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Yi X, Zhan H, Lyu J, Du J, Dai M, Zhao M, Zhang Y, Zhou C, Xu X, Fan Y, Li L, Dong B, Jiang X, Xiao Z, Zhou J, Zhao M, Zhang J, Fu Y, Chen T, Xu Y, Tian J, Liu Q, Zeng H. A chest CT-based nomogram for predicting survival in acute myeloid leukemia. BMC Cancer 2024; 24:458. [PMID: 38609917 PMCID: PMC11010287 DOI: 10.1186/s12885-024-12188-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 03/26/2024] [Indexed: 04/14/2024] Open
Abstract
BACKGROUND The identification of survival predictors is crucial for early intervention to improve outcome in acute myeloid leukemia (AML). This study aim to identify chest computed tomography (CT)-derived features to predict prognosis for acute myeloid leukemia (AML). METHODS 952 patients with pathologically-confirmed AML were retrospectively enrolled between 2010 and 2020. CT-derived features (including body composition and subcutaneous fat features), were obtained from the initial chest CT images and were used to build models to predict the prognosis. A CT-derived MSF nomogram was constructed using multivariate Cox regression incorporating CT-based features. The performance of the prediction models was assessed with discrimination, calibration, decision curves and improvements. RESULTS Three CT-derived features, including myosarcopenia, spleen_CTV, and SF_CTV (MSF) were identified as the independent predictors for prognosis in AML (P < 0.01). A CT-MSF nomogram showed a performance with AUCs of 0.717, 0.794, 0.796 and 0.792 for predicting the 1-, 2-, 3-, and 5-year overall survival (OS) probabilities in the validation cohort, which were significantly higher than the ELN risk model. Moreover, a new MSN stratification system (MSF nomogram plus ELN risk model) could stratify patients into new high, intermediate and low risk group. Patients with high MSN risk may benefit from intensive treatment (P = 0.0011). CONCLUSIONS In summary, the chest CT-MSF nomogram, integrating myosarcopenia, spleen_CTV, and SF_CTV features, could be used to predict prognosis of AML.
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Affiliation(s)
- Xiaoping Yi
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha, China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, China
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, China
- Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, China
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China
| | - Huien Zhan
- Department of Hematology, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Jun Lyu
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Juan Du
- Department of Hematology, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Min Dai
- Department of Hematology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Min Zhao
- Department of Nuclear Medicine, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Yu Zhang
- Department of Hematology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Cheng Zhou
- Department of Hematology, Xiangya Hospital, Central South University, Changsha, China
| | - Xin Xu
- Department of Geriatrics, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Yi Fan
- Department of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Lin Li
- Department of Hematology, Hunan Provincial People' Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, China
| | - Baoxia Dong
- Department of Hematology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai,, China
| | - Xinya Jiang
- Department of Hematology, The First Affiliated Hospital of Jinan University, Guangzhou, China
- Department of Hematology, Xiangya Hospital, Central South University, Changsha, China
| | - Zeyu Xiao
- The Guangzhou Key Laboratory of Molecular and Functional Imaging for Clinical Translation, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Jihao Zhou
- Department of Hematology, Shenzhen People's Hospital, Second Clinical Medical College of Jinan University, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Minyi Zhao
- Department of Hematology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Jian Zhang
- Department of Hematology, The Third Xiangya hospital, Central South University, Changsha, China
| | - Yan Fu
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Tingting Chen
- Department of Hematology, Shenzhen People's Hospital, Second Clinical Medical College of Jinan University, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Yang Xu
- Department of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Jie Tian
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
| | - Qifa Liu
- Department of Hematology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
| | - Hui Zeng
- Department of Hematology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
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Han L, Wu J, Lyu X, Yu J, Han X, Zhao H, Bian Z, Li W, Fan W, He C, Wang W, Zhang M, Li Y, Liu C, Sun H, Cao H, Sang L, Zhang J, Jiang Z, Peng J. Genetic mutation signature for relapse prediction in normal karyotype acute myeloid leukemia. Exp Hematol 2023; 128:67-76. [PMID: 37739208 DOI: 10.1016/j.exphem.2023.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/28/2023] [Accepted: 09/08/2023] [Indexed: 09/24/2023]
Abstract
Risk stratification for normal karyotype acute myeloid leukemia (NK-AML) remains unsatisfactory, which is reflected by the high incidence of leukemia relapse. This study aimed to evaluate the role of gene mutations and clinical characterization in predicting the relapse of patients with NK-AML. A prognostic system for NK-AML was constructed. A panel of gene mutations was explored using next-generation sequencing. A nomogram algorithm was used to build a genomic mutation signature (GMS) nomogram (GMSN) model that combines GMS, measurable residual disease, and clinical factors to predict relapse in 347 patients with NK-AML from four centers. Patients in the GMS-high group had a higher 5-year incidence of relapse than those in the GMS-low group (p < 0.001). The 5-year incidence of relapse was also higher in patients in the GMSN-high group than in those in the GMSN-intermediate and -low groups (p < 0.001). The 5-year disease-free survival and overall survival rates were lower in patients in the GMSN-high group than in those in the GMSN-intermediate and -low groups (p < 0.001) as confirmed by training and validation cohorts. This study illustrates the potential of GMSN as a predictor of NK-AML relapse.
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Affiliation(s)
- Lijie Han
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Jiaying Wu
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaodong Lyu
- Central Lab, the Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China
| | - Jifeng Yu
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaolin Han
- Department of Hematology, the First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Hongmian Zhao
- Department of Hematology, Huaihe Hospital of Henan University, Kaifeng, China
| | - Zhilei Bian
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wei Li
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Wenjuan Fan
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chen He
- Laboratory of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Weimin Wang
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Mengmeng Zhang
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yafei Li
- Laboratory of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chao Liu
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Hui Sun
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Haixia Cao
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Li'na Sang
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jun Zhang
- Department of Oncology, the Second Affiliated Hospital of Guizhou Medical University, Kaili, China
| | - Zhongxing Jiang
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Jie Peng
- Department of Hematology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Department of Oncology, the Second Affiliated Hospital of Guizhou Medical University, Kaili, China.
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3
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Chen E, Jiao C, Yu J, Gong Y, Jin D, Ma X, Cui J, Wu Z, Zhou J, Wang H, Su B, Ge J. Assessment of 2022 European LeukemiaNet risk classification system in real-world cohort from China. Cancer Med 2023; 12:21615-21626. [PMID: 38098254 PMCID: PMC10757130 DOI: 10.1002/cam4.6696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 10/09/2023] [Accepted: 10/26/2023] [Indexed: 12/31/2023] Open
Abstract
BACKGROUND The European LeukemiaNet (ELN) risk classification system for acute myeloid leukemia (AML) patients has been used worldwide. In 2022, the ELN risk classification system modified risk genes including CEBPA mutation status, myelodysplasia-related (MR) gene mutations and internal tandem duplications of FLT3 (FLT3-ITD). METHODS We include newly diagnosed de novo AML patients at our center from January 2017 to December 2021, regardless of the further treatment received. Clinical data and date of survival were included. Survival analysis were performed using the Kaplan-Meier method, and the log-rank test was used to compare survival between different risk groups. RESULTS We include 363 newly diagnosed de novo AML patients from 2017 to 2021 to assess the accuracy of the ELN risk classification system. Their survival results show that the ELN-2022 risk classification system is not superior to the ELN-2017 version; for patients with FLT3-ITD mutations but without FLT3 inhibitor treatment, their survival is similar to the ELN-2022 adverse risk group. The ELN-2022 risk classification system cannot accurately clarify ECOG performance status (PS) 2-4 patients, especially in the ELN-2022 favorable risk group. CONCLUSION The ELN-2022 risk stratification system may not be appropriate for patients unable to receive intensive therapy or FLT3 inhibitor; more real-world data is needed to straify patients with worse ECOG PS and inferior intensive therapy.
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Affiliation(s)
- Enbo Chen
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
| | - Changqing Jiao
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
| | - Jian Yu
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
| | - Yu Gong
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
- Department of HematologyChaoyang HospitalHuainanAnhuiChina
| | - Duo Jin
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
- Department of HematologyTaihe County People's HospitalFuyangAnhuiChina
| | - Xiaoyu Ma
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
| | - Jianling Cui
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
| | - Zhonghui Wu
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
| | - Junjie Zhou
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
| | - Haixia Wang
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
| | - Bobing Su
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
| | - Jian Ge
- Department of HematologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhuiChina
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4
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Boscaro E, Urbino I, Catania FM, Arrigo G, Secreto C, Olivi M, D'Ardia S, Frairia C, Giai V, Freilone R, Ferrero D, Audisio E, Cerrano M. Modern Risk Stratification of Acute Myeloid Leukemia in 2023: Integrating Established and Emerging Prognostic Factors. Cancers (Basel) 2023; 15:3512. [PMID: 37444622 DOI: 10.3390/cancers15133512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 07/02/2023] [Accepted: 07/04/2023] [Indexed: 07/15/2023] Open
Abstract
An accurate estimation of AML prognosis is complex since it depends on patient-related factors, AML manifestations at diagnosis, and disease genetics. Furthermore, the depth of response, evaluated using the level of MRD, has been established as a strong prognostic factor in several AML subgroups. In recent years, this rapidly evolving field has made the prognostic evaluation of AML more challenging. Traditional prognostic factors, established in cohorts of patients treated with standard intensive chemotherapy, are becoming less accurate as new effective therapies are emerging. The widespread availability of next-generation sequencing platforms has improved our knowledge of AML biology and, consequently, the recent ELN 2022 recommendations significantly expanded the role of new gene mutations. However, the impact of rare co-mutational patterns remains to be fully disclosed, and large international consortia such as the HARMONY project will hopefully be instrumental to this aim. Moreover, accumulating evidence suggests that clonal architecture plays a significant prognostic role. The integration of clinical, cytogenetic, and molecular factors is essential, but hierarchical methods are reaching their limit. Thus, innovative approaches are being extensively explored, including those based on "knowledge banks". Indeed, more robust prognostic estimations can be obtained by matching each patient's genomic and clinical data with the ones derived from very large cohorts, but further improvements are needed.
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Affiliation(s)
- Eleonora Boscaro
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
| | - Irene Urbino
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
| | - Federica Maria Catania
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
| | - Giulia Arrigo
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
| | - Carolina Secreto
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
| | - Matteo Olivi
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
| | - Stefano D'Ardia
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
| | - Chiara Frairia
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
| | - Valentina Giai
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
| | - Roberto Freilone
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
| | - Dario Ferrero
- Division of Hematology, Department of Molecular Biotechnology and Health Sciences, University of Torino, 10126 Turin, Italy
| | - Ernesta Audisio
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
| | - Marco Cerrano
- Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy
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5
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Rausch C, Rothenberg-Thurley M, Dufour A, Schneider S, Gittinger H, Sauerland C, Görlich D, Krug U, Berdel WE, Woermann BJ, Hiddemann W, Braess J, von Bergwelt-Baildon M, Spiekermann K, Herold T, Metzeler KH. Validation and refinement of the 2022 European LeukemiaNet genetic risk stratification of acute myeloid leukemia. Leukemia 2023:10.1038/s41375-023-01884-2. [PMID: 37041198 DOI: 10.1038/s41375-023-01884-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/13/2023] [Accepted: 03/20/2023] [Indexed: 04/13/2023]
Abstract
The revised 2022 European LeukemiaNet (ELN) AML risk stratification system requires validation in large, homogeneously treated cohorts. We studied 1118 newly diagnosed AML patients (median age, 58 years; range, 18-86 years) who received cytarabine-based induction chemotherapy between 1999 and 2012 and compared ELN-2022 to the previous ELN-2017 risk classification. Key findings were validated in a cohort of 1160 mostly younger patients. ELN-2022 reclassified 15% of patients, 3% into more favorable, and 12% into more adverse risk groups. This was mainly driven by patients reclassified from intermediate- to adverse-risk based on additional myelodysplasia-related mutations being included as adverse-risk markers. These patients (n = 79) had significantly better outcomes than patients with other adverse-risk genotypes (5-year OS, 26% vs. 12%) and resembled the remaining intermediate-risk group. Overall, time-dependent ROC curves and Harrel's C-index controlling for age, sex, and AML type (de novo vs. sAML/tAML) show slightly worse prognostic discrimination of ELN-2022 compared to ELN-2017 for OS. Further refinement of ELN-2022 without including additional genetic markers is possible, in particular by recognizing TP53-mutated patients with complex karyotypes as "very adverse". In summary, the ELN-2022 risk classification identifies a larger group of adverse-risk patients at the cost of slightly reduced prognostic accuracy compared to ELN-2017.
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Affiliation(s)
- Christian Rausch
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Maja Rothenberg-Thurley
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Annika Dufour
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Stephanie Schneider
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
- Institute of Human Genetics, University Hospital, LMU Munich, Munich, Germany
| | - Hanna Gittinger
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Cristina Sauerland
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Dennis Görlich
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Utz Krug
- Department of Medicine 3, Klinikum Leverkusen, Leverkusen, Germany
| | - Wolfgang E Berdel
- Department of Medicine A, University Hospital Münster, Münster, Germany
| | | | - Wolfgang Hiddemann
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jan Braess
- Department of Oncology and Hematology, Hospital Barmherzige Brüder, Regensburg, Germany
| | - Michael von Bergwelt-Baildon
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - Karsten Spiekermann
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - Tobias Herold
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.
- German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Klaus H Metzeler
- Department of Hematology, Cellular Therapy and Hemostaseology, University Hospital Leipzig, Leipzig, Germany.
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6
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Li F, Ye W, Yao Y, Wei W, Lin X, Zhuang H, Li C, Li X, Ling Q, Hu C, Huang X, Qian Y, Mao S, Huang J, Lu Y, Jin J. Spermatogenesis associated serine rich 2 like plays a prognostic factor and therapeutic target in acute myeloid leukemia by regulating the JAK2/STAT3/STAT5 axis. J Transl Med 2023; 21:115. [PMID: 36774517 PMCID: PMC9921581 DOI: 10.1186/s12967-023-03968-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 02/04/2023] [Indexed: 02/13/2023] Open
Abstract
BACKGROUND Spermatogenesis associated serine rich 2 like (SPATS2L) was highly expressed in homoharringtonine (HHT) resistant acute myeloid leukemia (AML) cell lines. However, its role is little known in AML. The present study aimed to investigate the function of SPATS2L in AML pathogenesis and elucidate the underlying molecular mechanisms. METHODS Overall survival (OS), event-free survival (EFS), relapse-free survival (RFS) were used to evaluate the prognostic impact of SPATS2L for AML from TCGA database and ourcohort. ShRNA was used to knockdown the expression of SPATS2L. Apoptosis was assessed by flow cytometry. The changes of proteins were assessed by Western blot(WB). A xenotransplantation mice model was used to evaluate in vivo growth and survival. RNA sequencing was performed to elucidate the molecular mechanisms underlying the role of SPATS2L in AML. RESULTS SPATS2L expression increased with increasing resistance indexes(RI) in HHT-resistant cell lines we had constructed. Higher SPATS2L expression was observed in intermediate/high-risk patients than in favorable patients. Meanwhile, decreased SPATS2L expression was observed in AML patients achieving complete remission (CR). Multivariate analysis showed high SPATS2L expression was an independent poor predictor of OS, EFS, RFS in AML. SPATS2L knock down (KD) suppressed cell growth, induced apoptosis, and suppressed key proteins of JAK/STAT pathway, such as JAK2, STAT3, STAT5 in AML cells. Inhibiting SPATS2L expression markedly enhanced the pro-apoptotic effects of traditional chemotherapeutics (Ara-c, IDA, and HHT). CONCLUSIONS High expression of SPATS2L is a poor prognostic factor in AML, and targeting SPATS2L may be a promising therapeutic strategy for AML patients.
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Affiliation(s)
- Fenglin Li
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China ,grid.203507.30000 0000 8950 5267Department of Hematology, The Affiliated People’s Hospital of Ningbo University, Baizhang road 251#, Ningbo, China
| | - Wenle Ye
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China
| | - Yiyi Yao
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China
| | - Wenwen Wei
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China
| | - Xiangjie Lin
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China
| | - Haihui Zhuang
- grid.203507.30000 0000 8950 5267Department of Hematology, The Affiliated People’s Hospital of Ningbo University, Baizhang road 251#, Ningbo, China
| | - Chenying Li
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China ,grid.13402.340000 0004 1759 700XZhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, China
| | - Xia Li
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China ,grid.13402.340000 0004 1759 700XZhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, China
| | - Qing Ling
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China
| | - Chao Hu
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China ,grid.13402.340000 0004 1759 700XZhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, China
| | - Xin Huang
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China ,grid.13402.340000 0004 1759 700XZhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, China
| | - Yu Qian
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China
| | - Shihui Mao
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China
| | - Jiansong Huang
- grid.13402.340000 0004 1759 700XDepartment of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China ,grid.13402.340000 0004 1759 700XZhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, China
| | - Ying Lu
- Department of Hematology, The Affiliated People's Hospital of Ningbo University, Baizhang road 251#, Ningbo, China.
| | - Jie Jin
- Department of Hematology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun road 79#, Hangzhou, China. .,Zhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, China. .,Zhejiang University Cancer Center, Hangzhou, China.
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7
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Ningombam A, Verma D, Kumar R, Singh J, Ali MS, Pandey AK, Singh I, Bakhshi S, Sharma A, Pushpam D, Palanichamy JK, Tanwar P, Singh AR, Chopra A. Prognostic relevance of NPM1, CEBPA, and FLT3 mutations in cytogenetically normal adult AML patients. AMERICAN JOURNAL OF BLOOD RESEARCH 2023; 13:28-43. [PMID: 36937459 PMCID: PMC10017593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 01/06/2023] [Indexed: 03/21/2023]
Abstract
BACKGROUND Acute myeloid leukemia with normal cytogenetics (CN-AML) is the largest group of AML patients with very heterogenous patient outcomes. The revised World Health Organization classification of the hematolymphoid tumours, 2022, has incorporated AML with Nucleophosphmin1 (NPM1) and CCAAT/enhancer binding protein-alpha (CEBPA) mutations as distinct entities. Despite the existing evidence of the prognostic relevance of FMS-like tyrosine kinase-3 internal tandem duplication (FLT3-ITD) in AML, it has not been included in the revised classification. METHOD In this prospective study, we determined the prevalence of NPM1, CEBPA, and FLT3 gene mutations in 151 de novo CN-AML adult patients (age ≥18 years) in a tertiary care hospital in north India. Additionally, the prognostic relevance of these mutations was also evaluated. RESULTS NPM1, FLT3-ITD, and CEBPA mutations were found in 33.11%, 23.84%, and 15.77% of CN-AML patients, respectively. CEBPA mutations were found at 3 domains: transactivation domain 1 (TAD1) in 10 (6.62%), transactivation domain 2 (TAD2) in 5 (3.31%), and basic leucine zipper domain (bZIP) in 11 (7.82%) patients. Patients with NPM1 mutation had better clinical remission rate (CR) (P=0.003), event-free survival (P=0.0014), and overall survival (OS) (P=0.0017). However, FLT3-ITD and CEBPA mutations did not show any association with CR (P=0.404 and 0.92, respectively). Biallelic CEBPA mutations were found in 12 (7.95%) patients and were associated with better OS (P=0.043). CONCLUSIONS These findings indicate that NPM1 and CEBPA mutations can be precisely used for risk stratification in CN-AML patients.
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Affiliation(s)
| | | | | | - Jay Singh
- Laboratory Oncology, AIIMSNew Delhi, India
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8
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Wang SL. Genetic changes in refractory relapsed acute myeloid leukemia with NPM1 mutation: A case report. World J Clin Cases 2022; 10:13058-13063. [PMID: 36569004 PMCID: PMC9782936 DOI: 10.12998/wjcc.v10.i35.13058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 11/04/2022] [Accepted: 11/18/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Acute myeloid leukemia is often associated with gene mutation or chromosome abnormality, which is an important factor affecting prognosis. The 5-year survival rate of patients with acute myeloid leukemia without hematopoietic stem cell transplantation is low. For patients who only received chemotherapy and whose first remission lasted > 5 years, there are few reports of gene spectrum changes between relapse and initial diagnosis.
CASE SUMMARY We report a 41-year-old woman who presented to our hospital with complaints of dizziness, poor appetite and wasting. She was diagnosed with acute myelomonocytic leukemia (M4b) with NPM1 mutation and only received chemotherapy. Her first remission lasted > 5 years. New genetic variants were detected upon relapse that may have been related to relapse and chemotherapy resistance.
CONCLUSION Mutations in WT1 (R394fs/A387fs)/PTPN11 T73I/ETV6 S350P and JAK2 W659R may be related to relapse and chemotherapy resistance in acute myeloid leukemia.
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Affiliation(s)
- Shuang-Ling Wang
- Department of Hematology and Oncology, The Second Affiliated Hospital of Medical College of Shantou University, Shantou 515041, Guangdong Province, China
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9
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Pastore F, Pastore A, Rothenberg-Thurley M, Metzeler KH, Ksienzyk B, Schneider S, Bohlander SK, Braess J, Sauerland MC, Görlich D, Berdel WE, Wörmann B, von Bergwelt-Baildon MS, Hiddemann W, Spiekermann K. Molecular profiling of patients with cytogenetically normal acute myeloid leukemia and hyperleukocytosis. Cancer 2022; 128:4213-4222. [PMID: 36271776 DOI: 10.1002/cncr.34495] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/29/2022] [Accepted: 08/24/2022] [Indexed: 01/31/2023]
Abstract
BACKGROUND Acute myeloid leukemia (AML) with initial hyperleukocytosis is associated with high early mortality and a poor prognosis. The aims of this study were to delineate the underlying molecular landscape in the largest cytogenetic risk group, cytogenetically normal acute myeloid leukemia (CN-AML), and to assess the prognostic relevance of recurrent mutations in the context of hyperleukocytosis and clinical risk factors. METHODS The authors performed a targeted sequencing of 49 recurrently mutated genes in 56 patients with newly diagnosed CN-AML and initial hyperleukocytosis of ≥100 G/L treated in the AMLCG99 study. The median number of mutated genes per patient was 5. The most common mutations occurred in FLT3 (73%), NPM1 (75%), and TET2 (45%). RESULTS The predominant pathways affected by mutations were signaling (84% of patients), epigenetic modifiers (75% of patients), and nuclear transport (NPM1; 75%) of patients. AML with hyperleukocytosis was enriched for molecular subtypes that negatively affected the prognosis, including a high percentage of patients presenting with co-occurring mutations in signaling and epigenetic modifiers such as FLT3 internal tandem duplications and TET2 mutations. CONCLUSIONS Despite these unique molecular features, clinical risk factors, including high white blood count, hemoglobin level, and lactate dehydrogenase level at baseline, remained the predictors for overall survival and relapse-free survival in hyperleukocytotic CN-AML.
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Affiliation(s)
- Friederike Pastore
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, Ludwig Maximilian University Munich, Munich, Germany
| | - Alessandro Pastore
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, Ludwig Maximilian University Munich, Munich, Germany
| | - Maja Rothenberg-Thurley
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, Ludwig Maximilian University Munich, Munich, Germany
| | - Klaus H Metzeler
- Department of Hematology and Cell Therapy, University Leipzig, Leipzig, Germany
| | - Bianka Ksienzyk
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, Ludwig Maximilian University Munich, Munich, Germany
| | - Stephanie Schneider
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, Ludwig Maximilian University Munich, Munich, Germany.,Institute of Human Genetics, Ludwig Maximilian University Munich, Munich, Germany
| | - Stefan K Bohlander
- Leukemia and Blood Cancer Research Unit, Department of Molecular Medicine and Pathology, University of Auckland, Auckland, New Zealand
| | - Jan Braess
- Department of Oncology and Hematology, Hospital Barmherzige Brüder, Regensburg, Germany
| | - Maria C Sauerland
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Dennis Görlich
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Wolfgang E Berdel
- Department of Medicine A, Hematology and Oncology, University of Münster, Münster, Germany
| | - Bernhard Wörmann
- Department of Medicine, Hematology, Oncology, and Tumor Immunology, Charite-Universitätsmedizin Berlin, Berlin, Germany
| | - Michael S von Bergwelt-Baildon
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, Ludwig Maximilian University Munich, Munich, Germany
| | - Wolfgang Hiddemann
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, Ludwig Maximilian University Munich, Munich, Germany
| | - Karsten Spiekermann
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, Ludwig Maximilian University Munich, Munich, Germany
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10
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Blachly JS, Walter RB, Hourigan CS. The present and future of measurable residual disease testing in acute myeloid leukemia. Haematologica 2022; 107:2810-2822. [PMID: 36453518 PMCID: PMC9713561 DOI: 10.3324/haematol.2022.282034] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Indexed: 12/04/2022] Open
Abstract
Considerable progress has been made in the past several years in the scientific understanding of, and available treatments for, acute myeloid leukemia (AML). Achievement of a conventional remission, evaluated cytomorphologically via small bone marrow samples, is a necessary but not sufficient step toward cure. It is increasingly appreciated that molecular or immunophenotypic methods to identify and quantify measurable residual disease (MRD) - populations of leukemia cells below the cytomorphological detection limit - provide refined information on the quality of response to treatment and prediction of the risk of AML recurrence and leukemia-related deaths. The principles and practices surrounding MRD remain incompletely determined however and the genetic and immunophenotypic heterogeneity of AML may prevent a one-sizefits- all approach. Here, we review the current approaches to MRD testing in AML, discuss strengths and limitations, highlight recent technological advances that may improve such testing, and summarize ongoing initiatives to generate the clinical evidence needed to advance the use of MRD testing in patients with AML.
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Affiliation(s)
- James S. Blachly
- Division of Hematology/Department of Medicine, The Ohio State University - The James Comprehensive Cancer Center, Columbus, OH,Department of Biomedical Informatics, The Ohio State University, Columbus, OH,J.S. Blachly
| | - Roland B. Walter
- Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA,Division of Hematology/Department of Medicine, University of Washington, Seattle, WA,Department of Laboratory Medicine & Pathology, University of Washington, Seattle, WA, USA,Department of Epidemiology, University of Washington, Seattle, WA
| | - Christopher S. Hourigan
- Laboratory of Myeloid Malignancies, Hematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
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11
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Zhang N, Liu X, Wu J, Li X, Wang Q, Chen G, Ma L, Wu S, Zhou F. Serum proteomics screening intercellular adhesion molecule-2 improves intermediate-risk stratification in acute myeloid leukemia. Ther Adv Hematol 2022; 13:20406207221132346. [PMID: 36324489 PMCID: PMC9619266 DOI: 10.1177/20406207221132346] [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: 04/22/2022] [Accepted: 09/12/2022] [Indexed: 11/22/2022] Open
Abstract
Background The clinical risk classification of acute myelocytic leukemia (AML) is largely based on cytogenetic and molecular genetic detection. However, the optimal treatment for intermediate-risk AML patients remains uncertain. Further refinement and improvement of prognostic stratification are therefore necessary. Objectives The aim of this study was to identify serum protein biomarkers to refine risk stratification in AML patients. Design This study is a retrospective study. Methods Label-free proteomics was used to identify the differential abundance of serum proteins in AML patients. Transcriptomic data were combined to identify key altered markers that could indicate the risk rank of AML patients. The survival status was assessed by Kaplan-Meier and multivariate Cox regression analyses. Results We delineated serum protein expression in a population of AML patients. Many biological processes were influenced by the identified differentially expressed proteins. Association analysis of transcriptome data showed that intercellular adhesion molecule-2 (ICAM2) had a higher survival prediction value in the intermediate-risk AML group. ICAM2 was detrimental for intermediate-risk AML, regardless of whether patients received bone marrow transplantation. ICAM2 well distinguishes the intermediate group of patients, whose probability of survival is comparable to that of patients with the ELN-2017 according to the reference classification. In addition, newly established stratified clinical features were associated with leukemia stem cell scores. Conclusion The inclusion of ICAM2 expression into the AML risk classification according to ELN-2017 was a good way to transfer patients from three to two groups. Thus, providing more information for clinical decision-making to improve intermediate-risk stratification in AML patients.
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Affiliation(s)
| | | | - Jinxian Wu
- Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xinqi Li
- Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Qian Wang
- Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Guopeng Chen
- Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Linlu Ma
- Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Sanyun Wu
- Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, China
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12
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Molecular Measurable Residual Disease Assessment before Hematopoietic Stem Cell Transplantation in Pediatric Acute Myeloid Leukemia Patients: A Retrospective Study by the I-BFM Study Group. Biomedicines 2022; 10:biomedicines10071530. [PMID: 35884834 PMCID: PMC9313005 DOI: 10.3390/biomedicines10071530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 06/14/2022] [Accepted: 06/24/2022] [Indexed: 11/16/2022] Open
Abstract
Hematopoietic stem cell transplantation (HSCT) is a curative post-remission treatment in patients with acute myeloid leukemia (AML), but relapse after transplant is still a challenging event. In recent year, several studies have investigated the molecular minimal residual disease (qPCR-MRD) as a predictor of relapse, but the lack of standardized protocols, cut-offs, and timepoints, especially in the pediatric setting, has prevented its use in several settings, including before HSCT. Here, we propose the first collaborative retrospective I-BFM-AML study assessing qPCR-MRD values in pretransplant bone marrow samples of 112 patients with a diagnosis of AML harboring t(8;21)(q22; q22)RUNX1::RUNX1T1, or inv(16)(p13q22)CBFB::MYH11, or t(9;11)(p21;q23)KMT2A::MLLT3, or FLT3-ITD genetic markers. We calculated an ROC cut-off of 2.1 × 10−4 that revealed significantly increased OS (83.7% versus 57.1%) and EFS (80.2% versus 52.9%) for those patients with lower qPCR-MRD values. Then, we partitioned patients into three qPCR-MRD groups by combining two different thresholds, 2.1 × 10−4 and one lower cut-off of 1 × 10−2, and stratified patients into low-, intermediate-, and high-risk groups. We found that the 5-year OS (83.7%, 68.6%, and 39.2%, respectively) and relapse-free survival (89.2%, 73.9%, and 67.9%, respectively) were significantly different independent of the genetic lesion, conditioning regimen, donor, and stem cell source. These data support the PCR-based approach playing a clinical relevance in AML transplant management.
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13
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Schmucker AM, Leiby BE, Wilde L. Validation of AML-score in Older Adults Receiving CPX-351 Intensive Induction Chemotherapy for Treatment of Secondary Acute Myeloid Leukemia. CLINICAL LYMPHOMA, MYELOMA & LEUKEMIA 2022; 22:e206-e212. [PMID: 34686446 DOI: 10.1016/j.clml.2021.09.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 09/13/2021] [Accepted: 09/20/2021] [Indexed: 06/13/2023]
Abstract
INTRODUCTION/BACKGROUND The AML-Score has been validated in patients receiving traditional induction chemotherapies but not CPX-351. We conducted a retrospective analysis to evaluate, among patients with secondary acute myeloid leukemia who received intensive induction with CPX-351, if the AML-Score associates with (1) complete remission (CR) and (2) early mortality (EM) within 60 days of induction. MATERIALS AND METHODS We abstracted demographic and clinical data from consecutive patients receiving CPX-351 at Sidney Kimmel Cancer Center at Thomas Jefferson University Hospital between September 2017 and November 2020. We used descriptive statistics and receiver operating curves to evaluate the relationship between AML-Score and rates of CR and EM. RESULTS In total, 40 patients were included. 27 (67.5%) were male, 27 (67.5%) were white, 36 (90.0%) were not Hispanic or Latino, and 29 (72.5%) were aged ≥60 years. Twenty-seven patients (67.5%) had a CR, and 4 (10%) experienced EM. Observed rates of CR and EM generally increased with increasing predicted risk. The area under the curve was 0.75 (95% CI 0.60-0.90) for CR and 0.82 (95% CI 0.68-0.96) for EM. CONCLUSION The AML-Score tool trends in the correct direction for predicting CR and EM, and thus may facilitate oncologist prognostication and treatment planning for patients receiving CPX-351. However, its clinical utility is limited by its underestimation of the risk of CR and overestimation of the risk of EM. Further validation in a larger cohort is needed to calculate accurate point estimates of CR and EM risk in this population.
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Affiliation(s)
- Abigail M Schmucker
- Department of Internal Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Benjamin E Leiby
- Division of Biostatistics, Department of Pharmacology and Experimental Therapeutics, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA
| | - Lindsay Wilde
- Department of Medical Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA.
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14
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TERT genetic variability and telomere length as factors affecting survival and risk in acute myeloid leukaemia. Sci Rep 2021; 11:23301. [PMID: 34857839 PMCID: PMC8640063 DOI: 10.1038/s41598-021-02767-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/22/2021] [Indexed: 11/16/2022] Open
Abstract
Acute myeloid leukaemia (AML) is a neoplasm of immature myeloid cells characterized by various cytogenetic alterations. The present study showed that in addition to the FLT3-ITD and NPM1 mutation status, telomere length (TL) and telomerase reverse transcriptase (TERT) gene polymorphisms may affect risk and overall survival (OS) in AML. TL was longer in healthy controls than in AML patients and positively correlated with age in the patients, but not in healthy subjects. TL was found to be independently affected by the presence of the FLT3-ITD mutation. As for the TERT gene polymorphism, AML patients with the TERT rs2853669 CC genotype were characterized by significantly shorter OS than patients carrying the T allele. Another observation in our study is the difference in TL and OS in patients belonging to various risk stratification groups related to the FLT3-ITD and NPM1 mutation status. Patients with adverse risk classification (mutation in FLT3-ITD and lack of mutation in NPM1) presented with the shortest telomeres and significantly worse OS. In conclusion, OS of AML patients appears to be affected by TERT gene variability and TL in addition to other well-established factors such as age, WBC count, or FLT3-ITD and NPM1 mutation status.
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15
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Moser C, Jurinovic V, Sagebiel-Kohler S, Ksienzyk B, Batcha AMN, Dufour A, Schneider S, Rothenberg-Thurley M, Sauerland CM, Görlich D, Berdel WE, Krug U, Mansmann U, Hiddemann W, Braess J, Spiekermann K, Greif PA, Vosberg S, Metzeler KH, Kumbrink J, Herold T. A clinically applicable gene expression-based score predicts resistance to induction treatment in acute myeloid leukemia. Blood Adv 2021; 5:4752-4761. [PMID: 34535016 PMCID: PMC8759116 DOI: 10.1182/bloodadvances.2021004814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 07/06/2021] [Indexed: 11/20/2022] Open
Abstract
Prediction of resistant disease at initial diagnosis of acute myeloid leukemia (AML) can be achieved with high accuracy using cytogenetic data and 29 gene expression markers (Predictive Score 29 Medical Research Council; PS29MRC). Our aim was to establish PS29MRC as a clinically usable assay by using the widely implemented NanoString platform and further validate the classifier in a more recently treated patient cohort. Analyses were performed on 351 patients with newly diagnosed AML intensively treated within the German AML Cooperative Group registry. As a continuous variable, PS29MRC performed best in predicting induction failure in comparison with previously published risk models. The classifier was strongly associated with overall survival. We were able to establish a previously defined cutoff that allows classifier dichotomization (PS29MRCdic). PS29MRCdic significantly identified induction failure with 59% sensitivity, 77% specificity, and 72% overall accuracy (odds ratio, 4.81; P = 4.15 × 10-10). PS29MRCdic was able to improve the European Leukemia Network 2017 (ELN-2017) risk classification within every category. The median overall survival with high PS29MRCdic was 1.8 years compared with 4.3 years for low-risk patients. In multivariate analysis including ELN-2017 and clinical and genetic markers, only age and PS29MRCdic were independent predictors of refractory disease. In patients aged ≥60 years, only PS29MRCdic remained as a significant variable. In summary, we confirmed PS29MRC as a valuable classifier to identify high-risk patients with AML. Risk classification can still be refined beyond ELN-2017, and predictive classifiers might facilitate clinical trials focusing on these high-risk patients with AML.
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Affiliation(s)
- Christian Moser
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
| | - Vindi Jurinovic
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
- Department of Pediatrics, Dr. von Hauner Children’s Hospital
| | | | - Bianka Ksienzyk
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
| | - Aarif M. N. Batcha
- Institute for Medical Information Processing, Biometry, and Epidemiology, LMU Munich, Munich, Germany
- DIFUTURE, Data Integration for Future Medicine (DiFuture, www.difuture.de)
| | - Annika Dufour
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
| | - Stephanie Schneider
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
- Institute of Human Genetics, University Hospital, LMU Munich, Munich, Germany
| | - Maja Rothenberg-Thurley
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
| | | | | | - Wolfgang E. Berdel
- Department of Medicine, Hematology, and Oncology, University of Münster, Münster, Germany
| | - Utz Krug
- Department of Medicine III, Hospital Leverkusen, Leverkusen, Germany
| | - Ulrich Mansmann
- Institute for Medical Information Processing, Biometry, and Epidemiology, LMU Munich, Munich, Germany
- DIFUTURE, Data Integration for Future Medicine (DiFuture, www.difuture.de)
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Wolfgang Hiddemann
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Jan Braess
- Department of Oncology and Hematology, Hospital Barmherzige Brüder, Regensburg, Germany; and
| | - Karsten Spiekermann
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Philipp A. Greif
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Sebastian Vosberg
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Klaus H. Metzeler
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
- Medical Clinic and Policlinic I, Hematology and Cellular Therapy, Leipzig University Hospital, Leipzig, Germany
| | - Jörg Kumbrink
- Institute of Pathology
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Tobias Herold
- Laboratory for Leukemia Diagnostics, Department of Internal Medicine III, University Hospital
- Research Unit Apoptosis in Hematopoietic Stem Cells, Helmholtz Zentrum München, German Center for Environmental Health (HMGU), Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
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16
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Itzykson R, Fournier E, Berthon C, Röllig C, Braun T, Marceau-Renaut A, Pautas C, Nibourel O, Lemasle E, Micol JB, Adès L, Lebon D, Malfuson JV, Gastaud L, Goursaud L, Raffoux E, Wattebled KJ, Rousselot P, Thomas X, Chantepie S, Cluzeau T, Serve H, Boissel N, Terré C, Celli-Lebras K, Preudhomme C, Thiede C, Dombret H, Gardin C, Duployez N. Genetic identification of patients with AML older than 60 years achieving long-term survival with intensive chemotherapy. Blood 2021; 138:507-519. [PMID: 34410352 DOI: 10.1182/blood.2021011103] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 05/05/2021] [Indexed: 02/06/2023] Open
Abstract
To design a simple and reproducible classifier predicting the overall survival (OS) of patients with acute myeloid leukemia (AML) ≥60 years of age treated with 7 + 3, we sequenced 37 genes in 471 patients from the ALFA1200 (Acute Leukemia French Association) study (median age, 68 years). Mutation patterns and OS differed between the 84 patients with poor-risk cytogenetics and the 387 patients with good (n = 13), intermediate (n = 339), or unmeasured (n = 35) cytogenetic risk. TP53 (hazards ratio [HR], 2.49; P = .0003) and KRAS (HR, 3.60; P = .001) mutations independently worsened the OS of patients with poor-risk cytogenetics. In those without poor-risk cytogenetics, NPM1 (HR, 0.57; P = .0004), FLT3 internal tandem duplications with low (HR, 1.85; P = .0005) or high (HR, 3.51; P < 10-4) allelic ratio, DNMT3A (HR, 1.86; P < 10-4), NRAS (HR, 1.54; P = .019), and ASXL1 (HR, 1.89; P = .0003) mutations independently predicted OS. Combining cytogenetic risk and mutations in these 7 genes, 39.1% of patients could be assigned to a "go-go" tier with a 2-year OS of 66.1%, 7.6% to the "no-go" group (2-year OS 2.8%), and 3.3% of to the "slow-go" group (2-year OS of 39.1%; P < 10-5). Across 3 independent validation cohorts, 31.2% to 37.7% and 11.2% to 13.5% of patients were assigned to the go-go and the no-go tiers, respectively, with significant differences in OS between tiers in all 3 trial cohorts (HDF [Hauts-de-France], n = 141, P = .003; and SAL [Study Alliance Leukemia], n = 46; AMLSG [AML Study Group], n = 223, both P < 10-5). The ALFA decision tool is a simple, robust, and discriminant prognostic model for AML patients ≥60 years of age treated with intensive chemotherapy. This model can instruct the design of trials comparing the 7 + 3 standard of care with less intensive regimens.
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Affiliation(s)
- Raphael Itzykson
- Service Hématologie Adultes, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France
- Génomes, Biologie Cellulaire et Thérapeutique, Unité 944, Université de Paris, Centre National de la Recherche Scientifique (CNRS), INSERM, Paris, France
| | - Elise Fournier
- Département d'Hématologie, Canther (Cancer Heterogeneity, Plasticity and Resistance to Therapies), Unité 1277, Centre Hospitalier Universitaire de Lille, Université de Lille, INSERM, Lille, France
| | - Céline Berthon
- Département d'Hématologie, Canther (Cancer Heterogeneity, Plasticity and Resistance to Therapies), Unité 1277, Centre Hospitalier Universitaire de Lille, Université de Lille, INSERM, Lille, France
| | - Christoph Röllig
- Medizinische Klinik and
- Poliklinik 1, Universitätsklinikum Techniche Universität Dresden, Dresden, Germany
| | - Thorsten Braun
- Service d'Hématologie Clinique, Hôpital Avicenne, AP-HP, Bobigny, France
| | - Alice Marceau-Renaut
- Département d'Hématologie, Canther (Cancer Heterogeneity, Plasticity and Resistance to Therapies), Unité 1277, Centre Hospitalier Universitaire de Lille, Université de Lille, INSERM, Lille, France
| | - Cécile Pautas
- Service d'Hématologie Clinique, Hôpital Henri Mondor, AP-HP, Créteil, France
| | - Olivier Nibourel
- Département d'Hématologie, Canther (Cancer Heterogeneity, Plasticity and Resistance to Therapies), Unité 1277, Centre Hospitalier Universitaire de Lille, Université de Lille, INSERM, Lille, France
| | - Emilie Lemasle
- Service d'Hématologie, Centre Henri Becquerel, Rouen, France
| | - Jean-Baptiste Micol
- Département d'Hématologie, Institut Gustave Roussy, Université Paris-Saclay, Villejuif, France
| | - Lionel Adès
- Service Hématologie Seniors, Hôpital Saint-Louis, AP-HP, Paris, France
| | | | - Jean-Valère Malfuson
- Service d'Hématologie Clinique, Hôpital d'Instruction des Armées Percy, Clamart, France
| | - Lauris Gastaud
- Département d'Oncologie Médicale, Centre Antoine Lacassagne, Nice, France
| | - Laure Goursaud
- Département d'Hématologie, Canther (Cancer Heterogeneity, Plasticity and Resistance to Therapies), Unité 1277, Centre Hospitalier Universitaire de Lille, Université de Lille, INSERM, Lille, France
| | - Emmanuel Raffoux
- Service Hématologie Adultes, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France
| | | | - Philippe Rousselot
- Département d'Hématologie Clinique, Hôpital André Mignot, Centre Hospitalier de Versailles, Le Chesnay, France
- Unité Mixte de Recherche (UMR) 1184, Infectious Disease Models for Innovative Therapies (IDMIT) Department, Université Paris-Saclay, Commissariat à l'Énergie Atomique et Aux Énergies Alternatives (CEA), INSERM, Paris, France
| | - Xavier Thomas
- Service d'Hématologie Clinique, Hospices Civils de Lyon, Hôpital Lyon Sud, Pierre-Bénite, France
| | | | - Thomas Cluzeau
- Service d'Hématologie, Université Cote d'Azur, CHU de Nice, Nice, France
| | - Hubert Serve
- Department of Medicine 2, Hematology and Oncology, Goethe University Frankfurt, Frankfurt, Germany
| | - Nicolas Boissel
- Service Hématologie Adolescents Jeunes Adultes, Hôpital Saint-Louis, AP-HP, Paris, France
| | - Christine Terré
- Laboratoire de Cytogénétique, CH Versailles, Le Chesnay, France
| | | | - Claude Preudhomme
- Département d'Hématologie, Canther (Cancer Heterogeneity, Plasticity and Resistance to Therapies), Unité 1277, Centre Hospitalier Universitaire de Lille, Université de Lille, INSERM, Lille, France
| | | | - Hervé Dombret
- Service Hématologie Adultes, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France
- Institut de Recherche Saint-Louis (IRSL), Equipe d'Accueil (EA) 3518, Université de Paris, Hôpital Saint-Louis, Paris, France
| | - Claude Gardin
- Service d'Hématologie Clinique, Hôpital Avicenne, AP-HP, Bobigny, France
- Institut de Recherche Saint-Louis (IRSL), Equipe d'Accueil (EA) 3518, Université de Paris, Hôpital Saint-Louis, Paris, France
| | - Nicolas Duployez
- Département d'Hématologie, Canther (Cancer Heterogeneity, Plasticity and Resistance to Therapies), Unité 1277, Centre Hospitalier Universitaire de Lille, Université de Lille, INSERM, Lille, France
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17
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Preleukemic and leukemic evolution at the stem cell level. Blood 2021; 137:1013-1018. [PMID: 33275656 DOI: 10.1182/blood.2019004397] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 12/01/2020] [Indexed: 02/07/2023] Open
Abstract
Hematological malignancies are an aggregate of diverse populations of cells that arise following a complex process of clonal evolution and selection. Recent approaches have facilitated the study of clonal populations and their evolution over time across multiple phenotypic cell populations. In this review, we present current concepts on the role of clonal evolution in leukemic initiation, disease progression, and relapse. We highlight recent advances and unanswered questions about the contribution of the hematopoietic stem cell population to these processes.
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18
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Hu X, Wang B, Chen Q, Huang A, Fu W, Liu L, Zhang Y, Tang G, Cheng H, Ni X, Gao L, Chen J, Chen L, Zhang W, Yang J, Cao S, Yu L, Wang J. A clinical prediction model identifies a subgroup with inferior survival within intermediate risk acute myeloid leukemia. J Cancer 2021; 12:4912-4923. [PMID: 34234861 PMCID: PMC8247394 DOI: 10.7150/jca.57231] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Accepted: 05/19/2021] [Indexed: 12/19/2022] Open
Abstract
Intermediate risk acute myeloid leukemia (AML) comprises around 50% of AML patients and is featured with heterogeneous clinical outcomes. The study aimed to generate a prediction model to identify intermediate risk AML patients with an inferior survival. We performed targeted next generation sequencing analysis for 121 patients with 2017 European LeukemiaNet-defined intermediate risk AML, revealing 122 mutated genes, with 24 genes mutated in > 10% of patients. A prognostic nomogram characterized by white blood cell count ≥10×109/L at diagnosis, mutated DNMT3A and genes involved in signaling pathways was developed for 110 patients who were with clinical outcomes. Two subgroups were identified: intermediate low risk (ILR; 43.6%, 48/110) and intermediate high risk (IHR; 56.4%, 62/110). The model was prognostic of overall survival (OS) and relapse-free survival (RFS) (OS: Concordance index [C-index]: 0.703, 95%CI: 0.643-0.763; RFS: C-index: 0.681, 95%CI 0.620-0.741), and was successfully validated with two independent cohorts. Allogeneic hematopoietic stem cell transplantation (alloHSCT) reduced the relapse risk of IHR patients (3-year RFS: alloHSCT: 40.0±12.8% vs. chemotherapy: 8.6±5.8%, P= 0.010). The prediction model can help identify patients with an unfavorable prognosis and refine risk-adapted therapy for intermediate risk AML patients.
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Affiliation(s)
- Xiaoxia Hu
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Bianhong Wang
- Department of Hematology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 102218, China.,Department of Hematology, Chinese PLA General Hospital, Beijing, 100853, China
| | - Qi Chen
- Department of Health Statistics, Second Military Medical University, Shanghai 200433, China
| | - Aijie Huang
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Weijia Fu
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Lixia Liu
- Acornmed Biotechnology Co., Ltd. Beijing, 100176, China
| | - Ying Zhang
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Gusheng Tang
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Hui Cheng
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Xiong Ni
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Lei Gao
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Jie Chen
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Li Chen
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Weiping Zhang
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Jianmin Yang
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
| | - Shanbo Cao
- Acornmed Biotechnology Co., Ltd. Beijing, 100176, China
| | - Li Yu
- Department of Hematology, Chinese PLA General Hospital, Beijing, 100853, China.,Department of Hematology and Oncology, Shenzhen University General Hospital; Shenzhen University International Cancer Center, Shenzhen University Health Science Center, Shenzhen, 518000, China
| | - Jianmin Wang
- Department of Hematology, Institute of Hematology, Changhai Hospital, Shanghai 200433, China
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19
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Kantarjian HM, Short NJ, Fathi AT, Marcucci G, Ravandi F, Tallman M, Wang ES, Wei AH. Acute Myeloid Leukemia: Historical Perspective and Progress in Research and Therapy Over 5 Decades. CLINICAL LYMPHOMA MYELOMA & LEUKEMIA 2021; 21:580-597. [PMID: 34176779 DOI: 10.1016/j.clml.2021.05.016] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 05/20/2021] [Accepted: 05/22/2021] [Indexed: 12/17/2022]
Abstract
With the Food and Drug Administration approval of 9 agents for different acute myeloid leukemia (AML) indications, the prognosis and management of AML is evolving rapidly. Herein, we review the important milestones in the history of AML research and therapy, discuss insights regarding prognostic assessment and prediction of treatment outcome, detail practical supportive care measures, and summarize the current treatment landscape and areas of evolving research.
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Affiliation(s)
| | - Nicholas J Short
- Department of Leukemia, MD Anderson Cancer Center, Houston, TX, USA
| | - Amir T Fathi
- Leukemia Program, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Guido Marcucci
- Gehr Family Center for Leukemia Research City of Hope, Duarte, CA, USA
| | - Farhad Ravandi
- Department of Leukemia, MD Anderson Cancer Center, Houston, TX, USA
| | - Martin Tallman
- Leukemia Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, New York, NY, USA
| | - Eunice S Wang
- Leukemia Service, Department of Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Andrew H Wei
- Department of Clinical Hematology, The Alfred Hospital and Monash University, Melbourne, Australia
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20
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Laribi K, Sobh M, Ghez D, Baugier de Materre A. Impact of age, functional status, and comorbidities on quality of life and outcomes in elderly patients with AML: review. Ann Hematol 2021; 100:1359-1376. [PMID: 33796898 DOI: 10.1007/s00277-020-04375-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 12/08/2020] [Indexed: 12/17/2022]
Abstract
The incidence of acute myeloid leukemia increases with age, and more than half of AML patients are over 60 years old. Treating elderly AML patients presents several challenges and uncertainties, linked partly to disease characteristics and partly to the difficulty of establishing which patients could benefit from the best treatment. Although some elderly fit patients can receive intensive therapy, many of them are not treated and not enrolled in clinical trials. Yet supportive care is associated with significantly lower survival rates compared to intensive therapy or lower intensive therapy. A poorer prognosis in elderly patients is related to age, functional status, and comorbidities, combined with leukemia characteristics. Chronological age is not the best surrogate factor for selecting patients eligible for intensive chemotherapy. Scoring systems-including patient characteristics (ECOG, comorbidities) and disease characteristics (cytogenetics and molecular parameters)-designed to evaluate probabilities of response to treatment, morbidity, and survival may be used to balance the risk-benefit ratio for intensive therapy. A geriatric assessment (GA) to evaluate physical function, comorbidities, nutritional status, cognitive function, and social support could help identify the most vulnerable patients so that they can receive intensive therapy. A GA would also help take the necessary steps to improve tolerance to treatment. Evaluating markers of fitness and quality of life as part of clinical trials should be favored.
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Affiliation(s)
- Kamel Laribi
- Department of Hematology, Centre Hospitalier Le Mans, 194 Avenue Rubillard, 72000, Le Mans, France.
| | - Mohamad Sobh
- Department of Hematology, The Ottawa Hospital, 501 Smyth Rd, Ottawa, ON, K1H 8L6, Canada
| | - David Ghez
- Department of Hematology, Institut Gustave Roussy, 114 rue Edouard Vaillant, 94805, Villejuif, France
| | - Alix Baugier de Materre
- Geriatric Department, Assistance Publique-Hôpitaux de Paris, Hôpital Broca, 54-56 Pascal, 75013, Paris, France
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21
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Kantarjian HM, Kadia TM, DiNardo CD, Welch MA, Ravandi F. Acute myeloid leukemia: Treatment and research outlook for 2021 and the MD Anderson approach. Cancer 2021; 127:1186-1207. [PMID: 33734442 DOI: 10.1002/cncr.33477] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 12/31/2020] [Accepted: 01/11/2021] [Indexed: 12/17/2022]
Abstract
The unraveling of the pathophysiology of acute myeloid leukemia (AML) has resulted in rapid translation of the information into clinical practice. After more than 40 years of slow progress in AML research, the US Food and Drug Administration has approved nine agents for different AML treatment indications since 2017. In this review, we detail the progress that has been made in the research and treatment of AML, citing key publications related to AML research and therapy in the English literature since 2000. The notable subsets of AML include acute promyelocytic leukemia (APL), core-binding factor AML (CBF-AML), AML in younger patients fit for intensive chemotherapy, and AML in older/unfit patients (usually at the age cutoff of 60-70 years). We also consider within each subset whether the AML is primary or secondary (therapy-related, evolving from untreated or treated myelodysplastic syndrome or myeloproliferative neoplasm). In APL, therapy with all-trans retinoic acid and arsenic trioxide results in estimated 10-year survival rates of ≥80%. Treatment of CBF-AML with fludarabine, high-dose cytarabine, and gemtuzumab ozogamicin (GO) results in estimated 10-year survival rates of ≥75%. In younger/fit patients, the "3+7" regimen (3 days of daunorubicin + 7 days of cytarabine) produces less favorable results (estimated 5-year survival rates of 35%; worse in real-world experience); regimens that incorporate high-dose cytarabine, adenosine nucleoside analogs, and GO are producing better results. Adding venetoclax, FLT3, and IDH inhibitors into these regimens has resulted in encouraging preliminary data. In older/unfit patients, low-intensity therapy with hypomethylating agents (HMAs) and venetoclax is now the new standard of care. Better low-intensity regimens incorporating cladribine, low-dose cytarabine, and other targeted therapies (FLT3 and IDH inhibitors) are emerging. Maintenance therapy now has a definite role in the treatment of AML, and oral HMAs with potential treatment benefits are also available. In conclusion, AML therapy is evolving rapidly and treatment results are improving in all AML subsets as novel agents and strategies are incorporated into traditional AML chemotherapy. LAY SUMMARY: Ongoing research in acute myeloid leukemia (AML) is progressing rapidly. Since 2017, the US Food and Drug Administration has approved 10 drugs for different AML indications. This review updates the research and treatment pathways for AML.
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Affiliation(s)
| | - Tapan M Kadia
- Department of Leukemia, MD Anderson Cancer Center, Houston, Texas
| | | | - Mary Alma Welch
- Department of Leukemia, MD Anderson Cancer Center, Houston, Texas
| | - Farhad Ravandi
- Department of Leukemia, MD Anderson Cancer Center, Houston, Texas
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22
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Kantarjian H, Kadia T, DiNardo C, Daver N, Borthakur G, Jabbour E, Garcia-Manero G, Konopleva M, Ravandi F. Acute myeloid leukemia: current progress and future directions. Blood Cancer J 2021; 11:41. [PMID: 33619261 PMCID: PMC7900255 DOI: 10.1038/s41408-021-00425-3] [Citation(s) in RCA: 313] [Impact Index Per Article: 104.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 12/14/2020] [Accepted: 01/18/2021] [Indexed: 12/12/2022] Open
Abstract
Progress in the understanding of the biology and therapy of acute myeloid leukemia (AML) is occurring rapidly. Since 2017, nine agents have been approved for various indications in AML. These included several targeted therapies like venetoclax, FLT3 inhibitors, IDH inhibitors, and others. The management of AML is complicated, highlighting the need for expertise in order to deliver optimal therapy and achieve optimal outcomes. The multiple subentities in AML require very different therapies. In this review, we summarize the important pathophysiologies driving AML, review current therapies in standard practice, and address present and future research directions.
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Affiliation(s)
- Hagop Kantarjian
- Department of Leukemia, MD Anderson Cancer Center, Houston, TX, USA.
| | - Tapan Kadia
- Department of Leukemia, MD Anderson Cancer Center, Houston, TX, USA
| | - Courtney DiNardo
- Department of Leukemia, MD Anderson Cancer Center, Houston, TX, USA
| | - Naval Daver
- Department of Leukemia, MD Anderson Cancer Center, Houston, TX, USA
| | - Gautam Borthakur
- Department of Leukemia, MD Anderson Cancer Center, Houston, TX, USA
| | - Elias Jabbour
- Department of Leukemia, MD Anderson Cancer Center, Houston, TX, USA
| | | | - Marina Konopleva
- Department of Leukemia, MD Anderson Cancer Center, Houston, TX, USA
| | - Farhad Ravandi
- Department of Leukemia, MD Anderson Cancer Center, Houston, TX, USA
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23
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Ma TT, Lin XJ, Cheng WY, Xue Q, Wang SY, Liu FJ, Yan H, Zhu YM, Shen Y. Development and validation of a prognostic model for adult patients with acute myeloid leukaemia. EBioMedicine 2020; 62:103126. [PMID: 33232873 PMCID: PMC7689519 DOI: 10.1016/j.ebiom.2020.103126] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 10/28/2020] [Accepted: 10/28/2020] [Indexed: 12/22/2022] Open
Abstract
Background The high heterogeneity of acute myeloid leukaemia (AML) reflected in the patient- and disease-related factors accounts for the unsatisfactory prognosis despite the introduction of novel therapeutic approaches and drugs in recent years. Methods In the development set (n = 412), parameters including age, hematopoietic cell transplantation-comorbidity index, white blood cell count, hemoglobin, biallelic CEBPA mutations, DNMT3A mutations, FLT3-ITD/NPM1 status, and ELN cytogenetic risk status were identified as independent prognostic factors for overall survival (OS) in the multivariable Cox regression analysis. A nomogram combining these predictors for individual risk estimation was established thereby. Findings The prognostic model demonstrated promising performance in the development cohort. The calibration plot, C-index (0.74), along with the 1-, 2- and 3-year area under the receiver operating characteristic curve (AUC, 0.76, 0.79, and 0.74, respectively) in the validation set (n = 238) substantiated the robustness of the model. In addition to stratifying young (age ≤ 60 years) and elderly patients (age > 60 years) into three and two risk groups with significant distinct outcomes, the prognostic model succeeded in distinguishing eligible candidates for hematopoietic stem cell transplantation. Interpretation The prognostic model is capable of survival prediction, risk stratification and helping with therapeutic decision-making with the use of easily acquired variables in daily clinical routine. Funding This work was supported in part by grants from the National Natural Science Foundation of China (81770141), the National Key R&D Program of China (2016YFE0202800), and Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (20161406).
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Affiliation(s)
- Ting-Ting Ma
- Shanghai Institute of Haematology, Department of Haematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai, China
| | - Xiao-Jing Lin
- Shanghai Institute of Haematology, Department of Haematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai, China
| | - Wen-Yan Cheng
- Shanghai Institute of Haematology, Department of Haematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai, China
| | - Qing Xue
- Shanghai Institute of Haematology, Department of Haematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai, China
| | - Shi-Yang Wang
- Shanghai Institute of Haematology, Department of Haematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai, China
| | - Fu-Jia Liu
- Shanghai Institute of Haematology, Department of Haematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai, China
| | - Han Yan
- Shanghai Institute of Haematology, Department of Haematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai, China
| | - Yong-Mei Zhu
- Shanghai Institute of Haematology, Department of Haematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai, China
| | - Yang Shen
- Shanghai Institute of Haematology, Department of Haematology, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai, China.
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24
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Burnett A, Stone R. AML: New Drugs but New Challenges. CLINICAL LYMPHOMA MYELOMA & LEUKEMIA 2020; 20:341-350. [DOI: 10.1016/j.clml.2020.02.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 01/30/2020] [Accepted: 02/05/2020] [Indexed: 12/20/2022]
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25
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Silveira DRA, Quek L, Santos IS, Corby A, Coelho-Silva JL, Pereira-Martins DA, Vallance G, Brown B, Nardinelli L, Silva WF, Velloso EDRP, Lucena-Araujo AR, Traina F, Peniket A, Vyas P, Rego EM, Bendit I, Rocha V. Integrating clinical features with genetic factors enhances survival prediction for adults with acute myeloid leukemia. Blood Adv 2020; 4:2339-2350. [PMID: 32453839 PMCID: PMC7252562 DOI: 10.1182/bloodadvances.2019001419] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Accepted: 04/15/2020] [Indexed: 12/18/2022] Open
Abstract
The 2017 European LeukemiaNet 2017 acute myeloid leukemia (AML) risk stratification (ELN2017) is widely used for risk-stratifying patients with AML. However, its applicability in low- and middle-income countries is limited because of a lack of full cytogenetic and molecular information at diagnosis. Here, we propose an alternative for risk stratification (the Adapted Genetic Risk [AGR]), which permits cytogenetic or molecular missing data while retaining prognostic power. We first analyzed 167 intensively treated patients with nonacute promyelocytic leukemia AML enrolled in São Paulo, Brazil (Faculdade de Medicina da Universidade de São Paulo), as our training data set, using ELN2017 as the standard for comparison with our AGR. Next, we combined our AGR with clinical prognostic parameters found in a Cox proportional hazards model to create a novel scoring system (survival AML score, SAMLS) that stratifies patients with newly diagnosed AML. Finally, we have used 2 independent test cohorts, Faculdade de Medicina de Ribeirão Preto (FMRP; Brazil, n = 145) and Oxford University Hospitals (OUH; United Kingdom, n = 157) for validating our findings. AGR was statistically significant for overall survival (OS) in both test cohorts (FMRP, P = .037; OUH, P = .012) and disease-free survival in FMRP (P = .04). The clinical prognostic features in SAMLS were age (>45 years), white blood cell count (<1.5 or >30.0 × 103/μL), and low albumin levels (<3.8 g/dL), which were associated with worse OS in all 3 cohorts. SAMLS showed a significant difference in OS in the training cohort (P < .001) and test cohorts (FMRP, P = .0018; OUH, P < .001). Therefore, SAMLS, which incorporates the novel AGR evaluation with clinical parameters, is an accurate tool for AML risk assessment.
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Affiliation(s)
- Douglas R A Silveira
- Service of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil
- Department of Hematology, AC Camargo Cancer Center, São Paulo, Brazil
| | - Lynn Quek
- Medical Research Council MHU, BRC Hematology Theme, Oxford Biomedical Research Center, Oxford Center for Hematology, WIMM, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
- Department of Hematology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Itamar S Santos
- Internal Medicine Department, Faculdade de Medicina, University of São Paulo, São Paulo, Brazil
| | - Anna Corby
- Medical Research Council MHU, BRC Hematology Theme, Oxford Biomedical Research Center, Oxford Center for Hematology, WIMM, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Juan L Coelho-Silva
- Department of Medical Images, Hematology and Clinical Oncology, University of São Paulo at Ribeirao Preto Medical School, Ribeirao Preto, Brazil
| | - Diego A Pereira-Martins
- Department of Medical Images, Hematology and Clinical Oncology, University of São Paulo at Ribeirao Preto Medical School, Ribeirao Preto, Brazil
| | - Grant Vallance
- Department of Hematology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Benjamin Brown
- Medical Research Council MHU, BRC Hematology Theme, Oxford Biomedical Research Center, Oxford Center for Hematology, WIMM, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Luciana Nardinelli
- Service of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil
| | - Wellington F Silva
- Leukemia Unit, Cancer Institute of São Paulo, University of São Paulo Medical School, São Paulo, Brazil; and
| | - Elvira D R P Velloso
- Service of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil
- Leukemia Unit, Cancer Institute of São Paulo, University of São Paulo Medical School, São Paulo, Brazil; and
| | | | - Fabiola Traina
- Department of Medical Images, Hematology and Clinical Oncology, University of São Paulo at Ribeirao Preto Medical School, Ribeirao Preto, Brazil
| | - Andy Peniket
- Department of Hematology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Paresh Vyas
- Medical Research Council MHU, BRC Hematology Theme, Oxford Biomedical Research Center, Oxford Center for Hematology, WIMM, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
- Department of Hematology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Eduardo M Rego
- Service of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil
- Leukemia Unit, Cancer Institute of São Paulo, University of São Paulo Medical School, São Paulo, Brazil; and
| | - Israel Bendit
- Service of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil
| | - Vanderson Rocha
- Service of Hematology, Transfusion and Cell Therapy and Laboratory of Medical Investigation in Pathogenesis and Directed Therapy in Onco-Immuno-Hematology, HCFMUSP, University of São Paulo Medical School, São Paulo, Brazil
- Department of Hematology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
- Leukemia Unit, Cancer Institute of São Paulo, University of São Paulo Medical School, São Paulo, Brazil; and
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Ayatollahi H, Bazi A, Sadeghian MH, Fani A, Siyadat P, Sheikhi M, Sargazi-Aval O. The Survival of Patients with t(15;17)(q22;q12) Positive Acute Promyelocytic Leukemia: A Study in North-East of Iran. IRANIAN JOURNAL OF PATHOLOGY 2020; 15:175-181. [PMID: 32754212 PMCID: PMC7354063 DOI: 10.30699/ijp.2020.101417.2007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Accepted: 04/09/2019] [Indexed: 11/06/2022]
Abstract
Background & Objective Acute promyelocytic leukemia (APL) with t(15;17)(q22;q12) is a relatively common subtype of acute myeloid leukemia (AML). Here, our objective was to ascertain the survival of patients with this leukemia in north-east of Iran. Methods Survival rates of 42 APL patients with t(15;17)(q22;q12) were assessed. Clinical information was obtained from archived medical records. Statistical analysis was performed by SPSS 18 software using log-ranked test and Kaplan Maier survival analysis. Results Females and males comprised 49% and 51%, respectively. The mean age at diagnosis was 34.3 ± 14.1 years old. During the study period, 17 demises occurred in males, while this number was 7 in females. The mean survival of patients (month) was 23.22 ± 3.57 (95% CI: 16.21 ± 30.2). The five-year survival rate obtained 30%. Regarding demographic and clinical features, the highest rates of 5-year survival were recorded in patients with 20-35 years old (47.6%), males (51%), white blood cell count <10 × 10 9 /l (48%), and platelet count >140 × 10 9 /l (100%). Conclusion Younger age, lower WBC count and higher platelet count were significantly associated with longer survival in AML patients with t(15;17)(q22; q12).
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Affiliation(s)
- Hossein Ayatollahi
- Cancer Molecular Pathology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Ali Bazi
- Clinical Research Development Unit, Amir-Al-Momenin Hospital, Zabol University of Medical Sciences, Zabol, Iran
| | - Mohammad Hadi Sadeghian
- Cancer Molecular Pathology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Ali Fani
- Cancer Molecular Pathology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Payam Siyadat
- Department of Hematology, School of Allied Medical Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Maryam Sheikhi
- Cancer Molecular Pathology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Omolbanin Sargazi-Aval
- Cancer Molecular Pathology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.,Department of Hematology, Faculty of Allied Medical Sciences, Zabol University of Medical Sciences, Zabol, Iran
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Validation and refinement of the revised 2017 European LeukemiaNet genetic risk stratification of acute myeloid leukemia. Leukemia 2020; 34:3161-3172. [PMID: 32231256 PMCID: PMC7685975 DOI: 10.1038/s41375-020-0806-0] [Citation(s) in RCA: 115] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 03/10/2020] [Accepted: 03/13/2020] [Indexed: 12/17/2022]
Abstract
The revised 2017 European LeukemiaNet (ELN) recommendations for genetic risk stratification of acute myeloid leukemia have been widely adopted, but have not yet been validated in large cohorts of AML patients. We studied 1116 newly diagnosed AML patients (age range, 18–86 years) who had received induction chemotherapy. Among 771 patients not selected by genetics, the ELN-2017 classification re-assigned 26.5% of patients into a more favorable or, more commonly, a more adverse-risk group compared with the ELN-2010 recommendations. Forty percent of the cohort, and 51% of patients ≥60 years, were classified as adverse-risk by ELN-2017. In 599 patients <60 years, estimated 5-year overall survival (OS) was 64% for ELN-2017 favorable, 42% for intermediate-risk and 20% for adverse-risk patients. Among 517 patients aged ≥60 years, corresponding 5-year OS rates were 37, 16, and 6%. Patients with biallelic CEBPA mutations or inv(16) had particularly favorable outcomes, while patients with mutated TP53 and a complex karyotype had especially poor prognosis. DNMT3A mutations associated with inferior OS within each ELN-2017 risk group. Our results validate the prognostic significance of the revised ELN-2017 risk classification in AML patients receiving induction chemotherapy across a broad age range. Further refinement of the ELN-2017 risk classification is possible.
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Liu CJ, Hong YC, Kuan AS, Yeh CM, Tsai CK, Liu YC, Hsiao LT, Wang HY, Ko PS, Chen PM, Liu JH, Gau JP. The risk of early mortality in elderly patients with newly diagnosed acute myeloid leukemia. Cancer Med 2020; 9:1572-1580. [PMID: 31902138 PMCID: PMC7013048 DOI: 10.1002/cam4.2740] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 11/01/2019] [Accepted: 11/17/2019] [Indexed: 12/17/2022] Open
Abstract
Background Acute myeloid leukemia (AML) is a common hematologic neoplasm with high incidence and mortality in the elderly. Our aims were to explore risk factors for early mortality in elderly AML patients and develop a new prognostic score. Methods We enrolled newly diagnosed AML patients age 60 and above at Taipei Veterans General Hospital between July 2008 and May 2017. The primary endpoint was early mortality, defined as death within two months after AML diagnosis. A multivariate Cox proportional hazards model was used to build a risk‐scoring system incorporating significant risk factors for AML. Results The final cohort included 277 elderly AML patients. The median age was 74 (range 60‐96), and 61.7% were male. The two‐month mortality rate was 29.9%. Age ≥ 80 (adjusted HR 1.88), myocardial infarction (adjusted HR 1.87), ECOG ≥ 2 (adjusted HR 2.10), complex karyotype (adjusted HR 3.21), bone marrow blasts ≥ 70% (adjusted HR 1.88), WBC ≥ 100 × 109/L (adjusted HR 3.31), and estimated glomerular filtration rate (eGFR) < 45 (adjusted HR 2.60) were identified as independent predictors for early mortality in the multivariate analysis. A simplified score incorporating the seven factors was developed with good predictive ability measured by Harrell's C statistic [0.72 (95% CI 0.66‐0.78)]. Conclusions We identified seven potential risk factors for early mortality and built up a new prognostic score for elderly AML patients. The new score may help clinicians stratify patients and initiate appropriate management. Further validation of our findings on other cohorts is warranted.
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Affiliation(s)
- Chia-Jen Liu
- Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Public Health, National Yang-Ming University, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Ying-Chung Hong
- School of Medicine, National Yang-Ming University, Taipei, Taiwan.,Division of Hematology and Oncology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - Ai Seon Kuan
- Institute of Public Health, National Yang-Ming University, Taipei, Taiwan.,Division of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chiu-Mei Yeh
- Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Public Health, National Yang-Ming University, Taipei, Taiwan
| | - Chun-Kuang Tsai
- Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yao-Chung Liu
- Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Liang-Tsai Hsiao
- Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Hao-Yuan Wang
- Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Po-Shen Ko
- Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Po-Min Chen
- Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Jin-Hwang Liu
- Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Biopharmaceutical Sciences, National Yang-Ming University, Taipei, Taiwan.,Chong Hin Loon Memorial Cancer and Biotherapy Research Center, National Yang-Ming University, Taipei, Taiwan
| | - Jyh-Pyng Gau
- Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
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Comprehensive prognostic scoring systems could improve the prognosis of adult acute myeloid leukemia patients. Int J Hematol 2019; 110:575-583. [PMID: 31440963 DOI: 10.1007/s12185-019-02721-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 08/06/2019] [Accepted: 08/06/2019] [Indexed: 12/17/2022]
Abstract
Acute myeloid leukemia (AML) is a heterogeneous malignancy characterized by a dismal outcome. To enable better outcomes, it is necessary to develop individual therapies based on risk stratification. In the present study, we established two new comprehensive prognostic scoring systems (CPSS) for overall survival (OS) and relapse-free survival (RFS) using the Cox proportional hazards regression, CPSS integrated and weighted age, AML type, lactic dehydrogenase (LDH), ECOG score, cytogenetics, and gene mutations. We divided patients into three risk groups-low-, intermediate-, and high-risk-with 1-year OS rates of 100.0%, 82.9%, and 38.2%, respectively (p < 0.0001), and patients undergoing complete remission (CR) were also separated into low-risk, intermediate-risk, and high-risk groups, with 1-year RFS rates of 87.7%, 58.4%, and 30.2%, respectively (p < 0.0001). We conclude that CPSS that integrate clinical characteristics, cytogenetic abnormalities, and gene mutations may improve the stratification of AML patients.
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Kobayashi H, Lei C, Wu Y, Huang CJ, Yasumoto A, Jona M, Li W, Wu Y, Yalikun Y, Jiang Y, Guo B, Sun CW, Tanaka Y, Yamada M, Yatomi Y, Goda K. Intelligent whole-blood imaging flow cytometry for simple, rapid, and cost-effective drug-susceptibility testing of leukemia. LAB ON A CHIP 2019; 19:2688-2698. [PMID: 31287108 DOI: 10.1039/c8lc01370e] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Drug susceptibility (also called chemosensitivity) is an important criterion for developing a therapeutic strategy for various cancer types such as breast cancer and leukemia. Recently, functional assays such as high-content screening together with genomic analysis have been shown to be effective for predicting drug susceptibility, but their clinical applicability is poor since they are time-consuming (several days long), labor-intensive, and costly. Here we present a highly simple, rapid, and cost-effective liquid biopsy for ex vivo drug-susceptibility testing of leukemia. The method is based on an extreme-throughput (>1 million cells per second), label-free, whole-blood imaging flow cytometer with a deep convolutional autoencoder, enabling image-based identification of the drug susceptibility of every single white blood cell in whole blood within 24 hours by simply flowing a drug-treated whole blood sample as little as 500 μL into the imaging flow cytometer without labeling. Our results show that the method accurately evaluates the drug susceptibility of white blood cells from untreated patients with acute lymphoblastic leukemia. Our method holds promise for affordable precision medicine.
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Combining gene mutation with gene expression analysis improves outcome prediction in acute promyelocytic leukemia. Blood 2019; 134:951-959. [PMID: 31292112 DOI: 10.1182/blood.2019000239] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Accepted: 05/23/2019] [Indexed: 12/15/2022] Open
Abstract
By combining the analysis of mutations with aberrant expression of genes previously related to poorer prognosis in both acute promyelocytic leukemia (APL) and acute myeloid leukemia, we arrived at an integrative score in APL (ISAPL) and demonstrated its relationship with clinical outcomes of patients treated with all-trans retinoic acid (ATRA) in combination with anthracycline-based chemotherapy. Based on fms-like tyrosine kinase-3-internal tandem duplication mutational status; the ΔNp73/TAp73 expression ratio; and ID1, BAALC, ERG, and KMT2E gene expression levels, we modeled ISAPL in 159 patients (median ISAPL score, 3; range, 0-10). ISAPL modeling identified 2 distinct groups of patients, with significant differences in early mortality (P < .001), remission (P = .004), overall survival (P < .001), cumulative incidence of relapse (P = .028), disease-free survival (P = .03), and event-free survival (P < .001). These data were internally validated by using a bootstrap resampling procedure. At least for patients treated with ATRA and anthracycline-based chemotherapy, ISAPL modeling may identify those who need to be treated differently to maximize their chances for a cure.
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Keiffer G, Palmisiano N. Acute Myeloid Leukemia: Update on Upfront Therapy in Elderly Patients. Curr Oncol Rep 2019; 21:71. [DOI: 10.1007/s11912-019-0823-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Next Generation Sequencing in AML-On the Way to Becoming a New Standard for Treatment Initiation and/or Modulation? Cancers (Basel) 2019; 11:cancers11020252. [PMID: 30795628 PMCID: PMC6406956 DOI: 10.3390/cancers11020252] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 02/08/2019] [Accepted: 02/12/2019] [Indexed: 12/19/2022] Open
Abstract
Acute myeloid leukemia (AML) is a clonal disease caused by genetic abberations occurring predominantly in the elderly. Next generation sequencing (NGS) analysis has led to a deeper genetic understanding of the pathogenesis and the role of recently discovered genetic precursor lesions (clonal hematopoiesis of indeterminate/oncogenic potential (CHIP/CHOP)) in the evolution of AML. These advances are reflected by the inclusion of certain mutations in the updated World Health Organization (WHO) 2016 classification and current treatment guidelines by the European Leukemia Net (ELN) and National Comprehensive Cancer Network (NCCN) and results of mutational testing are already influencing the choice and timing of (targeted) treatment. Genetic profiling and stratification of patients into molecularly defined subgroups are expected to gain ever more weight in daily clinical practice. Our aim is to provide a concise summary of current evidence regarding the relevance of NGS for the diagnosis, risk stratification, treatment planning and response assessment in AML, including minimal residual disease (MRD) guided approaches. We also summarize recently approved drugs targeting genetically defined patient populations with risk adapted- and individualized treatment strategies.
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Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data. BMC Bioinformatics 2018; 19:322. [PMID: 30208855 PMCID: PMC6134797 DOI: 10.1186/s12859-018-2344-6] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Accepted: 08/29/2018] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The inclusion of high-dimensional omics data in prediction models has become a well-studied topic in the last decades. Although most of these methods do not account for possibly different types of variables in the set of covariates available in the same dataset, there are many such scenarios where the variables can be structured in blocks of different types, e.g., clinical, transcriptomic, and methylation data. To date, there exist a few computationally intensive approaches that make use of block structures of this kind. RESULTS In this paper we present priority-Lasso, an intuitive and practical analysis strategy for building prediction models based on Lasso that takes such block structures into account. It requires the definition of a priority order of blocks of data. Lasso models are calculated successively for every block and the fitted values of every step are included as an offset in the fit of the next step. We apply priority-Lasso in different settings on an acute myeloid leukemia (AML) dataset consisting of clinical variables, cytogenetics, gene mutations and expression variables, and compare its performance on an independent validation dataset to the performance of standard Lasso models. CONCLUSION The results show that priority-Lasso is able to keep pace with Lasso in terms of prediction accuracy. Variables of blocks with higher priorities are favored over variables of blocks with lower priority, which results in easily usable and transportable models for clinical practice.
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Chen P, Zhu KW, Zhang DY, Yan H, Liu H, Liu YL, Cao S, Zhou G, Zeng H, Chen SP, Zhao XL, Yang J, Chen XP. Influence of UGT1A1 polymorphisms on the outcome of acute myeloid leukemia patients treated with cytarabine-base regimens. J Transl Med 2018; 16:197. [PMID: 30016963 PMCID: PMC6050722 DOI: 10.1186/s12967-018-1579-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 07/13/2018] [Indexed: 12/18/2022] Open
Abstract
BACKGROUNDS UDP-glucuronosyltransferase 1A subfamily (UGT1A) enzymes can inactivate cytarabine (Ara-C) by glucuronidation, and thus serves as candidate genes for interindividual difference in Ara-C response. UGT1A1 is a major UGT1A isoform expressed in human liver. METHODS UGT1A1*6 and *28 polymorphisms resulting in reduced UGT1A1 activity were genotyped in 726 adult acute myeloid leukemia (AML) patients treated with Ara-C based regimens. Influences of both polymorphisms on chemosensitivity and disease prognosis of the patients were evaluated. RESULTS After one or two courses of Ara-C based induction chemotherapy, the complete remission (CR) rate was significantly higher in patients carrying the UGT1A1*6 (77.0%) or the UGT1A1*28 (76.4%) alleles as compared with corresponding wild-type homozygotes (66.9 and 68.5%, respectively). Carriers of the UGT1A1*6 or *28 alleles showed significantly decreased risk of non-CR (OR = 0.528, 95% CI 0.379-0.737, P = 1.7 × 10-4) and better overall survival (HR = 0.787, 95% CI 0.627-0.990, P = 0.040) as compared with homozygotes for both polymorphisms. CONCLUSION Our results suggest that UGT1A1*28 and UGT1A1*6 are associated with improved clinical outcomes in Chinese AML patients treated with Ara-C.
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Affiliation(s)
- Peng Chen
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha, 410078, Hunan, People's Republic of China
| | - Ke-Wei Zhu
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha, 410078, Hunan, People's Republic of China
| | - Dao-Yu Zhang
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha, 410078, Hunan, People's Republic of China
| | - Han Yan
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha, 410078, Hunan, People's Republic of China
| | - Han Liu
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha, 410078, Hunan, People's Republic of China
| | - Yan-Ling Liu
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha, 410078, Hunan, People's Republic of China
| | - Shan Cao
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha, 410078, Hunan, People's Republic of China
| | - Gan Zhou
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha, 410078, Hunan, People's Republic of China
| | - Hui Zeng
- Department of Hematology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
| | - Shu-Ping Chen
- Department of Hematology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
| | - Xie-Lan Zhao
- Department of Hematology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China
| | - Jing Yang
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, People's Republic of China
| | - Xiao-Ping Chen
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China. .,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha, 410078, Hunan, People's Republic of China. .,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.
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Clinical Significance of Serum Ferritin at Diagnosis in Patients With Acute Myeloid Leukemia: A YACHT Multicenter Retrospective Study. CLINICAL LYMPHOMA MYELOMA & LEUKEMIA 2018; 18:415-421. [DOI: 10.1016/j.clml.2018.03.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Revised: 03/22/2018] [Accepted: 03/27/2018] [Indexed: 11/19/2022]
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Michaelis LC, Klepin HD, Walter RB. Advancements in the management of medically less-fit and older adults with newly diagnosed acute myeloid leukemia. Expert Opin Pharmacother 2018; 19:865-882. [PMID: 29697000 DOI: 10.1080/14656566.2018.1465562] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
INTRODUCTION Treating acute myeloid leukemia (AML) in older adults remains daunting. The unique biology often renders conventional chemotherapies less effective. Accurately predicting the toxicities of treatment is another unresolved challenge. Treatment planning thus requires a good knowledge of the current trial data and familiarity with clinical tools, including formal fitness and geriatric assessments. Both obstacles - disease biology and patient fitness - might be easier overcome with specific, AML cell-targeted agents rather than traditional cytotoxic chemotherapy. This may be the future of AML therapy, but it is not our current state. AREAS COVERED Herein, the authors appraise the data supporting a standard induction approach, including an outline of how to predict treatment-related mortality and a review of the most up-to-date methods of geriatric assessment. They also discuss treatment expectations with less-intense therapies and highlight novel agents in development. Finally, they provide a basic approach to choosing treatment intensity. EXPERT OPINION In an older and/or medically less-fit patient, treatment choice should begin with a thorough disease assessment, a formal evaluation of patient fitness and frailty. There should also be a clear communication with the patient and patient's family about the risks and anticipated benefits of either an intense or nonintense treatment approach.
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Affiliation(s)
- Laura C Michaelis
- a Associate Professor of Medicine, Department of Hematology and Oncology , Medical College of Wisconsin , Milwaukee , WI , USA
| | - Heidi D Klepin
- b Associate Professor of Internal Medicine, Section on Hematology and Oncology , Wake Forest School of Medicine , Winston-Salem , NC , USA
| | - Roland B Walter
- c Associate Member, Clinical Research Division , Fred Hutchinson Cancer Research Center , Seattle , WA , USA.,d Associate Professor of Medicine, Department of Medicine, Division of Hematology , University of Washington , Seattle , WA , USA.,e Adjunct Associate Professor, Department of Epidemiology , University of Washington , Seattle , WA , USA
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Chen J, Yang L, Fan Y, Xu Y, Han Y, Tang X, Qiu H, Fu C, Miao M, Chen F, Wu D. Comparison of Autologous Stem Cell Transplantation versus Haploidentical Donor Stem Cell Transplantation for Favorable- and Intermediate-Risk Acute Myeloid Leukemia Patients in First Complete Remission. Biol Blood Marrow Transplant 2018; 24:779-788. [DOI: 10.1016/j.bbmt.2017.12.796] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Accepted: 12/18/2017] [Indexed: 01/03/2023]
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Snijder B, Vladimer GI, Krall N, Miura K, Schmolke AS, Kornauth C, Lopez de la Fuente O, Choi HS, van der Kouwe E, Gültekin S, Kazianka L, Bigenzahn JW, Hoermann G, Prutsch N, Merkel O, Ringler A, Sabler M, Jeryczynski G, Mayerhoefer ME, Simonitsch-Klupp I, Ocko K, Felberbauer F, Müllauer L, Prager GW, Korkmaz B, Kenner L, Sperr WR, Kralovics R, Gisslinger H, Valent P, Kubicek S, Jäger U, Staber PB, Superti-Furga G. Image-based ex-vivo drug screening for patients with aggressive haematological malignancies: interim results from a single-arm, open-label, pilot study. LANCET HAEMATOLOGY 2017; 4:e595-e606. [PMID: 29153976 PMCID: PMC5719985 DOI: 10.1016/s2352-3026(17)30208-9] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Revised: 10/13/2017] [Accepted: 10/16/2017] [Indexed: 02/07/2023]
Abstract
Background Patients with refractory or relapsed haematological malignancies have few treatment options and short survival times. Identification of effective therapies with genomic-based precision medicine is hampered by intratumour heterogeneity and incomplete understanding of the contribution of various mutations within specific cancer phenotypes. Ex-vivo drug-response profiling in patient biopsies might aid effective treatment identification; however, proof of its clinical utility is limited. Methods We investigated the feasibility and clinical impact of multiparametric, single-cell, drug-response profiling in patient biopsies by immunofluorescence, automated microscopy, and image analysis, an approach we call pharmacoscopy. First, the ability of pharmacoscopy to separate responders from non-responders was evaluated retrospectively for a cohort of 20 newly diagnosed and previously untreated patients with acute myeloid leukaemia. Next, 48 patients with aggressive haematological malignancies were prospectively evaluated for pharmacoscopy-guided treatment, of whom 17 could receive the treatment. The primary endpoint was progression-free survival in pharmacoscopy-treated patients, as compared with their own progression-free survival for the most recent regimen on which they had progressive disease. This trial is ongoing and registered with ClinicalTrials.gov, number NCT03096821. Findings Pharmacoscopy retrospectively predicted the clinical response of 20 acute myeloid leukaemia patients to initial therapy with 88·1% accuracy. In this interim analysis, 15 (88%) of 17 patients receiving pharmacoscopy-guided treatment had an overall response compared with four (24%) of 17 patients with their most recent regimen (odds ratio 24·38 [95% CI 3·99–125·4], p=0·0013). 12 (71%) of 17 patients had a progression-free survival ratio of 1·3 or higher, and median progression-free survival increased by four times, from 5·7 (95% CI 4·1–12·1) weeks to 22·6 (7·4–34·0) weeks (hazard ratio 3·14 [95% CI 1·37–7·22], p=0·0075). Interpretation Routine clinical integration of pharmacoscopy for treatment selection is technically feasible, and led to improved treatment of patients with aggressive refractory haematological malignancies in an initial patient cohort, warranting further investigation. Funding Austrian Academy of Sciences; European Research Council; Austrian Science Fund; Austrian Federal Ministry of Science, Research and Economy; National Foundation for Research, Technology and Development; Anniversary Fund of the Austrian National Bank; MPN Research Foundation; European Molecular Biology Organization; and Swiss National Science Foundation.
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Affiliation(s)
- Berend Snijder
- CeMM Research Center for Molecular Medicine, Vienna, Austria; Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Gregory I Vladimer
- CeMM Research Center for Molecular Medicine, Vienna, Austria; Allcyte, Vienna, Austria
| | - Nikolaus Krall
- CeMM Research Center for Molecular Medicine, Vienna, Austria
| | - Katsuhiro Miura
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
| | - Ann-Sofie Schmolke
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
| | - Christoph Kornauth
- Clinical Institute of Pathology, Medical University of Vienna, Vienna, Austria
| | | | - Hye-Soo Choi
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
| | - Emiel van der Kouwe
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
| | - Sinan Gültekin
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
| | - Lukas Kazianka
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
| | | | - Gregor Hoermann
- Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria
| | - Nicole Prutsch
- Clinical Institute of Pathology, Medical University of Vienna, Vienna, Austria
| | - Olaf Merkel
- Clinical Institute of Pathology, Medical University of Vienna, Vienna, Austria
| | - Anna Ringler
- CeMM Research Center for Molecular Medicine, Vienna, Austria; Christian Doppler Laboratory for Chemical Epigenetics and Anti-Infectives, Vienna, Austria
| | - Monika Sabler
- CeMM Research Center for Molecular Medicine, Vienna, Austria
| | - Georg Jeryczynski
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
| | - Marius E Mayerhoefer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | | | - Katharina Ocko
- Pharmacy Department, Vienna General Hospital, Vienna, Austria
| | - Franz Felberbauer
- Division of General Surgery, Department of Surgery, Medical University of Vienna, Vienna, Austria
| | - Leonhard Müllauer
- Clinical Institute of Pathology, Medical University of Vienna, Vienna, Austria
| | - Gerald W Prager
- Department of Internal Medicine I, Division of Oncology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Belgin Korkmaz
- Division of General Surgery, Department of Surgery, Medical University of Vienna, Vienna, Austria
| | - Lukas Kenner
- Clinical Institute of Pathology, Medical University of Vienna, Vienna, Austria; Ludwig Boltzmann Institute for Cancer Research, Vienna, Austria; Unit of Laboratory Animal Pathology, University of Veterinary Medicine, Vienna, Austria
| | - Wolfgang R Sperr
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria; Ludwig Boltzmann Institute for Cancer Research, Vienna, Austria
| | | | - Heinz Gisslinger
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
| | - Peter Valent
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria; Ludwig Boltzmann Cluster Oncology, Medical University of Vienna, Vienna, Austria
| | - Stefan Kubicek
- CeMM Research Center for Molecular Medicine, Vienna, Austria; Christian Doppler Laboratory for Chemical Epigenetics and Anti-Infectives, Vienna, Austria
| | - Ulrich Jäger
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
| | - Philipp B Staber
- Department of Internal Medicine I, Division of Hematology and Hemostaseology, Medical University of Vienna, Vienna, Austria
| | - Giulio Superti-Furga
- CeMM Research Center for Molecular Medicine, Vienna, Austria; Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria.
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Xu L, Zhang M, Li H, Guan W, Liu B, Liu F, Wang H, Li J, Yang S, Tong X, Wang H. SH3BGRL as a novel prognostic biomarker is down-regulated in acute myeloid leukemia. Leuk Lymphoma 2017; 59:918-930. [PMID: 28679293 DOI: 10.1080/10428194.2017.1344843] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
- Limei Xu
- Department of Hematology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Mingming Zhang
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Hui Li
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Wen Guan
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Bin Liu
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Fengqi Liu
- Department of Hematology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Hehua Wang
- Department of Hematology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Juan Li
- Department of Hematology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Shulan Yang
- Centre for Translational Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiuzhen Tong
- Department of Hematology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Haihe Wang
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory of Ministry of Education, Sun Yat-sen University, Guangzhou, China
- Guangdong Engineering and Technology Research Center for Disease-Model Animals, Sun Yat-sen University, Guangzhou, China
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41
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Patterns of Care and Survival for Elderly Acute Myeloid Leukemia—Challenges and Opportunities. Curr Hematol Malig Rep 2017; 12:290-299. [DOI: 10.1007/s11899-017-0388-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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42
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Abstract
Myelodysplastic syndrome (MDS) is a heterogeneous, clonal stem cell disorder of the blood and marrow typically diagnosed based on the presence of persistent cytopenia(s), dysplastic cells, and genetic markers. Common issues that arise in the clinical management include difficulty confirming MDS diagnosis, lack of a standard approach with novel agents in MDS, and few prospective long-term, randomized controlled MDS clinical studies to guide allogeneic blood and marrow transplant. With the recent genetic characterization of MDS, certain aspects of these issues will be better addressed by integrating genetic data into clinical study design and clinical practice.
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Affiliation(s)
- Kim-Hien T Dao
- Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health & Science University, Mail Code: UHN73C, 3181 South West Sam Jackson Park Road, Portland, OR 97239, USA.
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Gorin NC, Labopin M, Czerw T, Pabst T, Blaise D, Dumas PY, Nemet D, Arcese W, Trisolini SM, Wu D, Huynh A, Zuckerman T, Meijer E, Cagirgan S, Cornelissen J, Houhou M, Polge E, Mohty M, Nagler A. Autologous stem cell transplantation for adult acute myelocytic leukemia in first remission-Better outcomes after busulfan and melphalan compared with busulfan and cyclophosphamide: A retrospective study from the Acute Leukemia Working Party of the European Society for Blood and Marrow Transplantation (EBMT). Cancer 2016; 123:824-831. [PMID: 27906458 DOI: 10.1002/cncr.30400] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 08/24/2016] [Indexed: 11/11/2022]
Abstract
BACKGROUND Autologous stem cell transplantation (ASCT) for adult acute myelogenous leukemia (AML) is a valid therapeutic option for patients with good-risk and intermediate-risk disease. The authors used the registry of the European Society for Blood and Marrow Transplantation to compare combined busulfan and melphalan (BUMEL) with combined busulfan and cyclophosphamide (BUCY) before transplantation. METHODS From 2005 to 2013, 853 patients with available cytogenetics underwent ASCT in first remission, including 257 after receiving BUMEL and 596 after receiving BUCY. The proportion of patients with good-risk AML was lower in those who received BUMEL (14% vs 20%; P = .02). More patients who received BUMEL underwent autograft in molecular remission (89% vs 78%; P = .02). Three years after transplantation, the relapse incidence (RI) was 48.7%, the leukemia-free survival (LFS) rate was 47.7%, the overall survival (OS) rate was 66.2%, and the nonrelapse mortality (NRM) rate was 3.6%. RESULTS Patients who underwent an autograft after receiving BUMEL fared better than those who underwent an autograft after receiving BUCY with a lower RI (39.5% vs 52.2%; hazard ratio [HR], 0.65; 95% confidence interval [CI], 0.49-0.87; P = .003) a better LFS (55.4% vs 44.6%; HR, 0.69; 95% CI, 0.53-0.89; P = .005), and a better OS (73.8% vs 63%; HR, 0.62; 95% CI, 0.47-0.82; P = .0007). There was no difference in the NRM rate (BUMEL vs BUCY, 4.5% vs 3.2%, respectively). Among 74 patients in the BUMEL group and 187 in the BUCY group who underwent autograft in molecular remission, the RI was 30% versus 51%, respectively (univariate analysis; P = .01), and the LFS rate was 66% versus 47%, respectively (univariate analysis; P = .03). CONCLUSIONS In patients with AML in first complete remission who undergo ASCT, the BUMEL combination is a better preparative regimen. Cancer 2017;123:824-31. © 2016 American Cancer Society.
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Affiliation(s)
- Norbert-Claude Gorin
- Department of Hematology and Cellular Therapy, European Society for Blood and Marrow Transplantation (EBMT), National Institute of Health and Medical Research (INSERM) Unit 938, St. Antoine Public Assistance Hospital, Pierre and Marie Curie University, Paris, France.,EBMT Office, INSERM Unit 938, St. Antoine Public Assistance Hospital, Pierre and Marie Curie University, Paris, France
| | - Myriam Labopin
- EBMT Office, INSERM Unit 938, St. Antoine Public Assistance Hospital, Pierre and Marie Curie University, Paris, France
| | - Tomasz Czerw
- Department of Bone Marrow Transplantation and Oncohematology, Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice, Poland
| | - Thomas Pabst
- Department of Oncology, University Hospital Bern, Bern, Switzerland
| | - Didier Blaise
- Aix Marseille University, CNRS, INSERM, CRCM, Institut Paoli-calmettes, Marseille, France
| | - Pierre-Yves Dumas
- Department of Hematology, Haut-Leveque Hospital, University Hospital Center of Bordeaux, Pessac, France
| | - Damir Nemet
- Department of Hematology, University Hospital Center Rebro, Zagreb, Croatia
| | - William Arcese
- Stem Cell Transplant Unit, Rome Transplant Network, Tor Vergata University Polyclinic, Tor Vergata University, Rome, Italy
| | - Silvia Maria Trisolini
- Department of Cellular Biotechnology and Hematology, Louisiana Sapienza University, Rome, Italy
| | - Depei Wu
- Department of Hematology, First Affiliated Hospital of Soochow University, Suzhou Jiangsu, China
| | - Anne Huynh
- The Cancer University Institute of Toulouse Oncopole, Toulouse, France
| | - Tsila Zuckerman
- Department of Hematology and Bone Marrow Transplantation, Rambam Medical Center, Haifa, Israel.,Technion-Israel Institute of Technology, Haifa, Israel
| | - Ellen Meijer
- Department of Hematology, Free University Medical Center, Amsterdam, the Netherlands
| | - Seckin Cagirgan
- Department of Hematology, Ege University Medical School, Izmir, Turkey
| | - Jan Cornelissen
- Daniel den Hoed Cancer Center, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Mohamed Houhou
- Department of Hematology and Cellular Therapy, European Society for Blood and Marrow Transplantation (EBMT), National Institute of Health and Medical Research (INSERM) Unit 938, St. Antoine Public Assistance Hospital, Pierre and Marie Curie University, Paris, France
| | - Emmanuelle Polge
- Department of Hematology and Cellular Therapy, European Society for Blood and Marrow Transplantation (EBMT), National Institute of Health and Medical Research (INSERM) Unit 938, St. Antoine Public Assistance Hospital, Pierre and Marie Curie University, Paris, France
| | - Mohamad Mohty
- Department of Hematology and Cellular Therapy, European Society for Blood and Marrow Transplantation (EBMT), National Institute of Health and Medical Research (INSERM) Unit 938, St. Antoine Public Assistance Hospital, Pierre and Marie Curie University, Paris, France
| | - Arnon Nagler
- EBMT Office, INSERM Unit 938, St. Antoine Public Assistance Hospital, Pierre and Marie Curie University, Paris, France.,Department of Hematology and Bone Marrow Transplantation, Chaim Sheba Medical Center, Tel Hashomer, Israel
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44
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Inhibition of FLT3 in AML: a focus on sorafenib. Bone Marrow Transplant 2016; 52:344-351. [PMID: 27775694 DOI: 10.1038/bmt.2016.251] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2016] [Revised: 08/16/2016] [Accepted: 08/17/2016] [Indexed: 11/08/2022]
Abstract
FMS-like tyrosine kinase 3 (FLT3) is one of the most commonly mutated genes in AML. FLT3 is mutated in ~30% of patients with AML, either by internal tandem duplications (FLT3-ITD) of the juxta-membrane domain or by a point mutation, usually involving the tyrosine kinase domain. Several FLT3 tyrosine kinase inhibitors are being evaluated in multiple studies aiming at improving outcomes. The most widely used is sorafenib, a potent multikinase inhibitor approved for hepatocellular carcinoma and renal cell carcinoma. Sorafenib monotherapy or in combination with conventional chemotherapy, has been evaluated in various settings in AML, including front-line, relapsed or refractory disease including post-allograft failures and, more recently, as post-transplant maintenance therapy. Encouraging data have emerged with several other agents like lestaurtinib, midostaurin, crenolanib, gilteritinib and quizartinib. Although transient responses to FLT3 inhibitors are often observed in case of disease relapse, the most promising approach is the use of FLT3 inhibitors either in combination with induction chemotherapy or as consolidation/maintenance therapy after allogeneic hematopoietic cell transplantation. In this review, we summarize the clinical data on sorafenib and other FLT3 inhibitors in AML.
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Podoltsev NA, Stahl M, Zeidan AM, Gore SD. Selecting initial treatment of acute myeloid leukaemia in older adults. Blood Rev 2016; 31:43-62. [PMID: 27745715 DOI: 10.1016/j.blre.2016.09.005] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2015] [Revised: 08/05/2016] [Accepted: 09/30/2016] [Indexed: 11/30/2022]
Abstract
More than half of the patients with acute myeloid leukaemia (AML) are older than 60years. The treatment outcomes in this group remain poor with a median overall survival of <1year. Selecting initial treatment for these patients involves an assessment of 'fitness' for induction chemotherapy. This is done based on patient and disease-related characteristics which help to estimate treatment-related mortality and chance of complete remission with induction chemotherapy. If the risk of treatment-related mortality is high and/or the likelihood of a patient achieving a complete remission is low, lower-intensity treatment (low-dose cytarabine, decitabine and azacitidine) should be discussed. As outcomes in both groups of patients remain poor, enrolment into clinical trials of novel agents with varying mechanisms of action should be considered for all older adults with AML. Novel agents in Phase III development include CPX-351, guadecitabine (SGI-110), quizartinib, crenolanib, sapacitabine, vosaroxin and volasertib.
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Affiliation(s)
- Nikolai A Podoltsev
- Department of Internal Medicine, Hematology Section, Yale University School of Medicine, New Haven, CT, USA.
| | - Maximilian Stahl
- Yale Traditional Internal Medicine Program, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA.
| | - Amer M Zeidan
- Department of Internal Medicine, Hematology Section, Yale University School of Medicine, New Haven, CT, USA.
| | - Steven D Gore
- Department of Internal Medicine, Hematology Section, Yale University School of Medicine, New Haven, CT, USA.
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Wilop S, Chou WC, Jost E, Crysandt M, Panse J, Chuang MK, Brümmendorf TH, Wagner W, Tien HF, Kharabi Masouleh B. A three-gene expression-based risk score can refine the European LeukemiaNet AML classification. J Hematol Oncol 2016; 9:78. [PMID: 27585840 PMCID: PMC5009640 DOI: 10.1186/s13045-016-0308-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Accepted: 08/24/2016] [Indexed: 12/18/2022] Open
Abstract
Background Risk stratification based on cytogenetics of acute myeloid leukemia (AML) remains imprecise. The introduction of novel genetic and epigenetic markers has helped to close this gap and increased the specificity of risk stratification, although most studies have been conducted in specific AML subpopulations. In order to overcome this limitation, we used a genome-wide approach in multiple AML populations to develop a robust prediction model for AML survival. Methods We conducted a genome-wide expression analysis of two data sets from AML patients enrolled into the AMLCG-1999 trial and from the Tumor Cancer Genome Atlas (TCGA) to develop a prognostic score to refine current risk classification and performed a validation on two data sets of the National Taiwan University Hospital (NTUH) and an independent AMLCG cohort. Results In our training set, using a stringent multi-step approach, we identified a small three-gene prognostic scoring system, named Tri-AML score (TriAS) which highly correlated with overall survival (OS). Multivariate analysis revealed TriAS to be an independent prognostic factor in all tested training and additional validation sets, even including age, current cytogenetic-based risk stratification, and three other recently developed expression-based scoring models for AML. Conclusions The Tri-AML score allows robust and clinically practical risk stratification for the outcome of AML patients. TriAS substantially refined current ELN risk stratification assigning 44.5 % of the patients into a different risk category. Electronic supplementary material The online version of this article (doi:10.1186/s13045-016-0308-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Stefan Wilop
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Wen-Chien Chou
- Department of Laboratory Medicine, National Taiwan University Hospital, Taipei, Taiwan.,Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Edgar Jost
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Martina Crysandt
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Jens Panse
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Ming-Kai Chuang
- Department of Laboratory Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Tim H Brümmendorf
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Wolfgang Wagner
- Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular, Engineering, University Hospital of the RWTH Aachen, Aachen, Germany.,Institute for Biomedical Engineering - Cell Biology, University Hospital of the RWTH, Aachen, Germany
| | - Hwei-Fang Tien
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Behzad Kharabi Masouleh
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Medical Faculty, RWTH Aachen University, Aachen, Germany.
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Bhatnagar B, Garzon R. Long noncoding RNAs to predict survival in acute myeloid leukemia: a step toward personalized medicine? Biomark Med 2016; 10:935-8. [PMID: 27548737 DOI: 10.2217/bmm-2016-0173] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
- Bhavana Bhatnagar
- Department of Internal Medicine, Division of Hematology, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.,The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Ramiro Garzon
- Department of Internal Medicine, Division of Hematology, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.,The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
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Zhang DY, Yuan XQ, Yan H, Cao S, Zhang W, Li XL, Zeng H, Chen XP. Association between DCK 35708 T>C variation and clinical outcomes of acute myeloid leukemia in South Chinese patients. Pharmacogenomics 2016; 17:1519-31. [PMID: 27548009 DOI: 10.2217/pgs-2016-0084] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
AIM DCK is a rate-limiting enzyme in cytarabine activation. rs4643786 and rs67437265 (P122S) variants are reported to affect DCK activity. PATIENTS & METHODS A total of 282 newly diagnosed acute myeloid leukemia (AML) patients were treated with cytarabine combined chemotherapy and genotyped for rs4643786 and rs67437265. Prognosis data were obtained through regular follow-up. DCK mRNA expression was detected in pretreatment blood or bone marrow mononuclear cells. RESULTS rs4643786 showed strong linkage disequilibrium with rs67437265. rs4643786 CT heterozygotes showed significantly higher complete remission rate (p = 0.028), superior overall survival (p = 0.006) and relapse-free survival (p = 0.020) than wild-type TT homozygotes. rs4643786 polymorphism was an independent predictor for AML prognosis. CONCLUSION DCK rs4643786 may serve as an independent predictor of drug response and AML outcome.
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Affiliation(s)
- Dao-Yu Zhang
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, Hunan, PR China
| | - Xiao-Qing Yuan
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, Hunan, PR China
| | - Han Yan
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, Hunan, PR China
| | - Shan Cao
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, Hunan, PR China
| | - Wei Zhang
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, Hunan, PR China
| | - Xiao-Lin Li
- Department of Hematology, Xiang-Ya Hospital, Central South University, Changsha 410008, Hunan, PR China
| | - Hui Zeng
- Department of Hematology, Xiang-Ya Hospital, Central South University, Changsha 410008, Hunan, PR China
| | - Xiao-Ping Chen
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, Hunan, PR China.,Institute of Clinical Pharmacology, Central South University; Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, Hunan, PR China.,Hunan Province Cooperation Innovation Center for Molecular Target New Drug Study, Hengyang 421001, Hunan, PR China
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Chen Y, Yang T, Zheng X, Yang X, Zheng Z, Zheng J, Liu T, Hu J. The outcome and prognostic factors of 248 elderly patients with acute myeloid leukemia treated with standard-dose or low-intensity induction therapy. Medicine (Baltimore) 2016; 95:e4182. [PMID: 27472687 PMCID: PMC5265824 DOI: 10.1097/md.0000000000004182] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
The prognosis of elderly patients with acute myeloid leukemia (AML) is poor, and the recommendation of standard-dose or low-intensity induction regimen for these patients remains controversial. We retrospectively analyzed treatment outcome and prognostic factors of elderly AML patients who had received either standard-dose or low-intensity induction regimens.Two hundred forty-eight elderly AML patients with good Eastern Cooperative Oncology Group performance status (ECOG PS ≤ 2) received one of three regimens for induction in this study: standard-dose cytarabine plus idarubicin (IA; n = 144) or daunorubicin (DA; n = 42); low-intensity cytarabine, aclarubicin, and granulocyte colony-stimulating factor (G-CSF) (CAG; n = 62).After first induction treatment cycle, the overall complete remission (CR) rate was 42.7%. Patients in IA group had a higher CR rate than in DA or CAG group (49.3%, 35.7%, and 32.3%, respectively; P = 0.046). The 1-year, 3-year, and 5-year overall survival (OS) rates were 42.2%, 18.9%, and 13.5% for these 248 patients, with median survival of 9.2 months. Long-term survival of IA group was better than DA or CAG group. The 1-year, 3-year, and 5-year OS rates of IA group were 45.9%, 23.5%, and 19.4%, respectively, as compared to 39.8%, 8.3%, and estimated 2.4% in DA group, and 34.9%, 15.9%, and 6.3% in CAG group, respectively. Early induction mortality and 2-year relapse rates showed no difference among 3 groups. Univariate analysis and multivariate analysis identified lactic dehydrogenase (LDH) more than two times of upper normal limit at diagnosis and nonremission after first induction cycle as adverse prognostic factors for OS. A simple and valid scoring model was constructed for risk stratification and prediction of long-term survival of elderly AML patients.Standard-dose IA regimen could improve the prognosis of elderly AML patients with good performance status compared with standard-dose DA or low-intensity CAG regimen. All prognostic factors and risk assessment should be considered to ensure that each patient receives the suitable individualized treatment.
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Affiliation(s)
| | | | | | | | | | | | | | - Jianda Hu
- Fujian Provincial Key Laboratory of Hematology, Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, Fujian, P. R. China
- Correspondence: Jianda Hu, Fujian Provincial Key Laboratory of Hematology, Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian, P. R. China (e-mail: )
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50
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Seiter K, Ahmed N, Shaikh A, Baskind P, Liu D. CLAG-based induction therapy in previously untreated high risk acute myeloid leukemia patients. Leuk Res 2016; 46:74-8. [DOI: 10.1016/j.leukres.2016.04.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Revised: 04/16/2016] [Accepted: 04/23/2016] [Indexed: 01/21/2023]
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