Zeidner, Joshua F.

Abstract Clonal cytopenia of undetermined significance (CCUS) represents a distinct disease entity characterized by myeloid-related somatic mutations with a variant allele fraction of ≥2% in individuals with unexplained cytopenia(s) but without a myeloid neoplasm (MN). Notably, CCUS carries a risk of progressing to MN, particularly in cases featuring high-risk mutations. Understanding CCUS requires dedicated studies to elucidate its risk factors and natural history. Our analysis of 357 patients with CCUS investigated the interplay between clonality, cytopenia, and prognosis. Multivariate analysis identified 3 key adverse prognostic factors: the presence of splicing mutation(s) (score = 2 points), platelet count of <100 × 109/L (score = 2.5), and ≥2 mutations (score = 3). Variable scores were based on the coefficients from the Cox proportional hazards model. This led to the development of the clonal cytopenia risk score (CCRS), which stratified patients into low- (score of <2.5 points), intermediate- (score of 2.5 to <5), and high-risk (score of ≥5) groups. The CCRS effectively predicted 2-year cumulative incidence of MN for low- (6.4%), intermediate- (14.1%), and high-risk (37.2%) groups, respectively, by the Gray test (P < .0001). We further validated the CCRS by applying it to an independent CCUS cohort of 104 patients, demonstrating a c-index of 0.64 (P = .005) in stratifying the cumulative incidence of MN. Our study underscores the importance of integrating clinical and molecular data to assess the risk of CCUS progression, making the CCRS a valuable tool that is practical and easily calculable. These findings are clinically relevant, shaping the management strategies for CCUS and informing future clinical trial designs.

Background: Acute myeloid leukemia (AML) therapy in older patients (age ≥ 60) has undergone a transformation with the introduction of multiple targeted therapies, which has allowed more patients to receive therapy than before. The most successful has been the combination of venetoclax + azacitidine (VA) which generated higher overall complete response rates in phase 2 studies than would be expected with azacitidine alone, leading to accelerated FDA approval on 21Nov2018. The VIALE-A phase 3 study confirmed the improved overall survival (OS, median 14.7 versus 9.6 months) of VA, leading to full FDA approval for marketing. This retrospective analysis provides real world data on the impact of baseline clinical and genomic markers of individuals receiving intensive chemotherapy versus VA. Methods: The precision medicine Beat AML Master Trial (NCT03013998) assigns patients to biomarker specific sub-study treatments based on targeted DNA sequencing and cytogenetics. However, a large subset of patients did not enroll on a sub-study, but were followed for off-study treatment and OS. From this subset, patients enrolled onward from 21Nov2018, when VA received accelerated approval, were examined for differences in clinical/genetic characteristics and OS in those receiving venetoclax + hypomethylating agent (V/HMA), any form of intensive chemotherapy (IC), alternative non-intensive therapy (NIT), or no therapy. The genetic mutations identified in this study are characterized by a variant allele frequency of 20%+, as defined in the trial for determining the dominant clone. The method of Kaplan-Meier was used to estimate OS, and the Cox model was fit to associate patient characteristics with OS. Results: From 21Nov2018, a total of 468 AML patients consented to the Beat AML trial and did not enroll to a sub-study. Treatment was chosen by the investigator based upon available clinical and genomic data. Of these 468 patients, 62 did not receive treatment, 2 had treatment data missing, 226 were treated with V/HMA, 112 with IC, and 66 with NIT. Demographics for all patients include median age 71 (60-90), 40% female, performance status (PS) (0-20%; 1-55%; 2-22%; 3-3%), median white blood cell (WBC) 4.1 (range 0.3-298.6), complex karyotype (CK) 20.6%, core binding factor (CBF) 7.8%, KMT2A-rearranged 3.6%, NPM1-mutated (m) 15.6%, IDH2m 14.6%, TP53m 13.2%, FLT3-ITD/TKD 12.9%, and NRASm/ PTPN11m/ KRASm/ NF1m/ CBLm 23.6%. Demographics that were significantly different (p<0.01) among the three groups (V/HMA, IC, and NIT) include age (younger in IC), PS (worse in NIT), AST/ALT (worse in NIT), CBF (more in IC), CK and TP53m (less in IC). Of the 404 patients who underwent treatment with V/HMA, IC, or NIT, 208 have died with those surviving having a median follow-up of 22.3 months. Figure 1 summarizes the OS of each treatment group. The median OS (95% CI) from time of initiating therapy is 13.6 (10.9-16.8) for V/HMA, 33.8 (20.7-not reached) for IC, and 11.6 (5.2-21.3) months for NIT. Univariable analysis for OS was significant at p<0.05 for increased age, WBC, PS, hemoglobin, CBF, CK, NPM1m, TP53m, TET2m and IC versus V/HMA. Multivariable analysis was significant at p<0.05 (hazard ratio) for increased age (1.14), PS (1.83), WBC (1.08), hemoglobin (0.91), and select genomic aberrations including CBF (0.37), NPM1m (0.35), and TP53m (2.1). Conclusions: These results from a large cohort of older AML patients treated with V/HMA, IC, or NIT show that their outcome is best defined by pre-treatment clinical features previously identified including age, performance status, WBC and hemoglobin along with limited genomic characteristics including CBF, NPM1m, and TP53m. While univariate analysis of OS favored IC over V/HMA and NIT, multivariable analysis supports that this advantage was most likely due to the favorable clinical and genomic features. The OS of V/HMA patients in this cohort is similar to that in the VIALE-A registration study of VA, providing further justification for this treatment for older AML patients deemed ineligible for intensive chemotherapy. Additionally, this data supports use of the patient cohort in this study for ongoing work in understanding and/or validating biomarkers associated with survival with V/HMA.

Background. Acute myeloid leukemia (AML) is a heterogenous disease that occurs primarily in older adults with a median age of 69 years at diagnosis. Most studies that characterize the genomic landscape of AML include younger adults with the majority of patients being younger than 60 years of age. We aimed to study the mutational landscape of newly diagnosed AML patients aged 60 years or older. Methods.Samples were collected from the multi-center Beat AML Master Trial (Burd, Nat Med 2020). Patients were enrolled between 2016 and 2023. Informed consent was obtained according to the Declaration of Helsinki. Patients diagnosed with non-APL AML and who were aged ≥ 60 years old were included. Patients underwent bone marrow aspiration and biopsy, cytogenetic analysis, FLT3-ITD ratio assessment (LeukoStrat CDx FLT3 Mutation Assay, Invivoscribe) and next generation sequencing (NGS) using FoundationOne®Heme(Foundation Medicine) to interrogate the entire coding region of 406 genes and select introns of 31 genes involved in rearrangements, as well as RNA sequencing to interrogate 265 genes known to be somatically altered in human hematological malignancies. The presence of multiple hotspot mutations within one gene in an individual patient was counted as one gene mutation. Patterns of co-occurrence between gene mutations were calculated using the Phi correlation coefficient. Statistical analyses were performed using R statistical software. P<0.01 was considered statistically significant. Results. A total of 1088 newly diagnosed AML patients were identified, of whom 1032 were 60 years or older. Patients had a median age of 72 years at time of diagnosis (range 60-92 years). Forty-two percent of the patients were female, most patients were non-Hispanic and 79% were Caucasian. NGS data were available for 1024 patients and mutations were identified in 461 different genes. Patients had a median number of 11.0 mutations (range 3.0 to 28.0). The most frequently mutated genes were DNMT3A (n=257; 25.1%), TP53(n=255; 24.9%), TET2 (n=243; 23.7%), RUNX1 (n=225; 22.0%), SRSF2 (n=221; 21.6%), ASXL1 (n=216; 21.1%), NPM1 (n=206; 20.1%), FLT3 (n=205; 20.0%), IDH2 (n=190; 18.6%), NRAS (n=208; 16.9%), PTPN11(n=104; 10.2%), STAG2 (n=101, 9.9% and IDH1 (n=99; 9.7%) (Figure 1A). FLT3-ITD was present in 98 (12.1%) of the 810 patients who were tested. Strongest significant co-occurrence was found between FLT3and NPM1 (n=103), STAG2 and ASXL1 (n=63), ASXL1 and RUNX1 (n=92), ASXL1 and SRSF2 (n=88), RUNX1 and SRSF2 (n=94), STAG2 and SRSF2 (n=51) and DNMT3A and NPM1 (n=92) (p<0.01). Pairwise negative correlations were observed between TP53 and NPM1 (n=6), TP53 and SRSF2 (n=17), and between NPM1 and RUNX1 (n=6) (p<0.01) (Figure 1B). The cytogenetic profiles and the full genomic landscape will be presented during the ASH meeting. Discussion. This is the largest study investigating the mutational profile in older adults with AML aged 60 years and older. Due to the 7-day screening period of the Beat AML study, patient selection was biased towards less-rapidly proliferative AML. We showed that the pattern of gene mutations was markedly different from other studies in AML that mainly included younger AML patients (Papaemmanuil, NEJM 2016; TCGA, NEJM 2013 ). The frequency of mutated TP53 was substantially higher in older AML patients, as was the occurrence of myelodysplasia-related gene mutations (e.g., SRSF2, RUNX1, ASXL1, STAG2, U2AF1, and SF3B1) and gene mutations in IDH1, IDH2 and TET2. In contrast, NPM1 mutation was less frequently mutated in older AML patients. Furthermore, we demonstrated that a large proportion (46%) of the AML patients older than 60 years of age do have a mutation that is potentially targetable for treatment ( FLT3 IDH1 IDH2 and NPM1). The high incidence of mutated TP53 and MDS-related gene mutations underscores the increased incidence of high-risk AML and the need for innovative personalized therapies in this older age group. Figure 1. A. Co-occurrence of the 15 most frequently mutated genes, and B. co-correlation between the 15 most frequently mutated genes. Blue indicates positive correlation, red indicated negative correlation. Only significant correlations (p<0.01) are shown.

Abstract Background: Clonal cytopenia of undetermined significance (CCUS) is defined as persistent unexplained cytopenia with evidence of clonality [myeloid-associated somatic mutations (MTs) or cytogenetic [CG] abnormalities] but without definitive evidence of myeloid neoplasms (MN). The outcomes in CCUS patients (pts) are not well understood. Methods: The CCUS International Study database includes pts from 17 institutions who meet the criteria of CCUS and do not have other causes of cytopenia. Pts with MDS defining CG abnormalities were excluded. We collected baseline clinical data, laboratory parameters, CGs, molecular genetics, treatment, and disease course. Diverse gene panels from different institutions were collated to include a total of 70 myeloid-related somatic genes (30 genes in common). 2018 IWG MDS response criteria were used to determine response rate (RR). Disease progression (DP) is defined by progression to MN. The relationship between independent variables and DP and death was assessed using Cox proportional hazards models. Progression-free survival (PFS) and overall survival (OS) were estimated using Kaplan-Meier method. All statistical analysis was performed using SAS. Results: A total of 258 pts were captured by July 2021. The median age was 71 (IQR 63-77) years, and 66% were male. Among 73 (28%) pts with known malignancy history, 27 (37%) pts received previous chemo- or radiation therapy. 27 (10%) pts had non-malignant hematology comorbidities. 91 (35%) had cardiovascular disease, and 33 (13%) had inflammatory disease. (Table 1) The red blood cell and platelet transfusion-dependent rates were 7.3% and 2.3%, respectively. The median number of MTs was 2 (IQR 1-3), with 221 (86%) pts had ≥1 MT, of which 116 (53%) had ≥ 2 MTs. The most common 5 MTs were TET2 (n=78, 30%), SRSF2 (n=50, 19%), DNMT3A (n=47, 18%), ASXL1 (n=40, 16%), and U2AF1 (n=22, 9%) (Figure 1). The median VAF (mVAF) was 28% (IQR: 9.2%, 43%) with VAF < 10% in 47 (18%) and VAF ≥40% in 78 (30.2%) of the MTs. mVAF of the all genes are shown in Figure 2. Among pts with CG abnormalities (n=62, 24%), trisomy 8 and -Y are the most common karyotypes (n=15 for each, 24%) (Table 2). Eighty one (31%) patients received various treatments for CCUS with modest RR, including growth factors (n=47, 18.2%, RR: 25.5%), supportive care (n=23, 9%, RR: 26%), immunoglobulin/immunosuppressive therapy (n=15, 6%, RR: 40%), and DNMTi (n=8, 3%, RR=13%). The median length of follow-up was 15.6 (IQR 6.9-30.6) months. 24 pts progressed to MN, 14 (58.3%) of which were MDS, 8 (33.3%) CMML, and 2 (8.3%) AML. The 2-year PFS was 86.1% (95% CI: 80-93%) with a median PFS of 16.3 (IQR: 3.7, 21) months. In the multivariable model, positive MT of KRAS (HR: 8.4, 95% CI: 1.9-36.9, p=0.005) and CBL (HR: 16.5, 95% CI: 3.7-73.8, p=0.003) were significantly associated with DP. In the functional pathway analysis, having at least 1 splicing factor MT was significantly associated with DP (HR: 2.6, 95% CI:1.2-5.9, p=0.02). TP53 was not significantly associated with DP (HR: 1.2, 95% CI: 0.2-8.7, p=0.88). Having >1 MT (HR: 3.57, 95% CI: 1.19-10.7, p=0.02) compared to a single MT was significantly associated with DP (Figure 3). Over the follow-up period, 35 pts died. The 2-year OS was 81% (95% CI: 74.9-87.9%). In the multivariable model, MT of KRAS (HR: 6.1, 95% CI: 1.8-20, p=0.003), CBL (HR: 7.3, 95% CI: 1.7-31, p=0.007), and FLT3 (HR: 19.9, 95% CI: 2.5-155, p=0.004) were significantly associated with inferior survival. In the functional pathway analysis, MTs in activated signaling pathway were significantly associated with death (HR: 4.1, 95% CI: 1.8-9, p<0.001). None of the pts with TP53 MT died. Having >1 MT was not statistically significantly associated with higher risk of death (HR: 1.5, 95% CI: 0.7-3.0, p=0.28) (Figure 4). After adjustment for co-MT status and comorbidities, baseline Hb<10 g/dL (HR: 3.7, 95% CI: 1.8-7.9, p<0.001) was significantly associated with greater mortality. Conclusion: This large retrospective study summarizes the CCUS pts' characteristics, with different MT patterns and VAF. We confirmed the impact of having >1 MT on DP, but not OS. Genes involved in activated signaling had a significant impact on both DP and OS. TP53 MT was not associated with worse outcome. Findings may be due to limited cases in the particular genes and different gene panels from multiple institutions. A longer follow-up is planned to further describe the predictors for outcome in this ongoing study. Figure 1 Figure 1. Disclosures Komrokji: Jazz: Consultancy, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMSCelgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Acceleron: Consultancy; PharmaEssentia: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy; Taiho Oncology: Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy. Zeidan: BioCryst: Other: Clinical Trial Committees; Kura: Consultancy, Other: Clinical Trial Committees; Ionis: Consultancy; Geron: Other: Clinical Trial Committees; Incyte: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Boehringer Ingelheim: Consultancy, Research Funding; Novartis: Consultancy, Other: Clinical Trial Committees, Travel support, Research Funding; Janssen: Consultancy; Cardiff Oncology: Consultancy, Other: Travel support, Research Funding; Loxo Oncology: Consultancy, Other: Clinical Trial Committees; Aprea: Consultancy, Research Funding; AstraZeneca: Consultancy; Agios: Consultancy; BeyondSpring: Consultancy; Gilead: Consultancy, Other: Clinical Trial Committees; Daiichi Sankyo: Consultancy; Jazz: Consultancy; Astex: Research Funding; BMS: Consultancy, Other: Clinical Trial Committees, Research Funding; Acceleron: Consultancy, Research Funding; Pfizer: Other: Travel support, Research Funding; Genentech: Consultancy; Epizyme: Consultancy; Jasper: Consultancy; Astellas: Consultancy; ADC Therapeutics: Research Funding; AbbVie: Consultancy, Other: Clinical Trial Committees, Research Funding. Madanat: Blue Print Pharmaceutical: Honoraria; Stem line pharmaceutical: Honoraria; Onc Live: Honoraria; Geron Pharmaceutical: Consultancy. Coombs: LOXO: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Genentech: Honoraria; MEI Pharma: Honoraria. Griffiths: Celgene/Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Takeda Oncology: Consultancy, Honoraria; Taiho Oncology: Consultancy, Honoraria; Apellis Pharmaceuticals: Research Funding; Novartis: Honoraria; Alexion Pharmaceuticals: Consultancy, Research Funding; Boston Biomedical: Consultancy; Astex Pharmaceuticals: Honoraria, Research Funding; Genentech: Research Funding; Abbvie: Consultancy, Honoraria. Lai: Astellas: Speakers Bureau; Jazz Pharma: 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; Genentech: 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; Jazz Pharma: Speakers Bureau; Macrogenics: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Foran: trillium: Research Funding; actinium: Research Funding; kura: Research Funding; boehringer ingelheim: Research Funding; takeda: Research Funding; abbvie: Research Funding; aptose: Research Funding; pfizer: Honoraria; novartis: Honoraria; servier: Honoraria; bms: Honoraria; revolution medicine: Honoraria; OncLive: Honoraria; gamida: Honoraria; certara: Honoraria; sanofi aventis: Honoraria; syros: Honoraria; taiho: Honoraria; h3bioscience: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding. Badar: Pfizer Hematology-Oncology: Membership on an entity's Board of Directors or advisory committees. Desai: Astex: Research Funding; Janssen R&D: Research Funding; Kura Oncology: Consultancy; Takeda: Consultancy; Bristol Myers Squibb: Consultancy; Agios: Consultancy. Ades: ABBVIE: Honoraria; CELGENE/BMS: Honoraria; NOVARTIS: Honoraria; TAKEDA: Honoraria; JAZZ: Honoraria, Research Funding; CELGENE: Research Funding. Brunner: Novartis, Celgene, Takeda, AstraZeneca: Research Funding; Celgene, Forty Seven Inc, Jazz: Other: Advisory Board. Carraway: Celgene, a Bristol Myers Squibb company: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Other: Independent review committee; Stemline: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Other: Independent review committee; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Agios: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Astex: Other: Independent review committee; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Prebet: BMS: Research Funding; BMS, Curios, Daichi: Consultancy. Patnaik: Kura Oncology: Research Funding; Stemline Therapeutics: Membership on an entity's Board of Directors or advisory committees; Stemline Therapeutics: Membership on an entity's Board of Directors or advisory committees. Savona: Karyopharm: Consultancy, Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy, Membership on an entity's Board of Directors or advisory committees; CTI: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS-Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; NOVARTIS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Taiho: Consultancy, Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; ALX Oncology: Research Funding; Astex: Research Funding; Incyte: Research Funding. Al-Kali: Novartis: Research Funding; Astex: Other: Research support to institution.

Abstract Introduction: Clonal hematopoiesis of indeterminate potential (CHIP) is defined by the presence and subsequent expansion of leukemia-associated driver mutations (MT). These MT predominantly involve epigenetic regulators such as DNMT3A, ASXL1, and TET2 (DAT, 75%). CHIP is a disease of aging and is associated with increased all-cause mortality. Clonal Hematopoiesis (CH), when present in the context of unexplained cytopenias and MT variant allele fractions (VAF) >20%, is termed as clonal cytopenias of undetermined significance (CCUS). Chronic myelomonocytic leukemia (CMML) is a hematological malignancy characterized by TET2, ASXL1, and SRSF2MT as well as sustained monocytosis. It usually arises in the setting of existing CH and clonal monocytosis. Here, we assessed the clonal compositions involving DAT genes in patients (pts) with CHIP, CCUS, and CMML. Methods: We included 1008 pts: 54 (5%) with CHIP, 334 (33%) with CCUS, and 620 (62%) with CMML. Demographics, laboratory parameters, and mutational spectrum at diagnosis were collected. We characterized and compared DAT MT in all three cohorts and assessed correlations with clinical parameters. MT locus and type along with protein sequences were analyzed using ProteinPaint. All statistical analyses were performed using R. Results: Of the 1008 pts, 427 (42%) had DAT MT; 36 had CHIP (67%); 96 had CCUS (29%), and 296 had CMML (48%). The median age was 71 years (IQR 65-76), and 68% were male. CMML pts had higher white blood cell counts, absolute neutrophil counts, absolute monocyte counts, and lower hemoglobin and platelet counts in comparison to CCUS and CHIP pts. The distribution of age and sex were similar among the three groups. After a median follow-up of 11 months (IQR 9.5-12.8), there were no myeloid progressions in the CHIP group and 17 (18%) in the CCUS group (8 of which developed CMML, Table 1). There were 738 protein-altering or splice-site DATMT in 495 unique MT hotspots. Pts with TET2MT were older (71 years, compared to DNMT3AMT: 69 years and ASXL1MT: 69 years , p<0.022). ASXL1MT were more common in males (75%, compared to DNMT3AMT: 52% and TET2MT: 66%, p=0.005). The mean VAF (mVAF) were 15.5% for DNMT3AMT, 35% for ASXL1MT and 39.2% TET2MT, respectively (p<0.001). We then compared DATMT characteristics in CHIP, CCUS, and CMML groups: DNMT3AMT were most common in CHIP, followed by CCUS, and were very rare in CMML (35% vs. 15% vs. 3%, p<0.001), with mVAF of DNMT3AMT increasing across this spectrum (CHIP: 6.5% vs. CCUS: 17.1% vs. CMML: 43.4%, p<0.0001). While DNMT3A missense MTs were most common (n=62, 67.4%), the AML-associated R882 hotspot MT was seen in 26 (28%) pts (CHIP: n=3, 5%, CCUS: n=10, 16%, and CMML n=13, 21%, Figure 1a). None of the DNMT3AMT CHIP and CCUS pts progressed to CMML.ASXL1MT were most frequently seen in CMML (n=178, 28.6%), followed by CHIP (n=4, 7.4%), and CCUS (n=17, 5%, p<0.001). The mVAF of ASXL1MT was significantly lower in CHIP, followed by CCUS, and CMML (11% vs. 34% vs. 36%, p<0.0001). Truncating ASXL1 MTs were most common (n=205, 53%). Mutational hotspots included G646W (n=81, CCUS: n=6, 3%, CMML: n=75, 37%) and E635 (n=27, CHIP: n=1, 0.5%, CCUS: n=1, 0.5%, CMML: n=27, 13%, Figure 1b). Four ASXL1MT CCUS pts transformed to CMML (R965, E635, G646W, Q910*, and Q925*); of which 2 co-mutated with TET2MT, one with SRSF2MT, and one with an additional ASXL1MT.TET2MT were frequently encountered in CMML, followed by CCUS and CHIP pts (CMML: n=205, 33% vs. CCUS: n=88, 26.3% vs. CHIP: n=15, 27.8%, p=0.02). The mVAF of TET2MT progressively increased across the 3 groups (CHIP: 14.1%, CCUS: 31.9%, CMML: 45.5%, p<0.001). TET2MT occurred across the span of the gene, with no clear hotspots identified, with nonsense MT being most frequent (n=150, 37.3%, Figure 1c). Among the nonsense and frameshift TET2MT (n=209), 131 (63%) involved the N terminal region, and 78 (37%) involved the catalytic domain. Among 8 CCUS pts that transformed to CMML, 6 had TET2MT, including 4 with spliceosome co-MT. Conclusion: While CMML, a disease of aging, arises in the background of CH, the most common CH MT, DNMT3AMT, plays a minor role in this process, and in fact, DNMT3AMT tend to occur at younger ages. While DNMT3A MT and ASXL1MT are preferentially observed in hotspots, TET2MT span the entire gene. Clonal compositions largely involving truncating TET2MT and frameshift ASXL1MT, in conjunction with splicing MT, shape the CMML genotype. Figure 1 Figure 1. Disclosures Komrokji: Geron: Honoraria; Novartis: Honoraria; Agios: Honoraria, Speakers Bureau; Abbvie: Honoraria, Speakers Bureau; JAZZ: Honoraria, Speakers Bureau; BMS: Honoraria, Speakers Bureau; Acceleron: Honoraria. Zeidan: Genentech: Consultancy; BeyondSpring: Consultancy; Kura: Consultancy, Other: Clinical Trial Committees; Amgen: Consultancy, Research Funding; Cardiff Oncology: Consultancy, Other: Travel support, Research Funding; Astex: Research Funding; Epizyme: Consultancy; Geron: Other: Clinical Trial Committees; Boehringer Ingelheim: Consultancy, Research Funding; AstraZeneca: Consultancy; Acceleron: Consultancy, Research Funding; Astellas: Consultancy; Novartis: Consultancy, Other: Clinical Trial Committees, Travel support, Research Funding; Agios: Consultancy; Aprea: Consultancy, Research Funding; AbbVie: Consultancy, Other: Clinical Trial Committees, Research Funding; Loxo Oncology: Consultancy, Other: Clinical Trial Committees; Pfizer: Other: Travel support, Research Funding; ADC Therapeutics: Research Funding; Gilead: Consultancy, Other: Clinical Trial Committees; BMS: Consultancy, Other: Clinical Trial Committees, Research Funding; Jazz: Consultancy; Incyte: Consultancy, Research Funding; Ionis: Consultancy; Jasper: Consultancy; Daiichi Sankyo: Consultancy; Janssen: Consultancy; BioCryst: Other: Clinical Trial Committees. Coombs: LOXO: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Genentech: Honoraria; MEI Pharma: Honoraria. Madanat: Blue Print Pharmaceutical: Honoraria; Stem line pharmaceutical: Honoraria; Onc Live: Honoraria; Geron Pharmaceutical: Consultancy. Griffiths: Takeda Oncology: Consultancy, Honoraria; Novartis: Honoraria; Taiho Oncology: Consultancy, Honoraria; Apellis Pharmaceuticals: Research Funding; Alexion Pharmaceuticals: Consultancy, Research Funding; Boston Biomedical: Consultancy; Astex Pharmaceuticals: Honoraria, Research Funding; Celgene/Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Genentech: Research Funding; Abbvie: Consultancy, Honoraria. Lai: Jazz Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astellas: Speakers Bureau; Jazz Pharma: Speakers Bureau; Macrogenics: 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; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Savona: CTI: Consultancy, Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; BMS-Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; NOVARTIS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Taiho: Consultancy, Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; ALX Oncology: Research Funding; Astex: Research Funding; Incyte: Research Funding. Litzow: AbbVie: Research Funding; Actinium: Research Funding; Pluristem: Research Funding; Amgen: Research Funding; Astellas: Research Funding; Jazz: Other: Advisory Board; Omeros: Other: Advisory Board; Biosight: Other: Data monitoring committee. Al-Kali: Novartis: Research Funding; Astex: Other: Research support to institution. Patnaik: StemLine: Research Funding; Kura Oncology: Research Funding.

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Abstract Background: Pev (TAK-924/MLN4924), a novel investigational NAE inhibitor, enhances the anti-leukemic effects of aza in AML cell lines and murine xenografts (Smith et al, Blood 2011). Single-agent pev activity was confirmed in relapsed/refractory AML pts (Swords et al, Br J Haematol 2015). This open-label, multi-center, dose-escalation study (NCT01814826) investigated pev + aza in treatment-naïve older AML pts. Dose-limiting toxicities (DLTs)includedG2 hyperbilirubinemia and G4 AST elevation (n=1 each) at pev 30 mg/m2. The maximum tolerated dose (MTD) for the combination was pev 20 mg/m2 + aza 75 mg/m2 (Swords et al, ASH 2014).We present updated safety/efficacy results for the MTD cohort (fully enrolled). Methods: Primary objectives included safety and tolerability assessments of pev + aza in addition to defining the MTD. Secondary objectives included pharmacokinetics (PK) and disease response assessments. Treatment-naïve pts ≥60 yrs unlikely to benefit from standard induction therapy (defined by ≥1 of: antecedent hematologic disease; known adverse cytogenetic risk; ECOG PS 2; ≥75 yrs), received pev 20 or 30 mg/m2 IV on d 1, 3 and 5, + fixed-dose aza (75 mg/m2 IV/SC) on d 1-5, 8 and 9, every 28 d until disease progression or unacceptable toxicity. Adverse events (AEs) were assessed per NCI-CTCAE v4.03; response per IWG criteria for AML. Bone marrow samples were collected at screening to assess cytogenetic risk (CALGB) and mutation profile; serial samples for PK analysis were drawn in cycle 1. Results: Demographics:As of May 17 2016, 61 pts (median age 75 yrs [range 61-89]; 54% male; 77% ECOG PS 0/1, 23% ECOG PS 2; 57% de novo, 43% secondary AML; median marrow blasts 36% [range 5-92]) had received pev 20 mg/m2, of whom 48% had intermediate-, 30% adverse-, and 3% favorable-risk cytogenetics. Safety/PK: Pts received a median of 4 cycles (range 1-33), and 23/61 pts (38%) received ≥6 cycles of pev + aza. The most common AEs were constipation (46%), nausea (44%), fatigue (43%), and anemia (39%). Fifty pts (82%) experienced ≥G3 AEs; the most frequent (≥15%) were anemia, febrile neutropenia (each 28%), thrombocytopenia (21%), neutropenia (18%), and pneumonia (15%). ≥G3 AST/ALT elevations were reported in 5% of pts. Forty-one pts (67%) experienced serious AEs; the most frequent (≥10%) were febrile neutropenia, neutropenia (each 25%), and pneumonia (11%). Two pts discontinued due to pev related toxicity (G3 febrile neutropenia). There were 11 on-study deaths unrelated to study therapy. In the MTD expansion phase (n=55), 2 pts experienced DLTs of transient G3/4 transaminase elevations, and were successfully re-challenged following dose reduction to remain on study. Pev PK was not altered by the addition of aza. Responses: Overall response rate (ORR) in 52 response-evaluable pts was 60% (18CR, 5CRi, 8PR; Figure 1), with a median duration of remission of 8.3 mos (95% CI: 5.75, 12.06); 19/31 (61%) responses occurred within the first 2 cycles.Of the 23 pts with CR/CRi, 14 had responses lasting ≥4 cycles, 2 went on to have allogeneic stem cell transplant, 9 had intermediate-, 7 adverse-, and 1 favorable-risk cytogenetics. ORR was: 64% (14/22; 7CR, 3CRi, 4PR) vs 57% (17/30; 11CR, 2CRi, 4PR) for pts with low- (<30%) vs high- (≥30%) marrow blasts; 58% (18/31; 11CR, 3CRi, 4PR) vs 62% (13/21; 7CR, 2CRi, 4PR) for de novo vs secondary AML pts; 61% (14/23; 8CR, 1CRi, 5PR) vs 50% (8/16; 5CR, 2CRi, 1PR) for intermediate- vs adverse-risk cytogenetic pts; 83% (19/23; 14CR, 2CRi, 3PR) vs 41% (12/29; 5CR, 3CRi, 4PR) for pts who received ≥6 cycles vs <6 cycles of aza, respectively. Responses were seen in pts with typically refractory disease; 7/11 pts with TP53 mutations achieved either a CR/CRi (n=3) or PR (n=4); 4 stayed on study for >10 cycles. After a median follow-up of 16.4 mos, 6-mo survival was 52%. Median overall survival was: 7.0 mos for the MTD cohort; 8.5 vs 5.2 mos for pts with low- (<30%) vs high- (≥30%) marrow blasts (Figure 2); 5.6 vs 11.2 mos for de novo vs secondary AML pts (Figure 3); and 16.1 vs 5.3 mos for pts aged 65-74 vs ≥75 yrs, respectively. Conclusion: Pev + aza was well tolerated. Response rates and durable remissions were observed with limited additional toxicity beyond what is expected for aza alone. The timing and frequency of responses suggests benefit from the addition of pev compared to aza alone (Dombret et al, Blood 2015). At the time of writing, a randomized phase 2 study in low-blast AML/high-risk myelodysplastic syndromes is ongoing. Disclosures Coutre: Janssen: Consultancy; Pharmacylics, LLC, an AbbVie Company: Consultancy, Research Funding; AbbVie: Research Funding. Zeidner:Tolero: Research Funding; Merck: Research Funding; Takeda: Research Funding; Otsuka: Consultancy; Agios: Honoraria. Foran:medscape: Honoraria; Millennium Pharmaceuticals, Inc.: Research Funding; novartis: Honoraria; pfizer: Honoraria; karyopharm: Honoraria; boehringer ingelheim: Research Funding; agios: Research Funding; Cellerant: Research Funding. Cruz:Millennium Pharmaceuticals, Inc.: Honoraria; Millennium Pharmaceuticals, Inc.: Speakers Bureau. Erba:Novartis: Consultancy, Speakers Bureau; Celator: Research Funding; Daiichi Sankyo: Consultancy; Celgene: Consultancy, Speakers Bureau; Juno: Research Funding; Millennium Pharmaceuticals, Inc.: Research Funding; Pfizer: Consultancy; Seattle Genetics: Consultancy, Research Funding; Incyte: Consultancy, DSMB, Speakers Bureau; Amgen: Consultancy, Research Funding; Agios: Research Funding; Sunesis: Consultancy; Gylcomimetics: Other: DSMB; Astellas: Research Funding; Ariad: Consultancy; Jannsen: Consultancy, Research Funding. Berdeja:Abbvie, Acetylon, Amgen, Bluebird, BMS, Calithera, Celgene, Constellation, Curis, Epizyme, Janssen, Karyopharm, Kesios, Novartis, Onyx, Takeda, Tragara: Research Funding. Tam:Millennium Pharmaceuticals, Inc.: Consultancy. Vardhanabhuti:Millennium Pharmaceuticals Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Dobler:Millennium Pharmaceuticals Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Faessel:Millennium Pharmaceuticals Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Dash:Millennium Pharmaceuticals Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Sedarati:Millennium Pharmaceuticals Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Dezube:Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment, Equity Ownership. Savona:Takeda: Research Funding; Amgen Inc.: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Research Funding; Sunesis: Research Funding; Ariad: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees.

Abstract Abstract 47 Background In adults with newly diagnosed, poor-risk AML we previously demonstrated that induction therapy with Flavopiridol in combination with Ara-C and Mitoxantrone (FLAM,) in a timed-sequential manner, yields complete remission (CR) rates of 67% and median disease-free survival (DFS) of 13.6 months. These data suggest that FLAM might improve outcomes relative to standard “7+3” in newly diagnosed AML with poor-risk features. Thus, we are conducting a phase II randomized trial comparing the CR rates with FLAM vs. 7+3 induction for all newly diagnosed adult patients with AML with intermediate and poor-risk features. We also previously identified a population of CD34+CD38− cells with intermediate aldehyde dehydrogenase (ALDH) activity that appears to represent a leukemic stem cell (LSC) population. We are examining the effects of FLAM vs. 7+3 in eradicating this LSC population and determining if persistence of LSC's predicts for relapse. Objectives The primary objective is to compare the rate of CR after 1 cycle of FLAM vs. 1 cycle of 7+3. The secondary objectives are to compare toxicities, survival rates, and presence or absence of minimal residual disease (MRD) after both induction regimens. Methods All newly diagnosed adult patients aged 18–70 without favorable risk features were randomized in a 2:1 fashion between FLAM and 7+3 at 90 mg/m2 of Daunorubicin. To achieve balanced randomization, patients were stratified by age, secondary AML and leukocyte count. CD34+ cell subsets were analyzed by flow cytometry for CD38 expression and ALDH activity by Aldefluor. The trial is ongoing. Results To date, 62 patients are evaluable for the primary end point. Demographics and results are depicted in table 1. Patient characteristics were similar in both arms, although there were more patients with poor risk features in the FLAM arm than 7+3. Overall grade > 3 toxicity was similar between both arms. However, there were 3 cases of grade > 3 tumor lysis syndrome (TLS) with FLAM, with 1 death, vs. 0 with 7+3. There were also 3 deaths with FLAM before day 60 vs. 0 with 7+3. CR rate with FLAM was 68% (28/41), with 1 cycle of 7+3 was 48% (10/21) (p = 0.17), and with 2 cycles (7+3 + 5+2) was 52% (11/21). CR rates based on specific risk factors are depicted in table 2. There was a trend toward improved CR rates in patients with adverse genetics with FLAM (p = 0.17). Putative AML LSC's were distinguished from normal hematopoietic stem cells based on ALDH activity. The persistence of putative LSC's in patients after therapy was highly predictive of subsequent clinical relapse. Conclusions Based on the current CR rate of 68%, FLAM holds promise as a therapeutic option for patients with newly diagnosed AML with intermediate and poor risk features. In this preliminary analysis, there is a suggestion that FLAM leads to higher CR rates in patients with adverse genetics than 7+3. Additionally, the detection of MRD consisting of a residual putative LSC population strongly portended subsequent relapse, even in patients without evidence of leukemia. Disclosures: Off Label Use: Flavopiridol (Alvocidib) is an anti-leukemia agent.