clinical-molecular prognostic scoring system to determine outcome for myelofibrosis undergoing allogeneic stem cell transplantation. Patients and Methods We examined 361 myelofibrosis patients, of whom 260 had PMF and 101 SMF at time of transplantation. A training cohort of 205 patients was used to create a clinical-molecular transplant scoring system (MTSS) predicting survival from Cox models, internally validated by use of bootstrap and cross-validation. Model discrimination was measured by the concordance index (C). The final MTSS was externally validated in a cohort of 156 patients and was furthermore applied to posttransplant non-relapse mortality as a secondary objective. Results Multivariable analysis on 5-year survival identified age ≥57 years, Karnofsky performance status 25 × 109/L at time of transplantation, HLA-mismatched unrelated donor, ASXL1 mutated and CALR-/MPL-unmutated genotype being independent prognostic factors for outcome. The uncorrected concordance index for the final survival model was 0.723 (95% CI, 0.713-0.733), and bias-corrected indices were similar. A weighted score of 2 was assigned to transplantation from an HLA-mismatched unrelated donor and an CALR-/MPL-unmutated genotype, whereas a score of 1 was assigned to older age, leukocytosis, thrombocytopenia, ASXL1 mutation, and poor performance status. The MTSS consisted of four distinct risk groups showing 5-year survival in the validation cohort of 83% (95% CI, 71-95%) for low (score 0-2), 64% (95% CI, 53-75%) for intermediate (score 3-4), 37% (95% CI, 17-57%) for high (score 5), and 22% (95% CI, 4-39%) for very high risk (score >5), respectively (P Conclusion The MTSS integrates clinical, molecular as well as transplant-specific risk factors that independently affected survival. We show here that this internally and externally validated system accurately discriminated different risk for death and may improve counseling compared with currently existing systems, as well as facilitate design of clinical trials in the transplant setting.

Current Genetic Models for Prediction of Primary Myelofibrosis

Aim. To study the relationship of karyotype, JAK2, CALR, and MPL driver mutations and ASXL1 mutation status with the progression and prediction of primary myelofibrosis (PMF). Materials &amp; Methods. The trial included 110 PMF patients (38 men and 72 women), median age was 59 years (range 18-82) with median follow-up after diagnosis of 2.6 years (range 0.1-23). The patients were examined for JAK2, CALR, MPL, and ASXL1 mutations. Restriction fragment length polymorphism technique was used for the analysis of V617F substitution in JAK2 and 515 codon mutation in MPL. CALR (exon 9) and ASXL1 (exon 12) mutation tests were performed using Sanger direct sequencing. In 48 (44 %) out of 110 patients bone marrow cell karyotype was determined. Clinical and hematological parameters and median overall survival (OS) of patients were analyzed with regard to detected genetic aberrations and combinations of them. Results. JAK2, CALR, MPL mutations were detected in 55 (50 %), 28 (25.5 %), and 7 (6.4 %) out of 110 patients, respectively. Triple negative (TN) status was identified in 20 (18.2 %) out of 110 examined patients. ASXL1 mutations were detected in 22 (20 %) out of 110 patients. Out of 48 patients in 32 (66.7 %) normal karyotype, in 3 (6.3 %) favorable karyotype, in 4 (8.3 %) intermediate-prognosis karyotype, and in 9 (18.7 %) unfavorable karyotype were detected. The comparison of clinical and hematological parameters showed a number of significant differences. JAK2-positive patients had a higher hemoglobin level (median 129 g/L; p = 0.021). TN was associated with a high IPSS risk (p = 0.011), low hemoglobin level (median 101 g/L; p = 0.006), drop in platelet count (median 266 &lt;sup&gt;x&lt;/sup&gt; 10&lt;sup&gt;9&lt;/sup&gt;/L; p = 0.041), increased lymphocyte count (median 26.9 &lt;sup&gt;х&lt;/sup&gt; 10&lt;sup&gt;9&lt;/sup&gt;/L; р = 0.001). The detection of terminating mutations in ASXL1 correlated with palpable enlarged spleen (р = 0.050), reduced platelet count (median 184 х 10&lt;sup&gt;9&lt;/sup&gt;/L; р = 0.016), leukocyte count &gt; 25 х 10&lt;sup&gt;9&lt;/sup&gt;/L (р = 0.046), and blast count &gt; 1 % (р &lt; 0.001). Univariate regression analysis showed that terminating mutations in ASXL1 (hazard ratio [HR] 2.9; р = 0.018), unfavorable karyotype (HR 8.2; р &lt; 0.001), and TN (ОР 8.1; р &lt; 0.001) had prognostic value for OS. ASXL1 mutation was associated with significantly worse OS in TN patients. Median OS of ASXL1-negative patients without high-risk chromosomal aberrations was significantly longer than in patients with high-risk karyotype and/ or ASXL1 mutation. Conclusion. Several genetic defects in tumor cells are associated with phenotypic manifestations of PMF. Based on the results of cytogenetic analysis and mutation determination of JAK2, CALR, MPL, and ASXL1, patients can be classified in different “genetic” risk groups when PMF is diagnosed.

Poor Prognostic Implication of ASXL1 Mutations in Korean Patients With Chronic Myelomonocytic Leukemia.

BackgroundMolecular genetic abnormalities are observed in over 90% of chronic myelomonocytic leukemia (CMML) cases. Recently, several studies have demonstrated the negative prognostic impact of ASXL1 mutations in CMML patients. We evaluated the prognostic impact of ASXL1 mutations and compared five CMML prognostic models in Korean patients with CMML.MethodsWe analyzed data from 36 of 57 patients diagnosed as having CMML from January 2000 to March 2016. ASXL1 mutation analysis was performed by direct sequencing, and the clinical and laboratory features of patients were compared according to ASXL1 mutation status.ResultsASXL1 mutations were detected in 18 patients (50%). There were no significant differences between the clinical and laboratory characteristics of ASXL1-mutated (ASXL1+) CMML and ASXL1-nonmutated (ASXL1−) CMML patients (all P>0.05). During the median follow-up of 14 months (range, 0–111 months), the overall survival (OS) of ASXL1+ CMML patients was significantly inferior to that of ASXL1− CMML patients with a median survival of 11 months and 19 months, respectively (log-rank P=0.049). An evaluation of OS according to the prognostic models demonstrated inferior survival in patients with a higher risk category according to the Mayo molecular model (log-rank P=0.001); the other scoring systems did not demonstrate a significant association with survival.ConclusionsWe demonstrated that ASXL1 mutations, occurring in half of the Korean CMML patients examined, were associated with inferior survival. ASXL1 mutation status needs to be determined for risk stratification in CMML.

Prognostic impact of ASXL1 mutations in patients with myelodysplastic syndromes and multilineage dysplasia with or without ring sideroblasts

IntroductionThe 2016 World Health Organization (WHO) classification of myeloid neoplasms reclassified patients with myelodysplastic syndromes (MDS) with multilineage dysplasia (MLD) based on the presence or absence of ring sideroblasts (RS). We performed this study to validate this change in the context of relevant gene mutations. MethodsWHO-defined MDS and MLD were identified with detailed clinical, cytogenetic and outcomes data. A 32-gene targeted exome sequencing panel was performed on bone marrow samples obtained at diagnosis. ResultsNinety eight patients were included; 59 (60%) MDS-MLD and 39 (40%) MDS-RS-MLD. There were no significant differences in the median overall survival (OS) in the two groups (25 months each, p = 0.6). Among the myeloid-relevant gene mutations, presence of ASXL1 (HR 2.5, p = 0.005) was identified as an adverse prognostic factor in a multivariate analysis. ConclusionWhile segregation of MDS-MLD based on RS holds little prognostic relevance, ASXL1 mutational status significantly and independently predicts poor outcomes.

"Proliferative" Versus "Dysplastic" Chronic Myelomonocytic Leukemia: Molecular and Prognostic Correlates

▪Background: The 2016 revision to the World Health Organization (WHO) classification of myeloid neoplasms has recommended distinction between "proliferative" (WBC ≥ 13 x 10(9)/L) and "dysplastic" (WBC < 13 X 10(9)/L) subtypes of chronic myelomonocytic leukemia (CMML). In the current study of 261 molecularly-annotated cases, we sought to clarify the prognostic relevance of distinguishing proliferative from dysplastic CMML and also describe differences in the distribution of disease-associated mutations.Methods: 261 patients with WHO-defined CMML were included in the study. All patients had bone marrow (BM) biopsies and cytogenetics performed at diagnosis. Targeted capture assays were carried out on BM DNA specimens obtained at diagnosis for the following genes; TET2, DNMT3A, IDH1, IDH2, ASXL1, EZH2, SUZ12, SRSF2, SF3B1, ZRSR2, U2AF1, PTPN11, Tp53, SH2B3, RUNX1, CBL, NRAS, KRAS, JAK2, CSF3R, FLT3, KIT, CALR, MPL, NPM1, CEBPA, IKZF, and SETBP. The 2016 WHO criteria were used to sub-classify CMML into proliferative and dysplastic subtypes.Results:Among the 261 study patients, 65% were males and median age was 70 years. 154 (59%), 64 (25%) and 43 (16%) patients were classified as CMML-0, 1 and 2, respectively. At a median follow-up of 23 months, 174 (67%) deaths and 37 (14%) leukemic transformations were documented. Mutational frequencies were; TET2 45%, ASXL1 45%, SRSF2 40%, NRAS 14%, SETBP1 13%, CBL 10%, JAK2 7%, RUNX1 6%, U2AF1 6%, DNMT3A 6%, SF3B1 5%, ZRSR2 4%, Tp53 4%, IDH2 4%, KRAS 3%, PTPN11 2%, SH2B3 1%, CSF3R 1%, IDH1 1%, EZH2 1%, SUZ12 1%, KIT 1%, FLT3 1%, and CALR 1%. Risk stratification was based on the Mayo Molecular Model: 31% high, 30% intermediate-1, 28% intermediate-2 and 11 % low risk.i) Dysplastic versus proliferative CMML: phenotypic and molecular differences139 (53%) patients had proliferative and 122 (47%) dysplastic subtypes. There was no difference between the CMML subtypes in terms of age and gender distribution, hemoglobin level, platelet count or BM blast content. Patients with proliferative CMML had higher absolute monocyte counts (AMC) (p<0.0001), circulating immature myeloid cells (IMC, p<0.001), circulating blasts (p<0.001) and serum LDH levels (p=0.01). The following gene mutations were more common in proliferative vs dysplastic CMML: ASXL1 (54% vs 37%, p=0.009), JAK2 (11% vs 3%, p=0.01) and CBL (11% vs 8%, p=0.047); SF3B1 mutations were more common in dysplastic CMML (8% vs 1%, p=0.02). There was no difference in the incidence of TET2, DNMT3A and SRSF2 mutations whereas there was a trend towards a higher prevalence of NRAS (p=0.06) and CSF3R (p=0.06) mutations in proliferative CMML. Cytogenetic abnormalities (p=0.03), including higher risk categories by the Spanish (p=0.03) and the Mayo-French (p=0.01) systems were more common in proliferative CMML.ii) Impact on overall and leukemia-free survival:Median survival for the entire cohort (n=261) was 24 months. In univariate analysis, survival was shorter in patients with proliferative (median 20 months) versus dysplastic (median 29 months) CMML (p=0.008; HR1.5, 95% CI 1.1-2.1; Figure 1A). Other variables of significance, in univariate analysis, included hemoglobin (p=0.001), leukocyte count (p=0.001), AMC (p=0.003), PB blast % (p=0.003), IMC (p=0.01), BM blast % (p=0.045), abnormal karyotype (p=0.02), ASXL1 (p=0.01) and DNMT3A (p=0.0003) mutations. In multivariable analysis, the difference in survival between proliferative and dysplastic subtypes remained significant with the addition of hemoglobin level (p=0.01), PB blast % (p=0.02), IMC (p=0.04), BM blast % (p=0.01) or DNMT3A mutations (p=0.01). This was, however, not the case with addition of leukocyte count (p=0.32), AMC (p=0.18) or ASXL1 mutational status (p=0.14); whereas the adverse impact on survival from the latter three parameters remained significant. The prognostic impact of ASXL1 mutations was most apparent in dysplastic CMML (Figure 1B). There was no difference in leukemic transformation rates (p=0.4).Conclusions: In the context of current prognostic models, sub-classification of CMML into proliferative and dysplastic subtypes might not provide additional prognostic value. The apparent difference in survival between the two subtypes of CMML is probably accounted for by the higher prevalence of leukocytosis/monocytosis and of ASXL1 mutations in proliferative CMML. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Gene Expression Profiling Identifies Distinct Signatures for Dysplastic and Proliferative Chronic Myelomonocytic Leukemia

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