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  • 1
    In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 3274-3274
    Abstract: 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 〈 0.001) and allogeneic bone marrow transplant (15% vs 5%) compared to AAs; however, AML transformation rate was similar (21% vs 25%, p= .31, respectively). With a median follow up of 36 months (mo) (range .9-128.5), the median OS for AAs was 17.9 mo vs. 27.5 mo for WTs (p=.03, Figure 1). In a multivariable Cox analysis that include age and IPSS-R, AA pts retained their worse outcome compared to WTs (HR 1.68, CI 1.17-2.41, p= .005). Somatic mutational data were available on 321 pts (24 AAs). Overall, the most frequently mutated genes were: TET2 (16%), SF3B1 (13%), ASXL1 (13%), DNMT3A (10%), BCOR/BCORL1 (10%), STAG2 (10%), U2AF1 (8%), ZRSR2 (7%), and TP53 (5%). AA pts were more likely to have Tp53 (17% vs 4%, p = .04), and ZRSR2 mutations (21% vs 6%, p = .02). As a group, mutations in transcription factors (including SETBP1,RUNX1, BCOR, BCORL1, ETV6, NPM1, and CEBPA) and chromatin modifications (including ASXL1, SUZ12, EZH2, MLL, and KDM6A) were more common in WTs compared to AA pts (p= .02 and .049, respectively). Conclusion: In our cohort, AA pts with MDS had worse OS compared to WTs. Adjusting for IPSS-R risk categories and age did not negate this poor outcome. On a molecular level, AAs are more likely to have poor-risk mutations such as TP53, and less likely to have mutations in transcription factors and chromatin modifications pathways, which may have contributed to their inferior outcomes, and suggests that treatments targeting these pathways in AA pts may have less benefit. Figure 1: Overall survival by race Figure 1:. Overall survival by race Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2014
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  • 2
    In: The FASEB Journal, Wiley, Vol. 26, No. S1 ( 2012-04)
    Type of Medium: Online Resource
    ISSN: 0892-6638 , 1530-6860
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2012
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  • 3
    In: Contemporary Clinical Trials, Elsevier BV, Vol. 143 ( 2024-08), p. 107568-
    Type of Medium: Online Resource
    ISSN: 1551-7144
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2024
    detail.hit.zdb_id: 2176813-4
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  • 4
    In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 1054-1054
    Abstract: 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 〈 .001), and had lower white blood cell count (28 vs 3.5 X 109/L, p 〈 .001). Median hemoglobin (10 vs 10) g/dl and platelet counts (57 vs 60) k/uL were similar between the two groups. With a median follow up of 26.4 months (mo, range, .93-95.4), median OS was shorter for sAML than for pAML (12.9 vs 16.2 mo, p= .03). Overall, the most common mutations were: NPM1 (35%), DNMT3A (27%), FLT3 (25%), RUNX1 (14%), IDH1 (12%), IDH2 (12%), STAG2 (12%), TET2 (11%), NRAS (8%), ASXL1 (8%), U2AF1 (8%), PTPN11 (7%), WT1 (6%), BCOR (5%), and PHF6 (5%). Mutations in SF3B1, U2AF1/2, BCOR/BCORL1, ETV6, ASXL1, JAK2, STAG2, and APC were more common in sAML compared to pAML, whereas mutations in DNMT3A, NPM1, CEBPA, and FLT3 were more common in pAML. Mutations in activated pathways in splicing machinery, transcription, chromatin modification, cohesion and RAS pathway were more prominent in sAML, while mutations in DNA methylation and signaling pathways occurred more frequently in pAML. Serial sample analyses at multiple time points demonstrated intra-tumor heterogeneity in most cases of sAML, which was supported by additional cross sectional analyses of VAF in multiple gene mutations in each case. These findings prompted us to evaluate secondary events in the cohort of pts whose sAML originated from an initial MDS stage, defined by ancestral mutations. Among genes frequently affected by mutations, TET2 and ASXL1 were identified as founder events, whereas STAG2, NRAS and PTPN11 were observed in subclonal sAML derived from founder MDS clones. In pAML, however, TET2 and ASXL1 mutations were found to be secondary lesions, while IDH1 and DNMT3A were identified as ancestral events. Conclusion Clear genomic variations exist between sAML and pAML that suggest differences in the pathophysiology of both diseases. Specific therapies should be directed to the activated pathways according to the unique clonal hierarchy in each AML subtype. Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2014
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  • 5
    In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 168-168
    Abstract: Background The Revised International Prognostic Scoring System (IPSS-R) was developed to risk stratify untreated patients (pts) with MDS. It has since been validated in pts treated with a single line of drug therapy, and has been modified in untreated pts to include mutational data; however, these approaches do not reflect typical MDS pts who receive different types of treatment in different sequences. We propose a prognostic model that incorporates mutational data and predicts outcome in pts with primary and secondary MDS regardless of their initial or subsequent treatments. Methods Clinical and mutational data of 333 pts with newly diagnosed MDS who were treated at out institution between 1/2000-1/2012 were analyzed. The IPSS-R was calculated at diagnosis. Survival was calculated from the date of diagnosis to last follow up or death. A panel of 62 gene mutations obtained by next generation targeted deep sequencing selected based on the frequency observed in a separate cohort of MDS patients analyzed by whole exome sequencing (WES). A Cox proportional multivariate analysis including age, IPSS-R score and mutations that are present in 〉 /= 10 pts was used to select independent prognostic factors. The fit of the proposed model to the data was assessed by using the Akaike information criterion (AIC). Results Pt clinical characteristics are summarized in Table 1. Median age was 68 years (range, 20-87); 214 pts (64%) had de novo MDS, 39 (12%) had prior antecedentl hematologic disorders, 37 (11%) secondary MDS, and 43 (13%) had chronic myelomonocytic leukemia (CMML). Pts received between 0-7 lines of therapy: 15% did not receive any treatment, 85% received at least one treatment, 40% received 〉 /=2 treatments, 20% received 〉 /= 3 treatments and 14% of pts eventually underwent hematopoietic cell transplant (HCT). First line therapies included: growth factors (30%), azacitidine +/- combination (32%), decitabine +/- combination (7%), single agent lenalidomide (5%), investigational agents (5%), induction chemotherapy with cytarabine and an anthracycline (7+3, 2%), and immunosuppressive therapy (4%). With a median follow-up of 38 months (mo) (range, 0.4-128.5), 70 pts (21%) progressed to AML and the median OS was 35.1 mo (range, 0.4-128.5). Per IPSS-R risk groups, median OS for very low was 35 mo, low 35 mo, intermediate 22 mo, high 19 mo, and very high 12 mo, Figure 1. Among the 62 gene mutations, 25 were present in 〉 /= 10 pts: TET2 (17%), ASXL1 (15%), SF3B1 (14%), STAG2 (11%), DNMT3A (11%), RUNX1 (10%), U2AF1 (9%), GPR98 (8%), ZRSR2 (7%), BCOR (6%), TP53 (5%), NF1 (5%), EZH2 (5%), APC (5%), SUZ12 (5%), BCORL1 (4%), CBL (4%), PRPF8 (4%), NRAS (3%), CUX1 (3%), DDX54 (3%), IDH2 (3%), KDM6A (3%), PHF6 (3%), and SETBP1 (3%). A Cox proportional hazard analysis including age, IPSS-R score, and the 25 genes mutations listed above identified the following as independent prognostic factors: age, IPSS-R, ASXL1, BCOR, BCORL1, EZH2, IDH2, SF3B1,TP53. The linear predictive Cox model score obtained using the fitted coefficients of each prognostic factor was: ASXL1 X 0.65+BCOR X 0.92+BCORL1 X (-1.65)+EZH2 X 0.71+IDH2 X (-1.0)+SF3B1 X (-0.59)+TP53 X 1.24+Age X 0.04+IPSS-R score X 0.43. Four prognostic groups were proposed: low (score 0-3.4, 80 pts, median OS 47.3 mo), intermediate-1 (score 3.5-4, 69 pts, median OS 30.2 mo), intermediate-2 (score 4.1-5.4, 131 pts, median OS 19.9 mo), and high (score 〉 /= 5.5, 53 pts, median OS 12.2 mo), p 〈 0.001, Figure 2. The new model demonstrated a markedly better fit, reflected in an AIC of 2026, compared to 2058 for the IPSS-R. Conclusion We propose a new mathematical model that incorporates age, IPSS-R score and several gene mutations that can accurately predict OS in pts with primary and secondary MDS as well as CMML regardless of initial or subsequent treatments, including HCT. This model also highlights the importance of mutational data along with clinical data for risk stratification in MDS. Figure 1 Overall survival by IPSS-R Figure 1. Overall survival by IPSS-R Figure 2 Overall survival by the new prognostic model Figure 2. Overall survival by the new prognostic model Table 1 Patient characteristics No. (%) / [Range] Total 333 Median age, years 68 [20-87] Male 205 (62) Female 128 (38) Median white blood cell (WBC) X 109/L 3.8 [0.69-125.9] Median absolute neutrophil count (ANC) X 109/L 1.62 [0.02-170] Median hemoglobin,g/dl 9.6 [3.9-14.6] Median platelets X 109/L 93 [4-776] Median bone marrow blasts % 2 [0-19] IPSS-R Very low 50 (15) Low 128 (38) Intermediate 59 (18) High 60 (18) Very high 36 (11) Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2014
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  • 6
    Online Resource
    Online Resource
    Wiley ; 2011
    In:  The FASEB Journal Vol. 25, No. S1 ( 2011-04)
    In: The FASEB Journal, Wiley, Vol. 25, No. S1 ( 2011-04)
    Type of Medium: Online Resource
    ISSN: 0892-6638 , 1530-6860
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2011
    detail.hit.zdb_id: 1468876-1
    SSG: 12
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  • 7
    In: The FASEB Journal, Wiley, Vol. 26, No. S1 ( 2012-04)
    Type of Medium: Online Resource
    ISSN: 0892-6638 , 1530-6860
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2012
    detail.hit.zdb_id: 1468876-1
    SSG: 12
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  • 8
    In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 1933-1933
    Abstract: 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 .
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2014
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 9
    In: Journal of Biological Chemistry, Elsevier BV, Vol. 272, No. 35 ( 1997-08), p. 22059-22066
    Type of Medium: Online Resource
    ISSN: 0021-9258
    Language: English
    Publisher: Elsevier BV
    Publication Date: 1997
    detail.hit.zdb_id: 2141744-1
    detail.hit.zdb_id: 1474604-9
    SSG: 12
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