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Limijadi EKS, Ismail QC, Retnoningrum D, Devi WR, Riansari A. Blast Cells Count Influences Bleeding Incidence in Acute Leukemia: Preliminary Study in South Kalimantan, Indonesia. Open Access Maced J Med Sci 2021. [DOI: 10.3889/oamjms.2021.6860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Background: Acute leukemia is a malignant disease involving hematopoietic tissue, characterized by abnormal blood cells in bone marrow or called blast cells. The most common complications of acute leukemia is bleeding. A high percentage of blasts has been reported to increase the risk of bleeding in acute leukemia. Preliminary study was needed to investigate relationship between blast cells count and bleeding incidence in acute leukemia.
Methods: Crosssectional study with observasional analytic in 18 adult subjects was conducted from November 2019 to March 2020 in Ulin Hospital Banjarmasin South Kalimantan. The data were taken from medical records of acute leukemia patients who met inclusion and exclusion criterias. Data analysis was using Fisher’s exact test.
Results: There were 7 men and 11 women in this study. Blast cells count in peripheral with cut off <50% was 9 (50%) and ≥50% was 9 (50%). It was same for blast cells count in bone marrow. Both of women and men mostly have bleeding in acute leukemia, and bleeding incidence in women is higher than men. Bleeding condition was happened both in peripheral and bone marrow blast cells count with cut of <50% and ≥50%. Significancy of relationship between blast cells count and bleeding incidence was 0.637.
Conclusion: There is no significant between blast cells count and the bleeding incidence in acute leukemia. Another parameters that could be influenced bleeding inceidence need to be investigate in acute leukemia.
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Yang L, Zhang H, Yang X, Lu T, Ma S, Cheng H, Yen K, Cheng T. Prognostic Prediction of Cytogenetically Normal Acute Myeloid Leukemia Based on a Gene Expression Model. Front Oncol 2021; 11:659201. [PMID: 34123815 PMCID: PMC8190396 DOI: 10.3389/fonc.2021.659201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 03/26/2021] [Indexed: 11/22/2022] Open
Abstract
Acute myeloid leukemia (AML) refers to a heterogeneous group of hematopoietic malignancies. The well-known European Leukemia Network (ELN) stratifies AML patients into three risk groups, based primarily on the detection of cytogenetic abnormalities. However, the prognosis of cytogenetically normal AML (CN-AML), which is the largest AML subset, can be hard to define. Moreover, the clinical outcomes associated with this subgroup are diverse. In this study, using transcriptome profiles collected from CN-AML patients in the BeatAML cohort, we constructed a robust prognostic Cox model named NEST (Nine-gEne SignaTure). The validity of NEST was confirmed in four external independent cohorts. Moreover, the risk score predicted by the NEST model remained an independent prognostic factor in multivariate analyses. Further analysis revealed that the NEST model was suitable for bone marrow mononuclear cell (BMMC) samples but not peripheral blood mononuclear cell (PBMC) samples, which indirectly indicated subtle differences between BMMCs and PBMCs. Our data demonstrated the robustness and accuracy of the NEST model and implied the importance of the immune dysfunction in the leukemogenesis that occurs in CN-AML, which shed new light on the further exploration of molecular mechanisms and treatment guidance for CN-AML.
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Affiliation(s)
- Liu Yang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Houyu Zhang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Xue Yang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Ting Lu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Shihui Ma
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Hui Cheng
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Kuangyu Yen
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Tao Cheng
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
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AML risk stratification models utilizing ELN-2017 guidelines and additional prognostic factors: a SWOG report. Biomark Res 2020; 8:29. [PMID: 32817791 PMCID: PMC7425159 DOI: 10.1186/s40364-020-00208-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 07/27/2020] [Indexed: 01/01/2023] Open
Abstract
Background The recently updated European LeukemiaNet risk stratification guidelines combine cytogenetic abnormalities and genetic mutations to provide the means to triage patients with acute myeloid leukemia for optimal therapies. Despite the identification of many prognostic factors, relatively few have made their way into clinical practice. Methods In order to assess and improve the performance of the European LeukemiaNet guidelines, we developed novel prognostic models using the biomarkers from the guidelines, age, performance status and select transcript biomarkers. The models were developed separately for mononuclear cells and viable leukemic blasts from previously untreated acute myeloid leukemia patients (discovery cohort, N = 185) who received intensive chemotherapy. Models were validated in an independent set of similarly treated patients (validation cohort, N = 166). Results Models using European LeukemiaNet guidelines were significantly associated with clinical outcomes and, therefore, utilized as a baseline for comparisons. Models incorporating age and expression of select transcripts with biomarkers from European LeukemiaNet guidelines demonstrated higher area under the curve and C-statistics but did not show a substantial improvement in performance in the validation cohort. Subset analyses demonstrated that models using only the European LeukemiaNet guidelines were a better fit for younger patients (age < 55) than for older patients. Models integrating age and European LeukemiaNet guidelines visually showed more separation between risk groups in older patients. Models excluding results for ASXL1, CEBPA, RUNX1 and TP53, demonstrated that these mutations provide a limited overall contribution to risk stratification across the entire population, given the low frequency of mutations and confounding risk factors. Conclusions While European LeukemiaNet guidelines remain a critical tool for triaging patients with acute myeloid leukemia, the findings illustrate the need for additional prognostic factors, including age, to improve risk stratification.
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Sellar RS, Gale RE, Khwaja A, Garbowski M, Loddo M, Stoeber K, Williams GH, Linch DC. Immunophenotypic analysis of cell cycle status in acute myeloid leukaemia: relationship to cytogenetics, genotype and clinical outcome. Br J Haematol 2018; 181:486-494. [PMID: 29676467 DOI: 10.1111/bjh.15211] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Accepted: 02/01/2018] [Indexed: 11/30/2022]
Abstract
Cell cycle status may play an important role in directing patient therapy. We therefore determined the cell cycle status of leukaemic cells by immunophenotypic analysis of bone marrow trephine biopsies from 181 patients with acute myeloid leukaemia (AML) and correlated the results with biological features and clinical outcome. There was considerable heterogeneity between patients. The presenting white cell count significantly correlated with the proportion of non-quiescent cells (P < 0·0001), of cycling cells beyond G1 (P < 0·0001) and the speed of cycling (P < 0·0001). Profiles in acute promyelocytic leukaemia (APL) differed from non-APL and were consistent with more differentiated cells with reduced proliferative potential, but no significant differences were observed between non-APL cytogenetic risk groups. NPM1 mutations but not FLT3 internal tandem duplication (FLT3ITD ) were significantly associated with a higher proportion of cells beyond G1 (P = 0·002) and faster speed of cycling (P = 0·003). Resistance to standard cytosine arabinoside and daunorubicin induction chemotherapy was significantly related to a slower speed of cycling (P = 0·0002), as was a higher relapse rate (P = 0·05), but not with the proportion of non-quiescent cells or actively cycling cells. These results show a link between the cycling speed of AML cells and the response to chemotherapy, and help to identify a group with a very poor prognosis.
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Affiliation(s)
- Rob S Sellar
- Department of Haematology, UCL Cancer Institute, London, UK
| | | | - Asim Khwaja
- Department of Haematology, UCL Cancer Institute, London, UK
| | | | - Marco Loddo
- Department of Pathology, UCL Cancer Institute, London, UK
| | - Kai Stoeber
- Department of Pathology, UCL Cancer Institute, London, UK.,Shinogi Ltd, London, UK
| | - Gareth H Williams
- Department of Pathology, UCL Cancer Institute, London, UK.,Oncologica Ltd, Cambridge, UK
| | - David C Linch
- Department of Haematology, UCL Cancer Institute, London, UK
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Percival ME, Lai C, Estey E, Hourigan CS. Bone marrow evaluation for diagnosis and monitoring of acute myeloid leukemia. Blood Rev 2017; 31:185-192. [PMID: 28190619 DOI: 10.1016/j.blre.2017.01.003] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Accepted: 01/31/2017] [Indexed: 12/20/2022]
Abstract
The diagnosis of acute myeloid leukemia (AML) can be made based on peripheral blood or bone marrow blasts. In this review, we will discuss the role of bone marrow evaluation and peripheral blood monitoring in the diagnosis, management, and follow up of AML patients. For patients with circulating blasts, it is reasonable to perform the necessary studies needed for diagnosis and risk stratification, including multiparametric flow cytometry, cytogenetics, and molecular analysis, on a peripheral blood specimen. The day 14 marrow is used to document hypocellularity in response to induction chemotherapy, but it is unclear if that assessment is necessary as it often does not affect immediate management. Currently, response assessments performed at count recovery for evaluation of remission and measurable residual disease rely on bone marrow sampling. For monitoring of relapse, peripheral blood evaluation may be adequate, but the sensitivity of bone marrow testing is in some cases superior. While bone marrow evaluation can certainly be avoided in particular situations, this cumbersome and uncomfortable procedure currently remains the de facto standard for response assessment.
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Affiliation(s)
- Mary-Elizabeth Percival
- Department of Medicine, University of Washington, Seattle, WA, USA; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
| | - Catherine Lai
- Myeloid Malignancies Section, Hematology Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Elihu Estey
- Department of Medicine, University of Washington, Seattle, WA, USA; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Christopher S Hourigan
- Myeloid Malignancies Section, Hematology Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
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