1
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Lewis JE, Cooper LAD, Jaye DL, Pozdnyakova O. Automated Deep Learning-Based Diagnosis and Molecular Characterization of Acute Myeloid Leukemia Using Flow Cytometry. Mod Pathol 2024; 37:100373. [PMID: 37925056 DOI: 10.1016/j.modpat.2023.100373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 10/23/2023] [Accepted: 10/28/2023] [Indexed: 11/06/2023]
Abstract
The current flow cytometric analysis of blood and bone marrow samples for diagnosis of acute myeloid leukemia (AML) relies heavily on manual intervention in the processing and analysis steps, introducing significant subjectivity into resulting diagnoses and necessitating highly trained personnel. Furthermore, concurrent molecular characterization via cytogenetics and targeted sequencing can take multiple days, delaying patient diagnosis and treatment. Attention-based multi-instance learning models (ABMILMs) are deep learning models that make accurate predictions and generate interpretable insights regarding the classification of a sample from individual events/cells; nonetheless, these models have yet to be applied to flow cytometry data. In this study, we developed a computational pipeline using ABMILMs for the automated diagnosis of AML cases based exclusively on flow cytometric data. Analysis of 1820 flow cytometry samples shows that this pipeline provides accurate diagnoses of acute leukemia (area under the receiver operating characteristic curve [AUROC] 0.961) and accurately differentiates AML vs B- and T-lymphoblastic leukemia (AUROC 0.965). Models for prediction of 9 cytogenetic aberrancies and 32 pathogenic variants in AML provide accurate predictions, particularly for t(15;17)(PML::RARA) [AUROC 0.929], t(8;21)(RUNX1::RUNX1T1) (AUROC 0.814), and NPM1 variants (AUROC 0.807). Finally, we demonstrate how these models generate interpretable insights into which individual flow cytometric events and markers deliver optimal diagnostic utility, providing hematopathologists with a data visualization tool for improved data interpretation, as well as novel biological associations between flow cytometric marker expression and cytogenetic/molecular variants in AML. Our study is the first to illustrate the feasibility of using deep learning-based analysis of flow cytometric data for automated AML diagnosis and molecular characterization.
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Affiliation(s)
- Joshua E Lewis
- Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Lee A D Cooper
- Department of Pathology, Northwestern University, Chicago, Illinois
| | - David L Jaye
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, Georgia
| | - Olga Pozdnyakova
- Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.
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2
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Lewis JE, Cooper LA, Jaye DL, Pozdnyakova O. Automated Deep Learning-Based Diagnosis and Molecular Characterization of Acute Myeloid Leukemia using Flow Cytometry. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.18.558289. [PMID: 37808719 PMCID: PMC10557578 DOI: 10.1101/2023.09.18.558289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Current flow cytometric analysis of blood and bone marrow samples for diagnosis of acute myeloid leukemia (AML) relies heavily on manual intervention in both the processing and analysis steps, introducing significant subjectivity into resulting diagnoses and necessitating highly trained personnel. Furthermore, concurrent molecular characterization via cytogenetics and targeted sequencing can take multiple days, delaying patient diagnosis and treatment. Attention-based multi-instance learning models (ABMILMs) are deep learning models which make accurate predictions and generate interpretable insights regarding the classification of a sample from individual events/cells; nonetheless, these models have yet to be applied to flow cytometry data. In this study, we developed a computational pipeline using ABMILMs for the automated diagnosis of AML cases based exclusively on flow cytometric data. Analysis of 1,820 flow cytometry samples shows that this pipeline provides accurate diagnoses of acute leukemia [AUROC 0.961] and accurately differentiates AML versus B- and T-lymphoblastic leukemia [AUROC 0.965]. Models for prediction of 9 cytogenetic aberrancies and 32 pathogenic variants in AML provide accurate predictions, particularly for t(15;17)(PML::RARA) [AUROC 0.929], t(8;21)(RUNX1::RUNX1T1) [AUROC 0.814], and NPM1 variants [AUROC 0.807]. Finally, we demonstrate how these models generate interpretable insights into which individual flow cytometric events and markers deliver optimal diagnostic utility, providing hematopathologists with a data visualization tool for improved data interpretation, as well as novel biological associations between flow cytometric marker expression and cytogenetic/molecular variants in AML. Our study is the first to illustrate the feasibility of using deep learning-based analysis of flow cytometric data for automated AML diagnosis and molecular characterization.
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Affiliation(s)
- Joshua E. Lewis
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Lee A.D. Cooper
- Department of Pathology, Northwestern University, Chicago, IL, USA
| | - David L. Jaye
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA
| | - Olga Pozdnyakova
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA
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3
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Weeda V, Mestrum SGC, Leers MPG. Flow Cytometric Identification of Hematopoietic and Leukemic Blast Cells for Tailored Clinical Follow-Up of Acute Myeloid Leukemia. Int J Mol Sci 2022; 23:ijms231810529. [PMID: 36142442 PMCID: PMC9506284 DOI: 10.3390/ijms231810529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/06/2022] [Accepted: 09/07/2022] [Indexed: 11/16/2022] Open
Abstract
Acute myeloid leukemia (AML) is a myeloid malignancy that is characterized by the accumulation of leukemic blast cells, which originate from hematopoietic stem cells that have undergone leukemic transformation and/or are more mature progenitors that have gained stemness features. Currently, no consensus exists for the flow cytometric identification of normal blast cells and their leukemic counterparts by their antigenic expression profile. Differentiating between the benign cells and the malignant cells is crucial for the further deployment of immunophenotype panels for the clinical follow-up of AML patients. This review provides an overview of immunophenotypic markers that allow the identification of leukemic blast cells in the bone marrow with multiparameter flow cytometry. This technique allows the identification of hematopoietic blast cells at the level of maturing cells by their antigen expression profile. While aberrant antigen expression of a single immunophenotypic marker cell cannot be utilized in order to differentiate leukemic blast cells from normal blast cells, combinations of multiple immunophenotypic markers can enable the distinction of normal and leukemic blast cells. The identification of these markers has provided new perspectives for tailored clinical follow-up, including therapy management, diagnostics, and prognostic purposes. The immunophenotypic marker panels, however, should be developed by carefully considering the variable antigen marker expression profile of individual patients.
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Affiliation(s)
- Vera Weeda
- Department of Clinical Chemistry & Hematology, Zuyderland Medical Centre, 6162BG Sittard-Geleen, The Netherlands
| | - Stefan G. C. Mestrum
- Department of Clinical Chemistry & Hematology, Zuyderland Medical Centre, 6162BG Sittard-Geleen, The Netherlands
- Department of Molecular Cell Biology, GROW-School for Oncology and Reproduction, Maastricht University Medical Centre, 6200MD Maastricht, The Netherlands
- Correspondence: ; Tel.: +31-6-36176124
| | - Math P. G. Leers
- Department of Clinical Chemistry & Hematology, Zuyderland Medical Centre, 6162BG Sittard-Geleen, The Netherlands
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4
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Sorigue M, Juncà J, Zamora L. On the distinction between acute leukemia with mutated NPM1 and acute promyelocytic leukemia by flow cytometry. Int J Lab Hematol 2022; 44:e187-e190. [PMID: 35916217 DOI: 10.1111/ijlh.13530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 01/19/2021] [Accepted: 02/23/2021] [Indexed: 12/01/2022]
Affiliation(s)
- Marc Sorigue
- Hematology Laboratory, Hospital Germans Trias i Pujol (ICO Badalona), Barcelona, Spain
| | - Jordi Juncà
- Hematology Laboratory, Hospital Germans Trias i Pujol (ICO Badalona), Barcelona, Spain
| | - Lurdes Zamora
- Hematology Laboratory, Hospital Germans Trias i Pujol (ICO Badalona), Barcelona, Spain
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5
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Soare DS, Radu E, Dumitru I, Vlădăreanu AM, Bumbea H. Quantitative analyses of CD7, CD33, CD34, CD56, and CD123 within the FLT3-ITD/ NPM1-MUT myeloblastic/monocytic bulk AML blastic populations. Leuk Lymphoma 2021; 62:2716-2726. [PMID: 34034609 DOI: 10.1080/10428194.2021.1927018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
The most frequent mutations in acute myeloid leukemia (AML) - FLT3-ITD and NPM1 - are associated with a specific immunophenotype. We evaluated the levels of surface antigens in an uninvestigated AML patient population according to the combination of FLT3-ITD/NPM1 mutations. Antigen levels were calculated as the geometric mean fluorescence index (MFI) ratio between myeloblasts or monoblasts/monocytes and a negative population for the specific antigen. In myeloblastic populations, FLT3-ITD cases presented CD7high MFI values (p < .001), while NPM1-MUT cases presented CD33high (p < .001), and CD34low (p < .001) MFI values. Within the monoblastic/monocytic populations, CD56high expression was observed only in the FLT3-WT/NPM1-MUT population (p=.003). The single common antigen expression between myeloblasts and monoblasts/monocytes was CD123high expression only within the FLT3-ITD/NPM1-MUT subgroup. Our results present a subtle influence of FLT3-ITD/NPM1 mutations upon antigen expression profiles in myeloblasts vs monoblasts/monocytes, and we described a novel correlation between the presence of NPM1 and CD56high values within bulk leukemic monoblasts/monocytes.
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Affiliation(s)
- Dan-Sebastian Soare
- Bone Marrow Transplant Unit, University Emergency Hospital Bucharest, Bucharest, Romania.,Cellular Biology and Histology Department, Faculty of General Medicine, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Eugen Radu
- Microbiology Department, Faculty of General Medicine, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania.,Molecular Pathology Laboratory, University Emergency Hospital Bucharest, Bucharest, Romania
| | - Ion Dumitru
- Transfusion Department, University Emergency Hospital Bucharest, Bucharest, Romania
| | - Ana Maria Vlădăreanu
- Hematology Department, University Emergency Hospital Bucharest, Bucharest, Romania.,Hematology Department, Faculty of General Medicine, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Horia Bumbea
- Bone Marrow Transplant Unit, University Emergency Hospital Bucharest, Bucharest, Romania.,Hematology Department, Faculty of General Medicine, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
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6
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Chen X, Zhu H, Qiao C, Zhao S, Liu L, Wang Y, Jin H, Qian S, Wu Y. Next-generation sequencing reveals gene mutations landscape and clonal evolution in patients with acute myeloid leukemia. ACTA ACUST UNITED AC 2021; 26:111-122. [PMID: 33491606 DOI: 10.1080/16078454.2020.1858610] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
OBJECTIVES The study aims to understand geneome diversification and complexity that developed in Acute myeloid leukemia (AML). METHODS Next-generation sequencing (NGS) was used to identify the genetic profiles of 22 genes relevant to hematological malignancy in 204 patients with de novo non-M3 AML. RESULTS At time of initial diagnosis, at least one mutation was identified in 80.9% of patients (165/204). The most commonly mutated gene was NPM1 (22.1%), followed by ASXL1 (18.1%), TET2 (18.1%), IDH2 (15.7%), CEBPA (14.7%), FLT3-ITD (13.2%) and DNMT3A (11.8%). Mutations landscape analysis indicated several patterns of co-occurring and mutual exclusive gene mutations. Some correlation was observed between gene mutations and clinicohematological features. Multivariate analysis showed that age >60 years, karyotypes, IDH2 and KIT mutations were the independent unfavorable prognostic factors for OS; NPM1-mut/ FLT3-ITD-wt was independently correlated with prolonged OS; whereas the independent poor risk factors for RFS were karyotypes, high WBC and RUNX1 mutation. According to different genotype demonstrated by multivariate analysis, 163 patients with intermediate-risk cytogenetics were classified into three subgroups: patients with NPM1-mut/ FLT3-ITD-wt or biallelic CEBPA mutation as favorable risk, patients with KIT, IDH2, TP53 or NRAS mutations as unfavorable risk, and the remaining was the intermediate risk. We also obtain information of clonal evolution during leukemia progression by observing five patients who underwent repeat NGS at relapse in our cohort. CONCLUSION NGS techniques is a useful tool for discovering related gene mutations and clonal evolution in AML genomes, leading to novel targeted therapeutic approaches that could improve patients outcomes.
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Affiliation(s)
- Xiao Chen
- Department of Hematology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.,Key Laboratory of Hematology of Nanjing Medical University, Nanjing, People's Republic of China.,Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing, People's Republic of China
| | - Han Zhu
- Department of Hematology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.,Key Laboratory of Hematology of Nanjing Medical University, Nanjing, People's Republic of China.,Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing, People's Republic of China
| | - Chun Qiao
- Department of Hematology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.,Key Laboratory of Hematology of Nanjing Medical University, Nanjing, People's Republic of China.,Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing, People's Republic of China
| | - Sishu Zhao
- Department of Hematology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.,Key Laboratory of Hematology of Nanjing Medical University, Nanjing, People's Republic of China.,Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing, People's Republic of China
| | - Lu Liu
- Department of Hematology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.,Key Laboratory of Hematology of Nanjing Medical University, Nanjing, People's Republic of China.,Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing, People's Republic of China
| | - Yan Wang
- Department of Hematology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.,Key Laboratory of Hematology of Nanjing Medical University, Nanjing, People's Republic of China.,Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing, People's Republic of China
| | - Huimin Jin
- Department of Hematology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.,Key Laboratory of Hematology of Nanjing Medical University, Nanjing, People's Republic of China.,Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing, People's Republic of China
| | - Sixuan Qian
- Department of Hematology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.,Key Laboratory of Hematology of Nanjing Medical University, Nanjing, People's Republic of China.,Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing, People's Republic of China
| | - Yujie Wu
- Department of Hematology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.,Key Laboratory of Hematology of Nanjing Medical University, Nanjing, People's Republic of China.,Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing, People's Republic of China
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7
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Alexander TB, Orgel E. Mixed Phenotype Acute Leukemia: Current Approaches to Diagnosis and Treatment. Curr Oncol Rep 2021; 23:22. [PMID: 33544265 DOI: 10.1007/s11912-020-01010-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/17/2020] [Indexed: 11/30/2022]
Abstract
PURPOSE OF REVIEW Mixed phenotype acute leukemia (MPAL) is a rare subtype of acute leukemia with features of both acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). The review examines current definitions and controversies in classification of MPAL, new insights into genomic drivers and pathogenesis, recent evidence to support treatment recommendations, and opportunities for future research. RECENT FINDINGS Recent collaborative efforts have made progress in understanding the genomic landscape and optimal therapy for MPAL. The preponderance of retrospective data supports beginning therapy with ALL directed regimens. Differences in prognosis for adult and children with MPAL have led to divergent approaches for therapy intensity, including use of stem cell transplantation consolidation. MPAL remains a challenging leukemia to understand, research, and treat due to low incidence, shifting and subjective approaches to classification, and innate biological heterogeneity. Ongoing research hopes to surmount these obstacles through prospective studies within large cooperative groups to provide new insight into targetable biology and further refine optimal therapy.
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Affiliation(s)
- Thomas B Alexander
- University of North Carolina, 170 Manning Drive, 1185A Physicians Office Building, CB # 7236, Chapel Hill, NC, 27599, USA.
| | - Etan Orgel
- Children's Hospital Los Angeles, 4650 Sunset Blvd, MS 54, Los Angeles, CA, 90027, USA
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8
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Arana Rosainz MJ, Nguyen N, Wahed A, Lelenwa LC, Aakash N, Schaefer K, Rios A, Kanaan Z, Chen L. Acute myeloid leukemia with mutated NPM1 mimics acute promyelocytic leukemia presentation. Int J Lab Hematol 2020; 43:218-226. [PMID: 33099879 DOI: 10.1111/ijlh.13357] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 09/02/2020] [Accepted: 09/17/2020] [Indexed: 01/18/2023]
Abstract
OBJECTIVES To investigate clinicopathological and molecular features of NPM1-mutated acute myeloid leukemia that presented with infrequent acute promyelocytic leukemia (APL)-like phenotype and clinical presentation. METHODS Cases with both de novo or secondary Acute Myeloid Leukemia (AML) were retrieved. Data from flow cytometry immunophenotyping, cytogenetics, molecular studies, and clinical presentation were analyzed. RESULTS Cases presented with abnormal coagulation parameters and low platelets count; four of them showed a DIC index compatible with overt DIC. Two cases showed Auer rods. In all cases, immunophenotypes mimicked APL: blasts expressed CD33, CD13, and cytoplasmic MPO but did not express CD34, HLA-DR, or CD11b. Notably, CD4 expression was observed in all cases. Neither t(15;17) nor PML/RARα gene rearrangement was detected. NPM1 gene mutation was identified in all cases. In four cases, TET2 or IDH2 co-mutations were identified. CONCLUSIONS Our findings provide additional evidence of association between NPM1-mutated AML with TET2 or IDH2 co-mutations and the APL-like immunophenotype. This AML subset was found to exist in both de novo and secondary AML. High WBC count and blasts with low to moderate side scatter and significant expression of CD4 are observed features that could assist in the differential diagnosis with APL. The occurrence of significant elevated D-dimer levels, or even overt DIC observed at diagnosis in these cases could be relevant for this AML subtype.
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Affiliation(s)
- Manuel J Arana Rosainz
- Department of Pathology and Laboratory Medicine, Health Sciences Center at Houston, McGovern Medical School at Houston, The University of Texas, Houston, TX, USA
| | - Nghia Nguyen
- Department of Pathology and Laboratory Medicine, Health Sciences Center at Houston, McGovern Medical School at Houston, The University of Texas, Houston, TX, USA
| | - Amer Wahed
- Department of Pathology and Laboratory Medicine, Health Sciences Center at Houston, McGovern Medical School at Houston, The University of Texas, Houston, TX, USA
| | - Laura C Lelenwa
- Department of Pathology and Laboratory Medicine, Health Sciences Center at Houston, McGovern Medical School at Houston, The University of Texas, Houston, TX, USA
| | - Nfn Aakash
- Department of Pathology and Laboratory Medicine, Health Sciences Center at Houston, McGovern Medical School at Houston, The University of Texas, Houston, TX, USA
| | - Karen Schaefer
- Flow Cytometry Laboratory, Memorial Hermann Health System, Houston, TX, USA
| | - Adan Rios
- Division of Medical Oncology, Department of Internal Medicine, Health Sciences Center at Houston, McGovern Medical School at Houston, The University of Texas, Houston, TX, USA
| | - Zeyad Kanaan
- Division of Medical Oncology, Department of Internal Medicine, Health Sciences Center at Houston, McGovern Medical School at Houston, The University of Texas, Houston, TX, USA
| | - Lei Chen
- Department of Pathology and Laboratory Medicine, Health Sciences Center at Houston, McGovern Medical School at Houston, The University of Texas, Houston, TX, USA
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9
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Bain BJ, Béné MC. Morphological and Immunophenotypic Clues to the WHO Categories of Acute Myeloid Leukaemia. Acta Haematol 2019; 141:232-244. [PMID: 30965338 DOI: 10.1159/000496097] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Accepted: 12/08/2018] [Indexed: 01/08/2023]
Abstract
Diagnosis and classification of acute myeloid leukaemia (AML) require cytogenetic and molecular genetic investigation. However, while these evaluations are pending, morphology supplemented by immunophenotyping can provide clues to the diagnosis of specific cytogenetic/genetic categories of AML. Most importantly, acute promyelocytic leukaemia can be diagnosed with a high degree of certainty. However, provisional identification of cases associated with t(8; 21), inv(16), t(1; 22), and NPM1 mutation may also be possible. In addition, transient abnormal myelopoiesis of Down's syndrome can generally be diagnosed morphologically.
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MESH Headings
- Chromosome Inversion
- Chromosomes, Human/genetics
- Down Syndrome/genetics
- Humans
- Leukemia, Promyelocytic, Acute/classification
- Leukemia, Promyelocytic, Acute/diagnosis
- Leukemia, Promyelocytic, Acute/genetics
- Leukemia, Promyelocytic, Acute/therapy
- Myelopoiesis/genetics
- Neoplasm Proteins/genetics
- Nuclear Proteins/genetics
- Nucleophosmin
- Translocation, Genetic
- World Health Organization
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Affiliation(s)
- Barbara J Bain
- Department of Haematology, St Mary's Hospital, London, United Kingdom,
| | - Marie C Béné
- Hematology Biology, Nantes University Hospital, Nantes, France
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10
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Wang B, Liu Y, Hou G, Wang L, Lv N, Xu Y, Xu Y, Wang X, Xuan Z, Jing Y, Li H, Jin X, Deng A, Wang L, Gao X, Dou L, Liang J, Chen C, Li Y, Yu L. Mutational spectrum and risk stratification of intermediate-risk acute myeloid leukemia patients based on next-generation sequencing. Oncotarget 2017; 7:32065-78. [PMID: 27062340 PMCID: PMC5077997 DOI: 10.18632/oncotarget.7028] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2015] [Accepted: 01/13/2016] [Indexed: 11/25/2022] Open
Abstract
Intermediate-risk acute myeloid leukemia (IR-AML), which accounts for a substantial number of AML cases, is highly heterogeneous. Although several mutations have been identified, the heterogeneity of AML is uncertain because novel mutations have yet to be discovered. Here we applied next generation sequencing (NGS) platform to screen mutational hotspots in 410 genes relevant to hematological malignancy. IR-AML samples (N=95) were sequenced by Illumina Hiseq and mutations in 101 genes were identified. Only seven genes (CEBPA, NPM1, DNMT3A, FLT3-ITD, NRAS, IDH2 and WT1) were mutated in more than 10% of patients. Genetic interaction analysis identified several cooperative and exclusive patterns of overlapping mutations. Mutational analysis indicated some correlation between genotype and phenotype. FLT3-ITD mutations were identified as independent factors of poor prognosis, while CEBPA mutations were independent favorable factors. Co-occurrence of FLT3-ITD, NPM1 and DNMT3A mutations was identified with associated with specific clinical AML features and poor outcomes. Furthermore, by integrating multiple mutations in the survival analysis, 95 IR-AML patients could be stratified into three distinct risk groups allowing reductions in IR-AML by one-third. Our study offers deep insights into the molecular pathogenesis and biology of AML and indicated that the prognosis of IR-AML could be further stratified by different mutation combinations which may direct future treatment intervention.
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Affiliation(s)
- Bianhong Wang
- Medical Center, Tsinghua University, Beijing 100084, China
| | - Yangyang Liu
- Research and Development Department, Annoroad Gene Technology Co. Ltd, Beijing 100176, China
| | - Guangyuan Hou
- Research and Development Department, Annoroad Gene Technology Co. Ltd, Beijing 100176, China
| | - Lili Wang
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Na Lv
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Yuanyuan Xu
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Yihan Xu
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Xiuli Wang
- Research and Development Department, Annoroad Gene Technology Co. Ltd, Beijing 100176, China
| | - Zhaoling Xuan
- Research and Development Department, Annoroad Gene Technology Co. Ltd, Beijing 100176, China
| | - Yu Jing
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Honghua Li
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Xiangshu Jin
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Ailing Deng
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Li Wang
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Xiaoning Gao
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Liping Dou
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Junbin Liang
- Research and Development Department, Annoroad Gene Technology Co. Ltd, Beijing 100176, China
| | - Chongjian Chen
- Research and Development Department, Annoroad Gene Technology Co. Ltd, Beijing 100176, China
| | - Yonghui Li
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
| | - Li Yu
- Department of Hematology, Chinese PLA General Hospital, Beijing 100853, China
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11
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Tiribelli M, Geromin A, Cavallin M, Di Giusto S, Simeone E, Fanin R, Damiani D. ABCG2 and CD200 define patients at high risk of relapse in ELN favorable subgroup of AML. Eur J Haematol 2017; 99:269-274. [DOI: 10.1111/ejh.12915] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/07/2017] [Indexed: 12/26/2022]
Affiliation(s)
- Mario Tiribelli
- Division of Hematology and Stem Cell Transplantation; Azienda Sanitaria Universitaria Integrata; Udine Italy
| | - Antonella Geromin
- Division of Hematology and Stem Cell Transplantation; Azienda Sanitaria Universitaria Integrata; Udine Italy
| | - Margherita Cavallin
- Division of Hematology and Stem Cell Transplantation; Azienda Sanitaria Universitaria Integrata; Udine Italy
| | - Sara Di Giusto
- Division of Hematology and Stem Cell Transplantation; Azienda Sanitaria Universitaria Integrata; Udine Italy
| | - Erica Simeone
- Division of Hematology and Stem Cell Transplantation; Azienda Sanitaria Universitaria Integrata; Udine Italy
| | - Renato Fanin
- Division of Hematology and Stem Cell Transplantation; Azienda Sanitaria Universitaria Integrata; Udine Italy
| | - Daniela Damiani
- Division of Hematology and Stem Cell Transplantation; Azienda Sanitaria Universitaria Integrata; Udine Italy
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12
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Li C, Zhu B, Chen J, Huang X. Feature genes predicting the FLT3/ITD mutation in acute myeloid leukemia. Mol Med Rep 2016; 14:89-94. [PMID: 27177049 PMCID: PMC4918602 DOI: 10.3892/mmr.2016.5260] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2015] [Accepted: 02/25/2016] [Indexed: 01/17/2023] Open
Abstract
In the present study, gene expression profiles of acute myeloid leukemia (AML) samples were analyzed to identify feature genes with the capacity to predict the mutation status of FLT3/ITD. Two machine learning models, namely the support vector machine (SVM) and random forest (RF) methods, were used for classification. Four datasets were downloaded from the European Bioinformatics Institute, two of which (containing 371 samples, including 281 FLT3/ITD mutation-negative and 90 mutation-positive samples) were randomly defined as the training group, while the other two datasets (containing 488 samples, including 350 FLT3/ITD mutation-negative and 138 mutation-positive samples) were defined as the test group. Differentially expressed genes (DEGs) were identified by significance analysis of the micro-array data by using the training samples. The classification efficiency of the SCM and RF methods was evaluated using the following parameters: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and the area under the receiver operating characteristic curve. Functional enrichment analysis was performed for the feature genes with DAVID. A total of 585 DEGs were identified in the training group, of which 580 were upregulated and five were downregulated. The classification accuracy rates of the two methods for the training group, the test group and the combined group using the 585 feature genes were >90%. For the SVM and RF methods, the rates of correct determination, specificity and PPV were >90%, while the sensitivity and NPV were >80%. The SVM method produced a slightly better classification effect than the RF method. A total of 13 biological pathways were overrepresented by the feature genes, mainly involving energy metabolism, chromatin organization and translation. The feature genes identified in the present study may be used to predict the mutation status of FLT3/ITD in patients with AML.
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Affiliation(s)
- Chenglong Li
- Department of Hematology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072, P.R. China
| | - Biao Zhu
- Department of Hematology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072, P.R. China
| | - Jiao Chen
- Department of Hematology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072, P.R. China
| | - Xiaobing Huang
- Department of Hematology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, Sichuan 610072, P.R. China
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Dalal BI, Vakil AP, Khare NS, Wang SY, Richards MJ, Chen LYC. Abnormalities of the lymphocyte subsets and their immunophenotype, and their prognostic significance in adult patients with hemophagocytic lymphohistiocytosis. Ann Hematol 2015; 94:1111-7. [DOI: 10.1007/s00277-015-2350-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2014] [Accepted: 03/04/2015] [Indexed: 10/23/2022]
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O'Neill K, Aghaeepour N, Parker J, Hogge D, Karsan A, Dalal B, Brinkman RR. Deep profiling of multitube flow cytometry data. ACTA ACUST UNITED AC 2015; 31:1623-31. [PMID: 25600947 DOI: 10.1093/bioinformatics/btv008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2014] [Accepted: 01/02/2015] [Indexed: 01/11/2023]
Abstract
MOTIVATION Deep profiling the phenotypic landscape of tissues using high-throughput flow cytometry (FCM) can provide important new insights into the interplay of cells in both healthy and diseased tissue. But often, especially in clinical settings, the cytometer cannot measure all the desired markers in a single aliquot. In these cases, tissue is separated into independently analysed samples, leaving a need to electronically recombine these to increase dimensionality. Nearest-neighbour (NN) based imputation fulfils this need but can produce artificial subpopulations. Clustering-based NNs can reduce these, but requires prior domain knowledge to be able to parameterize the clustering, so is unsuited to discovery settings. RESULTS We present flowBin, a parameterization-free method for combining multitube FCM data into a higher-dimensional form suitable for deep profiling and discovery. FlowBin allocates cells to bins defined by the common markers across tubes in a multitube experiment, then computes aggregate expression for each bin within each tube, to create a matrix of expression of all markers assayed in each tube. We show, using simulated multitube data, that flowType analysis of flowBin output reproduces the results of that same analysis on the original data for cell types of >10% abundance. We used flowBin in conjunction with classifiers to distinguish normal from cancerous cells. We used flowBin together with flowType and RchyOptimyx to profile the immunophenotypic landscape of NPM1-mutated acute myeloid leukemia, and present a series of novel cell types associated with that mutation.
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Affiliation(s)
- Kieran O'Neill
- Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Nima Aghaeepour
- Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Jeremy Parker
- Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Donna Hogge
- Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Aly Karsan
- Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Bakul Dalal
- Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Ryan R Brinkman
- Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada Terry Fox Laboratory, BC Cancer Agency, Bioinformatics Graduate Program, University of British Columbia, Department of Hematopathology, Vancouver General Hospital and Faculty of Medical Genetics, University of British Columbia, Vancouver, Canada
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Hu Y, Lv X, Wu Y, Xu J, Wang L, Chen W, Zhang W, Li J, Zhang S, Qiu H. Expression of costimulatory molecule B7-H3 and its prognostic implications in human acute leukemia. ACTA ACUST UNITED AC 2014; 20:187-95. [PMID: 25130683 DOI: 10.1179/1607845414y.0000000186] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
OBJECTIVES This study focused on the expression pattern and clinical significance of B7-H3 expression in human acute leukemia. METHODS We systematically analyzed 134 patients with acute myeloid leukemia (101 cases) and acute lymphocytic leukemia (33 cases) by flow cytometry. RESULTS The frequency of B7-H3(+) cases was 44.8% in total. The B7-H3 expression rate differed from 0% to 74.8% in individual cases. The correlation between B7-H3 expression and traditional prognostic factors, such as age and gender, the white blood cell count was not confirmed. However, B7-H3 had a significant higher expression in CD34(+) cases and high risk karyotypes. CONCLUSIONS Owing to the expression of B7-H3 being statistically relevant in predicting disease progression and a shorter life survival, our results demonstrated that B7-H3 expression in acute leukemia predicts an unfavorable outcome.
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Dalal BI, Al Mugairi A, Pi S, Lee SY, Khare NS, Pal J, Bryant A, Vakil AP, Lau S, Abou Mourad YR. Aberrant expression of CD13 identifies a subgroup of standard-risk adult acute lymphoblastic leukemia with inferior survival. CLINICAL LYMPHOMA MYELOMA & LEUKEMIA 2013; 14:239-44. [PMID: 24411984 DOI: 10.1016/j.clml.2013.10.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2013] [Revised: 10/04/2013] [Accepted: 10/21/2013] [Indexed: 01/27/2023]
Abstract
BACKGROUND The standard-risk (SR) subgroup of acute lymphoblastic leukemia in adults (aALL) is a heterogeneous category, with a 20% to 40% relapse rate and a wide range of relapse-free survival (RFS) and overall survival (OS). There is a need to identify at the outset those patients with SR-aALL who are likely to have shorter RFS and OS, so they can be treated more aggressively. PATIENTS AND METHODS Flow cytometric data of 81 patients with SR-aALL treated with a standardized protocol were retrospectively analyzed. Thirty-two patients (40%) relapsed; the median RFS and OS were 12.5 months (range, 1-136 months) and 30 months (range, 3-235 months), respectively. Twenty-six patients survived ≥ 48 months. RESULTS Expression of myeloid antigen CD13, using the conventional ≥ 20% threshold and a lower ≥ 5% threshold, was seen in 17 (29%) of 59 and 29 (49%) of 59 patients, respectively, whereas dual expression of CD13 and CD33 was seen in 8 patients. CD13 positivity at ≥ 20% and ≥ 5% threshold was associated with a shorter RFS (P = .0158 and P < .0001, respectively) and OS (P = .0072 and P < .0001, respectively). Dual expression of CD13 (at ≥ 5% or ≥ 20% threshold) and CD33 was associated with inferior OS (P = .0038 and P = .0032, respectively) and RFS (P = .0705 and P = .2516, respectively). For ≥ 20% and ≥ 5% threshold of positivity, 16 of 42 and 28 of 42 who survived < 48 months were positive, compared with 1 of 17 and 1 of 17 who survived ≥ 48 months (P = .0133 and P < .0001, respectively). CONCLUSION Aberrant expression of CD13 in ≥ 5% of blasts of patients with SR-aALL is an adverse prognostic factor, delineating a subgroup of patients with SR-aALL that should be considered for more aggressive treatment.
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Affiliation(s)
- Bakul I Dalal
- Division of Laboratory Hematology, Vancouver General Hospital, Vancouver, BC, Canada.
| | - Areej Al Mugairi
- Division of Laboratory Hematology, Vancouver General Hospital, Vancouver, BC, Canada
| | - Steven Pi
- Division of Laboratory Hematology, Vancouver General Hospital, Vancouver, BC, Canada
| | - Soo Yeon Lee
- Division of Laboratory Hematology, Vancouver General Hospital, Vancouver, BC, Canada
| | - Nikisha S Khare
- Division of Laboratory Hematology, Vancouver General Hospital, Vancouver, BC, Canada
| | - Jason Pal
- Division of Laboratory Hematology, Vancouver General Hospital, Vancouver, BC, Canada
| | - Adam Bryant
- Leukemia/Bone Marrow Transplant Program of British Columbia, BC Cancer Agency and University of British Columbia, Vancouver, BC, Canada
| | - Alok P Vakil
- Division of Laboratory Hematology, Vancouver General Hospital, Vancouver, BC, Canada
| | - Sally Lau
- Leukemia/Bone Marrow Transplant Program of British Columbia, BC Cancer Agency and University of British Columbia, Vancouver, BC, Canada
| | - Yasser R Abou Mourad
- Leukemia/Bone Marrow Transplant Program of British Columbia, BC Cancer Agency and University of British Columbia, Vancouver, BC, Canada
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