ALBERT

Description: Bone marrow (BM) fibrosis is a key pathomorphologic feature of patients (pts) with primary myelofibrosis (PMF) and the fibrotic phases of essential thrombocythemia (post-ET MF) and polycythemia vera (post-PV MF). The degree of BM fibrosis appears to correlate with survival. Indeed worse survival has been associated with increased BM fibrosis. The BM stromal microenvironment is important in the pathogenesis of BM fibrosis. Cellular components (fibroblasts, macrophages, endothelial cells, adipocytes), structural fibrils (collagen, reticulin) and extracellular matrix components are all forming elements of the BM stroma. Increased stromal fibrosis has been linked to abnormalities in the number/ function of megakaryocytes and platelets in hematologic diseases. Several cytokines like Platelet Derived Growth Factor (PDGF) and Transforming Growth Factor-Beta (TGF-b) have been also linked to the pathophysiology of BM fibrosis. PDGF has been shown to increase fibroblast growth in megakaryocytes and platelets although increased PDGF did not correlate with increased production of either reticulin or collagenous fibrosis. Moreover, PMF pts have increased TGF-b levels in platelets, megakaryocytes, and monocytes. Nitric Oxide (NO) is a ubiquitous gas important in physiologic processes particularly vasodilatation. Dysregulation of NO levels has been implicated in pulmonary hypertension (PH), hemoglobinopathies, and cardiovascular diseases. In Peyronie’s disease, a localized fibrosis of the penile tunica albuginea, increased NO production by expression of iNOS decreases collagen deposition by neutralization of profibrotic reactive oxygen species and decreased myofibroblast formation. Aside from its role in maintaining normal vascular tone, NO also plays a role in fibroblast formation and collagen biosynthesis. We previously reported that ruxolitinib, a JAK1/2 inhibitor restores NO levels leading to improvement of PH in MF pts (Tabarroki et al., Leukemia 2014). We now hypothesize that plasma/serum NO level is a key regulator of BM fibrosis in MF and that ruxolitinib treatment (Tx) leads to improvement of BM fibrosis by NO modulation. Using a Sievers 280i NO analyzer we measured the plasma/serum NO level of a large cohort (n=75) of pts with myeloid and myeloproliferative neoplasms (MPN) [MDS, RARS/RCMD=8; MPN, ET=8, PV=8, MF=24, Mastocytosis=7; MDS/MPN, CMML=11, MDS/MPN-U, RARS-T=9]. Healthy subjects (n=10) were used as a control. MPN pts had low NO (nM) levels among the pts studied with the lowest level found in MF pts: MF=30.31±11.8, PV=39.0±16.1, ET=36±20.3, RARS=74.6±41.7 (P=.01), CMML=84.4±89.2 (P=.04), RCMD=163.4±103.8 (P

Description: Background: Aberrant epigenetic modifications, fundamental to the pathogenesis of MDS, provide rationale for the use of the so-called hypomethylating agents, decitabine (DAC) and azacitidine (AZA). As depletion of DNA methyltransferase 1 (DNMT1) by these agents is S-phase dependent, episodic dosing used in common practice (SD-DAC; 20 mg/m2 x 5 days, every 28 days, SD-AZA; 75 mg/m2 x 5-7 days, every 28 days) affects only a fraction of the malignant clones. Alternative dosing schedules of decitabine with lower doses given more frequently (LD-DAC; .1-.2 mg/kg SC once/twice weekly) may decrease toxicity and increase response rates by improved hematopoietic differentiation and DNMT1 depletion while avoiding cytotoxicity. Data comparing use of very low and standard-dose DAC or AZA are lacking. Methods: We compared response, survival, and toxicities of 242 MDS patients (pts) treated at our institution from 9/06-10/13 with LD-DAC (n=39), SD-DAC (n=17), or SD-AZA (n=186). Response was assessed per International Working Group 2006 (IWG) criteria, progression-free (PFS) from date of response, and overall survival (OS) from diagnosis. Results: There were no significant differences in baseline characteristics, including median age (70 vs. 74 years, P=.93), proportion of patients with ≥5% bone marrow blasts (27% vs. 35%, P=.54), high/very high cytogenetic risk by the Revised International Prognostic Scoring System (IPSS-R, 25% vs. 40%, P=.31), number of pts with comorbidities (44% vs. 29%, P=.38), median time from diagnosis to treatment (14.6 vs. 6.4 months, P=.25) or prior MDS treatment (AZA and/or lenalidomide, 46% vs. 53%, P=.17), between the LD-DAC and SD-DAC groups, respectively. Likewise, the LA-DAC and SD-AZA groups were similar with respect to median age (70 vs. 68 years, P=.15), proportion of patients with ≥5% bone marrow blasts (27% vs. 39%, P=.19), and high/very high cytogenetic risk by the IPSS-R (25% vs. 27%, P=.83). However, pts in the SD-AZA group had a shorter median time from diagnosis to treatment (2.9 vs. 14.6 months, P=.009) compared to LD-DAC. Median treatment duration was longer in LD-DAC pts compared to SD-DAC (9.1 vs. 3.1 months, P=.0008) with a median cumulative dose of 8.4 mg/kg (range 1.2-41.2) and 350 mg/m2 (range 175-975) for LD-DAC and SD-DAC, respectively. Compared to SD-DAC, the LD-DAC group required more frequent dose reductions/delays (67% vs. 20%, P=.004) and experienced more hematologic toxicity (85% vs. 29%, P〈 .0001), respectively. While median time to best response was similar for LD-DAC and SD-DAC (3 vs. 4.1 months, P=.52) there was a trend for higher IWG response rates (30% vs. 18%, P=.06) and lower disease progression rates (18% vs. 41%, P=.06) for LD-DAC compared to SD-DAC. However, this did not translate into a difference in median PFS (11 vs. 7.6 months, P= .34) or OS (23.9 vs. 18.2 months, P=.64, Figure 1). Comparing these results to SD-AZA, while LD-DAC had a longer median treatment duration (9.1 vs. 5.1 months, P=.052) and shorter median time to best response (3 vs. 5.3 months, P=.005) than SD-AZA, response rates were similar (30% vs. 31%, P=.5) and there were no significant differences with respect to median PFS (11 vs. 7.1 months, P=.059) or OS (23.9 vs. 21.1 months, P=.5, Figure 1). Conclusion: Pts treated with the LD-DAC strategy have a response rate at least equivalent to SD-DAC and SD-AZA, though they required more dose adjustments and receive treatment for a longer time period. Survival was similar for all dosing strategies. Very low-dose DAC is an active treatment approach and will be compared to standard-dose DAC and AZA in an upcoming randomized, prospective trial conducted through the MDS Clinical Research Consortium. Figure 1 Figure 1. Disclosures Off Label Use: Subcutaneous administration of very low-dose decitabine in treatment of MDS .

Description: Background For decades, cytogenetic analysis has played an essential role in AML risk stratification. Among the 50% of AML patients (pts) with normal karyotype (NK), outcome can vary widely. More recently, whole genome sequencing (WGS) and whole exome sequencing (WES) have identified several recurrent mutations that play an important role in AML pathogenesis and impact outcome. Pts with secondary AML (sAML) have a particularly poor prognosis, are not as responsive to standard induction chemotherapy, and often are referred in first complete remission to hematopoietic stem cell transplantation. We hypothesized that different genomic patterns exist between primary AML (pAML) and sAML that can distinguish the two, and can alter treatment recommendations. To negate the impact of chromosomal abnormalities, we focused our analyses on pts with NK. Methods We performed WES and multi-amplicon targeted deep sequencing on samples from bone marrow and peripheral blood of pts diagnosed with sAML at our institution between 1/2003- 1/2013 and who had NK cytogenetics. We compared them to pts with NK primary AML (pAML) whose data were extracted from The Cancer Genome Atlas (TCGA). A panel of 62 gene mutations that has been described as recurrent mutations in myeloid malignancies was included. Mutations were considered individually and grouped based on their functional pathways: RNA splicing (SF3B1, U2AF1/2, SRSF2, ZRSR2), DNA methylation (TET2, DNMT3A, IDH1/2), chromatin modification (ASXL1, EZH2, MLL, SUZ12, KDM6A), transcription (RUNX1, CEBPA, NPM1, BCOR/BCORL1, SETBP1, ETV6), activating signaling (FLT3, JAK2), cohesion (STAG2, SMC3, RAD21), RAS superfamily (K/NRAS, NF1, PTPN11, CBL) and tumor suppressor genes (TP53, APC, WT1, PHF6). Using deep sequencing methodology for resequencing or targeted sequencing, variant allelic frequency (VAF) was measured for each mutation detected. VAF was adjusted by zygosity evaluated by SNP-array karyotyping. For confirmation of clonal architecture, serial sample sequencing and single colony PCR were applied. Differences were compared using Fisher-exact test and Mann-Whitney U test for categorical and continues variables respectively. Results: Of 143 pts included, 101 (71%) had pAML and 42 (29%) had sAML. Compared to pAML, sAML pts were older (59 vs 69 years, p

Description: Background: African-American (AA) patients (pts) have a younger age at diagnosis and worse outcomes compared to whites (WTs) across many cancers, including acute myeloid and lymphoblastic leukemias. This difference may be related to disease biology rather than access to medical care or socioeconomic status. The incidence of MDS and age at diagnosis in national cancer registries in AAs is lower than in WTs. Detailed biological and clinical characteristics and outcome of AA pts with MDS compared to WTs have not been defined. Methods: We collected mutational and clinical data on MDS pts diagnosed from 1/2000-1/2012. Next-generation gene-targeted deep sequencing of 62 common gene mutations (selected based on frequencies established in a separate cohort of MDS pts studied by whole exome sequencing) were analyzed as individual mutations and then grouped into several functional pathways which were hypothesized to characterize MDS pathogenesis. International Prognostic Scoring System-Revised (IPSS-R) score was calculated as described previously. Overall survival (OS) was measured from the time of diagnosis to time of death or last follow up. Time-to-event analyses were performed by the Kaplan-Meier method, with curves compared by log rank test. Differences among variables were evaluated by the Fisher’s exact test and Mann-Whitney U test for categorical and continuous variables, respectively. Results: Of 341 pts, 44 (13%) were AA. Comparing WTs to AAs, pts had a similar median age (68 for both), absolute neutrophil count (1.6 vs 2.23) X 109/L, hemoglobin (9.7 vs 9.4) g/dL, platelets (93 vs 91) X 109/L, and bone marrow blasts (2% vs 3%), respectively. IPSS-R risk category distribution for WTs and AA was: very low 15% vs 9%, low 35% vs 30%, intermediate 18% vs 18%, high 16% vs 23%, very high 10% vs 18%, and not applicable 6% vs 2%, respectively. Among AA pts, 25% had very poor risk cytogenetics per IPSS-R criteria (complex 〉3) compared to 10% of WTs (p=.008) which led to 41% of AA pts having high and very high risk IPSS-R scores compared to 26% of WTs (p=.035). Further, WTs were more likely to receive a treatment (86% vs 66%, p