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  • American Society of Hematology  (5)
  • Yusa, Nozomi  (5)
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  • American Society of Hematology  (5)
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  • 1
    In: Blood, American Society of Hematology, Vol. 132, No. Supplement 1 ( 2018-11-29), p. 2254-2254
    Abstract: Background: Next-generation sequencing (NGS) is an attractive tool for prospective use in the field of precision medicine. Using NGS to guide therapy has provided a large volume of genomic data and therapeutic actionability of somatic NGS results. These data are evolving too rapidly to rely solely on human curation. So the interpretation of the clinical significance of such large amounts of genetic data remains the most severe bottleneck preventing the realization of precision medicine. Watson for Genomics (WfG) is a representative artificial intelligence (AI) software, which analyzes and categorizes genetic alterations that are related to disease progression and provides a list of potential therapeutic options within 3 minutes per sample. Recent reports suggested that WfG could empower tumor boards and improve patient care by providing a rapid, comprehensive approach for data analysis and consideration of the up-to-date availability of clinical trials (Patel NM, et.al. Oncologist. 2018). However, only limited data are available regarding the utility of AI-guided precision medicine approach in the field of hematological disease. The purpose of this study is to test the utility of AI in assisting the interpretation of high throughput genomic data from patients with the hematological disease. Methods: After obtaining written informed consent, we enrolled patients with hematological disease at our research hospital between May 2015 to June 2018. Genomic DNA was prepared from malignant cell fractions and normal tissues in each patient and subjected to comparative NGS, mainly targeted deep sequencing (TDS) with ready-made panels and, on demand, whole exome sequencing (WES). Sequence data was analyzed using a pipeline of in-house semi-automated medical informatics. After initial bioinformatics filtering, we used WfG to identify potential driver mutations, which were annotated as "pathogenic" or "likely pathogenic" (WfG version 39.132 and 39.135 as of July 2018). The results were compared with the findings of expert hematologists. Results: 247 paired samples (TDS, n= 143; WES, n= 104) collected from 187 patients were analyzed. Our cohort consisted of 63 patients with acute myeloid leukemia, 40 with myelodysplastic syndromes (MDS), 19 with myeloproliferative neoplasms (MPN), 9 with MDS/MPN, 10 with acute lymphoblastic leukemia/lymphoma, 17 with non Hodgkin lymphoma, 6 with multiple myeloma (MM) and others. In 151 of 187 patients, a total of 290 somatic driver mutations were identified by human curation. The frequently mutated genes were TP53 (n=31), NRAS (n=17), TET2 (n=16), U2AF1 (n=14), FLT3/ASXL1/WT1 (n=13 each), and DNMT3A/RUNX1 (n=12 each). WfG identified 79% (n=229) of driver mutations which human experts also did. There was some discordance between WfG and the human (Figure 1): Sixteen mutations were interpreted as "variant of unknown significance" by WfG, but these mutations were deduced as driver mutation by the human. Conversely, in two representative cases, WfG identified a relevant driver mutation that the human did not: FAM46C and SOCS1, from a patient with MM and with primary mediastinal large-B cell lymphoma, respectively. These examples indicate the potential for a mutually complementary or cooperative relationship between AI "software" and the human expert "hardware" in the interpretation of high throughput genomic data. Conclusion: Combing AI "software" and the human expert "hardware" will allow for the quick delivery of comprehensive information needed for patient care that outperforms what either can achieve individually in the field of hematological disease. Figure1. Comparison of potential driver mutations between human curation and Watson for Genomics. The size of the gene symbol indicates the total number of mutations identified 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: 2018
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 2
    In: Blood, American Society of Hematology, Vol. 134, No. Supplement_1 ( 2019-11-13), p. 5393-5393
    Abstract: Introduction: Therapy-related myeloid neoplasms (t-MNs) are among late complications of chemotherapy and/or radiotherapy. So far, the genetic landscape of t-MNs is not yet defined as there has been few reports for their comprehensive genomic analysis. Recently, in the field of hematological malignancies, accumulating evidence supported that tumor derived fragmentary DNA in serum, known as circulating tumor DNA (ctDNA), has the potential to serve as an alternative for conventional bone marrow (BM) analysis (Nakamura and Yokoyama et al, Blood 2019). However, no studies are available to support the utility of ctDNA to evaluate the clonal kinetics in t-MNs. In the present study, by using retrospective tracking of driver mutations in BM or available serum samples, we tried to elucidate when the founder clones had appeared and how they had evolved pre-, during, and post-cytotoxic chemotherapy for prior hematological malignancies. Methods: We retrospectively collected tumor samples, including BM, tumor-rich peripheral blood (PB), or alternatively, serum samples, at diagnosis and before diagnosis from 15 t-MNs patients in our hospital. We subjected tumor DNA and control buccal swab DNA to comparative whole-exome sequencing (WES, n=13) and/or whole-genome sequencing (WGS, n=2). After identifying somatic driver mutations, we designed droplet digital PCR (ddPCR) assays for each mutation identified. Results: All 15 patients had a history of primary hematological malignancies (malignant lymphoma, n=9; acute leukemia, n=4; multiple myeloma, n=2) and had received prior chemotherapy and/or radiotherapy with or without autologous stem cell transplantation (ASCT). The median age at presentation of t-MNs was 53 years (range, 6-74), and the median latent period between prior malignancy and t-MNs was 45 months (range, 10-161). Conventional cytogenetic analysis revealed high incidence of complex karyotype (38.4%) and MLL rearrangement (30.7%). WES and/or WGS revealed that 93.3% (n=14/15) of the cases contained at least one putative driver mutation in 17 genes (median of 1 mutation per patient [range 1-4] ). We found the most frequent mutations in TP53 and epigenetic modifier gene (KMT2D/KDM6A/ASXL1/ASXL2), mutated in 33% of the samples, followed by signal transduction proteins (MPL/BRAF/FLT3-TKD/KRAS, 26.7%). Together, the spectrums of driver mutations and cytogenetic alterations in our cohort were consistent with previous reports in t-MNs. Most importantly, we could trace back mutant clone using BM and/or serum before diagnosis of t-MNs in 7 patients. Particularly, in UPN-5 who developed MDS-EB1 after ASCT for lymphoma, ETV6 p.E153fs, a putative founder mutation of t-MNs, was applied to liquid biopsy to trace back. ETV6 ctDNA could be detected as early as 7 months prior to the development of MDS with variant allele frequency (VAF) of 0.06% (blue arrowhead in figure 1A). Most intriguingly, the proportion of ETV6 ctDNA varied with or without G-CSF administration during the clinical course; VAF increase from 0 to 47.0% on G-CSF and decrease from 47.0 to 1.2% off G-CSF. In UPN-10 who had been clinically diagnosed as t-MNs (MDS-EB2) after intensive chemotherapy for prior AML, not otherwise specified with normal karyotype, WGS identified 4 driver mutations in BM at diagnosis of t-MNs. Then, 4 driver mutations, WT1 p.A365fs, MLL rearrangement, inv(3), and del(20q) were all applied to combined analysis of ctDNA and BM as well. Unexpectedly, we could find the presence of the founder clone, inv(3), with high allele burden in BM at initial diagnosis of AML-NOS with normal karyotype (red arrowhead in figure 1B). On the contrary, we could not detect other 3 gene alterations until 4 months before diagnosis of t-MNs. Conclusions: These findings would contribute to outline the genetic landscape of t-MNs, and especially suggest the role of cytokine-related selective pressures after chemotherapy and of the potential pre-t-MNs conditions in the pathogenesis of t-MNs. Figure 1: Serial mutation and cytogenetic status of BM and/or ctDNA in two patients with t-MNs (UPN-5 and -10, in figure 1A and in 1B, respectively). Shaded areas indicate the period of cytotoxic chemotherapies. Abbreviations: M, months; VAF, variant allele frequency. Disclosures Nagamura-Inoue: AMED: Research Funding. Uchimaru:Daiichi Sankyo Co., Ltd..: Research Funding. Tojo:Torii Pharmaceutical: Research Funding; AMED: Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2019
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
    Location Call Number Limitation Availability
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  • 3
    In: Blood, American Society of Hematology, Vol. 132, No. Supplement 1 ( 2018-11-29), p. 247-247
    Abstract: Background: Allogeneic hematopoietic stem cell transplantation (alloSCT) is the only curative option for patients with high risk acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). Whereas, relapse is the main event in therapeutic failure for these patients. We previously reported the utility of residual circulating tumor DNA (ctDNA) status for identifying patients with AML and MDS at high risk for relapse post myeloablative alloSCT (Nakamura et al, ASH. 2017). However, it remains to be elucidated whether persistent mutation status in serum and bone marrow (BM) have comparable ability to identify patients at high risk for relapse. Additionally, recent reports indicated mutation persistence (MP) in BM based on three genes regarding clonal hematopoiesis, DNMT3A, TET2, and ASXL1 (DTA), was not informative for relapse prediction of patients with AML in the setting of chemotherapy (Jongen-Lavrencic et al, N Engl J Med. 2018). Therefore, the prognostic impact of residual ctDNA status based on DTA genes should also be tested. Methods: To address these questions, we retrospectively collected tumor and matched serum samples at diagnosis and 1 and 3 months post-alloSCT from 53 patients with AML and MDS. Cell-free DNA was extracted from serum samples. We subjected tumor DNA, extracted from BM or peripheral blood, and buccal swab DNA, to next-generation sequencing (NGS), identifying candidate driver mutations. After identifying driver mutations, we designed droplet digital PCR (ddPCR) assay. The primary endpoint was the cumulative incidence of relapse (CIR) rate, and the secondary endpoint was the overall survival (OS) rate. We used DeLong's test to compare the performance between two assays based on the area under the curve (AUC) of receiver operating characteristics (ROC) curves. Results: Driver mutations were identified in 51 of 53 patients by NGS, and our cohort consisted of 37 patients with AML and 14 patients with MDS. The median age of the patients was 53 years. The conventional cytogenetic risk category was an adverse or high risk in 39.2% of patients, and 49.0% were in relapse or refractory disease status at alloSCT, and all patients received myeloablative conditioning; in most cases, the stem cell source was cord blood. The most frequent mutations found involved epigenetic regulators (DNMT3A/TET2/ASXL1, mutated in 32.1%), followed by signal transduction proteins (NRAS/FLT3, 31.4%). We could design at least one representative ddPCR assay for 51 patients. There was a clear correlation of variant allele frequency measurement between diagnostic ctDNA and matched tumor DNA (r2 = 0.67; P 〈 0.0001). Sixteen patients relapsed after a median of 7 months post-alloSCT. Both MP in BM at 1 and 3 months post-alloSCT and corresponding ctDNA persistence (CP) in serum (MP1 and MP3; CP1 and CP3, respectively) were comparably associated with higher 3-year CIR rates and inferior OS rates [3-year CIR (3-year OS): MP1 vs. non-MP1: 72.9 (50.0)% vs. 13.8 (88.0)%; P = 0.0012 (.0304) (Figure 1A); CP1 vs. non-CP1: 65.6 (45.8)% vs. 9.0 (91.7)%; P = 0.0002 (.0014) (Figure 1B); MP3 vs. non-MP3; 80.0 (30.0)% vs. 11.6 (94.1)%; P = 0.0002 (.0007); CP3 vs. non-CP3: 71.4 (53.4)% vs. 8.4 (92.5)%; P 〈 0.0001 (.0021)]. We next tested whether CP based on DTA could also be helpful in relapse prediction, we performed a subset analysis of patients with DTA based ddPCR assays (n=12). As a result, CP based on DTA genes also had the prognostic impact on CIR (Figure 1C). Finally, we compared the discriminatory ability of CP with those of MP. There was no significant difference between either CP and MP (Figure 1D). Additionally, when CP1 was compared with CP3, CP3 was found to be a better indicator of CIR and OS. Conclusions: In summary, we, for the first time, demonstrated that non-invasive serum ctDNA-testing, regardless of DTA genes, had comparable utility to molecular MRD testing of BM with regard to identifying patients at high risk for relapse in AML and MDS undergoing myeloablative alloSCT. Although prospective large-scale analyses are needed to confirm our findings, such non-invasive ctDNA-testing might allow for rapid clinical decision-making and, ultimately, subsequent risk-adapted therapeutic interventions post-alloSCT in AML and MDS. Figure 1. CIR based on the 1 month (A) MP and (B) CP status. (C) CIR based on the 1month CP status according to DTA subset. (D) Comparison of ROC curves for relapse prediction between 1 month CP and MP. 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: 2018
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 4
    In: Blood, American Society of Hematology, Vol. 133, No. 25 ( 2019-06-20), p. 2682-2695
    Abstract: This study was performed to assess the utility of tumor-derived fragmentary DNA, or circulating tumor DNA (ctDNA), for identifying high-risk patients for relapse of acute myeloid leukemia and myelodysplastic syndrome (AML/MDS) after undergoing myeloablative allogeneic hematopoietic stem cell transplantation (alloSCT). We retrospectively collected tumor and available matched serum samples at diagnosis and 1 and 3 months post-alloSCT from 53 patients with AML/MDS. After identifying driver mutations in 51 patients using next-generation sequencing, we designed at least 1 personalized digital polymerase chain reaction assay per case. Diagnostic ctDNA and matched tumor DNA exhibited excellent correlations with variant allele frequencies. Sixteen patients relapsed after a median of 7 months post-alloSCT. Both mutation persistence (MP) in bone marrow (BM) at 1 and 3 months post-alloSCT and corresponding ctDNA persistence (CP) in the matched serum (MP1 and MP3; CP1 and CP3, respectively) were comparably associated with higher 3-year cumulative incidence of relapse (CIR) rates (MP1 vs non-MP1, 72.9% vs 13.8% [P = .0012]; CP1 vs non-CP1, 65.6% vs 9.0% [P = .0002] ; MP3 vs non-MP3, 80% vs 11.6% [P = .0002]; CP3 vs non-CP3, 71.4% vs 8.4% [P & lt; .0001]). We subsequently evaluated whether subset analysis of patients with 3 genes associated with clonal hematopoiesis, DNMT3A, TET2, and ASXL1 (DTA), could also be helpful in relapse prediction. As a result, CP based on DTA gene mutations also had the prognostic effect on CIR. These results, for the first time, support the utility of ctDNA as a noninvasive prognostic biomarker in patients with AML/MDS undergoing alloSCT.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2019
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
    Location Call Number Limitation Availability
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  • 5
    In: Blood, American Society of Hematology, Vol. 128, No. 22 ( 2016-12-02), p. 5262-5262
    Abstract: Next-generation sequencing (NGS) is an attractive tool for prospective use in the field of clinical oncology. However, for this purpose, further innovations are necessary including medical informatics which links somatic mutations to clinical intervention. This process is currently labor-intensive, involving experienced curators who pick up the relevant evidence among a growing body of knowledge and translate it into medical practice. We organized a clinical sequencing team, called as IMSUT Tumor Board, and have been integrating clinical and genomic information in hematological malignancies with the aid of a cognitive computing (CC) system. Genomic DNA was prepared from malignant cell fractions and normal tissues in each patient, and subjected to comparative NGS, mainly targeted deep sequencing with ready-made panels and, on demand, whole exome sequencing. Sequence data was analyzed using a pipeline of in-house semi-automated medical informatics, namely YOKOMON-GO. CC was used to identify candidate driver mutations and pathways in each patient, from which pathogenic information as well as applicable drug information was deduced. A summary of NGS data was reported and discussed in IMSUT Tumor Board to deliberate upon potentially actionable findings. Up to date, we have performed NGS analysis on 90 patients with AML, MDS, MPN, et al., among which informative and actionable findings could be obtained in 50 and 18 patients, respectively. Six patients actually received treatments motivated in IMSUT Tumor Board. Our preliminary results indicate that CC can be well suited to clinical sequencing. Disclosures Koyama: IBM: Employment.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2016
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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