Coombs, Catherine C.

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.

Abstract The management of chronic lymphocytic leukemia (CLL) has undergone unprecedented changes over the last decade. Modern targeted therapies are incorporated into clinical practice. Unfortunately, patients have begun to develop resistance or intolerance to multiple classes. Symptomatic patients previously treated with a BTK inhibitor (BTKi) and venetoclax represent a new and rapidly growing unmet need in CLL. Here, we define unmet needs in a modern treatment context. We also critically review the literature for PI3K inhibitors and chemoimmunotherapy and lack of data to support their utility following BTKis and venetoclax. Finally, we suggest opportunities to ensure the continued innovation for patients with CLL.

Supplemental Digital Content is available in the text

Background: Heterozygous somatic mutations in the genes encoding RNA splicing factors SF3B1, U2AF1, SRSF2 or ZRSR2 induce aberrant splicing in cancer cells and are among the most common mutations in patients with MDS, AML or CMML. H3B-8800 is an orally available small molecule that binds to the SF3b complex and induces alternative splicing changes in cells. Because splicing factor mutant cells depend on residual wild-type function of splicing factors for survival, we hypothesized that H3B-8800 would induce preferential cell killing of mutant cells by further perturbing splicing to synthetic lethality. In pre-clinical models, H3B-8800 preferentially kills spliceosome mutant cells and induces antitumor activity in xenograft leukemia models with core spliceosome mutations (Seiler M et al Nature Medicine 2018). Therefore, we conducted a phase I clinical trial (NCT02841540) of H3B-8800 in patients with MDS, AML or CMML. Here we describe the safety profile and clinical outcomes of the dose escalation cohorts in this phase I trial. Methods: This phase I trial explored the safety, pharmacokinetics (PK), and pharmacodynamics (PD) of H3B-8800 in patients with myeloid cancers. Dose escalation cohorts, employing a standard 3+3 design, examined 2 different once daily dosing regimens (schedule I: 5 days on/9 days off; schedule II: 21 days on/7 days off) in a 28-day cycle, with stratification based on lower-risk (LR) versus higher-risk (HR) myeloid neoplasms. Results: As of June 16th, 2019, 84 patients were enrolled at 24 centers in the US and Europe. Dose ranged from 1-40 mg among 65 patients on schedule I, while 19 patients were enrolled with dose ranging from 7-20 mg on schedule II. The patient population included AML (n=38), CMML (n=4), HR-MDS (n=20), LR-MDS (n=21) and 1 MDS with unknown risk level. Most patients (88%) had spliceosome mutations of interest. The most common mutations were in SRSF2 (p.P95H in 17, p.P95L in 9, p.P95_R102Del in 4), SF3B1 (p.K700E in 11, p.R625C in 4), and U2AF1 (p.Q157P in 6, p.S34F in 4). Patients remained on treatment from 7 to 819 days; 25 patients (30%) had time on treatment greater than 180 days, 20% more than 1 year and 2% over 2 years. The median therapy duration for LR-CMML/MDS, HR-CMML/MDS, and AML patients were 216, 62, and 47 days respectively. Most observed treatment related treatment-emergent adverse events (TEAEs) were Grade 1 or 2. The most common treatment-related (as judged by the investigator, >10% frequency) TEAEs in the patients treated on schedule I were diarrhea (75%), nausea (37%), fatigue (28%) and vomiting (27%). The most common treatment-related TEAEs in the patients treated on schedule II were diarrhea (68%), vomiting (42%), QTc prolongation (21%), nausea (16%), and fatigue (16%). The most common dose limiting toxicity was prolongation of the QTcF interval >500 msec (n=2, 40 mg on schedule I and n=1, 20 mg on schedule II, all ≥Grade 3) and bradycardia without other arrhythmias (n=1, 14 mg on schedule II, ≥Grade 3). No ophthalmic AEs were observed; 1 patient (LR-MDS) experienced durable marrow aplasia. The maximum tolerated dose (MTD) has not been confirmed for either Schedule I or Schedule II. PK analysis indicates that H3B-8800 is rapidly absorbed and exhibits dose-proportional increase in plasma exposure. Consistent dose-dependent target engagement (i.e., alteration in mature mRNA transcripts) was observed in blood mononuclear cells from patients enrolled in the 2 mg up to 40 mg dose cohorts on both schedules. Despite this splicing modulation, no objective complete responses (CR) or partial responses (PR) meeting International Working Group criteria were observed. One patient with CMML had a durable platelet response that began in Cycle 1 and persisted through Cycle 13. Nine red blood cell (RBC) transfusion-dependent patients with MDS or CMML and 2 patients with AML did not require RBC transfusions for ≥8 weeks (up to 28 weeks) while on study. One platelet transfusion-dependent patient with LR-MDS did not require platelet transfusions for ≥8 weeks. Conclusion: Results from this first-in-human multicenter prospective clinical trial of a splicing modulator in myeloid neoplasms demonstrate dose-dependent target engagement and predictable PK profile of H3B-8800, and safety even with prolonged dosing. Although no objective CR or PR were achieved, decreased RBC or platelet transfusion requirements were observed in 12 (14%) of enrolled patients. Disclosures Steensma: H3 Biosciences: Other: Research funding to institution, not investigator.; Pfizer: Consultancy; Aprea: Research Funding; Stemline: Consultancy; Arrowhead: Equity Ownership; Summer Road: Consultancy; Astex: Consultancy; Onconova: Consultancy. Wermke:Novartis: Honoraria, Research Funding. Greenberg:Notable Labs: Research Funding; Celgene: Research Funding; Genentech: Research Funding; H3 Biotech: Research Funding; Aprea: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees. Font:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Komrokji:Agios: Consultancy; JAZZ: Speakers Bureau; DSI: Consultancy; JAZZ: Consultancy; Incyte: Consultancy; Novartis: Speakers Bureau; celgene: Consultancy; pfizer: Consultancy. Yang:Agios: Consultancy; AstraZeneca: Research Funding. Brunner:Astra Zeneca: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Forty Seven Inc: Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding. Ades:Agios: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Jazz: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Silence Therapeutics: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Helsinn Healthcare: Membership on an entity's Board of Directors or advisory committees. Al-Kali:Astex Pharmaceuticals, Inc.: Research Funding. Coombs:H3 Biomedicine: Research Funding. Foran:Agios: Honoraria, Research Funding. Garcia-Manero:Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Amphivena: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding. Micol:AbbVie: Consultancy; Jazz Pharmaceuticals: Consultancy. Perez De Oteyza:Celgene: Speakers Bureau. Wang:Abbvie: Other: Advisory role; Kite: Other: Advisory role; Jazz: Other: Advisory role; Astellas: Other: Advisory role, Speakers Bureau; celyad: Other: Advisory role; Pfizer: Other: Advisory role, Speakers Bureau; Stemline: Other: Advisory role, Speakers Bureau; Daiichi: Other: Advisory role; Amgen: Other: Advisory role; Agios: Other: Advisory role. Watts:Pfizer: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees. Buonamici:H3 Biomedicine: Employment. Kim:H3 Biomedicine: Employment. Gourineni:H3 Biomedicine: Employment. Marino:H3 Biomedicine: Employment. Rioux:H3 Biomedicine: Employment. Schindler:H3 Biomedicine: Employment. Smith:H3 Biomedicine: Employment. Yao:H3 Biomedicine: Employment. Yuan:Eisai: Employment. Yu:H3 Biomedicine: Employment. Platzbecker:Abbvie: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding. OffLabel Disclosure: H3B-8800 (experimental, unapproved)

Abstract Abstract 1785 Background: Chronic lymphocytic leukemia (CLL) is a malignant lymphoproliferative disorder characterized by the progressive clonal expansion of CD5+ B cells. Approximately 8–10% of CLL patients have a first degree relative with CLL, indicating that genetic factors can contribute to disease susceptibility. Genome wide association (GWA) studies have identified 16 “common variants,” single-nucleotide polymorphisms (SNPs) with a population prevalence of >5%, that confer risk for CLL. Among patients with CLL, the clinical course can be highly heterogeneous. Studies have defined disease-characteristics that vary among patients that can be used as markers to help predict clinical outcome. African American (AA) CLL patients have a poorer overall survival than Caucasians. However, there is little information on whether there are distinctive, ethnic-associated disease-characteristics that contribute to differences in clinical outcome. Moreover, studies of the genetics of CLL have involved primarily Caucasian patients. For these reasons, we examined for ethnic-related differences in the distribution and prevalence of CLL-associated SNPs and adverse disease-associated characteristics among AA with CLL relative to those of Caucasian patients with this disease. Methods: The clinical and biologic characteristics of 43 AA CLL patients ascertained at Duke University and the Durham VA Medical Center were tabulated and compared to Caucasian CLL patients at the same centers. Fifteen SNPs were genotyped in this “discovery” cohort of 43 AA CLL patients using TaqMan SNP genotyping assays. As a “validation” cohort, 70 AA CLL patients ascertained by the CLL Research Consortium (CRC) were assayed using the same platform. Three control groups were considered in analysis: (1) previously published Caucasian CLL patients, (2) control AA genotypes reported in the HapMap database and (3) control AA with no history of malignancy from other GWA studies. The 3' untranslated region of CPEB1 was sequenced in AA CLL patients using conventional Sanger sequencing. Results: Among the Duke/Durham VA CLL patients, no significant differences were observed in age, WBC count, platelet count, or hemoglobin at diagnosis; lymphocyte doubling time; Rai stage; ZAP70 expression; or CD38 expression between AA and Caucasian patients. AA had a larger proportion of trisomy 12 and fewer 13q.14 deletions than Caucasians: 40.0% of AA had trisomy 12 and 15.0% had del 13q, compared to 14.6% and 40.7% of Caucasians, respectively. IGHV mutation status also varied between races, with 62.2% of AA having unmutated IGHV, compared to 38.4% of Caucasians. Disparities in clinical outcomes were similar to that reported in the SEER database: overall survival was 8.8 years in AA patients and 17.8 years in Caucasians, and time to first treatment was 2.8 years among AAs and 4.5 years for Caucasians. Risk allele frequencies among 15 genotyped SNPs showed that 14 SNPs had risk allele frequencies that statistically differed between AA patients and Caucasian CLL patients. In 9 of 14 SNPs, the risk allele was less common in AA than in Caucasians but similar to that AA controls. In the other 5 SNPs, the risk allele was more common in AA CLL than Caucasian CLL, and similar to that of AA controls in 4 of the SNPs. A single SNP, rs783540 (CPEB1) was found to have an increased frequency in AA patients with CLL when compared to both Caucasian CLL and control AA. As an exploratory analysis to identify possible pathogenic variants, the 3' UTR of CPEB1 was sequenced as there are no common non-synonymous SNPs in CPEB1. Preliminary review of the sequencing data revealed that a G insertion SNP (rs34816185) that alters a predicted miRNA binding site is in linkage disequilibrium with rs783540 (D'= 0.978). Conclusions: Most SNPs associated with CLL risk are less frequent in AA than in Caucasian CLL patients. However, rs783540 (intron 2, CPEB1) risk allele was more frequent in AA CLL than that previously reported in Caucasian CLL or AA controls. Initial data suggests that rs783540 is linked to a SNP in the 3' UTR of CPEB1, which may have functional significance. Studies to better delineate the functional and clinical implications of these germline variants are underway. Our data provide the first evidence of differential genetic risk as a determinant of CLL biology among different ethnic groups. Disclosures: No relevant conflicts of interest to declare.

AbstractThe incidence of chronic lymphocytic leukemia (CLL) is significantly lower in African Americans than whites, but overall survival is inferior. The biologic basis for these observations remains unexplored. We hypothesized that germline genetic predispositions differ between African Americans and whites with CLL and yield inferior clinical outcomes among African Americans. We examined a discovery cohort of 42 African American CLL patients ascertained at Duke University and found that the risk allele frequency of most single nucleotide polymorphisms known to confer risk of development for CLL is significantly lower among African Americans than whites. We then confirmed our results in a distinct cohort of 68 African American patients ascertained by the CLL Research Consortium. These results provide the first evidence supporting differential genetic risk for CLL between African Americans compared with whites. A fuller understanding of differential genetic risk may improve prognostication and therapeutic decision making for all CLL patients.