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Wang XZ, Gao XM, Wang JM, Cai H, Li J, Cao XX. Co-occurrence of Erdheim-Chester disease and clonally evolving acute myeloid leukemia with FLT3-ITD and PTPN11 mutations. Ann Hematol 2024; 103:3229-3233. [PMID: 38879649 DOI: 10.1007/s00277-024-05842-5] [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: 03/20/2024] [Accepted: 06/09/2024] [Indexed: 07/28/2024]
Abstract
Erdheim-Chester disease (ECD) is a rare histiocytosis that tends to co-exist with other myeloid malignancies. Here, we use genetic and transcriptomic sequencing to delineate a case of co-occurring BRAFV600E-mutated ECD and acute myeloid leukemia (AML), followed by AML remission and relapse. The AML relapse involved the extinction of clones with KMT2A-AFDN and FLT3-ITD, and the predominance of PTPN11-mutated subclones with distinct transcriptomic features. This case report has highlighted the screening for other myeloid malignancies at the diagnosis of ECD and the clinical significance of PTPN11-mutated AML subclones that require meticulous monitoring.
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Affiliation(s)
- Xue-Zhu Wang
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Xue-Min Gao
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Jun-Mei Wang
- Neuropathological Department, Beijing Tiantan Hospital Affiliated to Capital Medical University, Beijing Neurosurgical Institute, Beijing, China
| | - Hao Cai
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Jian Li
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Xin-Xin Cao
- Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
- State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
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Yao Y, Zhou Y, Zhuo N, Xie W, Meng H, Lou Y, Mao L, Tong H, Qian J, Yang M, Yu W, Zhou D, Jin J, Wang H. Co-mutation landscape and its prognostic impact on newly diagnosed adult patients with NPM1-mutated de novo acute myeloid leukemia. Blood Cancer J 2024; 14:118. [PMID: 39039048 PMCID: PMC11263537 DOI: 10.1038/s41408-024-01103-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 07/08/2024] [Accepted: 07/11/2024] [Indexed: 07/24/2024] Open
Affiliation(s)
- Yiyi Yao
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
| | - Yile Zhou
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
| | - Nanfang Zhuo
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
| | - Wanzhuo Xie
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
| | - Haitao Meng
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
| | - Yinjun Lou
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
| | - Liping Mao
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
| | - Hongyan Tong
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
- Zhejiang Provincial Clinical Research Center for Hematological disorders, Hangzhou, 310000, Zhejiang, PR China
- Zhejiang University Cancer Center, Hangzhou, 310000, Zhejiang, PR China
| | - Jiejing Qian
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
| | - Min Yang
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
| | - Wenjuan Yu
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
| | - De Zhou
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
| | - Jie Jin
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China
- Zhejiang Provincial Clinical Research Center for Hematological disorders, Hangzhou, 310000, Zhejiang, PR China
- Zhejiang University Cancer Center, Hangzhou, 310000, Zhejiang, PR China
| | - Huafeng Wang
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, PR China.
- Zhejiang Provincial Key Laboratory of Hematopoietic Malignancy, Zhejiang University, Hangzhou, 310000, Zhejiang, PR China.
- Zhejiang Provincial Clinical Research Center for Hematological disorders, Hangzhou, 310000, Zhejiang, PR China.
- Zhejiang University Cancer Center, Hangzhou, 310000, Zhejiang, PR China.
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Zhou Z, Zhuo N, Zhou Y, Sun C, Yao Y, Mao L, Zhang Y, Hong Q, Pan P, Tong H, Jin J, Wang H. Identification of the characteristics and prognostic impact of FUS::ERG and RUNX1::CBFA2T3 fusion genes in adult acute myeloid leukemia patients. Am J Hematol 2024; 99:1441-1444. [PMID: 38651500 DOI: 10.1002/ajh.27340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 03/16/2024] [Accepted: 04/11/2024] [Indexed: 04/25/2024]
Affiliation(s)
- Ziyue Zhou
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Nanfang Zhuo
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
- Zhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, People's Republic of China
| | - Yile Zhou
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
- Zhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, People's Republic of China
| | - Caihong Sun
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Yiyi Yao
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
- Zhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, People's Republic of China
| | - Liping Mao
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
- Zhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, People's Republic of China
- Zhejiang Provincial Clinical Research Center for Hematological Disorders, Hangzhou, People's Republic of China
| | - Yi Zhang
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
- Zhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, People's Republic of China
- Zhejiang Provincial Clinical Research Center for Hematological Disorders, Hangzhou, People's Republic of China
| | - Qing Hong
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Peifeng Pan
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Hongyan Tong
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
- Zhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, People's Republic of China
- Zhejiang Provincial Clinical Research Center for Hematological Disorders, Hangzhou, People's Republic of China
- Zhejiang University Cancer Center, Hangzhou, People's Republic of China
| | - Jie Jin
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
- Zhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, People's Republic of China
- Zhejiang Provincial Clinical Research Center for Hematological Disorders, Hangzhou, People's Republic of China
- Zhejiang University Cancer Center, Hangzhou, People's Republic of China
| | - Huafeng Wang
- Department of Hematology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
- Zhejiang Provincial Key Lab of Hematopoietic Malignancy, Zhejiang University, Hangzhou, People's Republic of China
- Zhejiang Provincial Clinical Research Center for Hematological Disorders, Hangzhou, People's Republic of China
- Zhejiang University Cancer Center, Hangzhou, People's Republic of China
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Bruserud Ø, Selheim F, Hernandez-Valladares M, Reikvam H. Monocytic Differentiation in Acute Myeloid Leukemia Cells: Diagnostic Criteria, Biological Heterogeneity, Mitochondrial Metabolism, Resistance to and Induction by Targeted Therapies. Int J Mol Sci 2024; 25:6356. [PMID: 38928061 PMCID: PMC11203697 DOI: 10.3390/ijms25126356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2024] [Revised: 05/31/2024] [Accepted: 06/05/2024] [Indexed: 06/28/2024] Open
Abstract
We review the importance of monocytic differentiation and differentiation induction in non-APL (acute promyelocytic leukemia) variants of acute myeloid leukemia (AML), a malignancy characterized by proliferation of immature myeloid cells. Even though the cellular differentiation block is a fundamental characteristic, the AML cells can show limited signs of differentiation. According to the French-American-British (FAB-M4/M5 subset) and the World Health Organization (WHO) 2016 classifications, monocytic differentiation is characterized by morphological signs and the expression of specific molecular markers involved in cellular communication and adhesion. Furthermore, monocytic FAB-M4/M5 patients are heterogeneous with regards to cytogenetic and molecular genetic abnormalities, and monocytic differentiation does not have any major prognostic impact for these patients when receiving conventional intensive cytotoxic therapy. In contrast, FAB-M4/M5 patients have decreased susceptibility to the Bcl-2 inhibitor venetoclax, and this seems to be due to common molecular characteristics involving mitochondrial regulation of the cellular metabolism and survival, including decreased dependency on Bcl-2 compared to other AML patients. Thus, the susceptibility to Bcl-2 inhibition does not only depend on general resistance/susceptibility mechanisms known from conventional AML therapy but also specific mechanisms involving the molecular target itself or the molecular context of the target. AML cell differentiation status is also associated with susceptibility to other targeted therapies (e.g., CDK2/4/6 and bromodomain inhibition), and differentiation induction seems to be a part of the antileukemic effect for several targeted anti-AML therapies. Differentiation-associated molecular mechanisms may thus become important in the future implementation of targeted therapies in human AML.
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MESH Headings
- Humans
- Cell Differentiation
- Leukemia, Myeloid, Acute/metabolism
- Leukemia, Myeloid, Acute/pathology
- Leukemia, Myeloid, Acute/diagnosis
- Leukemia, Myeloid, Acute/drug therapy
- Leukemia, Myeloid, Acute/genetics
- Mitochondria/metabolism
- Monocytes/metabolism
- Monocytes/pathology
- Drug Resistance, Neoplasm/genetics
- Molecular Targeted Therapy
- Antineoplastic Agents/pharmacology
- Antineoplastic Agents/therapeutic use
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Affiliation(s)
- Øystein Bruserud
- Acute Leukemia Research Group, Department of Clinical Science, University of Bergen, 5007 Bergen, Norway; (M.H.-V.); (H.R.)
- Section for Hematology, Department of Medicine, Haukeland University Hospital, 5009 Bergen, Norway
| | - Frode Selheim
- Proteomics Unit of University of Bergen (PROBE), University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway;
| | - Maria Hernandez-Valladares
- Acute Leukemia Research Group, Department of Clinical Science, University of Bergen, 5007 Bergen, Norway; (M.H.-V.); (H.R.)
- Department of Physical Chemistry, University of Granada, Avenida de la Fuente Nueva S/N, 18071 Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
| | - Håkon Reikvam
- Acute Leukemia Research Group, Department of Clinical Science, University of Bergen, 5007 Bergen, Norway; (M.H.-V.); (H.R.)
- Section for Hematology, Department of Medicine, Haukeland University Hospital, 5009 Bergen, Norway
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Selheim F, Aasebø E, Reikvam H, Bruserud Ø, Hernandez-Valladares M. Monocytic Differentiation of Human Acute Myeloid Leukemia Cells: A Proteomic and Phosphoproteomic Comparison of FAB-M4/M5 Patients with and without Nucleophosmin 1 Mutations. Int J Mol Sci 2024; 25:5080. [PMID: 38791118 PMCID: PMC11121526 DOI: 10.3390/ijms25105080] [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: 12/20/2023] [Revised: 04/14/2024] [Accepted: 04/24/2024] [Indexed: 05/26/2024] Open
Abstract
Even though morphological signs of differentiation have a minimal impact on survival after intensive cytotoxic therapy for acute myeloid leukemia (AML), monocytic AML cell differentiation (i.e., classified as French/American/British (FAB) subtypes M4/M5) is associated with a different responsiveness both to Bcl-2 inhibition (decreased responsiveness) and possibly also bromodomain inhibition (increased responsiveness). FAB-M4/M5 patients are heterogeneous with regard to genetic abnormalities, even though monocytic differentiation is common for patients with Nucleophosmin 1 (NPM1) insertions/mutations; to further study the heterogeneity of FAB-M4/M5 patients we did a proteomic and phosphoproteomic comparison of FAB-M4/M5 patients with (n = 13) and without (n = 12) NPM1 mutations. The proteomic profile of NPM1-mutated FAB-M4/M5 patients was characterized by increased levels of proteins involved in the regulation of endocytosis/vesicle trafficking/organellar communication. In contrast, AML cells without NPM1 mutations were characterized by increased levels of several proteins involved in the regulation of cytoplasmic translation, including a large number of ribosomal proteins. The phosphoproteomic differences between the two groups were less extensive but reflected similar differences. To conclude, even though FAB classification/monocytic differentiation are associated with differences in responsiveness to new targeted therapies (e.g., Bcl-2 inhibition), our results shows that FAB-M4/M5 patients are heterogeneous with regard to important biological characteristics of the leukemic cells.
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Affiliation(s)
- Frode Selheim
- Proteomics Unit of University of Bergen (PROBE), University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway
| | - Elise Aasebø
- Acute Leukemia Research Group, Department of Clinical Science, University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway; (E.A.); (H.R.); (Ø.B.)
| | - Håkon Reikvam
- Acute Leukemia Research Group, Department of Clinical Science, University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway; (E.A.); (H.R.); (Ø.B.)
- Section for Hematology, Department of Medicine, Haukeland University Hospital, 5009 Bergen, Norway
| | - Øystein Bruserud
- Acute Leukemia Research Group, Department of Clinical Science, University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway; (E.A.); (H.R.); (Ø.B.)
- Section for Hematology, Department of Medicine, Haukeland University Hospital, 5009 Bergen, Norway
| | - Maria Hernandez-Valladares
- Proteomics Unit of University of Bergen (PROBE), University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway
- Department of Physical Chemistry, University of Granada, Avenida de la Fuente Nueva S/N, 18071 Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
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Huang S, Chen P, Wang L, Xu L, Wang N, Li F, Dou L, Liu D. Next-generation sequencing reveals relapse and leukemia-free survival risks in newly diagnosed acute myeloid leukemia treated with CAG regimen combined with decitabine. CANCER PATHOGENESIS AND THERAPY 2024; 2:112-120. [PMID: 38601484 PMCID: PMC11002746 DOI: 10.1016/j.cpt.2023.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 10/01/2023] [Accepted: 10/07/2023] [Indexed: 04/12/2024]
Abstract
Background Acute myeloid leukemia (AML) is a heterogeneous hematopoietic malignancy whose prognosis is associated with several biomarkers. Decitabine, a deoxyribonucleic acid (DNA) methyltransferase (DNMT) inhibitor, combined with cytarabine, aclarubicin hydrochloride, and granulocyte colony-stimulating factor (DCAG), has been used in patients newly diagnosed with AML. This regimen has been especially used in older and fragile patients who are immunocompromised or have co-morbidities, as well as those with specific gene mutations. However, the integration of molecular risk stratification and treatment guidance for the DCAG regimen has not been well defined. Therefore, this study aimed to investigate the genetic mutations associated with AML and establish appropriate treatment strategies for patients newly diagnosed with AML. Methods This study analyzed the clinical data and genetic mutations based on next-generation sequencing (NGS) in 124 newly diagnosed patients with AML who received the DCAG regimen at the People's Liberation Army (PLA) General Hospital from January 2008 to August 2020. Factors associated with the cumulative incidence of relapse (CIR) and leukemia-free survival (LFS) in patients newly diagnosed with AML were analyzed. Results The most adverse prognosis of DCAG-treated patients was observed in those with FLT3-ITD, KIT, PTPN11, GATA2, or IDH1 mutations during univariable analysis, whereas PTPN11 mutation was solely significant in multivariable analysis, with an increased likelihood of CIR (P = 0.001) and reduced LFS duration (P = 0.077). Hyperleukocytosis was maintained as an independent risk factor for increased CIR risk (P = 0.044) and decreased LFS duration (P = 0.042) in multivariable analysis. In this study, we validated the risk classification of patients with AML receiving an epigenetic modifier-based induction regimen across a broad age range. Conclusion NGS demonstrated a dismal overall outcome in patients with the rare PTPN11 mutations, indicating the need for new therapies that target this high-risk subtype of AML. These results offer a potential molecular stratification and treatment guidance for patients with AML.
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Affiliation(s)
- Sai Huang
- Department of Hematology, Senior Department of Hematology, The Fifth Medical Center of PLA General Hospital, Beijing 100039, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing 100853, China
| | - Peng Chen
- Department of Hematology, Senior Department of Hematology, The Fifth Medical Center of PLA General Hospital, Beijing 100039, China
- Chinese PLA Medical School, Beijing 100853, China
| | - Lu Wang
- Department of Hematology, The First Medical Center of PLA General Hospital, Beijing 100853, China
| | - Lingmin Xu
- Department of Hematology, The First Medical Center of PLA General Hospital, Beijing 100853, China
| | - Nan Wang
- Chinese PLA Medical School, Beijing 100853, China
- Department of Hematology, The First Medical Center of PLA General Hospital, Beijing 100853, China
| | - Fei Li
- Department of Hematology, The First Medical Center of PLA General Hospital, Beijing 100853, China
| | - Liping Dou
- Department of Hematology, Senior Department of Hematology, The Fifth Medical Center of PLA General Hospital, Beijing 100039, China
| | - Daihong Liu
- Department of Hematology, Senior Department of Hematology, The Fifth Medical Center of PLA General Hospital, Beijing 100039, China
- National Clinical Research Center of Geriatric Diseases, Chinese PLA General Hospital, Beijing 100853, China
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7
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Lai A, Liu W, Wei H, Wang Y, Lin D, Zhou C, Liu B, Gu R, Li Y, Wei S, Gong B, Liu K, Gong X, Liu Y, Zhang G, Zhang J, Mi Y, Wang J, Qiu S. The RTK-RAS signaling pathway is enriched in patients with rare acute myeloid leukemia harboring t(16;21)(p11;q22)/ FUS::ERG. BLOOD SCIENCE 2024; 6:e00188. [PMID: 38742238 PMCID: PMC11090622 DOI: 10.1097/bs9.0000000000000188] [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: 11/28/2023] [Accepted: 04/01/2024] [Indexed: 05/16/2024] Open
Abstract
Acute myeloid leukemia (AML) with t(16;21)(p11;q22)/FUS::ERG is a rare AML subtype associated with poor prognosis. However, its clinical and molecular features remain poorly defined. We determined the clinicopathological, genomic, and transcriptomic characteristics and outcomes of patients with AML harboring FUS::ERG at our center. Thirty-six AML patients harboring FUS::ERG were identified, with an incidence rate of 0.3%. These patients were characterized by high lactate dehydrogenase levels (median: 838.5 U/L), elevated bone marrow blast counts (median: 71.5%), and a CD56-positive immunophenotype (94.3%). Notably, we found that RTK-RAS GTPase (RAS) pathway genes, including NRAS (33%) and PTPN11 (24%), were frequently mutated in this subtype. Transcriptome analysis revealed enrichment of the phosphatidylinositol-3-kinase-Akt (PI3K-Akt), mitogen-activated protein kinase (MAPK), and RAS signaling pathways and upregulation of BCL2, the target of venetoclax, in FUS::ERG AML compared to RUNX1::RUNX1T1 AML, a more common AML subtype with good prognosis. The median event-free survival in patients with FUS::ERG AML was 11.9 (95% confidence interval [CI]: 9.0-not available [NA]) months and the median overall survival was 18.2 (95% CI: 12.4-NA) months. Allogeneic hematopoietic stem cell transplantation failed to improve outcomes. Overall, the high incidence of RTK-RAS pathway mutations and high expression of BCL2 may indicate promising therapeutic targets in this high-risk AML subset.
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Affiliation(s)
- Anli Lai
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Wenbing Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Hui Wei
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
- Tianjin Key Laboratory of Cell Therapy for Blood Diseases, Tianjin 300020, China
| | - Ying Wang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
- Tianjin Key Laboratory of Cell Therapy for Blood Diseases, Tianjin 300020, China
| | - Dong Lin
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Chunlin Zhou
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Bingcheng Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Runxia Gu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Yan Li
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Shuning Wei
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Benfa Gong
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Kaiqi Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Xiaoyuan Gong
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Yuntao Liu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Guangji Zhang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Junping Zhang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Yingchang Mi
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
- Tianjin Key Laboratory of Cell Therapy for Blood Diseases, Tianjin 300020, China
| | - Jianxiang Wang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
- Tianjin Key Laboratory of Cell Therapy for Blood Diseases, Tianjin 300020, China
| | - Shaowei Qiu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China
- Tianjin Institutes of Health Science, Tianjin 301600, China
- Tianjin Key Laboratory of Cell Therapy for Blood Diseases, Tianjin 300020, China
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8
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Choi SJ, Kim HK, Suh EJ, Kwon SS, Shin S, Lee ST, Kim S. CEBPA double mutations associated with ABO antigen weakness in hematologic diseases. Blood Adv 2024; 8:1487-1493. [PMID: 38359363 PMCID: PMC10951908 DOI: 10.1182/bloodadvances.2023011572] [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: 09/01/2023] [Revised: 01/31/2024] [Accepted: 01/31/2024] [Indexed: 02/17/2024] Open
Abstract
ABSTRACT ABO antigen weakness is rarely observed in ABO typing for transfusion. Hematologic diseases and associated gene mutations have been suggested as potential causes of this phenomenon, yet the precise etiology has not been elucidated. Through ABO typing and genetic analysis data conducted over 7 years, we have reconfirmed the association between ABO antigen weakness and hematologic diseases, especially acute myeloid leukemia (odds ratio [OR], 2.55; 95% confidence interval [CI], 1.12-5.83) and myelodysplastic syndrome (OR, 6.94; 95% CI, 2.86-16.83), and discovered previously unidentified candidate genes, CEBPA (OR, 43.70; 95% CI, 18.12-105.40), NRAS (OR, 3.37; 95% CI, 1.46-7.79), U2AF1 (OR, 8.12; 95% CI, 2.86-23.03), and PTPN11 (OR, 4.52; 95% CI, 1.51-13.50), seemingly associated with this phenomenon. Among these, CEBPA double mutations displayed a significant association, with ABO antigen weakness being observed in 20 of the 25 individuals (80.0%) possessing these mutations. From this study, new factors associated with ABO antigen weakness have been identified.
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Affiliation(s)
- Seung Jun Choi
- Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Hyun Kyung Kim
- Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea
- Department of Obstetrics and Gynecology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Korea
| | - Eun Jung Suh
- Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Soon Sung Kwon
- Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Saeam Shin
- Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Seung-Tae Lee
- Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea
- Dxome, Seoul, Korea
| | - Sinyoung Kim
- Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea
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9
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Sun L, Yang PC, Luan L, Sun JF, Wang YT. Harmonizing the craft of crafting clinically endorsed small-molecule BCR-ABL tyrosine kinase inhibitors for the treatment of hematological malignancies. Eur J Pharm Sci 2024; 193:106678. [PMID: 38114052 DOI: 10.1016/j.ejps.2023.106678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/14/2023] [Accepted: 12/16/2023] [Indexed: 12/21/2023]
Abstract
The advancement and practical use of small-molecule tyrosine kinase inhibitors (TKIs) that specifically target the BCR-ABL fusion protein have introduced a revolutionary era of precision medicine for the treatment of chronic myeloid leukemia (CML) and Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ ALL). This review offers a comprehensive exploration of the synthesis, mechanisms of action, and clinical implementation of clinically validated TKIs in the context of BCR-ABL, emphasizing the remarkable strides made in achieving therapeutic precision. We delve into the intricate design and synthesis of these small molecules, highlighting the synthetic strategies and modifications that have led to increased selectivity, enhanced binding affinities, and reduced off-target effects. Additionally, we discuss the structural biology of BCR-ABL inhibition and how it informs drug design. The success of these compounds in inhibiting aberrant kinase activity is a testament to the meticulous refinement of the synthetic process. Furthermore, this review provides a detailed analysis of the clinical applications of these TKIs, covering not only their efficacy in achieving deep molecular responses but also their impact on patient outcomes, safety profiles, and resistance mechanisms. We explore ongoing research efforts to overcome resistance and enhance the therapeutic potential of these agents. In conclusion, the synthesis and utilization of clinically validated small-molecule TKIs targeting BCR-ABL exemplify the transformative power of precision medicine in the treatment of hematological malignancies. This review highlights the evolving landscape of BCR-ABL inhibition and underscores the continuous commitment to refining and expanding the therapeutic repertoire for these devastating diseases.
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Affiliation(s)
- Lu Sun
- Zhongshan Hospital Affiliated to Dalian University, Dalian 116001, China
| | - Peng-Cheng Yang
- Key Laboratory of Natural Medicines of the Changbai Mountain, Ministry of Education, College of Pharmacy, Yanbian University, Yanji, Jilin 133002, China
| | - Li Luan
- Zhongshan Hospital Affiliated to Dalian University, Dalian 116001, China.
| | - Jin-Feng Sun
- Key Laboratory of Natural Medicines of the Changbai Mountain, Ministry of Education, College of Pharmacy, Yanbian University, Yanji, Jilin 133002, China.
| | - Ya-Tao Wang
- First People's Hospital of Shangqiu, Shangqiu, Henan 476100, China; The Rogel Cancer Center, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan 48109, United States.
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10
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Selheim F, Aasebø E, Bruserud Ø, Hernandez-Valladares M. High Mitochondrial Protein Expression as a Potential Predictor of Relapse Risk in Acute Myeloid Leukemia Patients with the Monocytic FAB Subtypes M4 and M5. Cancers (Basel) 2023; 16:8. [PMID: 38201437 PMCID: PMC10778527 DOI: 10.3390/cancers16010008] [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: 10/24/2023] [Revised: 12/08/2023] [Accepted: 12/12/2023] [Indexed: 01/12/2024] Open
Abstract
AML is a highly aggressive and heterogeneous form of hematological cancer. Proteomics-based stratification of patients into more refined subgroups may contribute to a more precise characterization of the patient-derived AML cells. Here, we reanalyzed liquid chromatography-tandem mass spectrometry (LC-MS/MS) generated proteomic and phosphoproteomic data from 26 FAB-M4/M5 patients. The patients achieved complete hematological remission after induction therapy. Twelve of them later developed chemoresistant relapse (RELAPSE), and 14 patients were relapse-free (REL_FREE) long-term survivors. We considered not only the RELAPSE and REL_FREE characteristics but also integrated the French-American-British (FAB) classification, along with considering the presence of nucleophosmin 1 (NPM1) mutation and cytogenetically normal AML. We found a significant number of differentially enriched proteins (911) and phosphoproteins (257) between the various FAB subtypes in RELAPSE patients. Patients with the myeloblastic M1/M2 subtype showed higher levels of RNA processing-related routes and lower levels of signaling related to terms like translation and degranulation when compared with the M4/M5 subtype. Moreover, we found that a high abundance of proteins associated with mitochondrial translation and oxidative phosphorylation, particularly observed in the RELAPSE M4/M5 NPM1 mutated subgroup, distinguishes relapsing from non-relapsing AML patient cells with the FAB subtype M4/M5. Thus, the discovery of subtype-specific biomarkers through proteomic profiling may complement the existing classification system for AML and potentially aid in selecting personalized treatment strategies for individual patients.
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Affiliation(s)
- Frode Selheim
- Proteomics Unit of University of Bergen (PROBE), University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway
| | - Elise Aasebø
- Acute Leukemia Research Group, Department of Clinical Science, University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway; (E.A.); (Ø.B.)
| | - Øystein Bruserud
- Acute Leukemia Research Group, Department of Clinical Science, University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway; (E.A.); (Ø.B.)
- Section for Hematology, Department of Medicine, Haukeland University Hospital, 5009 Bergen, Norway
| | - Maria Hernandez-Valladares
- Proteomics Unit of University of Bergen (PROBE), University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway
- Department of Physical Chemistry, Institute of Biotechnology, Excellence Unit in Chemistry Applied to Biomedicine and Environment, School of Sciences, University of Granada, Campus Fuentenueva s/n, 18071 Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
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11
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Liu Y, Zhang W, Jang H, Nussinov R. SHP2 clinical phenotype, cancer, or RASopathies, can be predicted by mutant conformational propensities. Cell Mol Life Sci 2023; 81:5. [PMID: 38085330 PMCID: PMC11072105 DOI: 10.1007/s00018-023-05052-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/20/2023] [Accepted: 11/11/2023] [Indexed: 12/18/2023]
Abstract
SHP2 phosphatase promotes full activation of the RTK-dependent Ras/MAPK pathway. Its mutations can drive cancer and RASopathies, a group of neurodevelopmental disorders (NDDs). Here we ask how same residue mutations in SHP2 can lead to both cancer and NDD phenotypes, and whether we can predict what the outcome will be. We collected and analyzed mutation data from the literature and cancer databases and performed molecular dynamics simulations of SHP2 mutants. We show that both cancer and Noonan syndrome (NS, a RASopathy) mutations favor catalysis-prone conformations. As to cancer versus RASopathies, we demonstrate that cancer mutations are more likely to accelerate SHP2 activation than the NS mutations at the same genomic loci, in line with NMR data for K-Ras4B more aggressive mutations. The compiled experimental data and dynamic features of SHP2 mutants lead us to propose that different from strong oncogenic mutations, SHP2 activation by NS mutations is less likely to induce a transition of the ensemble from the SHP2 inactive state to the active state. Strong signaling promotes cell proliferation, a hallmark of cancer. Weak, or moderate signals are associated with differentiation. In embryonic neural cells, dysregulated differentiation is connected to NDDs. Our innovative work offers structural guidelines for identifying and correlating mutations with clinical outcomes, and an explanation for why bearers of RASopathy mutations may have a higher probability of cancer. Finally, we propose a drug strategy against SHP2 variants-promoting cancer and RASopathies.
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Affiliation(s)
- Yonglan Liu
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD, 21702, USA
| | - Wengang Zhang
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD, 21702, USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
| | - Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, 69978, Tel Aviv, Israel.
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12
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Segura J, Rose Y, Bi C, Duarte J, Burley SK, Bittrich S. RCSB Protein Data Bank: visualizing groups of experimentally determined PDB structures alongside computed structure models of proteins. FRONTIERS IN BIOINFORMATICS 2023; 3:1311287. [PMID: 38111685 PMCID: PMC10726007 DOI: 10.3389/fbinf.2023.1311287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 11/17/2023] [Indexed: 12/20/2023] Open
Abstract
Recent advances in Artificial Intelligence and Machine Learning (e.g., AlphaFold, RosettaFold, and ESMFold) enable prediction of three-dimensional (3D) protein structures from amino acid sequences alone at accuracies comparable to lower-resolution experimental methods. These tools have been employed to predict structures across entire proteomes and the results of large-scale metagenomic sequence studies, yielding an exponential increase in available biomolecular 3D structural information. Given the enormous volume of this newly computed biostructure data, there is an urgent need for robust tools to manage, search, cluster, and visualize large collections of structures. Equally important is the capability to efficiently summarize and visualize metadata, biological/biochemical annotations, and structural features, particularly when working with vast numbers of protein structures of both experimental origin from the Protein Data Bank (PDB) and computationally-predicted models. Moreover, researchers require advanced visualization techniques that support interactive exploration of multiple sequences and structural alignments. This paper introduces a suite of tools provided on the RCSB PDB research-focused web portal RCSB. org, tailor-made for efficient management, search, organization, and visualization of this burgeoning corpus of 3D macromolecular structure data.
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Affiliation(s)
- Joan Segura
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, San Diego, CA, United States
| | - Yana Rose
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, San Diego, CA, United States
| | - Chunxiao Bi
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, San Diego, CA, United States
| | - Jose Duarte
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, San Diego, CA, United States
| | - Stephen K. Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, San Diego, CA, United States
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ, United States
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, United States
- Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ, United States
| | - Sebastian Bittrich
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California San Diego, San Diego, CA, United States
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13
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Yang J, Zhao L, Wu Y, Niu T, Gong Y, Chen X, Huang X, Liu J, Dai Y, Ma H. The clinical features and prognostic implications of PTPN11 mutation in adult patients with acute myeloid leukemia in China. Cancer Med 2023; 12:21111-21117. [PMID: 37937729 PMCID: PMC10726903 DOI: 10.1002/cam4.6669] [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: 07/19/2023] [Revised: 10/03/2023] [Accepted: 10/19/2023] [Indexed: 11/09/2023] Open
Abstract
BACKGROUND The clinical significance of protein tyrosine phosphatase nonreceptor type 11 mutation (PTPN11mut ) in acute myeloid leukemia (AML) is underestimated. METHODS We collected the data of AML patients with mutated PTPN11 and wild-type PTPN11 (PTPN11wt ) treated at our hospital and analyzed their clinical characteristics and prognosis. RESULTS Fifty-nine PTPN11mut and 124 PTPN11wt AML patients were included. PTPN11mut was more common in myelomonocytic and monocytic leukemia, and was more likely to co-mutate with KRAS, KMT2C, NRAS, U2AF1, NOTCH1, IKZF1, and USH2A mutations than PTPN11wt . The overall survival for AML patients with PTPN11mut was significantly shorter than that for those with PTPN11wt (p = 0.03). The negative impact of PTPN11mut on overall survival was pronounced in the "favorable" and "intermediate" groups of ELN2017 risk stratification, as well as in the wild-type NPM1 group (p = 0.01, p = 0.01, and p = 0.04). CONCLUSION PTPN11mut is associated with distinct clinical and molecular characteristics, and adverse prognosis in AML patients.
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Affiliation(s)
- Jinjun Yang
- Department of Hematology and Institute of Hematology, West China HospitalSichuan UniversityChengduChina
| | - Lei Zhao
- Department of Hematology and Institute of Hematology, West China HospitalSichuan UniversityChengduChina
| | - Yu Wu
- Department of Hematology and Institute of Hematology, West China HospitalSichuan UniversityChengduChina
| | - Ting Niu
- Department of Hematology and Institute of Hematology, West China HospitalSichuan UniversityChengduChina
| | - Yuping Gong
- Department of Hematology and Institute of Hematology, West China HospitalSichuan UniversityChengduChina
| | - Xinchuan Chen
- Department of Hematology and Institute of Hematology, West China HospitalSichuan UniversityChengduChina
| | - Xiaoou Huang
- Department of Hematology and Institute of Hematology, West China HospitalSichuan UniversityChengduChina
| | - Jiazhuo Liu
- Department of Hematology and Institute of Hematology, West China HospitalSichuan UniversityChengduChina
| | - Yang Dai
- Department of Hematology and Institute of Hematology, West China HospitalSichuan UniversityChengduChina
| | - Hongbing Ma
- Department of Hematology and Institute of Hematology, West China HospitalSichuan UniversityChengduChina
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14
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Huang R, Zhang YT, Lin Y, Pang RL, Yang Z, Zhao WH. Clinical Characteristics and Prognosis of Acute Myeloid Leukemia Patients with Protein Tyrosine Phosphatase Non-Receptor Type 11 Gene Mutation. Pharmgenomics Pers Med 2023; 16:1011-1026. [PMID: 38023823 PMCID: PMC10648958 DOI: 10.2147/pgpm.s420254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 10/27/2023] [Indexed: 12/01/2023] Open
Abstract
Objective The purpose of our study was to investigate the clinical characteristics, molecular biological characteristics and prognosis of acute myeloid leukemia (AML) patients with protein tyrosine phosphatase non-receptor type 11 (PTPN11) gene mutation. Methods The clinical data of 30 newly diagnosed adult AML patients with PTPN11 gene mutation were analyzed retrospectively. Kaplan-Meier and Cox proportional risk regression model were examined for prognostic analysis and prognostic factor screening. Results High-frequency mutation sites of PTPN11 gene are located in exon 3 of chromosome 12, which are D61 and A72 (16.7%), followed by E76 (13.3%). The median variant allele frequency (VAF) of PTPN11 mutant gene is 18.4%. The patients were divided into two groups according to PTPN11 VAF 35.3% (upper quartile). We observed that the peripheral blood leukocyte count in patients with VAF ≥35.3% was significantly higher than patients with VAF < 35.3% (p = 0.019) and also closely related to M5 (p = 0.016) and internal tandem duplication (ITD) of FMS-like tyrosine kinase 3 (FLT3) (FLT3-ITD) mutation (p = 0.048). Taking PTPN11 VAF 20% and 35.3% as the cutoff value, the patients were divided into two groups, and the overall survival and event-free survival (EFS) of the two groups were not significant. Multivariate analysis of Cox risk ratio model showed that white blood cell count and Eastern Cooperative Oncology Group (ECOG) physical status score were independent risk factors affecting the EFS. Conclusion Our study observed that PTPN11 VAF may not be a prognostic factor in patients with PTPN11mut AML. Newly diagnosed high white blood cell count and poor performance status were independent risk factors for EFS in PTPN11mut AML.
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Affiliation(s)
- Rui Huang
- Department of Hematology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People’s Republic of China
| | - Yi-Ting Zhang
- Department of Hematology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People’s Republic of China
| | - Yu Lin
- Department of Hematology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People’s Republic of China
| | - Ru-Li Pang
- Department of Hematology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People’s Republic of China
| | - Zhi Yang
- Department of Hematology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People’s Republic of China
| | - Wei-Hua Zhao
- Department of Hematology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People’s Republic of China
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15
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Zhang L, Xu L. Fgf2 and Ptpn11 play a role in cerebral injury caused by sevoflurane anesthesia. Medicine (Baltimore) 2023; 102:e36108. [PMID: 37960778 PMCID: PMC10637467 DOI: 10.1097/md.0000000000036108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 10/23/2023] [Indexed: 11/15/2023] Open
Abstract
Sevoflurane is a new inhaled anesthetic, which has better physical properties than the existing inhalational anesthetics, rapid induction, less tissue uptake, and faster recovery. Sevoflurane can directly dilators cerebral blood vessels and increase cerebral blood flow, but it also reduces cerebral oxygen metabolism rate, thereby reducing cerebral blood flow. However, the role of Fgf2 and Ptpn11 in cerebral injury caused by sevoflurane anesthesia remains unclear. The sevoflurane anesthesia brain tissue datasets GSE139220 and GSE141242 were downloaded from gene expression omnibus (GEO). Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis (WGCNA) was performed. Construction and analysis of protein-protein interaction (PPI) Network. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG), comparative toxicogenomics database (CTD) were performed. A heat map of gene expression was drawn. TargetScan was used to screen miRNAs regulating DEGs. 500 DEGs were identified. According to GO, in Biological Process analysis, they were mainly enriched in response to hypoxia, blood vessel development, inner ear development, neural tube closure, and aging. In Cellular Component (CC), they were mainly enriched in plasma membrane, integral component of membrane, and basal lamina. In Molecular Function (MF), they were mainly associated with protein binding, Wnt-activated receptor activity, and organic anion transmembrane transporter activity. In the KEGG analysis, they were mainly enriched in proteoglycans in cancer, pathways in cancer, transcriptional misregulation in cancer, basal cell carcinoma, thyroid hormone signaling pathway. In the Metascape enrichment analysis, the GO enrichment items revealed upregulated regulation of vascular endothelial cell proliferation, platelet-derived growth factor receptor signaling pathway, inner ear development, and response to hypoxia. A total of 20 modules were generated. Gene Expression Heatmap showed that the core genes (Fgf2, Pdgfra, Ptpn11, Slc2a1) were highly expressed in sevoflurane anesthesia brain tissue samples. CTD Analysis showed that the 4 core genes (Fgf2, Pdgfra, Ptpn11, Slc2a1) were associated with neurodegenerative diseases, brain injuries, memory disorders, cognitive disorders, neurotoxicity, drug-induced abnormalities, neurological disorders, developmental disorders, and intellectual disabilities. Fgf2 and Ptpn11 are highly expressed in brain tissue after sevoflurane anesthesia, higher the expression level of Fgf2 and Ptpn11, worse the prognosis.
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Affiliation(s)
- Lin Zhang
- Department of Anesthesiology, The Third Affiliated Hospital of Beijing University of Chinese Medicine, Beijing, China
| | - Lingyan Xu
- Department of Disease Control and Prevention, The Third Affiliated Hospital of Beijing University of Chinese Medicine, Beijing, China
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Sheng L, Liu Y, Zhu Y, Zhou J, Hua H. Analysis of the clinical characteristics and prognosis of adult de novo acute myeloid leukemia (none APL) with PTPN11 mutations. Open Med (Wars) 2023; 18:20230830. [PMID: 38025540 PMCID: PMC10655689 DOI: 10.1515/med-2023-0830] [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: 05/28/2023] [Revised: 09/13/2023] [Accepted: 09/29/2023] [Indexed: 12/01/2023] Open
Abstract
We discuss the clinical characteristics and prognostic significance of adult individuals with PTPN11 mutations who have developed acute myeloid leukemia (AML) (none acute promyelocytic leukemia). Next generation sequencing and Sanger sequencing were used to detect 51 gene mutations, and multiplex-PCR was used to detect 41 fusion genes from 232 de novo adult AML patients retrospectively. About 7.76% patients harbored PTPN11 mutations, 20 PTPN11 alterations were identified, all of which were missense mutations in the N-SH2 (n = 16) and PTP (n = 4) domains located in exon 3. Patients with PTPN11 mut had significantly higher platelet counts and hemoglobin levels (p < 0.001), which were mainly detected in M5 (n = 12, 66.67%, p < 0.001) subtype. Patients with MLL-AF6 positive showed a higher frequency of PTPN11 mut (p = 0.018) in the 118 AML cases. PTPN11 mut were accompanied by other mutations, which were NPM1 (44.44%), DNMT3A (38.89%), FLT3 (38.89%), and NRAS (17.2%). PTPN11 mut had a negative impact on the complete remission rate in M5 subtype patients (p < 0.001). However, no statistically significant effect on overall survival (OS) with PTPN11 mut patients in the whole cohort and age group (p > 0.05) was observed. Further analysis revealed no significant difference in OS among NPM1 mut/PTPN11 mut, NPM1 mut/PTPN11 wt, DNMT3A mut/PTPN11 mut, and DNMT3A mut/PTPN11 wt patients (p > 0.05). Multivariate analysis showed the proportion of bone marrow blasts ≥65.4% was a factor significantly affecting OS in PTPN11 mut patients (p = 0.043).
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Affiliation(s)
- Li Sheng
- Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, China
| | - Yajiao Liu
- Nursing Department, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310000, China
| | - Yingying Zhu
- Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, China
| | - Jingfen Zhou
- Department of Hematology, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214122, China
| | - Haiying Hua
- Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, China
- Department of Hematology, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214122, China
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17
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Seipel K, Kohler S, Bacher U, Pabst T. HSP90 Inhibitor PU-H71 in Combination with BH3-Mimetics in the Treatment of Acute Myeloid Leukemia. Curr Issues Mol Biol 2023; 45:7011-7026. [PMID: 37754227 PMCID: PMC10529370 DOI: 10.3390/cimb45090443] [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: 07/26/2023] [Revised: 08/11/2023] [Accepted: 08/21/2023] [Indexed: 09/28/2023] Open
Abstract
Targeting the molecular chaperone HSP90 and the anti-apoptotic proteins MCL1 and BCL2 may be a promising novel approach in the treatment of acute myeloid leukemia (AML). The HSP90 inhibitor PU-H71, MCL1 inhibitor S63845, and BCL2 inhibitor venetoclax were assessed as single agents and in combination for their ability to induce apoptosis and cell death in leukemic cells. AML cells represented all major morphologic and molecular subtypes including FLT3-ITD and TP53 mutant AML cell lines and a variety of patient-derived AML cells. Results: PU-H71 and combination treatments with MCL1 inhibitor S63845 or BCL2 inhibitor venetoclax induced cell cycle arrest and apoptosis in susceptible AML cell lines and primary AML. The majority of the primary AML samples were responsive to PU-H71 in combination with BH3 mimetics. Elevated susceptibility to PU-H71 and S63845 was associated with FLT3 mutated AML with CD34 < 20%. Elevated susceptibility to PU-H71 and venetoclax was associated with primary AML with CD117 > 80% and CD11b < 45%. The combination of HSP90 inhibitor PU-H71 and MCL1 inhibitor S63845 may be a candidate treatment for FLT3-mutated AML with moderate CD34 positivity while the combination of HSP90 inhibitor PU-H71 and BCL2 inhibitor venetoclax may be more effective in the treatment of primitive AML with high CD117 and low CD11b positivity.
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Affiliation(s)
- Katja Seipel
- Department for Biomedical Research, University of Bern, 3008 Bern, Switzerland;
| | - Scarlett Kohler
- Department for Biomedical Research, University of Bern, 3008 Bern, Switzerland;
| | - Ulrike Bacher
- Department of Hematology, University Hospital Bern, 3010 Bern, Switzerland;
| | - Thomas Pabst
- Department of Medical Oncology, University Hospital Bern, 3010 Bern, Switzerland;
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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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19
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Testa U, Pelosi E, Castelli G. Genetic, Phenotypic, and Clinical Heterogeneity of NPM1-Mutant Acute Myeloid Leukemias. Biomedicines 2023; 11:1805. [PMID: 37509445 PMCID: PMC10376179 DOI: 10.3390/biomedicines11071805] [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: 05/16/2023] [Revised: 06/13/2023] [Accepted: 06/21/2023] [Indexed: 07/30/2023] Open
Abstract
The current classification of acute myeloid leukemia (AML) relies largely on genomic alterations. AML with mutated nucleophosmin 1 (NPM1-mut) is the largest of the genetically defined groups, involving about 30% of adult AMLs and is currently recognized as a distinct entity in the actual AML classifications. NPM1-mut AML usually occurs in de novo AML and is associated predominantly with a normal karyotype and relatively favorable prognosis. However, NPM1-mut AMLs are genetically, transcriptionally, and phenotypically heterogeneous. Furthermore, NPM1-mut is a clinically heterogenous group. Recent studies have in part clarified the consistent heterogeneities of these AMLs and have strongly supported the need for an additional stratification aiming to improve the therapeutic response of the different subgroups of NPM1-mut AML patients.
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Affiliation(s)
- Ugo Testa
- Department of Oncology, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Elvira Pelosi
- Department of Oncology, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
| | - Germana Castelli
- Department of Oncology, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy
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20
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Cao L, Ai Y, Dong Y, Li D, Wang H, Sun K, Wang C, Zhang M, Yan D, Li H, Liang G, Yang B. Bioinformatics analysis reveals the landscape of immune cell infiltration and novel immune-related biomarkers in moyamoya disease. Front Genet 2023; 14:1101612. [PMID: 37265961 PMCID: PMC10230076 DOI: 10.3389/fgene.2023.1101612] [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: 11/18/2022] [Accepted: 04/28/2023] [Indexed: 06/03/2023] Open
Abstract
Objective: This study aimed to identify immune infiltration characteristics and new immunological diagnostic biomarkers in the cerebrovascular tissue of moyamoya disease (MMD) using bioinformatics analysis. Methods: GSE189993 and GSE141022 were downloaded from the GEO database. Differentially expressed gene and PPI analysis were performed. After performing WGCNA, the most significant module associated with MMD was obtained. Next, functional pathways according to GSEA, GO, and KEGG were enriched for the aforementioned core genes obtained from PPI and WGCNA. Additionally, immune infiltration, using the CIBERSORT deconvolution algorithm, immune-related biomarkers, and the relationship between these genes, was further explored. Finally, diagnostic accuracy was verified with ROC curves in the validation dataset GSE157628. Results: A total of 348 DEGs were screened, including 89 downregulated and 259 upregulated genes. The thistlel module was detected as the most significant module associated with MMD. Functional analysis of the core genes was chiefly involved in the immune response, immune system process, protein tyrosine kinase activity, secretory granule, and so on. Among 13 immune-related overlapping genes, 4 genes (BTK, FGR, PTPN11, and SYK) were identified as potential diagnostic biomarkers, where PTPN11 showed the highest specificity and sensitivity. Meanwhile, a higher proportion of eosinophils, not T cells or B cells, was demonstrated in the specific immune infiltration landscape of MMD. Conclusion: Immune activities and immune cells were actively involved in the progression of MMD. BTK, FGR, PTPN11, and SYK were identified as potential immune diagnostic biomarkers. These immune-related genes and cells may provide novel insights for immunotherapy in the future.
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Affiliation(s)
- Lei Cao
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yunzheng Ai
- Department of Neurosurgery, General Hospital of Northern Theater Command, Shenyang, China
| | - Yang Dong
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Dongpeng Li
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Hao Wang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kaiwen Sun
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chenchao Wang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Manxia Zhang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Dongming Yan
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Hongwei Li
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Guobiao Liang
- Department of Neurosurgery, General Hospital of Northern Theater Command, Shenyang, China
| | - Bo Yang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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21
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Liu Y, Zhang J, Du Z, Huang J, Cheng Y, Yi W, Li T, Yang J, Chen C. Comprehensive analysis of PTPN family expression and prognosis in acute myeloid leukemia. Front Genet 2023; 13:1087938. [PMID: 36699453 PMCID: PMC9868563 DOI: 10.3389/fgene.2022.1087938] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 12/23/2022] [Indexed: 01/11/2023] Open
Abstract
Background: Tyrosyl phosphorylation is carried out by a group of enzymes known as non-receptor protein tyrosine phosphatases (PTPNs). In the current investigation, it is hoped to shed light on the relationships between the expression patterns of PTPN family members and the prognosis of acute myeloid leukemia (AML). Methods: PTPN expression was examined using GEPIA and GEO databases. To investigate the connection between PTPN expression and survival in AML patients, we downloaded data from the Broad TCGA Firehose and Clinical Proteomic Tumor Analysis (CPTAC) of the Cancer Genome Atlas (TCGA). We used quantitative real-time PCR (qRT-PCR) to confirm that essential genes were performed in clinical samples and cell lines. We then used western blot to verify that the genes expressed in the above databases were positive in normal tissues, AML patient samples, and AML cell lines. Next, we investigated associations between genome-wide expression profiles and PTPN6 expression using the GEO datasets. We investigated the interactive exploration of multidimensional cancer genomics using the cBioPortal datasets. Using the DAVID database, a study of gene ontology enrichment was performed. The protein-protein interaction (PPI) network was created using the STRING portal, and the gene-gene interaction network was performed using GeneMANIA. Results: Data from GEO and GEPIA revealed that most PTPN family members were linked to AML. Patients with leukemia have elevated levels of several PTPN members. All of the AML patients' poor overall survival (OS, p < .05) was significantly linked with higher expression of PTPN1, PTPN6, and PTPN7. Additionally, clinical samples showed that the expression of PTPN 6, PTPN 7, PTPN 13, and PTPN 14 was higher than normal in AML patients (p = .0116, p = .0034, p = .0092, and p = .0057, respectively) and AML cell lines (p = .0004, p = .0035, p = .0357, and p = .0177, respectively). Western blotting results showed that the expression of PTPN6 in AML samples and AML cell lines was significantly higher than that in normal control samples. Conclusion: Differentially expressed PTPN family members were found in AML. The prognosis of patients and PTPN gene expression were shown to be correlated. PTPN6 is one of these members and may be used as an AML diagnostic and prognostic marker.
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Affiliation(s)
- Yong Liu
- Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China
| | - Jing Zhang
- Department of Breast and Thyroid Surgery, Guangzhou Women and Children’s Medical Center, Guangzhou, China
| | - Zefan Du
- Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China
| | - Junbin Huang
- Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China
| | - Yucai Cheng
- Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China
| | - Wenfang Yi
- Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China
| | - Tianwen Li
- Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China
| | - Jing Yang
- Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China
| | - Chun Chen
- Division of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China,*Correspondence: Chun Chen,
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22
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Jiang G, Jin P, Xiao X, Shen J, Li R, Zhang Y, Li X, Xue K, Li J. Identification and validation of a novel CD8+ T cell-associated prognostic model based on ferroptosis in acute myeloid leukemia. Front Immunol 2023; 14:1149513. [PMID: 37138885 PMCID: PMC10150955 DOI: 10.3389/fimmu.2023.1149513] [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: 01/22/2023] [Accepted: 03/28/2023] [Indexed: 05/05/2023] Open
Abstract
Acute myeloid leukemia (AML) is a highly aggressive cancer with great heterogeneity and variability in prognosis. Though European Leukemia Net (ELN) 2017 risk classification has been widely used, nearly half of patients were stratified to "intermediate" risk and requires more accurate classification via excavating biological features. As new evidence showed that CD8+ T cell can kill cancer cells through ferroptosis pathway. We firstly use CIBERSORT algorithm to divide AMLs into CD8+ high and CD8+ low T cell groups, then 2789 differentially expressed genes (DEGs) between groups were identified, of which 46 ferroptosis-related genes associated with CD8+ T cell were sorted out. GO, KEGG analysis and PPI network were conducted based on these 46 DEGs. By jointly using LASSO algorithm and Cox univariate regression, we generated a 6-gene prognostic signature comprising VEGFA, KLHL24, ATG3, EIF2AK4, IDH1 and HSPB1. Low-risk group shows a longer overall survival. We then validated the prognostic value of this 6-gene signature using two independent external datasets and patient sample collection dataset. We also proved that incorporation of the 6-gene signature obviously enhanced the accuracy of ELN risk classification. Finally, gene mutation analysis, drug sensitive prediction, GSEA and GSVA analysis were conducted between high-risk and low-risk AML patients. Collectively, our findings suggested that the prognostic signature based on CD8+ T cell-related ferroptosis genes can optimize the risk stratification and prognostic prediction of AML patients.
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Affiliation(s)
- Ge Jiang
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Peng Jin
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiao Xiao
- Department of Orthopedic, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jie Shen
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ran Li
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yunxiang Zhang
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaoyang Li
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Kai Xue, ; Xiaoyang Li, ; Junmin Li,
| | - Kai Xue
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Kai Xue, ; Xiaoyang Li, ; Junmin Li,
| | - Junmin Li
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Kai Xue, ; Xiaoyang Li, ; Junmin Li,
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23
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Saultz JN, Tyner JW. Chasing leukemia differentiation through induction therapy, relapse and transplantation. Blood Rev 2023; 57:101000. [PMID: 36041918 DOI: 10.1016/j.blre.2022.101000] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 07/23/2022] [Accepted: 08/09/2022] [Indexed: 01/28/2023]
Abstract
Despite rapid advances in our understanding of acute myeloid leukemia (AML), the disease remains challenging to treat with 5-year survival for adult patients 20 years or older estimated to be 26% (Cancer 2021). The use of new targeted therapies including BCL2, IDH1/IDH2, and FLT3 inhibitors has revolutionized treatment approaches but also changed the disease trajectory with unique modes of resistance. Recent studies have shown that stem cell maturation state drives expression level and/or dependence on various pathways, critical to determining drug response. Instead of anticipating these changes, we remain behind the curve chasing the next expanded clone. This review will focus on current approaches to treatment in AML, including defining the significance of blast differentiation state on chemotherapeutic response, signaling pathway dependence, metabolism, immune response, and phenotypic changes. We conclude that multimodal treatment approaches are necessary to target both the immature and mature clones, thereby, sustaining drug response.
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Affiliation(s)
- Jennifer N Saultz
- Knight Cancer Institute, Oregon Health and Science University, Portland, OR, United States of America; Division of Hematology and Medical Oncology, Oregon Health and Science University, Portland, OR, United States of America.
| | - Jeffrey W Tyner
- Knight Cancer Institute, Oregon Health and Science University, Portland, OR, United States of America; Division of Hematology and Medical Oncology, Oregon Health and Science University, Portland, OR, United States of America; Department of Cell, Developmental and Cancer Biology, Oregon Health and Science University, Portland, OR, United States of America
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24
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Sun Y, Zhang F, Huo L, Cai W, Wang Q, Wen L, Yan L, Shen H, Xu X, Chen S. Clinical characteristics and prognostic analysis of acute myeloid leukemia patients with PTPN11 mutations. Hematology 2022; 27:1184-1190. [DOI: 10.1080/16078454.2022.2140274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Affiliation(s)
- Yueyue Sun
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Soochow University, Suzhou, People’s Republic of China
- Cyrus Tang hematology center, Soochow University, Suzhou, People’s Republic of China
| | - Fenghong Zhang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Soochow University, Suzhou, People’s Republic of China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, People’s Republic of China
| | - Li Huo
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Soochow University, Suzhou, People’s Republic of China
| | - Wenzhi Cai
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Soochow University, Suzhou, People’s Republic of China
| | - Qinrong Wang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Soochow University, Suzhou, People’s Republic of China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, People’s Republic of China
| | - Lijun Wen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Soochow University, Suzhou, People’s Republic of China
- Institute of Blood and Marrow Transplantation, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, People’s Republic of China
| | - Lingzhi Yan
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Soochow University, Suzhou, People’s Republic of China
| | - Hongjie Shen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Soochow University, Suzhou, People’s Republic of China
| | - Xiaoyu Xu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Soochow University, Suzhou, People’s Republic of China
| | - Suning Chen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Soochow University, Suzhou, People’s Republic of China
- Cyrus Tang hematology center, Soochow University, Suzhou, People’s Republic of China
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25
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Li S, Han Y, Zhang Q, Tang D, Li J, Weng L. Comprehensive molecular analyses of an autoimmune-related gene predictive model and immune infiltrations using machine learning methods in moyamoya disease. Front Mol Biosci 2022; 9:991425. [PMID: 36605987 PMCID: PMC9808060 DOI: 10.3389/fmolb.2022.991425] [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: 07/11/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022] Open
Abstract
Background: Growing evidence suggests the links between moyamoya disease (MMD) and autoimmune diseases. However, the molecular mechanism from genetic perspective remains unclear. This study aims to clarify the potential roles of autoimmune-related genes (ARGs) in the pathogenesis of MMD. Methods: Two transcription profiles (GSE157628 and GSE141025) of MMD were downloaded from GEO databases. ARGs were obtained from the Gene and Autoimmune Disease Association Database (GAAD) and DisGeNET databases. Differentially expressed ARGs (DEARGs) were identified using "limma" R packages. GO, KEGG, GSVA, and GSEA analyses were conducted to elucidate the underlying molecular function. There machine learning methods (LASSO logistic regression, random forest (RF), support vector machine-recursive feature elimination (SVM-RFE)) were used to screen out important genes. An artificial neural network was applied to construct an autoimmune-related signature predictive model of MMD. The immune characteristics, including immune cell infiltration, immune responses, and HLA gene expression in MMD, were explored using ssGSEA. The miRNA-gene regulatory network and the potential therapeutic drugs for hub genes were predicted. Results: A total of 260 DEARGs were identified in GSE157628 dataset. These genes were involved in immune-related pathways, infectious diseases, and autoimmune diseases. We identified six diagnostic genes by overlapping the three machine learning algorithms: CD38, PTPN11, NOTCH1, TLR7, KAT2B, and ISG15. A predictive neural network model was constructed based on the six genes and presented with great diagnostic ability with area under the curve (AUC) = 1 in the GSE157628 dataset and further validated by GSE141025 dataset. Immune infiltration analysis showed that the abundance of eosinophils, natural killer T (NKT) cells, Th2 cells were significant different between MMD and controls. The expression levels of HLA-A, HLA-B, HLA-C, HLA-DMA, HLA-DRB6, HLA-F, and HLA-G were significantly upregulated in MMD. Four miRNAs (mir-26a-5p, mir-1343-3p, mir-129-2-3p, and mir-124-3p) were identified because of their interaction at least with four hub DEARGs. Conclusion: Machine learning was used to develop a reliable predictive model for the diagnosis of MMD based on ARGs. The uncovered immune infiltration and gene-miRNA and gene-drugs regulatory network may provide new insight into the pathogenesis and treatment of MMD.
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Affiliation(s)
- Shifu Li
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China,National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, Hunan, China
| | - Ying Han
- Department of Oral and Maxillofacial Surgery, Center of Stomatology, Xiangya Hospital of Central South University, Changsha, Hunan, China,Center for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Qian Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China,National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, Hunan, China
| | - Dong Tang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China,National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, Hunan, China
| | - Jian Li
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China,National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, Hunan, China,Hydrocephalus Center, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Ling Weng
- National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, Hunan, China,Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China,Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China,Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China,Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China,*Correspondence: Ling Weng,
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26
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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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27
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Rivera D, Kim K, Kanagal-Shamanna R, Borthakur G, Montalban-Bravo G, Daver N, Dinardo C, Short NJ, Yilmaz M, Pemmaraju N, Takahashi K, Jabbour EJ, Pierce S, Konopleva M, Bhalla K, Garcia-Manero G, Ravandi F, Kantarjian H, Kadia TM. Implications of RAS mutational status in subsets of patients with newly diagnosed acute myeloid leukemia across therapy subtypes. Am J Hematol 2022; 97:1599-1606. [PMID: 36117258 DOI: 10.1002/ajh.26731] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Revised: 09/06/2022] [Accepted: 09/09/2022] [Indexed: 01/31/2023]
Abstract
Activating mutations in RAS have been reported in about 10-15% of patients with AML; previous studies have not identified a prognostic significance. However, RAS mutations have emerged as a potential resistance mechanism to treatment with inhibitors of FLT3, IDH, and BCL2. We aimed to determine the characteristics and outcomes of patients with RAS-mutated (RAS-mut) AML across therapy subsets of 1410 patients newly diagnosed (ND AML). RAS-mut was observed in 273 (20%) patients. Overall, patients with RAS-mut AML had an estimated 3-year survival rate of 38% vs. 28% in those with RAS wild type (RAS-wt), p = .01. Among patients with RAS-mut, favorable karyotype and concomitant NPM1 mutations were associated with a higher CR/CRi rate, OR 23.2 (95% CI: 2.7-192.7; p < .001) and OR 2.8 (95% CI: 1.1-6.9; p = .02), respectively, while secondary and treated secondary (ts)-AML were associated with low response rates, OR 0.34 (95% CI: 0.1-0.9; p = .04) and OR 0.22 (95% CI: 0.09-0.5; p = .001), respectively. Intensive chemotherapy was associated with high response rates OR 5.9 (95% CI: 2.9-12.2; p < .001). Better median OS was observed among those with favorable karyotype, HR 0.28 (95% CI: 0.1-0.6; p = .002), and those treated with intensive chemotherapy, HR 0.42 (95% CI: 0.2-0.6 p < .001). Conversely, ts- AML and co-occurrence of mutations in TP53 were associated with poor median OS; HR 2.3 (95% CI: 1.4-3.9; p = .001) and HR 1.7 (95% CI: 0.9-3.1; p = .06), respectively. The addition of venetoclax was associated with a non-significant improvement in CR/CRi and OS.
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Affiliation(s)
- Daniel Rivera
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Kunhwa Kim
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Rashmi Kanagal-Shamanna
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Gautam Borthakur
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | | | - Naval Daver
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Courtney Dinardo
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Nicholas J Short
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Musa Yilmaz
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Naveen Pemmaraju
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Koichi Takahashi
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Elias J Jabbour
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Sherry Pierce
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Marina Konopleva
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Kapil Bhalla
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Guillermo Garcia-Manero
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Farhad Ravandi
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Hagop Kantarjian
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Tapan M Kadia
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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28
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Almadhor A, Sattar U, Al Hejaili A, Ghulam Mohammad U, Tariq U, Ben Chikha H. An efficient computer vision-based approach for acute lymphoblastic leukemia prediction. Front Comput Neurosci 2022; 16:1083649. [PMID: 36507304 PMCID: PMC9729282 DOI: 10.3389/fncom.2022.1083649] [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: 10/29/2022] [Accepted: 11/14/2022] [Indexed: 11/25/2022] Open
Abstract
Leukemia (blood cancer) diseases arise when the number of White blood cells (WBCs) is imbalanced in the human body. When the bone marrow produces many immature WBCs that kill healthy cells, acute lymphocytic leukemia (ALL) impacts people of all ages. Thus, timely predicting this disease can increase the chance of survival, and the patient can get his therapy early. Manual prediction is very expensive and time-consuming. Therefore, automated prediction techniques are essential. In this research, we propose an ensemble automated prediction approach that uses four machine learning algorithms K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Naive Bayes (NB). The C-NMC leukemia dataset is used from the Kaggle repository to predict leukemia. Dataset is divided into two classes cancer and healthy cells. We perform data preprocessing steps, such as the first images being cropped using minimum and maximum points. Feature extraction is performed to extract the feature using pre-trained Convolutional Neural Network-based Deep Neural Network (DNN) architectures (VGG19, ResNet50, or ResNet101). Data scaling is performed by using the MinMaxScaler normalization technique. Analysis of Variance (ANOVA), Recursive Feature Elimination (RFE), and Random Forest (RF) as feature Selection techniques. Classification machine learning algorithms and ensemble voting are applied to selected features. Results reveal that SVM with 90.0% accuracy outperforms compared to other algorithms.
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Affiliation(s)
- Ahmad Almadhor
- Department of Computer Engineering and Networks, College of Computer and Information Sciences, Jouf University, Sakaka, Saudi Arabia,*Correspondence: Ahmad Almadhor
| | - Usman Sattar
- Department of Management Science, Beaconhouse National University, Lahore, Pakistan,Usman Sattar
| | - Abdullah Al Hejaili
- Computer Science Department, Faculty of Computers & Information Technology, University of Tabuk, Tabuk, Saudi Arabia
| | - Uzma Ghulam Mohammad
- Department of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan
| | - Usman Tariq
- Department of Management Information Systems, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Haithem Ben Chikha
- Department of Computer Engineering and Networks, College of Computer and Information Sciences, Jouf University, Sakaka, Saudi Arabia
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29
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Proteomic and phosphoproteomic landscapes of acute myeloid leukemia. Blood 2022; 140:1533-1548. [PMID: 35895896 PMCID: PMC9523374 DOI: 10.1182/blood.2022016033] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 07/14/2022] [Indexed: 01/21/2023] Open
Abstract
We have developed a deep-scale proteome and phosphoproteome database from 44 representative acute myeloid leukemia (AML) patients from the LAML TCGA dataset and 6 healthy bone marrow-derived controls. After confirming data quality, we orthogonally validated several previously undescribed features of AML revealed by the proteomic data. We identified examples of posttranscriptionally regulated proteins both globally (ie, in all AML samples) and also in patients with recurrent AML driver mutations. For example, samples with IDH1/2 mutations displayed elevated levels of the 2-oxoglutarate-dependent histone demethylases KDM4A/B/C, despite no changes in messenger RNA levels for these genes; we confirmed this finding in vitro. In samples with NPMc mutations, we identified several nuclear importins with posttranscriptionally increased protein abundance and showed that they interact with NPMc but not wild-type NPM1. We identified 2 cell surface proteins (CD180 and MRC1/CD206) expressed on AML blasts of many patients (but not healthy CD34+ stem/progenitor cells) that could represent novel targets for immunologic therapies and confirmed these targets via flow cytometry. Finally, we detected nearly 30 000 phosphosites in these samples; globally, AML samples were associated with the abnormal phosphorylation of specific residues in PTPN11, STAT3, AKT1, and PRKCD. FLT3-TKD samples were associated with increased phosphorylation of activating tyrosines on the cytoplasmic Src-family tyrosine kinases FGR and HCK and related signaling proteins. PML-RARA-initiated AML samples displayed a unique phosphorylation signature, and TP53-mutant samples showed abundant phosphorylation of serine-183 on TP53 itself. This publicly available database will serve as a foundation for further investigations of protein dysregulation in AML pathogenesis.
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30
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Eckardt JN, Stölzel F, Kunadt D, Röllig C, Stasik S, Wagenführ L, Jöhrens K, Kuithan F, Krämer A, Scholl S, Hochhaus A, Crysandt M, Brümmendorf TH, Naumann R, Steffen B, Kunzmann V, Einsele H, Schaich M, Burchert A, Neubauer A, Schäfer-Eckart K, Schliemann C, Krause SW, Herbst R, Hänel M, Hanoun M, Kaiser U, Kaufmann M, Rácil Z, Mayer J, Kroschinsky F, Berdel WE, Ehninger G, Serve H, Müller-Tidow C, Platzbecker U, Baldus CD, Schetelig J, Bornhäuser M, Thiede C, Middeke JM. Molecular profiling and clinical implications of patients with acute myeloid leukemia and extramedullary manifestations. J Hematol Oncol 2022; 15:60. [PMID: 35562747 PMCID: PMC9107142 DOI: 10.1186/s13045-022-01267-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 04/17/2022] [Indexed: 12/05/2022] Open
Abstract
Background Extramedullary manifestations (EM) are rare in acute myeloid leukemia (AML) and their impact on clinical outcomes is controversially discussed. Methods We retrospectively analyzed a large multi-center cohort of 1583 newly diagnosed AML patients, of whom 225 (14.21%) had EM. Results AML patients with EM presented with significantly higher counts of white blood cells (p < 0.0001), peripheral blood blasts (p < 0.0001), bone marrow blasts (p = 0.019), and LDH (p < 0.0001). Regarding molecular genetics, EM AML was associated with mutations of NPM1 (OR: 1.66, p < 0.001), FLT3-ITD (OR: 1.72, p < 0.001) and PTPN11 (OR: 2.46, p < 0.001). With regard to clinical outcomes, EM AML patients were less likely to achieve complete remissions (OR: 0.62, p = 0.004), and had a higher early death rate (OR: 2.23, p = 0.003). Multivariable analysis revealed EM as an independent risk factor for reduced overall survival (hazard ratio [HR]: 1.43, p < 0.001), however, for patients who received allogeneic hematopoietic cell transplantation (HCT) survival did not differ. For patients bearing EM AML, multivariable analysis unveiled mutated TP53 and IKZF1 as independent risk factors for reduced event-free (HR: 4.45, p < 0.001, and HR: 2.05, p = 0.044, respectively) and overall survival (HR: 2.48, p = 0.026, and HR: 2.63, p = 0.008, respectively). Conclusion Our analysis represents one of the largest cohorts of EM AML and establishes key molecular markers linked to EM, providing new evidence that EM is associated with adverse risk in AML and may warrant allogeneic HCT in eligible patients with EM. Supplementary Information The online version contains supplementary material available at 10.1186/s13045-022-01267-7.
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Affiliation(s)
- Jan-Niklas Eckardt
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany.
| | - Friedrich Stölzel
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany
| | - Desiree Kunadt
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany
| | - Christoph Röllig
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany
| | - Sebastian Stasik
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany
| | - Lisa Wagenführ
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany
| | - Korinna Jöhrens
- Department of Pathology, University Hospital Carl Gustav Carus, Dresden, Germany
| | - Friederike Kuithan
- Medical Care Center, University Hospital Carl Gustav Carus, Dresden, Germany
| | - Alwin Krämer
- German Cancer Research Center (DKFZ) and Medical Clinic V, University Hospital Heidelberg, Heidelberg, Germany
| | - Sebastian Scholl
- Department of Internal Medicine II, Jena University Hospital, Jena, Germany
| | - Andreas Hochhaus
- Department of Internal Medicine II, Jena University Hospital, Jena, Germany
| | - Martina Crysandt
- Department of Hematology, Oncology, Hemostaseology, and Cell Therapy, University Hospital RWTH Aachen, Aachen, Germany
| | - Tim H Brümmendorf
- Department of Hematology, Oncology, Hemostaseology, and Cell Therapy, University Hospital RWTH Aachen, Aachen, Germany
| | - Ralph Naumann
- Medical Clinic III, St. Marien-Hospital Siegen, Siegen, Germany
| | - Björn Steffen
- Medical Clinic II, University Hospital Frankfurt, Frankfurt (Main), Germany
| | - Volker Kunzmann
- Medical Clinic and Policlinic II, University Hospital Würzburg, Würzburg, Germany
| | - Hermann Einsele
- Medical Clinic and Policlinic II, University Hospital Würzburg, Würzburg, Germany
| | - Markus Schaich
- Department of Hematology, Oncology and Palliative Care, Rems-Murr-Hospital Winnenden, Winnenden, Germany
| | - Andreas Burchert
- Department of Hematology, Oncology and Immunology, Philipps-University-Marburg, Marburg, Germany
| | - Andreas Neubauer
- Department of Hematology, Oncology and Immunology, Philipps-University-Marburg, Marburg, Germany
| | - Kerstin Schäfer-Eckart
- Department of Internal Medicine V, Paracelsus Medizinische Privatuniversität and University Hospital Nuremberg, Nuremberg, Germany
| | | | - Stefan W Krause
- Medical Clinic V, University Hospital Erlangen, Erlangen, Germany
| | - Regina Herbst
- Medical Clinic III, Chemnitz Hospital AG, Chemnitz, Germany
| | - Mathias Hänel
- Medical Clinic III, Chemnitz Hospital AG, Chemnitz, Germany
| | - Maher Hanoun
- Department of Hematology, University Hospital Essen, Essen, Germany
| | - Ulrich Kaiser
- Medical Clinic II, St. Bernward Hospital, Hildesheim, Germany
| | - Martin Kaufmann
- Department of Hematology, Oncology and Palliative Care, Robert-Bosch-Hospital, Stuttgart, Germany
| | - Zdenek Rácil
- Department of Internal Medicine, Hematology and Oncology, Masaryk University Hospital, Brno, Czech Republic
| | - Jiri Mayer
- Department of Internal Medicine, Hematology and Oncology, Masaryk University Hospital, Brno, Czech Republic
| | - Frank Kroschinsky
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany
| | - Wolfgang E Berdel
- Department of Medicine A, University Hospital Münster, Münster, Germany
| | - Gerhard Ehninger
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany
| | - Hubert Serve
- Medical Clinic II, University Hospital Frankfurt, Frankfurt (Main), Germany
| | - Carsten Müller-Tidow
- German Cancer Research Center (DKFZ) and Medical Clinic V, University Hospital Heidelberg, Heidelberg, Germany
| | - Uwe Platzbecker
- Medical Clinic I Hematology and Celltherapy, University Hospital Leipzig, Leipzig, Germany
| | - Claudia D Baldus
- Department of Internal Medicine, University Hospital Kiel, Kiel, Germany
| | - Johannes Schetelig
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany.,DKMS Clinical Trials Unit, Dresden, Germany
| | - Martin Bornhäuser
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany.,German Consortium for Translational Cancer Research DKFZ, Heidelberg, Germany.,National Center for Tumor Diseases (NCT), Dresden, Germany
| | - Christian Thiede
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany
| | - Jan Moritz Middeke
- Department of Internal Medicine I, University Hospital Carl Gustav Carus, Fetscherstraße 74, 01307, Dresden, Saxony, Germany
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Liu J, Qin W, Wang B, Wang Z, Hua H, Zhou F, Jia Z, Wu P, Chao H, Lu X. PTPN11 mutations in adult acute myeloid leukaemia: prevalence and clinical implications in the context of NPM1 mutation. Leuk Res 2022; 118:106859. [DOI: 10.1016/j.leukres.2022.106859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 04/14/2022] [Accepted: 05/07/2022] [Indexed: 11/30/2022]
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32
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Sun L, Wang B, Sun T, Zhou F, Zhu B, Li C, Wan H, Ding Z. Investigation on the mechanism of 2,3,4',5-Tetrahydroxystilbene 2-o-D-glucoside in the treatment of inflammation based on network pharmacology. Comput Biol Med 2022; 145:105448. [PMID: 35364310 DOI: 10.1016/j.compbiomed.2022.105448] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 03/20/2022] [Accepted: 03/21/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Inflammation is the pathogenesis of various chronic diseases plaguing clinic for years.Fallopia multiflora (Thunb.) is a traditional Chinese herbal medicine with a long history of application in detoxification and anti-inflammation. 2,3,4',5-Tetrahydroxystilbene 2-o-D-glucoside (TSG) is a main active compound of F. multiflora. However, the mechanism of TSG in the treatment of inflammation remains unknown. METHODS Network pharmacology and molecular docking were employed to explore the mechanism of anti-inflammatory effect of TSG. Potential targets of TSG and inflammation were obtained from Swiss Target Prediction, Pharm Mapper, and GeneCards database. Protein-protein interaction (PPI) networks, GO and KEGG pathway enrichment analysis were performed to elucidate the interaction of targets. Moreover, the anti-inflammatory effect of TSG was validated by in vitro experiments using flow cytometry, RT-qPCR, Western blot, and immunocytochemistry assays. RESULTS PPI network and gene enrichment analysis showed that TSG may exert a protein kinase binding activity, and IKBKB, MAPK1, NFKBIA, and RELA were predicted as the targets of anti-inflammation. Verified by molecular docking and Western blot, TSG may target NF-κB and ERK2 related signals to alleviate inflammatory damage. Furthermore, TSG effectively downregulated the expression of inflammatory cytokine, the nuclear translocation of NF-κB p65, and the production of reactive oxygen species (ROS). CONCLUSION TSG possesses significant anti-inflammatory effect. TSG may display a protein kinase binding activity and target NF-κB and ERK2 related signals to treat the inflammation. This work may enlighten the potential application of TSG in anti-inflammation and indicate network pharmacology was an effective tool for the further study of TCM.
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Affiliation(s)
- Ling Sun
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, People's Republic of China.
| | - Bixu Wang
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, People's Republic of China.
| | - Tong Sun
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, People's Republic of China.
| | - Fangmei Zhou
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, People's Republic of China.
| | - Bingqi Zhu
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, People's Republic of China.
| | - Chang Li
- Institute of Cardio-cerebrovascular Disease, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, People's Republic of China.
| | - Haitong Wan
- Institute of Cardio-cerebrovascular Disease, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, People's Republic of China.
| | - Zhishan Ding
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, People's Republic of China.
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33
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Raveendra-Panickar D, Finlay D, Layng FI, Lambert LJ, Celeridad M, Zhao M, Barbosa K, De Backer LJS, Kwong E, Gosalia P, Rodiles S, Holleran J, Ardecky R, Grotegut S, Olson S, Hutchinson JH, Pasquale EB, Vuori K, Deshpande AJ, Cosford NDP, Tautz L. Discovery of novel furanylbenzamide inhibitors that target oncogenic tyrosine phosphatase SHP2 in leukemia cells. J Biol Chem 2022; 298:101477. [PMID: 34896393 PMCID: PMC8760490 DOI: 10.1016/j.jbc.2021.101477] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 12/03/2021] [Indexed: 11/11/2022] Open
Abstract
Disturbance of the dynamic balance between tyrosine phosphorylation and dephosphorylation of signaling molecules, controlled by protein tyrosine kinases and protein tyrosine phosphatases (PTPs), is known to lead to the development of cancer. While most approved targeted cancer therapies are tyrosine kinase inhibitors, PTPs have long been stigmatized as undruggable and have only recently gained renewed attention in drug discovery. One PTP target is the Src-homology 2 domain-containing phosphatase 2 (SHP2). SHP2 is implicated in tumor initiation, progression, metastasis, and treatment resistance, primarily because of its role as a signaling nexus of the extracellular signal-regulated kinase pathway, acting upstream of the small GTPase Ras. Efforts to develop small molecules that target SHP2 are ongoing, and several SHP2 allosteric inhibitors are currently in clinical trials for the treatment of solid tumors. However, while the reported allosteric inhibitors are highly effective against cells expressing WT SHP2, none have significant activity against the most frequent oncogenic SHP2 variants that drive leukemogenesis in several juvenile and acute leukemias. Here, we report the discovery of novel furanylbenzamide molecules as inhibitors of both WT and oncogenic SHP2. Importantly, these inhibitors readily cross cell membranes, bind and inhibit SHP2 under physiological conditions, and effectively decrease the growth of cancer cells, including triple-negative breast cancer cells, acute myeloid leukemia cells expressing either WT or oncogenic SHP2, and patient-derived acute myeloid leukemia cells. These novel compounds are effective chemical probes of active SHP2 and may serve as starting points for therapeutics targeting WT or mutant SHP2 in cancer.
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Affiliation(s)
- Dhanya Raveendra-Panickar
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Darren Finlay
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Fabiana Izidro Layng
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Lester J Lambert
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Maria Celeridad
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Ming Zhao
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Karina Barbosa
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Laurent J S De Backer
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Elizabeth Kwong
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Palak Gosalia
- Conrad Prebys Center for Chemical Genomics, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Socorro Rodiles
- Conrad Prebys Center for Chemical Genomics, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - John Holleran
- Conrad Prebys Center for Chemical Genomics, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Robert Ardecky
- Conrad Prebys Center for Chemical Genomics, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Stefan Grotegut
- Conrad Prebys Center for Chemical Genomics, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Steven Olson
- Conrad Prebys Center for Chemical Genomics, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - John H Hutchinson
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Elena B Pasquale
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Kristiina Vuori
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Aniruddha J Deshpande
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Nicholas D P Cosford
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA
| | - Lutz Tautz
- NCI-Designated Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA.
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Mouse Models of Frequently Mutated Genes in Acute Myeloid Leukemia. Cancers (Basel) 2021; 13:cancers13246192. [PMID: 34944812 PMCID: PMC8699817 DOI: 10.3390/cancers13246192] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/24/2021] [Accepted: 11/30/2021] [Indexed: 01/19/2023] Open
Abstract
Acute myeloid leukemia is a clinically and biologically heterogeneous blood cancer with variable prognosis and response to conventional therapies. Comprehensive sequencing enabled the discovery of recurrent mutations and chromosomal aberrations in AML. Mouse models are essential to study the biological function of these genes and to identify relevant drug targets. This comprehensive review describes the evidence currently available from mouse models for the leukemogenic function of mutations in seven functional gene groups: cell signaling genes, epigenetic modifier genes, nucleophosmin 1 (NPM1), transcription factors, tumor suppressors, spliceosome genes, and cohesin complex genes. Additionally, we provide a synergy map of frequently cooperating mutations in AML development and correlate prognosis of these mutations with leukemogenicity in mouse models to better understand the co-dependence of mutations in AML.
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Molecular associations, clinical, and prognostic implications of PTPN11 mutations in acute myeloid leukemia (Alliance). Blood Adv 2021; 6:1371-1380. [PMID: 34847232 PMCID: PMC8905707 DOI: 10.1182/bloodadvances.2021006242] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 11/10/2021] [Indexed: 12/04/2022] Open
Abstract
Patients with N-terminal SH2 domain PTPN11 mutations had an early death (<30 days) more often than those with phosphatase domain mutations. PTPN11 mutations are associated with inferior outcomes in AML patients with wild-type NPM1.
Prognostic factors associated with chemotherapy outcomes in patients with acute myeloid leukemia (AML) are extensively reported, and one gene whose mutation is recognized as conferring resistance to several newer targeted therapies is protein tyrosine phosphatase non-receptor type 11 (PTPN11). The broader clinical implications of PTPN11 mutations in AML are still not well understood. The objective of this study was to determine which cytogenetic abnormalities and gene mutations co-occur with PTPN11 mutations and how PTPN11 mutations affect outcomes of patients treated with intensive chemotherapy. We studied 1725 patients newly diagnosed with AML (excluding acute promyelocytic leukemia) enrolled onto the Cancer and Leukemia Group B/Alliance for Clinical Trials in Oncology trials. In 140 PTPN11-mutated patient samples, PTPN11 most commonly co-occurred with mutations in NPM1, DNMT3A, and TET2. PTPN11 mutations were relatively common in patients with an inv(3)(q21q26)/t(3;3)(q21;q26) and a normal karyotype but were very rare in patients with typical complex karyotype and core-binding factor AML. Mutations in the N-terminal SH2 domain of PTPN11 were associated with a higher early death rate than those in the phosphatase domain. PTPN11 mutations did not affect outcomes of NPM1-mutated patients, but these patients were less likely to have co-occurring kinase mutations (ie, FLT3-ITD), suggesting activation of overlapping signaling pathways. However, in AML patients with wild-type NPM1, PTPN11 mutations were associated with adverse patient outcomes, providing a rationale to study the biology and treatment approaches in this molecular group. This trial was registered at www.clinicaltrials.gov as #NCT00048958 (CALGB 8461), #NCT00899223 (CALGB 9665), and #NCT00900224 (CALGB 20202).
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Yanir AD, Krauss A, Stein J, Steinberg-Shemer O, Gilad O, Lotan SN, Dgany O, Krasnov T, Kodman Y, Feuerstein T, Mardoukh J, Fishman H, Geron I, Yacobovich J, Tamary H, Birger Y, Avrahami G, Izraeli S, Birenboim SB. Pediatric myelodysplastic syndrome with inflammatory manifestations: Diagnosis, genetics, treatment, and outcome. Pediatr Blood Cancer 2021; 68:e29138. [PMID: 34019335 DOI: 10.1002/pbc.29138] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 05/06/2021] [Accepted: 05/09/2021] [Indexed: 12/17/2022]
Abstract
BACKGROUND Inflammatory manifestations (IM) are well described in adult patients with myelodysplastic syndrome (MDS), but the presentation is highly variable and no standardized treatment exists. This phenomenon is rarely reported in children. As more pediatric patients are hematopoietic stem cell transplantation (HSCT) candidates, the role of anti-inflammatory treatment in relation to HSCT should be defined. PROCEDURE Here, we report a series of five children from a tertiary center. We describe the clinical presentation, molecular findings, and treatment options. RESULTS All patients presented with advanced MDS with blast percentages ranging 10-30%, all had severe IM. One patient had MDS secondary to severe congenital neutropenia, the other four patients had presumably primary MDS. All four were found to harbor a PTPN11 gene driver mutation, which is found in 35% of cases of juvenile myelomonocytic leukemia (JMML). The mutation was present in the myeloid lineage but not in T lymphocytes. Three had symptoms of Behcet's-like disease with trisomy 8 in their bone marrow. All patients were treated with anti-inflammatory medications (mainly systemic steroids) in an attempt to bring them to allogeneic HSCT in a better clinical condition. All demonstrated clinical improvement as well as regression in their MDS status post anti-inflammatory treatment. All have recovered from both MDS and their inflammatory symptoms post HSCT. CONCLUSION Primary pediatric MDS with IM is driven in some cases by PTPN11 mutations, and might be on the clinical spectrum of JMML. Anti-inflammatory treatment may reverse MDS progression and improve the outcome of subsequent HSCT.
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Affiliation(s)
- Asaf D Yanir
- BMT Unit, Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Aviva Krauss
- BMT Unit, Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Jerry Stein
- BMT Unit, Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Orna Steinberg-Shemer
- Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
- Pediatric Hematology Laboratory, Felsenstein Medical Research Center, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Oded Gilad
- Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Sharon Noy Lotan
- Pediatric Hematology Laboratory, Felsenstein Medical Research Center, Petach Tikva, Israel
| | - Orly Dgany
- Pediatric Hematology Laboratory, Felsenstein Medical Research Center, Petach Tikva, Israel
| | - Tatyana Krasnov
- Pediatric Hematology Laboratory, Felsenstein Medical Research Center, Petach Tikva, Israel
| | - Yona Kodman
- Immune Phenotype Laboratory, Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
| | - Tamar Feuerstein
- Immune Phenotype Laboratory, Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
| | - Jacques Mardoukh
- Cytogenetic Laboratory, Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
| | - Hila Fishman
- Pediatric Leukemia Laboratory, Felsenstein Medical Research Center, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Ifat Geron
- Pediatric Leukemia Laboratory, Felsenstein Medical Research Center, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Joanne Yacobovich
- Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Hannah Tamary
- Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
- Pediatric Hematology Laboratory, Felsenstein Medical Research Center, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yehudit Birger
- Pediatric Leukemia Laboratory, Felsenstein Medical Research Center, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Galia Avrahami
- Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Shai Izraeli
- Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
- Pediatric Leukemia Laboratory, Felsenstein Medical Research Center, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Shlomit Barzilai Birenboim
- Department of Hematology-Oncology, Schneider Children's Medical Center of Israel, Petach Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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Stasik S, Eckardt JN, Kramer M, Röllig C, Krämer A, Scholl S, Hochhaus A, Crysandt M, Brümmendorf TH, Naumann R, Steffen B, Kunzmann V, Einsele H, Schaich M, Burchert A, Neubauer A, Schäfer-Eckart K, Schliemann C, Krause S, Herbst R, Hänel M, Frickhofen N, Noppeney R, Kaiser U, Baldus CD, Kaufmann M, Rácil Z, Platzbecker U, Berdel WE, Mayer J, Serve H, Müller-Tidow C, Ehninger G, Bornhäuser M, Schetelig J, Middeke JM, Thiede C. Impact of PTPN11 mutations on clinical outcome analyzed in 1529 patients with acute myeloid leukemia. Blood Adv 2021; 5:3279-3289. [PMID: 34459887 PMCID: PMC8525221 DOI: 10.1182/bloodadvances.2021004631] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 04/13/2021] [Indexed: 12/18/2022] Open
Abstract
The tyrosine-protein phosphatase nonreceptor type 11 (PTPN11) is an important regulator of RAS signaling and frequently affected by mutations in patients with acute myeloid leukemia (AML). Despite the relevance for leukemogenesis and as a potential therapeutic target, the prognostic role is controversial. To investigate the prognostic impact of PTPN11 mutations, we analyzed 1529 adult AML patients using next-generation sequencing. PTPN11 mutations were detected in 106 of 1529 (6.93%) patients (median VAF: 24%) in dominant (36%) and subclonal (64%) configuration. Patients with PTPN11 mutations were associated with concomitant mutations in NPM1 (63%), DNMT3A (37%), and NRAS (21%) and had a higher rate of European LeukemiaNet (ELN) favorable cytogenetics (57.8% vs 39.1%; P < .001) and higher white blood cell counts (P = .007) compared with PTPN11 wild-type patients. In a multivariable analysis, PTPN11 mutations were independently associated with poor overall survival (hazard ratio [HR]: 1.75; P < .001), relapse-free survival (HR: 1.52; P = .013), and a lower rate of complete remission (odds ratio: 0.46; P = .008). Importantly, the deleterious effect of PTPN11 mutations was confined predominantly to the ELN favorable-risk group and patients with subclonal PTPN11 mutations (HR: 2.28; P < .001) but not found with dominant PTPN11 mutations (HR: 1.07; P = .775), presumably because of significant differences within the rate and spectrum of associated comutations. In conclusion, our data suggest an overall poor prognostic impact of PTPN11 mutations in AML, which is significantly modified by the underlying cytogenetics and the clonal context in which they occur.
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Affiliation(s)
- Sebastian Stasik
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
| | - Jan-Niklas Eckardt
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
| | - Michael Kramer
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
| | - Christoph Röllig
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
| | - Alwin Krämer
- Medizinische Klinik V, Universitätsklinikum Heidelberg, Heidelberg, Germany
| | - Sebastian Scholl
- Klinik für Innere Medizin II, Universitätsklinikum Jena, Jena, Germany
| | - Andreas Hochhaus
- Klinik für Innere Medizin II, Universitätsklinikum Jena, Jena, Germany
| | - Martina Crysandt
- Klinik für Hämatologie, Onkologie, Hämostasiologie und Stammzelltransplantation , Uniklinik RWTH Aachen, Aachen, Germany
| | - Tim H Brümmendorf
- Klinik für Hämatologie, Onkologie, Hämostasiologie und Stammzelltransplantation , Uniklinik RWTH Aachen, Aachen, Germany
| | - Ralph Naumann
- Medizinische Klinik III, St. Marien-Krankenhaus Siegen, Siegen, Germany
| | - Björn Steffen
- Medizinische Klinik II, Universitätsklinikum Frankfurt, Frankfurt am Main, Germany
| | - Volker Kunzmann
- Medizinische Klinik und Poliklinik II, Universitätsklinikum Würzburg, Würzburg, Germany
| | - Hermann Einsele
- Medizinische Klinik und Poliklinik II, Universitätsklinikum Würzburg, Würzburg, Germany
| | - Markus Schaich
- Klinik für Hämatologie, Onkologie und Palliativmedizin, Rems-Murr-Klinikum Winnenden, Winnenden, Germany
| | - Andreas Burchert
- Klinik für Hämatologie, Onkologie, Immunologie, Philipps Universität Marburg, Marburg, Germany
| | - Andreas Neubauer
- Klinik für Hämatologie, Onkologie, Immunologie, Philipps Universität Marburg, Marburg, Germany
| | - Kerstin Schäfer-Eckart
- Klinik für Innere Medizin V, Paracelsus Medizinische Privatuniversität, Klinikum Nürnberg Nord, Nürnberg, Germany
| | | | - Stefan Krause
- Medizinische Klinik V, Paracelsus Medizinische Privatuniversität, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Regina Herbst
- Medizinische Klinik III, Klinikum Chemnitz, Chemnitz, Germany
| | - Mathias Hänel
- Medizinische Klinik III, Klinikum Chemnitz, Chemnitz, Germany
| | | | - Richard Noppeney
- Klinik für Hämatologie, Universitätsklinikum Essen, Essen, Germany
| | - Ulrich Kaiser
- Medizinische Klinik II, St. Bernward Krankenhaus, Hildesheim, Germany
| | - Claudia D Baldus
- Hämatologie und Onkologie, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Martin Kaufmann
- Abteilung für Hämatologie, Onkologie und Palliativmedizin, Robert-Bosch-Krankenhaus, Stuttgart, Germany
| | - Zdenek Rácil
- Masaryk University and University Hospital, Department of Internal Medicine, Hematology and Oncology, Brno, Czech Republic
| | - Uwe Platzbecker
- Medizinische Klinik und Poliklinik I, Hämatologie und Zelltherapie, Universitätsklinikum Leipzig, Leipzig, Germany
| | - Wolfgang E Berdel
- Medizinische Klinik A, Universitätsklinikum Münster, Münster, Germany
| | - Jiri Mayer
- Masaryk University and University Hospital, Department of Internal Medicine, Hematology and Oncology, Brno, Czech Republic
| | - Hubert Serve
- Medizinische Klinik II, Universitätsklinikum Frankfurt, Frankfurt am Main, Germany
| | | | - Gerhard Ehninger
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
| | - Martin Bornhäuser
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
- National Center for Tumor Diseases, Dresden, Germany; and
| | - Johannes Schetelig
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
- DKMS Clinical Trials Unit, Dresden, Germany
| | - Jan M Middeke
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
| | - Christian Thiede
- Medizinische Klinik und Poliklinik I, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
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Yang L, Zhang H, Yang X, Lu T, Ma S, Cheng H, Yen K, Cheng T. Prognostic Prediction of Cytogenetically Normal Acute Myeloid Leukemia Based on a Gene Expression Model. Front Oncol 2021; 11:659201. [PMID: 34123815 PMCID: PMC8190396 DOI: 10.3389/fonc.2021.659201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 03/26/2021] [Indexed: 11/22/2022] Open
Abstract
Acute myeloid leukemia (AML) refers to a heterogeneous group of hematopoietic malignancies. The well-known European Leukemia Network (ELN) stratifies AML patients into three risk groups, based primarily on the detection of cytogenetic abnormalities. However, the prognosis of cytogenetically normal AML (CN-AML), which is the largest AML subset, can be hard to define. Moreover, the clinical outcomes associated with this subgroup are diverse. In this study, using transcriptome profiles collected from CN-AML patients in the BeatAML cohort, we constructed a robust prognostic Cox model named NEST (Nine-gEne SignaTure). The validity of NEST was confirmed in four external independent cohorts. Moreover, the risk score predicted by the NEST model remained an independent prognostic factor in multivariate analyses. Further analysis revealed that the NEST model was suitable for bone marrow mononuclear cell (BMMC) samples but not peripheral blood mononuclear cell (PBMC) samples, which indirectly indicated subtle differences between BMMCs and PBMCs. Our data demonstrated the robustness and accuracy of the NEST model and implied the importance of the immune dysfunction in the leukemogenesis that occurs in CN-AML, which shed new light on the further exploration of molecular mechanisms and treatment guidance for CN-AML.
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Affiliation(s)
- Liu Yang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Houyu Zhang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Xue Yang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Ting Lu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Shihui Ma
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Hui Cheng
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Kuangyu Yen
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
| | - Tao Cheng
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.,Department of Stem Cell and Regenerative Medicine, Peking Union Medical College, Tianjin, China.,Center for Stem Cell Medicine, Chinese Academy of Medical Sciences, Tianjin, China
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