Gangat, Naseema

Abstract Primary myelofibrosis (PMF) is one of three myeloproliferative neoplasms (MPN) that are morphologically and molecularly inter-related, the other two being polycythemia vera (PV) and essential thrombocythemia (ET). MPNs are characterized by JAK-STAT–activating JAK2, CALR, or MPL mutations that give rise to stem cell–derived clonal myeloproliferation, which is prone to leukemic and, in case of PV and ET, fibrotic transformation. Abnormal megakaryocyte proliferation is accompanied by bone marrow fibrosis and characterizes PMF, while the clinical phenotype is pathogenetically linked to ineffective hematopoiesis and aberrant cytokine expression. Among MPN-associated driver mutations, type 1–like CALR mutation has been associated with favorable prognosis in PMF, while ASXL1, SRSF2, U2AF1-Q157, EZH2, CBL, and K/NRAS mutations have been shown to be prognostically detrimental. Such information has enabled development of exclusively genetic (GIPSS) and clinically integrated (MIPSSv2) prognostic models that facilitate individualized treatment decisions. Allogeneic stem cell transplantation remains the only treatment modality in MF with the potential to prolong survival, whereas drug therapy, including JAK2 inhibitors, is directed mostly at the inflammatory component of the disease and is therefore palliative in nature. Similarly, disease-modifying activity remains elusive for currently available investigational drugs, while their additional value in symptom management awaits controlled confirmation. There is a need for genetic characterization of clinical observations followed by in vitro and in vivo preclinical studies that will hopefully identify therapies that target the malignant clone in MF to improve patient outcomes.

Abstract Background The detrimental effect of leukocytosis on survival in myeloproliferative neoplasms (MPN) has been well established for primary myelofibrosis (PMF), polycythemia vera (PV) and essential thrombocythemia (ET ) (JCO. 2018;36:310; BJH. 2020;189:291) Previous studies have also implicated leukocytosis as a risk factor for leukemic transformation (Mayo Clin Proc. 2017;92:1118) and thrombosis in MPN (Blood Adv. 2019;3:1729). However, it is currently not clear as to which component(s) of white blood cells is responsible for these observations. In the current study, we sought to examine the individual prognostic contribution of absolute neutrophil (ANC), lymphocyte (ALC) and monocyte (AMC) counts, on overall (OS), leukemia-free (LFS), and myelofibrosis-free (MFFS) survival and in ET. Methods Study patients (n=349) were retrospectively recruited from the Mayo Clinic MPN database of 1,249 WHO-defined ET patients, evaluated over five decades (1967-2021), based on availability of information on ANC, ALC and AMC. Conventional criteria were used for diagnosis and definitions of major complications, including leukemic or fibrotic transformation (Blood 2016;127:2391). Conventional statistical methods were applied using JMP Pro 14.0.0 software package, SAS Institute, Cary, NC. Multivariable analyses included previously established risk factors for survival. Results 349 patients (median age 57 years, range 18-89; females 61%) with ET were included in the study: 46% JAK2, 34% CALR, 16% triple-negative and 4% MPL mutated; IPSET risk category high 24%, intermediate 41%, and low 35%; presenting median (range) values were 13.8 g/dL (11.1-16.4) for hemoglobin, 8.2 x 10(9)/L (3.2-52) for leukocyte count, and 859 x 10(9)/L (451-3460) for platelet count; palpable splenomegaly was present in 48 (14%); median followup was 10 years (range 0-47), during which time 118 deaths, 52 fibrotic progressions, and 14 leukemic transformations were documented. Multivariable analysis identified older age (p<0.001), increased ANC (p<0.001), decreased ALC (p=0.03), and male sex (p=0.04), but not AMC (p=0.8), venous thrombosis (p=0.4), or arterial thrombosis (p=0.4), as independent risk factors for OS. ANC of ≥8 x 10(9)/L and ALC of <1.8 x 10(9)/L were determined as appropriate cut-off values by ROC analysis. Subsequent multivariable analysis using these cut-off values resulted in HR (95% CI) of 5.2 (3.4-7.9; p<0.001) for age >60 years, 3.1 (2.1-4.6; p<0.001) for ANC, and 2.0 (1.4-3.0; p<0.001) for ALC; male sex was no longer significant in this analysis (p=0.14). An operational HR-based risk score assigned 3 adverse risk points for older age (>60 years), 2 for increased ANC (≥8 x 10(9)/L) and 1 for ALC (<1.8 x 10(9)/L), resulting in an new Age Anc Alc (AAA; triple A) risk model for survival in ET with estimates of median survival ranging from 9.7 to 36.6 years (Figure 1). In addition, ALC <1.8 x 10(9)/L was associated with inferior LFS (p=0.06) and MFFS (p=0.07) while AMC as a continuous variable showed borderline significance for MFFS (p=0.18). In univariate analysis, JAK2V617F allele burden showed significant association with OS (p=0.02), LFS (p=0.05) and MFFS (p=0.001); however significance for OS was lost in mutivariable analysis that included ANC and ALC. An external validation cohort from the University of Florence (n=485) confirmed the independent survival risk contribution from age >60 years (p<0.001; HR 9.9, 95% CI 5.4-18.0), ANC ≥8 x 10(9)/L (p=0.02; 1.9, 1.1-3.5) and ALC <1.8 x 10(9)/L (p<0.001; 2.0, 1.3-3.0). The Triple A risk model was also effectively applied on the Florence validation cohort (Figure 1): median follow-up 8.4 years; 87 deaths; 43 fibrotic progression; 12 leukemic transformations. The association of ALC <1.8 x 10(9)/L (p=0.04) and AMC (p=0.002) with fibrotic transformation was also validated in the Florence cohort. Conclusions: The current study identifies increased ANC and decreased ALC as age-independent risk factors for survival in ET, thus allowing the development of a globally applicable simple to use "Triple A" risk model that is based on Age, ANC and ALC. Decreased ALC also predicted fibrotic and leukemic progression. Our observations suggest potential value for immune profiling as an additional prognostic tool in MPN. Figure 1 Figure 1. Disclosures Szuber: Novartis: Honoraria. Vannucchi: BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees.

Abstract Background: Venetoclax, a small-molecule inhibitor of B cell leukemia/lymphoma-2, in combination with hypomethylating agents (HMA) has shown improved efficacy and survival benefit compared to HMA alone (DiNardo et al, 2020) in elderly/unfit patients with acute myeloid leukemia (AML). Since FDA-approval of this regimen for elderly/unfit AML patients, it is frequently utilized both in the upfront and relapsed/refractory setting. Cardiac events with venetoclax are not well described. In the VIALE-E trial, which included patients ineligible for standard induction chemotherapy due to congestive heart failure or stable angina, 15% of patients receiving azacitidine plus venetoclax experienced atrial fibrillation as a serious adverse event, vs. 1% in the azacitidine plus placebo group (DiNardo et al, 2020). Our objective was to provide an estimate of the prevalence of and a description of all cardiac events that occurred in AML patients undergoing treatment with venetoclax + HMA. Methods: 170 consecutive patients with AML who received venetoclax +HMA (azacitidine or decitabine) outside the context of a clinical trial between 1/2017-11/2020 at the Mayo Clinic were included. Patients received venetoclax + HMA either as upfront treatment or for relapsed/refractory disease. Patients with relapse following allogeneic stem cell transplant were excluded. We evaluated all cardiac events that occurred while treatment with venetoclax + HMA was ongoing. Baseline patient and treatment characteristics were compared using the Mann-Whitney U-test and the Fisher's exact test. All statistics were computed using EZR (Version 1.53). Results: 1. Patient characteristics A total of 170 patients who received venetoclax + HMA (median age 69 years [range 17-91], 63% males) were included. ELN risk category was either adverse risk (48%, 82/170) or intermediate risk (48%, 82/170) in the majority of patients. 64% (109/170) of patients received venetoclax + HMA as upfront treatment. Characteristics including age, ELN cytogenetic risk, cardiovascular risk factors, and upfront vs relapsed therapy were similar among patients with or without cardiac events. The only exception was a higher incidence of CEBPA mutation amongst those with cardiac events (12% vs 2%, p=0.03). The majority (83%, 141/170) of patients underwent an echocardiogram prior to initiation of therapy. 2. Cardiac events Of 170 patients treated with venetoclax + HMA during the study period, 34 (20%) patients experienced a total of 48 cardiac events. Of patients experiencing cardiac events, 32% (11/34) had no pre-existing cardiac disease and 12% (4/34) had no cardiovascular risk factors (Table 1). The majority of events occurred early in treatment course: 41% during cycle 1, 26% during cycle 2 and 15% during cycle 3 (Table 1). The most frequently occurring cardiac event (21%, 10/48 events) was a decrease in left ventricular ejection fraction on echocardiography, which was associated with symptoms in all ten patients. Second most frequent was atrial fibrillation with rapid ventricular response at 17% (8/48 events), followed by troponin elevation without electrocardiogram changes at 15% (7/46 events). Of patients with troponin elevation, 57% (4/7 events) occurred in the setting of another inciting factor such as severe anemia, while 43% represented a troponin elevation without explanation (Table 1). Other cardiac events included heart failure with preserved ejection fraction (n=4), other symptomatic arrhythmia (n=4), and symptomatic pericardial effusion or pericarditis (n=3). In addition, 2 of 34 (6%) patients experienced fatal cardiopulmonary arrest. The majority (88%) of cardiac events required either inpatient admission (62%, 21/34 patients) or intensive care unit (ICU) care (26%, 9/34 patients). 77% of patients required new cardiac medications or procedural intervention (n=4). In 27% of cases (9/34 patients), the cardiac event directly contributed to death (Table 1). Conclusions: Cardiac complications were observed in one-fifth (20%) of AML patients treated with venetoclax + HMA, despite the absence of preexisting cardiac disease in a third of cases; moreover 27% of events were fatal. Further comparative studies are required to identify salient clinical features predictive of cardiac complications in these patients. Figure 1 Figure 1. Disclosures Al-Kali: Novartis: Research Funding; Astex: Other: Research support to institution. Litzow: Astellas: Research Funding; Amgen: Research Funding; Omeros: Other: Advisory Board; AbbVie: Research Funding; Actinium: Research Funding; Pluristem: Research Funding; Jazz: Other: Advisory Board; Biosight: Other: Data monitoring committee. Patnaik: Kura Oncology: Research Funding; StemLine: Research Funding.

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 Background: Therapy-related acute myeloid leukemia (AML) is a well-described entity and known to carry a worse prognosis, compared to de novo AML. In the current study, we sought to describe the presenting features and outcome of patients with AML, in the setting of previous history of cancer with or without exposure to chemotherapy or radiotherapy. Methods: A Mayo Clinic database of patients with AML was queried to identify patients with a previous history of cancer, both hematologic and solid tumors. A comparative analysis of presenting features, treatment details and survival were performed between patients with therapy-related AML (Group A) and those with AML and a history of cancer that had been managed with surgery alone (Group B). Results: A total of 250 patients (median age 68 years, range 19-90; 60% males) with AML and a previous history of cancer (both hematologic and solid) were identified; 182 (73%) cases were determined to be therapy-related AML (Group A) while the remaining 68 (27%) did not receive chemotherapy or radiotherapy for their antecedent cancer (Group B) (Table). Among group A patients 106 (58%) were exposed to chemotherapy, 37 (20%) to radiotherapy and 39 (22%) to combination chemotherapy and radiotherapy for their cancer. At the time of AML diagnosis, adverse karyotype was noted in 91 (51%) group A and 12 (19%) group B patients (p<0.0001); the incidence of adverse karyotype in patients exposed to chemotherapy vs radiotherapy alone vs combined chemoradiotherapy was 54% (57/106), 30% (11/37), and 59% (23/39) respectively (p=0.04). Group A patients, compared to those in group B, included more females (46% vs 24%; p=0.001), and more preceding hematologic malignancies (p=<0.0001). Next generation sequencing was performed in 74 patients and the results showed no significant difference between groups A and B (Table). Treatment and outcome in Groups A and B: Intensive and less intensive AML-directed chemotherapy were given to 100 (55%) and 44 (24%) patients in group A and 38 (56%) and 14 (21%) patients in group B (P=0.8). 79 (65%) remissions (complete remission (CR) 42 (29%) and CR with incomplete count recovery (CRi) 37 (26%) were documented in Group A and 37 (71%) remissions (CR: 21 (40%) and CRi=16 (31%) in Group B (P=0.2). After a median follow-up of 8.4 months (range: 0.9-217), 184 deaths were documented: 132 (72.5%) in Group A and 52 (76.5%) in Group B (P=0.5). 52 (36%) patients from Group A and 25 (48%) from Group B relapsed (P=0.1). The median (range) overall survival (OS) rates of patients from Group A was 13 (9-17) months and that of Group B was 14 (10-35) months (P=0.6). The 1-, 3- and 5-year OS rates were 52%, 28%, and 24% in Group A; and 62%, 33%, and 24% in Group B patients (Fig 1). Multivariable analysis identified relapse (HR 2.8, 95% CI 1.7-4.7) and failure to achieve CR/CRi (HR 2.8 95% CI 1.9-4.7) as risk factors for inferior survival (Fig 2a and 2b). The median (range) relapse free survival of patients in Group A was 28 (17 -81) and that of Group B was 27 (14 - 76) months (P=0.9) (Fig 2c). 28 patients underwent allogenic stem-cell transplant (25 in CR1 and 3 in CR2), 23 in Group A and 5 in Group B; the 1-, 3-, and 5-year OS of patients who underwent allogenic stem cell transplant were 88%, 72%, and 72% regardless of the group (Fig 2d). Conclusion: The current study did not find significant differences between AML patients with previous history of cancer with or without exposure to chemo/radiotherapy, in terms of either response to AML-directed therapy or overall or relapse-free survival, despite a higher prevalence of adverse karyotype in therapy-related AML. Figure 1 Figure 1. Disclosures 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. Al-Kali: Astex: Other: Research support to institution; Novartis: Research Funding. Litzow: Pluristem: Research Funding; Actinium: Research Funding; AbbVie: Research Funding; Astellas: Research Funding; Amgen: Research Funding; Jazz: Other: Advisory Board; Omeros: Other: Advisory Board; Biosight: Other: Data monitoring committee.