Lai, Catherine

Abstract Background We performed a prospective study evaluating a baseline GA battery and clinical outcomes in fit older adults (age ≥60 years) with AML and normal cardiac and renal function in the recent E-A NCTN E2906 phase 3 study. A patient-reported outcomes (PRO) assessment of Depression, Activities of Daily Living (ADL), Cognitive Function, Social Support (SS) domains, and comorbidity was performed at study registration to evaluate the prevalence of vulnerabilities and their impact on overall survival (OS) and 30-day induction mortality rates (IM) in this cohort selected for fitness to receive IC. Methods E2906 study design and results have been presented previously [n=727, age ≥60 years, randomized 1:1 to ‘standard 7&3‘ & high dose cytarabine (Arm A) vs. single agent clofarabine (CLO, Arm B), as remission induction (Step 1) and consolidation (Step 2)]. There was no difference in composite complete remission (CCR, 50%) or IM (8.5%), and CLO was inferior for OS. A baseline GA was a key secondary protocol objective, offered to all patients, and n=532 (73%) participated. We assessed Geriatric Depression Scale (GDS, none vs. any depressive symptoms, n=524); cognitive screen using Mini-Mental Exam Section (MMES, score 8/8 vs. <8, n=516); ADL & Instrumental ADL (iADL), (need for assistances vs. not n=526); a Medical Outcomes Study SS Survey (MOS-SS, measured as per unit increase, n=527); a Comorbidity survey ( ≤4 vs. ≥5 patient-reported comorbidities, n=530), patient-reported prescription medications use (PM, 0-3 vs. ≥4, n=519); and a survey of Sexual Desire (n=491) and Sexual Activity (n=477) within 4 weeks of AML diagnosis. Association of GA domains with OS, IM, and achievement of CCR was evaluated using the Chi-squared, Fisher's exact, and Wilcoxon rank sum test. Survival analysis was performed using the Cox proportional hazards models, adjusted for treatment arm. All p-values are 2-sided. Results The median age among those participating in GA battery was 67 yrs (range 60-85), including 38% age ≥70. There were 42% females, and ECOG performance status was 0 (28%), 1 (54%), 2 (16%), or 3 (2%). Central Cytogenetic review was classified (ELN2017) as Favorable (3%), Intermediate (66%), and Adverse (31%) risk. There was a notable rate of GA scores outside ‘normal’ clinical cutoff, including Depression (GDS 31%), cognitive and functional impairment [MMSE (37%), ADL (25%) and iADL (32%)], ≥5 Comorbidities (23%), and ≥4 PM's (44%). 81% & 76%, respectively, reported no sexual activity and low/none sexual desire. MOS-SS tended to be high in this cohort [mean (SD) score 87 (17)]. We observed a significant association of GA domains with OS & IM. For OS, absence of depressive symptoms [GDS, Hazard Ratio (HR) 0.79, 95% confidence Intervals (CI) 0.64-0.97, p=0.025)], MMES 8/8 (HR 0.78, 95%CI 0.64-0.96, p=0.016), requiring no assistance with ADLs (HR 0.65, 95%CI 0.52-0.82, p<0.001) and iADLs (HR 0.69, 95%CI 0.57-0.85, p<0.001), and ≤4 Comorbidities (HR 0.68, 95%CI 0.54-0.84, p=0.001) were significant for superior OS; use of ≥4 PM's was associated with inferior OS (HR 1.32, 95%CI 1.09-1.61, p=0.005). There was no association of sexual activity/desire, BMI ≥30 kg/m2, or MOS-SS with OS. IM was significantly higher among those with any depression symptoms (GDS, p=0.005), any ADL (p=0.010) or iADL (p=0.013) impairment, ≥5 comorbidities (p=0.037) and ≥4 PM's (p=0.001); there was no association with MOS-SS or MMES. There was no significant association of GA scores with cytogenetic risk group or with CCR rates. Only ADL independence (p=0.048), and possibly Comorbidity ≤4 (p=0.071), were associated with proceeding to Step 2. Conclusions In this large prospective cohort of fit older adults with AML selected to receive IC, we observed high rates of PRO-assessed GA vulnerability, which was significantly associated with inferior OS and higher IM rates, and (for ADL impairment) lower rates of proceeding to consolidation therapy. This suggests that functional and cognitive impairments are prevalent and can significantly impact outcome even in fit older adults. Despite potential long-term OS advantages of IC previously observed in E2906, efforts to systematically recognize those at higher risk based on GA PROs are needed to help identify patients who may be more appropriate for study of lower intensity treatment options to mitigate impact on IM and OS. SImilarly we plan to evaluate the potential benefit of GA-driven supportive care to improve patients' outcomes.

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.

AbstractBackgroundObesity (body mass index [BMI] ≥30 kg/m2) is an important epidemiological risk factor for developing acute myeloid leukemia (AML). Therefore, the authors studied the association of obesity with clinical and genetic phenotype and its impact on outcome in adults with AML.MethodsThe authors analyzed BMI in 1088 adults who were receiving intensive remission induction and consolidation therapy in two prospective, randomized therapeutic clinical trials of the Eastern Cooperative Oncology Group‐American College of Radiology Imaging Network: E1900 (ClinicalTrials.gov identifier NCT00049517; patients younger than 60 years) and E3999 (ClinicalTrials.gov identifier NCT00046930; patients aged 60 years or older).ResultsObesity was prevalent at diagnosis (33%) and, compared with nonobesity, was associated with intermediate‐risk cytogenetics group (p = .008), poorer performance status (p = .01), and a trend toward older age (p = .06). Obesity was not associated with somatic mutations among a selected 18‐gene panel that was tested in a subset of younger patients. Obesity was not associated with clinical outcome (including complete remission, early death, or overall survival), and the authors did not identify any patient subgroup that had inferior outcomes based on BMI. Obese patients were significantly more likely to receive <90% of the intended daunorubicin dose despite protocol specification, particularly in the E1900 high‐dose (90 mg/m2) daunorubicin arm (p = .002); however, this did not correlate with inferior overall survival on multivariate analysis (hazard ratio, 1.39; 95% confidence interval, 0.90–2.13; p = .14).ConclusionsObesity is associated with unique clinical and disease‐related phenotypic features in AML and may influence physician treatment decisions regarding daunorubicin dosing. However, the current study demonstrates that obesity is not a factor in survival, and strict adherence to body surface area‐based dosing is not necessary because dose adjustments do not affect outcomes.

12040 Background: Novel strategies are needed to assess frailty in the context of therapy decisions for older adults with acute myeloid leukemia (AML). Our objectives were to describe pre-treatment DAFI scores for older AML patients treated on clinical trials and explore their relationship with treatment outcomes. Methods: We conducted a exploratory analysis utilizing data from two clinical trials of adults aged ≥60 years with newly diagnosed AML (Alliance/CALGB 11001 [intensive therapy] and Alliance/CALGB 11002 [non-intensive therapy]). We included the subset of patients in each trial enrolled on geriatric assessment companion studies (Alliance/CALGB 361006, 361101). A DAFI score was calculated for each patient using 51 variables including demographic, geriatric assessment, and laboratory data derived from the geriatric assessment. Individuals with ≥90% items were included (consistent with other studies); DAFI scores ranged from 0 to 1 and were evaluated using established categories (0- <.2 [robust]; 0.2-<.35 [pre-frail]; 0.35+ [frail]) and as a continuous score. Associations between DAFI scores and toxicity and overall survival (OS) were evaluated with Fisher’s exact-testing and Kaplan Meier/cox proportional hazards, respectively. Results: The median age was 68 years (range 61, 82) and 72 years (range 61, 92) for those getting intensive (N=31) and less intensive therapy (N= 75), respectively. Individuals in the intensive study had a median pre-treatment DAFI score of 0.15 (range 0.05, 0.31) and were all categorized as robust (75%) or pre-frail (25%). There was no significant difference in median OS (14.6 vs. 14.7 months) or non-hematological grade 3+ adverse events (AEs; 85% vs. 89%) between robust vs. pre-frail individuals in this trial, respectively. However, pre-frail adults experienced a trend towards greater grade 4 non-hematological toxicity than robust individuals (67% vs 26%, p=0.05). In the non-intensive trial, the median DAFI score was 0.24 (range 0.04, 0.48) and most individuals were pre-frail (49.3%) or frail (17.3%). Non-hematologic grade 3+ AEs did not vary by DAFI group, 88% robust, 95% pre-frail, and 77% frail (p=0.15). Median OS was 7.4, 10.8, and 6.3 months for robust, pre-frail, and frail respectively (p=0.17). Adjusting for age, each 0.1 increase in DAFI score was associated with increased mortality hazard (HR 1.8, 95% CI 1.0-3.2). Conclusions: DAFI score calculation provides a potential novel strategy for categorization of frailty in AML. In our assessment, higher DAFI scores were associated with toxicity during intensive induction and mortality in the less intensive setting. This method should be studied in larger samples randomized by treatment intensity. Support: UG1CA189823; Bayer Healthcare/Berlex (CALGB 11001); NCT01253070 (CALGB 11001). Clinical trial information: NCT01253070, NCT01420926.

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 &lt; 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 &gt;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&lt;0.001). None of the pts with TP53 MT died. Having &gt;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&lt;10 g/dL (HR: 3.7, 95% CI: 1.8-7.9, p&lt;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 &gt;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) &gt;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&lt;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&lt;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&lt;0.001), with mVAF of DNMT3AMT increasing across this spectrum (CHIP: 6.5% vs. CCUS: 17.1% vs. CMML: 43.4%, p&lt;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&lt;0.001). The mVAF of ASXL1MT was significantly lower in CHIP, followed by CCUS, and CMML (11% vs. 34% vs. 36%, p&lt;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&lt;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.