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Zhang Z, Huang J, Zhang Z, Shen H, Tang X, Wu D, Bao X, Xu G, Chen S. Application of omics in the diagnosis, prognosis, and treatment of acute myeloid leukemia. Biomark Res 2024; 12:60. [PMID: 38858750 PMCID: PMC11165883 DOI: 10.1186/s40364-024-00600-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 05/17/2024] [Indexed: 06/12/2024] Open
Abstract
Acute myeloid leukemia (AML) is the most frequent leukemia in adults with a high mortality rate. Current diagnostic criteria and selections of therapeutic strategies are generally based on gene mutations and cytogenetic abnormalities. Chemotherapy, targeted therapies, and hematopoietic stem cell transplantation (HSCT) are the major therapeutic strategies for AML. Two dilemmas in the clinical management of AML are related to its poor prognosis. One is the inaccurate risk stratification at diagnosis, leading to incorrect treatment selections. The other is the frequent resistance to chemotherapy and/or targeted therapies. Genomic features have been the focus of AML studies. However, the DNA-level aberrations do not always predict the expression levels of genes and proteins and the latter is more closely linked to disease phenotypes. With the development of high-throughput sequencing and mass spectrometry technologies, studying downstream effectors including RNA, proteins, and metabolites becomes possible. Transcriptomics can reveal gene expression and regulatory networks, proteomics can discover protein expression and signaling pathways intimately associated with the disease, and metabolomics can reflect precise changes in metabolites during disease progression. Moreover, omics profiling at the single-cell level enables studying cellular components and hierarchies of the AML microenvironment. The abundance of data from different omics layers enables the better risk stratification of AML by identifying prognosis-related biomarkers, and has the prospective application in identifying drug targets, therefore potentially discovering solutions to the two dilemmas. In this review, we summarize the existing AML studies using omics methods, both separately and combined, covering research fields of disease diagnosis, risk stratification, prognosis prediction, chemotherapy, as well as targeted therapy. Finally, we discuss the directions and challenges in the application of multi-omics in precision medicine of AML. Our review may inspire both omics researchers and clinical physicians to study AML from a different angle.
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Affiliation(s)
- Zhiyu Zhang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Key Laboratory of Drug Research for Prevention and Treatment of Hyperlipidemic Diseases, Soochow University, Suzhou, 215123, Jiangsu, China
- Suzhou International Joint Laboratory for Diagnosis and Treatment of Brain Diseases, College of Pharmaceutical Sciences, Soochow University, Suzhou, 215123, Jiangsu, China
- MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou, 215123, Jiangsu Province, China
| | - Jiayi Huang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Zhibo Zhang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Hongjie Shen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Xiaowen Tang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Depei Wu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Xiebing Bao
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China.
| | - Guoqiang Xu
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Key Laboratory of Drug Research for Prevention and Treatment of Hyperlipidemic Diseases, Soochow University, Suzhou, 215123, Jiangsu, China.
- Suzhou International Joint Laboratory for Diagnosis and Treatment of Brain Diseases, College of Pharmaceutical Sciences, Soochow University, Suzhou, 215123, Jiangsu, China.
- MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou, 215123, Jiangsu Province, China.
| | - Suning Chen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China.
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Branco A, Rayabaram J, Miranda CC, Fernandes-Platzgummer A, Fernandes TG, Sajja S, da Silva CL, Vemuri MC. Advances in ex vivo expansion of hematopoietic stem and progenitor cells for clinical applications. Front Bioeng Biotechnol 2024; 12:1380950. [PMID: 38846805 PMCID: PMC11153805 DOI: 10.3389/fbioe.2024.1380950] [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: 02/02/2024] [Accepted: 04/25/2024] [Indexed: 06/09/2024] Open
Abstract
As caretakers of the hematopoietic system, hematopoietic stem cells assure a lifelong supply of differentiated populations that are responsible for critical bodily functions, including oxygen transport, immunological protection and coagulation. Due to the far-reaching influence of the hematopoietic system, hematological disorders typically have a significant impact on the lives of individuals, even becoming fatal. Hematopoietic cell transplantation was the first effective therapeutic avenue to treat such hematological diseases. Since then, key use and manipulation of hematopoietic stem cells for treatments has been aspired to fully take advantage of such an important cell population. Limited knowledge on hematopoietic stem cell behavior has motivated in-depth research into their biology. Efforts were able to uncover their native environment and characteristics during development and adult stages. Several signaling pathways at a cellular level have been mapped, providing insight into their machinery. Important dynamics of hematopoietic stem cell maintenance were begun to be understood with improved comprehension of their metabolism and progressive aging. These advances have provided a solid platform for the development of innovative strategies for the manipulation of hematopoietic stem cells. Specifically, expansion of the hematopoietic stem cell pool has triggered immense interest, gaining momentum. A wide range of approaches have sprouted, leading to a variety of expansion systems, from simpler small molecule-based strategies to complex biomimetic scaffolds. The recent approval of Omisirge, the first expanded hematopoietic stem and progenitor cell product, whose expansion platform is one of the earliest, is predictive of further successes that might arise soon. In order to guarantee the quality of these ex vivo manipulated cells, robust assays that measure cell function or potency need to be developed. Whether targeting hematopoietic engraftment, immunological differentiation potential or malignancy clearance, hematopoietic stem cells and their derivatives need efficient scaling of their therapeutic potency. In this review, we comprehensively view hematopoietic stem cells as therapeutic assets, going from fundamental to translational.
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Affiliation(s)
- André Branco
- Department of Bioengineering and Institute for Bioengineering and Biosciences (iBB), Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
- Associate Laboratory i4HB—Institute for Health and Bioeconomy, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Janakiram Rayabaram
- Protein and Cell Analysis, Biosciences Division, Invitrogen Bioservices, Thermo Fisher Scientific, Bangalore, India
| | - Cláudia C. Miranda
- Department of Bioengineering and Institute for Bioengineering and Biosciences (iBB), Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
- Associate Laboratory i4HB—Institute for Health and Bioeconomy, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
- AccelBio, Collaborative Laboratory to Foster Translation and Drug Discovery, Cantanhede, Portugal
| | - Ana Fernandes-Platzgummer
- Department of Bioengineering and Institute for Bioengineering and Biosciences (iBB), Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
- Associate Laboratory i4HB—Institute for Health and Bioeconomy, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Tiago G. Fernandes
- Department of Bioengineering and Institute for Bioengineering and Biosciences (iBB), Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
- Associate Laboratory i4HB—Institute for Health and Bioeconomy, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Suchitra Sajja
- Protein and Cell Analysis, Biosciences Division, Invitrogen Bioservices, Thermo Fisher Scientific, Bangalore, India
| | - Cláudia L. da Silva
- Department of Bioengineering and Institute for Bioengineering and Biosciences (iBB), Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
- Associate Laboratory i4HB—Institute for Health and Bioeconomy, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
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Wang J, Wang C, Hu A, Yu K, Kuang Y, Gajendran B, Zacksenhaus E, Sample KM, Xiao X, Liu W, Ben-David Y. FLI1 induces erythroleukemia through opposing effects on UBASH3A and UBASH3B expression. BMC Cancer 2024; 24:326. [PMID: 38461240 PMCID: PMC10925000 DOI: 10.1186/s12885-024-12075-2] [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: 07/21/2023] [Accepted: 03/01/2024] [Indexed: 03/11/2024] Open
Abstract
BACKGROUND FLI1 is an oncogenic transcription factor that promotes diverse malignancies through mechanisms that are not fully understood. Herein, FLI1 is shown to regulate the expression of Ubiquitin Associated and SH3 Domain Containing A/B (UBASH3A/B) genes. UBASH3B and UBASH3A are found to act as an oncogene and tumor suppressor, respectively, and their combined effect determines erythroleukemia progression downstream of FLI1. METHODS Promoter analysis combined with luciferase assays and chromatin immunoprecipitation (ChIP) analysis were applied on the UBASH3A/B promoters. RNAseq analysis combined with bioinformatic was used to determine the effect of knocking-down UBASH3A and UBASH3B in leukemic cells. Downstream targets of UBASH3A/B were inhibited in leukemic cells either via lentivirus-shRNAs or small molecule inhibitors. Western blotting and RT-qPCR were used to determine transcription levels, MTT assays to assess proliferation rate, and flow cytometry to examine apoptotic index. RESULTS Knockdown of FLI1 in erythroleukemic cells identified the UBASH3A/B genes as potential downstream targets. Herein, we show that FLI1 directly binds to the UBASH3B promoter, leading to its activation and leukemic cell proliferation. In contrast, FLI1 indirectly inhibits UBASH3A transcription via GATA2, thereby antagonizing leukemic growth. These results suggest oncogenic and tumor suppressor roles for UBASH3B and UBASH3A in erythroleukemia, respectively. Mechanistically, we show that UBASH3B indirectly inhibits AP1 (FOS and JUN) expression, and that its loss leads to inhibition of apoptosis and acceleration of proliferation. UBASH3B also positively regulates the SYK gene expression and its inhibition suppresses leukemia progression. High expression of UBASH3B in diverse tumors was associated with worse prognosis. In contrast, UBASH3A knockdown in erythroleukemic cells increased proliferation; and this was associated with a dramatic induction of the HSP70 gene, HSPA1B. Accordingly, knockdown of HSPA1B in erythroleukemia cells significantly accelerated leukemic cell proliferation. Accordingly, overexpression of UBASH3A in different cancers was predominantly associated with good prognosis. These results suggest for the first time that UBASH3A plays a tumor suppressor role in part through activation of HSPA1B. CONCLUSIONS FLI1 promotes erythroleukemia progression in part by modulating expression of the oncogenic UBASH3B and tumor suppressor UBASH3A.
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MESH Headings
- Humans
- Leukemia, Erythroblastic, Acute/genetics
- Leukemia, Erythroblastic, Acute/pathology
- Proto-Oncogene Protein c-fli-1/genetics
- Proto-Oncogene Protein c-fli-1/metabolism
- RNA, Small Interfering/genetics
- Genes, Tumor Suppressor
- Gene Expression Regulation
- Gene Expression Regulation, Neoplastic
- Cell Line, Tumor
- Oncogene Proteins, Fusion/genetics
- RNA-Binding Protein EWS/genetics
- Adaptor Proteins, Signal Transducing/metabolism
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Affiliation(s)
- Jie Wang
- State Key Laboratory for Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang-550014, Guizhou, People's Republic of China
- Natural Products Research Center of Guizhou Province, High Tech Zone, Province Science City, Baiyun District, Guiyang, 550014, China
| | - Chunlin Wang
- State Key Laboratory for Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang-550014, Guizhou, People's Republic of China
- Natural Products Research Center of Guizhou Province, High Tech Zone, Province Science City, Baiyun District, Guiyang, 550014, China
| | - Anling Hu
- State Key Laboratory for Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang-550014, Guizhou, People's Republic of China
- Natural Products Research Center of Guizhou Province, High Tech Zone, Province Science City, Baiyun District, Guiyang, 550014, China
| | - Kunlin Yu
- State Key Laboratory for Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang-550014, Guizhou, People's Republic of China
- Natural Products Research Center of Guizhou Province, High Tech Zone, Province Science City, Baiyun District, Guiyang, 550014, China
| | - Yi Kuang
- State Key Laboratory for Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang-550014, Guizhou, People's Republic of China
- Natural Products Research Center of Guizhou Province, High Tech Zone, Province Science City, Baiyun District, Guiyang, 550014, China
| | - Babu Gajendran
- State Key Laboratory for Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang-550014, Guizhou, People's Republic of China
- School of Pharmaceutical Sciences, Guizhou Medical University, Guizhou Province, Guiyang, 550025, People's Republic of China
| | - Eldad Zacksenhaus
- Department of Medicine, University of Toronto, Toronto, ON, Canada
- Division of Advanced Diagnostics, Toronto General Research Institute, University Health Network, Toronto, ON, Canada
| | | | - Xiao Xiao
- State Key Laboratory for Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang-550014, Guizhou, People's Republic of China
- Natural Products Research Center of Guizhou Province, High Tech Zone, Province Science City, Baiyun District, Guiyang, 550014, China
| | - Wuling Liu
- State Key Laboratory for Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang-550014, Guizhou, People's Republic of China.
- Natural Products Research Center of Guizhou Province, High Tech Zone, Province Science City, Baiyun District, Guiyang, 550014, China.
| | - Yaacov Ben-David
- State Key Laboratory for Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang-550014, Guizhou, People's Republic of China.
- Natural Products Research Center of Guizhou Province, High Tech Zone, Province Science City, Baiyun District, Guiyang, 550014, China.
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Cho U, Cha HJ, Kim HJ, Min SK, Kim HK, Jung HR, Park G, Kim JE. FLI-1 is expressed in a wide variety of hematolymphoid neoplasms: a special concern in the differential diagnosis. Clin Exp Med 2024; 24:18. [PMID: 38280044 PMCID: PMC10821826 DOI: 10.1007/s10238-023-01284-x] [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: 09/19/2023] [Accepted: 11/07/2023] [Indexed: 01/29/2024]
Abstract
Friend Leukemia Virus Integration 1 (FLI-1) is a member of E26 transformation-specific family of transcription factors that participates in hematopoietic and vascular endothelial cell development. Immunohistochemical detection of FLI-1 has been widely used to diagnose vascular tumors or, more evidently, Ewing's sarcoma. However, the expression pattern of FLI-1 in hematolymphoid neoplasms remains unclear. Therefore, in this study, we aimed to investigate the expression of FLI-1 in these tumors, focusing on high-grade lesions, which presents a diagnostic challenge by mimicking Ewing's sarcoma. We evaluated the expression FLI-1 in various types of lymphoid and plasmacytic tumors, including 27 plasmablastic lymphomas, 229 diffuse large B-cell lymphomas, 22 precursor T- or B-lymphoblastic lymphomas, 24 angioimmunoblastic-type nodal T-follicular helper cell lymphomas, 52 peripheral T-cell lymphomas, NOS, 18 Burkitt lymphomas, 18 non-gastric lymphomas of mucosa-associated lymphoid tissue, 38 chronic lymphocytic leukemia/small lymphocytic lymphomas, 15 mantle cell lymphomas, 23 gastric MALT lymphomas, 50 plasma cell myelomas, and 38 follicular lymphomas. We calculated the H-scores of FLI-1 immunostaining, ranging from 0 to 200, and used the scores to analyze the clinicopathological significance of FLI-1 statistically. FLI-1 was expressed to varying degrees in all types of hematological tumors. FLI-1 expression was detected in 84.1% of patients (466/554). FLI-1 was highly expressed in precursor T- or B-lymphoblastic lymphomas. Follicular lymphomas exhibited low FLI-1 expression. In plasmablastic lymphoma, 85.2% of the patients were focally positive for FLI-1. FLI-1 expression did not correlate with clinicopathological variables, such as demographic data or disease stage, in patients with plasmablastic lymphoma and diffuse large B-cell lymphoma. However, FLI-1 overexpression was associated with poorer overall survival in patients with plasmablastic lymphoma. This study demonstrates that FLI-1 is expressed in various hematolymphoid neoplasms. FLI-1 expression can lead to diagnostic confusion, especially in small blue round cell tumors, such as lymphoblastic lymphoma, plasmablastic lymphoma, and plasma cell myeloma, when distinguishing tumors positive for CD99 and CD56 without CD3, CD20, or CD45. Our findings also suggested the possibility of FLI-1 as a potential prognostic biomarker for plasmablastic lymphoma.
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Affiliation(s)
- Uiju Cho
- Department of Pathology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hee Jeong Cha
- Department of Pathology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Republic of Korea
| | - Hyun Jung Kim
- Department of Pathology, Sanggye Paik Hospital, Inje University, Seoul, Republic of Korea
| | - Soo Kee Min
- Department of Pathology, Chung-ang University Gwangmyeong Hospital, Gwangmyeong, Republic of Korea
| | - Hee Kyung Kim
- Department of Pathology, Soonchunhyang University Hospital, Bucheon, Republic of Korea
| | - Hye Ra Jung
- Department of Pathology, Keimyung University School of Medicine, Daegu, Republic of Korea
| | - Gyeongsin Park
- Department of Pathology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpodaero, Seocho-gu, Seoul, 06591, Republic of Korea.
| | - Ji Eun Kim
- Department of Pathology, Seoul National University Boramae Hospital, 20 Boramae-Ro 5-Gil, Dongjak-Gu, Seoul, 07061, Republic of Korea.
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Sharma R, Zhang C, Narendran A. The Small-Molecule E26-Transformation-Specific Inhibitor TK216 Attenuates the Oncogenic Properties of Pediatric Leukemia. Genes (Basel) 2023; 14:1916. [PMID: 37895265 PMCID: PMC10606408 DOI: 10.3390/genes14101916] [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: 07/13/2023] [Revised: 10/05/2023] [Accepted: 10/06/2023] [Indexed: 10/29/2023] Open
Abstract
The E26-transformation-specific (ETS) transcription factors regulate multiple aspects of the normal hematopoietic system. There is an increasing body of evidence suggesting aberrant ETS activity and its contribution to leukemia initiation and progression. In this study, we evaluated the small-molecule ETS inhibitor TK216 and demonstrated its anti-tumor activity in pediatric leukemia. We found TK216 induced growth inhibition, cell cycle arrest and apoptosis and inhibited the migratory capability of leukemic cells, without significantly inhibiting the cell viability of normal blood mononuclear cells. Priming the leukemic cells with 5-Azacitidine enhanced the cytotoxic effects of TK216 on pediatric leukemia cells. Importantly, we found purine-rich box1 (PU.1) to be a potential target of TK216 in myeloid and B-lymphoid leukemic cells. In addition, TK216 sharply decreased Mcl-1 protein levels in a dose-dependent manner. Consistent with this, TK216 also potentiated the cytotoxic effects of Bcl-2 inhibition in venetoclax-resistant cells. The sustained survival benefit provided to leukemic cells in the presence of bone-marrow-derived conditioned media is also found to be modulated by TK216. Taken together, our data indicates that TK216 could be a promising targeted therapeutic agent for the treatment of acute myeloid and B-lymphoid leukemia.
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Affiliation(s)
| | | | - Aru Narendran
- Department of Oncology, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr NW, Calgary, AB T2N 4N1, Canada
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Pappalardo XG, Risiglione P, Zinghirino F, Ostuni A, Luciano D, Bisaccia F, De Pinto V, Guarino F, Messina A. Human VDAC pseudogenes: an emerging role for VDAC1P8 pseudogene in acute myeloid leukemia. Biol Res 2023; 56:33. [PMID: 37344914 DOI: 10.1186/s40659-023-00446-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 06/08/2023] [Indexed: 06/23/2023] Open
Abstract
BACKGROUND Voltage-dependent anion selective channels (VDACs) are the most abundant mitochondrial outer membrane proteins, encoded in mammals by three genes, VDAC1, 2 and 3, mostly ubiquitously expressed. As 'mitochondrial gatekeepers', VDACs control organelle and cell metabolism and are involved in many diseases. Despite the presence of numerous VDAC pseudogenes in the human genome, their significance and possible role in VDAC protein expression has not yet been considered. RESULTS We investigated the relevance of processed pseudogenes of human VDAC genes, both in physiological and in pathological contexts. Using high-throughput tools and querying many genomic and transcriptomic databases, we show that some VDAC pseudogenes are transcribed in specific tissues and pathological contexts. The obtained experimental data confirm an association of the VDAC1P8 pseudogene with acute myeloid leukemia (AML). CONCLUSIONS Our in-silico comparative analysis between the VDAC1 gene and its VDAC1P8 pseudogene, together with experimental data produced in AML cellular models, indicate a specific over-expression of the VDAC1P8 pseudogene in AML, correlated with a downregulation of the parental VDAC1 gene.
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Affiliation(s)
- Xena Giada Pappalardo
- Department of Biomedical and Biotechnological Sciences, University of Catania, Via Santa Sofia 97, 95123, Catania, Italy
| | - Pierpaolo Risiglione
- Department of Biomedical and Biotechnological Sciences, University of Catania, Via Santa Sofia 97, 95123, Catania, Italy
| | - Federica Zinghirino
- Department of Biomedical and Biotechnological Sciences, University of Catania, Via Santa Sofia 97, 95123, Catania, Italy
| | - Angela Ostuni
- Department of Sciences, University of Basilicata, 85100, Potenza, Italy
| | - Daniela Luciano
- Department of Biomedical and Biotechnological Sciences, University of Catania, Via Santa Sofia 97, 95123, Catania, Italy
| | - Faustino Bisaccia
- Department of Sciences, University of Basilicata, 85100, Potenza, Italy
| | - Vito De Pinto
- Department of Biomedical and Biotechnological Sciences, University of Catania, Via Santa Sofia 97, 95123, Catania, Italy
- we.MitoBiotech S.R.L, C.so Italia 172, 95125, Catania, Italy
- I.N.B.B, National Institute for Biostructures and Biosystems, Interuniversity Consortium, Catania, Italy
- Research Centre on Nutraceuticals and Health Products (CERNUT), University of Catania, 95125, Catania, Italy
| | - Francesca Guarino
- Department of Biomedical and Biotechnological Sciences, University of Catania, Via Santa Sofia 97, 95123, Catania, Italy
- we.MitoBiotech S.R.L, C.so Italia 172, 95125, Catania, Italy
- I.N.B.B, National Institute for Biostructures and Biosystems, Interuniversity Consortium, Catania, Italy
- Research Centre on Nutraceuticals and Health Products (CERNUT), University of Catania, 95125, Catania, Italy
| | - Angela Messina
- we.MitoBiotech S.R.L, C.so Italia 172, 95125, Catania, Italy.
- I.N.B.B, National Institute for Biostructures and Biosystems, Interuniversity Consortium, Catania, Italy.
- Research Centre on Nutraceuticals and Health Products (CERNUT), University of Catania, 95125, Catania, Italy.
- Department of Biological, Geological and Environmental Sciences, University of Catania, Via Santa Sofia 97, 95123, Catania, Italy.
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7
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Punetha A, Kotiya D. Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice. Proteomes 2023; 11:2. [PMID: 36648960 PMCID: PMC9844371 DOI: 10.3390/proteomes11010002] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/03/2023] [Accepted: 01/04/2023] [Indexed: 01/12/2023] Open
Abstract
Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.
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Affiliation(s)
- Ankita Punetha
- Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, Rutgers University, 225 Warren St., Newark, NJ 07103, USA
| | - Deepak Kotiya
- Department of Pharmacology and Nutritional Sciences, University of Kentucky, 900 South Limestone St., Lexington, KY 40536, USA
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8
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Elucidating the importance and regulation of key enhancers for human MEIS1 expression. Leukemia 2022; 36:1980-1989. [PMID: 35624144 PMCID: PMC9343249 DOI: 10.1038/s41375-022-01602-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Revised: 05/05/2022] [Accepted: 05/12/2022] [Indexed: 11/20/2022]
Abstract
Myeloid ecotropic virus insertion site 1 (MEIS1) is essential for normal hematopoiesis and is a critical factor in the pathogenesis of a large subset of acute myeloid leukemia (AML). Despite the clinical relevance of MEIS1, its regulation is largely unknown. To understand the transcriptional regulatory mechanisms contributing to human MEIS1 expression, we created a knock-in green florescent protein (GFP) reporter system at the endogenous MEIS1 locus in a human AML cell line. Using this model, we have delineated and dissected a critical enhancer region of the MEIS1 locus for transcription factor (TF) binding through in silico prediction in combination with oligo pull-down, mass-spectrometry and knockout analysis leading to the identification of FLI1, an E-twenty-six (ETS) transcription factor, as an important regulator of MEIS1 transcription. We further show direct binding of FLI1 to the MEIS1 locus in human AML cell lines as well as enrichment of histone acetylation in MEIS1-high healthy and leukemic cells. We also observe a positive correlation between high FLI1 transcript levels and worse overall survival in AML patients. Our study expands the role of ETS factors in AML and our model constitutes a feasible tool for a more detailed understanding of transcriptional regulatory elements and their interactome.
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Shen Q, Zhou H, Zhang M, Wu R, Wang L, Wang Y, Chen J. Super enhancer-LncRNA SENCR promoted cisplatin resistance and growth of NSCLC through upregulating FLI1. J Clin Lab Anal 2022; 36:e24460. [PMID: 35500152 PMCID: PMC9169188 DOI: 10.1002/jcla.24460] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 03/13/2022] [Accepted: 04/10/2022] [Indexed: 01/21/2023] Open
Abstract
Background Super enhancer‐lncRNA smooth muscle and endothelial cell‐enriched migration/differentiation‐associated lncRNA (SENCR) were highly overexpressed in cisplatin‐resistant A549/DDP cells, while the mechanism was unclear. Methods SE‐lncRNA SENCR and FLI1 mRNA expression in A549/DDP cell, LAD tissues were detected. SENCR knockdown of A549/DDP cell and SENCR overexpression of cisplatin‐sensitive A549 cell were constructed. Experiments of cell‐confirmed function of SENCR and the correlation between SENCR and FLI1 were validated. Results The expression of SENCR and FLI1 mRNA in A549/DDP cell were both upregulated and mainly localized in the nucleus. Compared with DDP‐sensitive tissues with disease relief, SENCR expression was higher in DDP‐resistant tissues with disease progression from LAD. Knockdown of SENCR in A549/DDP reduced proliferation ability and cisplatin resistance, consistent with the decreased levels of proteins PCNA, MDMX, and P‐gp. Besides, whatever without cisplatin or with 2 μg/ml cisplatin, knockdown of SENCR reduced the migration, invasion, and colony formation abilities of A549/DDP cell and promoted apoptosis. However, when SENCR was overexpressed in A549 cell, all above results were reversed. Mechanistically, FLI1 expression was reduced after knocking down SENCR, while overexpressing SENCR increased FLI1 expression. Conclusion SE‐LncRNA SENCR was upregulated in A549/DDP, which could promote cisplatin resistance and growth of NSCLC cell through upregulating FLI1 expression.
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Affiliation(s)
- Qiang Shen
- First People's Hospital of Linping District, Hangzhou, China
| | - Huixin Zhou
- Department of Laboratory Medicine, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, Zhejiang, China
| | - Meijuan Zhang
- Department of Laboratory Medicine, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, Zhejiang, China
| | - Ruihao Wu
- Department of Laboratory Medicine, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, Zhejiang, China
| | - Liangxing Wang
- First People's Hospital of Linping District, Hangzhou, China
| | - Yumin Wang
- Department of Respiratory, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jie Chen
- Department of Intensive Care Unit, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
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10
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FLI1 regulates inflammation-associated genes to accelerate leukemogenesis. Cell Signal 2022; 92:110269. [DOI: 10.1016/j.cellsig.2022.110269] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/25/2022] [Accepted: 01/25/2022] [Indexed: 01/03/2023]
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11
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Hoff FW, Horton TM, Kornblau SM. Reverse phase protein arrays in acute leukemia: investigative and methodological challenges. Expert Rev Proteomics 2021; 18:1087-1097. [PMID: 34965151 DOI: 10.1080/14789450.2021.2020655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Acute leukemia results from a series of mutational events that alter cell growth and proliferation. Mutations result in protein changes that orchestrate growth alterations characteristic of leukemia. Proteomics is a methodology appropriate for study of protein changes found in leukemia. The high-throughput reverse phase protein array (RPPA) technology is particularly well-suited for the assessment of protein changes in samples derived from clinical trials. AREAS COVERED This review discusses the technical, methodological, and analytical issues related to the successful development of acute leukemia RPPAs. EXPERT COMMENTARY To obtain representative protein sample lysates, samples should be prepared from freshly collected blood or bone marrow material. Variables such as sample shipment, transit time, and holding temperature only have minimal effects on protein expression. CellSave preservation tubes are preferred for cells collected after exposure to chemotherapy, and incorporation of standardized guidelines for antibody validation is recommended. A more systematic biological approach to analyze protein expression is desired, searching for recurrent patterns of protein expression that allow classification of patients into risk groups, or groups of patients that may be treated similarly. Comparing RPPA protein analysis between cell lines and primary samples shows that cell lines are not representative of patient proteomic patterns.
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Affiliation(s)
- Fieke W Hoff
- Department of Internal Medicine, The University of Texas Southwestern Medical Center, TX, USA
| | - Terzah M Horton
- Department of Pediatrics, Texas Children's Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Steven M Kornblau
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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12
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ZMYND8-regulated IRF8 transcription axis is an acute myeloid leukemia dependency. Mol Cell 2021; 81:3604-3622.e10. [PMID: 34358447 DOI: 10.1016/j.molcel.2021.07.018] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 07/13/2021] [Accepted: 07/13/2021] [Indexed: 02/06/2023]
Abstract
The transformed state in acute leukemia requires gene regulatory programs involving transcription factors and chromatin modulators. Here, we uncover an IRF8-MEF2D transcriptional circuit as an acute myeloid leukemia (AML)-biased dependency. We discover and characterize the mechanism by which the chromatin "reader" ZMYND8 directly activates IRF8 in parallel with the MYC proto-oncogene through their lineage-specific enhancers. ZMYND8 is essential for AML proliferation in vitro and in vivo and associates with MYC and IRF8 enhancer elements that we define in cell lines and in patient samples. ZMYND8 occupancy at IRF8 and MYC enhancers requires BRD4, a transcription coactivator also necessary for AML proliferation. We show that ZMYND8 binds to the ET domain of BRD4 via its chromatin reader cassette, which in turn is required for proper chromatin occupancy and maintenance of leukemic growth in vivo. Our results rationalize ZMYND8 as a potential therapeutic target for modulating essential transcriptional programs in AML.
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13
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Giraud G, Kolovos P, Boltsis I, van Staalduinen J, Guyot B, Weiss-Gayet M, IJcken WV, Morlé F, Grosveld F. Interplay between FLI-1 and the LDB1 complex in murine erythroleukemia cells and during megakaryopoiesis. iScience 2021; 24:102210. [PMID: 33733070 PMCID: PMC7940982 DOI: 10.1016/j.isci.2021.102210] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 12/22/2020] [Accepted: 02/17/2021] [Indexed: 11/29/2022] Open
Abstract
Transcription factors are key players in a broad range of cellular processes such as cell-fate decision. Understanding how they act to control these processes is of critical importance for therapy purposes. FLI-1 controls several hematopoietic lineage differentiation including megakaryopoiesis and erythropoiesis. Its aberrant expression is often observed in cancer and is associated with poor prognosis. We showed that FLI-1 interacts with the LDB1 complex, which also plays critical roles in erythropoiesis and megakaryopoiesis. In this study, we aimed to unravel how FLI-1 and the LDB1 complex act together in murine erythroleukemia cells and in megakaryocyte. Combining omics techniques, we show that FLI-1 enables the recruitment of the LDB1 complex to regulatory sequences of megakaryocytic genes and to enhancers. We show as well for the first time that FLI-1 is able to modulate the 3D chromatin organization by promoting chromatin looping between enhancers and promoters most likely through the LDB1 complex. FLI-1 is important for the recruitment of the LDB1 complex FLI-1 is important for chromatin looping FLI-1 and the LDB1 complex co-regulate megakaryopoiesis
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Affiliation(s)
- Guillaume Giraud
- Department of Cell Biology, Erasmus Medical Centre, 3015CN Rotterdam, the Netherlands
| | - Petros Kolovos
- Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis 68100, Greece
| | - Ilias Boltsis
- Department of Cell Biology, Erasmus Medical Centre, 3015CN Rotterdam, the Netherlands
| | - Jente van Staalduinen
- Department of Cell Biology, Erasmus Medical Centre, 3015CN Rotterdam, the Netherlands
| | - Boris Guyot
- CNRS UMR5286, Centre de Recherche en Cancérologie de Lyon, Lyon, France.,Inserm U1052, Centre de Recherche en Cancérologie de Lyon, Lyon, France.,Université de Lyon, Lyon, France.,Department of Immunity, Virus and Microenvironment, Lyon, France
| | - Michele Weiss-Gayet
- Institut NeuroMyoGène, CNRS UMR 5310 - INSERM U1217 - Université de Lyon - Université Claude Bernard Lyon 1, Lyon, France
| | - Wilfred van IJcken
- Biomics Center, Erasmus University Medical Center, 3015CN Rotterdam, the Netherlands
| | - François Morlé
- Institut NeuroMyoGène, CNRS UMR 5310 - INSERM U1217 - Université de Lyon - Université Claude Bernard Lyon 1, Lyon, France
| | - Frank Grosveld
- Department of Cell Biology, Erasmus Medical Centre, 3015CN Rotterdam, the Netherlands
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14
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Xu X, Cheng L, Fan Y, Mao W. Tumor Microenvironment-Associated Immune-Related Genes for the Prognosis of Malignant Pleural Mesothelioma. Front Oncol 2020; 10:544789. [PMID: 33042835 PMCID: PMC7526499 DOI: 10.3389/fonc.2020.544789] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2020] [Accepted: 08/21/2020] [Indexed: 12/11/2022] Open
Abstract
Malignant pleural mesothelioma (MPM) is a rare but highly aggressive thoracic malignancy. ESTIMATE algorithm-derived immune scores are commonly used to quantify the immune and stromal components in tumors. Thus, this algorithm may help determine the tumor microenvironment (TME)-related gene expression profile associated with tumor immunity. This study aimed at mining public databases to determine a potential correlation between differentially expressed genes (DEGs) and survival in patients with MPM. We categorized patients from the Gene Expression Omnibus database according to their immune/stromal scores into high- and low-score groups. Functional enrichment analysis and the construction of protein-protein interaction networks showed that the DEGs identified were primarily involved in the TME. Furthermore, we validated these genes in an independent cohort of patients with MPM from The Cancer Genome Atlas database. DEG analysis showed that 29 DEGs were cancer driver genes. Subsequently, 14 TME-related genes, which have been previously neglected, were shown to exhibit significant prognostic potential in MPM. In conclusion, immune/stromal scores are novel predictors of a poor prognosis in patients with MPM. We identified DEGs that are involved in immunity against MPM and may contribute to patient survival. Owing to their potential as prognostic factors for MPM, these 14 TME-related genes need to be studied in detail in the future.
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Affiliation(s)
- Xiaoling Xu
- Department of Medical Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.,Department of Medical Oncology, Institute of Cancer Research and Basic Medical Sciences of Chinese Academy of Sciences, Cancer Hospital of University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, China
| | - Lei Cheng
- Department of Thoracic Radiotherapy, Institute of Cancer Research and Basic Medical Sciences of Chinese Academy of Sciences, Cancer Hospital of University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, China
| | - Yun Fan
- Department of Medical Oncology, Institute of Cancer Research and Basic Medical Sciences of Chinese Academy of Sciences, Cancer Hospital of University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, China
| | - Weimin Mao
- Department of Medical Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.,Department of Thoracic Surgery, Institute of Cancer Research and Basic Medical Sciences of Chinese Academy of Sciences, Cancer Hospital of University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, China
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15
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van Dijk AD, de Bont ESJM, Kornblau SM. Targeted therapy in acute myeloid leukemia: current status and new insights from a proteomic perspective. Expert Rev Proteomics 2020; 17:1-10. [PMID: 31945303 DOI: 10.1080/14789450.2020.1717951] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Introduction: The biological heterogeneity of acute myeloid leukemia (AML) complicates personalized medicine. Individual prognosis is typically based on the presence of chromosomal and genetic lesions. Nevertheless, these classifications often lack a priori information about response to therapy. Since the protein expression landscape reflects the functional activity state of cells, we hypothesize that analyzing this can be used for the identification of protein activity markers to provide better risk stratification as well as may provide targeted therapeutic guidance in AML.Areas covered: Herein, we review recently new adopted drugs in the treatment for AML and discuss how quantitative proteomic techniques may contribute to better therapeutic selection in AML.Expert commentary: The net functional state of the cell is defined by the activity of protein within all the pathways that are active in the cell. Recognition of the proteomic profile of the leukemic blast could, therefore, complement current classification systems by providing a better a priori description of what pathways are important within a cell as a guide to the selection of therapy for the patient.
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Affiliation(s)
- Anneke D van Dijk
- Division of Pediatric Oncology/Hematology, Department of Pediatrics, University Medical Center Groningen, Groningen, the Netherlands
| | - Eveline S J M de Bont
- Division of Pediatric Oncology/Hematology, Department of Pediatrics, University Medical Center Groningen, Groningen, the Netherlands
| | - Steven M Kornblau
- Department of Leukemia, University of Texas MD Anderson Cancer Center, Houston, TX, USA
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16
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Cai J, Cai H, Chen J, Yang X. Identifying "Many-to-Many" Relationships between Gene-Expression Data and Drug-Response Data via Sparse Binary Matching. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2020; 17:165-176. [PMID: 29994482 DOI: 10.1109/tcbb.2018.2849708] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Identifying gene-drug patterns is a critical step in pharmacology for unveiling disease mechanisms and drug discovery. The availability of high-throughput technologies accumulates massive large-scale pharmacological and genomic data, and thus provides a new substantial opportunity to deeply understand how the oncogenic genes and the therapeutic drugs relate to each other. However, most previous studies merely used the pharmacological and genomic datasets without any prior knowledge to infer the gene-drug patterns. Here, we proposed a novel network-guided sparse binary matching model (NSBM) to decode these relationships hidden in the datasets. Not only the large-scale gene-expression data and drug-response data are jointly analyzed in our method, but also the additional prior information of genes and drugs are integrated into the form of network-based regularization. The essential structure of the NSBM model is a convex quadratic minimization problem with network-based penalties. It was demonstrated to be superior when compared with two benchmark methods through extensive experiments on both synthetic and empirical data. Posterior validation, including gene-ontology and enrichment analysis, confirmed the effectiveness of NSBM in revealing gene-drug patterns on a large-scale heterogeneous data source.
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17
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Park SW, Do HJ, Choi W, Kim JH. Fli-1 promotes proliferation and upregulates NANOGP8 expression in T-lymphocyte leukemia cells. Biochimie 2019; 168:1-9. [PMID: 31626853 DOI: 10.1016/j.biochi.2019.10.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 10/10/2019] [Indexed: 11/27/2022]
Abstract
Friend leukemia integration 1 (Fli-1) is a member of the E26 transformation-specific (ETS) transcription factor family. Fli-1 regulates normal hematopoiesis and vasculogenesis, and its aberrant expression underlies virus-induced leukemias and various types of human cancers. NANOGP8, a retro-pseudogene of stem cell mediator NANOG, is expressed predominantly in cancer cells and plays a role in tumorigenesis. In this study, we demonstrate that Fli-1 expression enhances human acute T-cell leukemia Jurkat cell proliferation and that Fli-1 acts as a transcriptional activator of NANOGP8 expression in these cells. NANOGP8 and Fli-1 are highly expressed in Jurkat cells, whereas NANOG was undetectable at both the RNA and protein levels. Moreover, the expression of endogenous NANOGP8 was significantly influenced by gain of function and loss of function of Fli-1. Promoter-reporter assays showed that NANOGP8 transcription was significantly upregulated by dose-dependent Fli-1 overexpression. A series of deletion mutagenesis of NANOGP8 promoter sequence revealed that NANOGP8 promoter activity was tightly regulated and found the minimal promoter region sufficient to activate NANOGP8 transcription mediated by Fli-1. Moreover, site-directed mutagenesis of the putative binding site abolished both NANOGP8 full-length and minimal promoter activities. Binding assays revealed that Fli-1 directly interacts with the potent binding site in NANOG promoter region. Taken together, our data demonstrate that Fli-1 is a novel upstream transcriptional activator of NANOGP8 and provide the molecular details of Fli-1-mediated NANOGP8 gene expression. Ultimately, these findings may contribute to understanding the expanded regulatory mechanisms of oncogenic NANOGP8 and ETS family transcription factors in leukemogenesis.
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Affiliation(s)
- Sung-Won Park
- Department of Biomedical Science, College of Life Science, CHA University, Seongnam-Si, Gyeonggi-Do, 13488, South Korea
| | - Hyun-Jin Do
- Department of Biomedical Science, College of Life Science, CHA University, Seongnam-Si, Gyeonggi-Do, 13488, South Korea
| | - Wonbin Choi
- Department of Biomedical Science, College of Life Science, CHA University, Seongnam-Si, Gyeonggi-Do, 13488, South Korea
| | - Jae-Hwan Kim
- Department of Biomedical Science, College of Life Science, CHA University, Seongnam-Si, Gyeonggi-Do, 13488, South Korea.
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18
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Hoff FW, Hu CW, Qutub AA, de Bont ESJM, Horton TM, Kornblau SM. Shining a light on cell signaling in leukemia through proteomics: relevance for the clinic. Expert Rev Proteomics 2018; 15:613-622. [PMID: 29898608 PMCID: PMC6444923 DOI: 10.1080/14789450.2018.1487781] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
INTRODUCTION Although cure rates for acute leukemia have steadily improved over the past decades, leukemia remains a deadly disease. Enhanced risk stratification and new therapies are needed to improve outcome. Extensive genetic analyses have identified many mutations that contribute to the development of leukemia. However, most mutations occur infrequently and most gene alterations have been difficult to target. Most patients have more than one driver mutation in combination with secondary mutations, that result in a leukemic transformation via the alteration of proteins. The proteomics of acute leukemia could more directly identify proteins to facilitate risk stratification, predict chemoresistance and aid selection of therapy. Areas covered: This review discusses aberrantly expressed proteins identified by mass spectrometry and reverse phase protein arrays and their relationship to survival. In addition, we will discuss proteins in the context of functionally related protein groups. Expert commentary: Proteomics is a powerful tool to analyze protein abundance and functional alterations simultaneously for large numbers of patients. In the forthcoming years, validation of tools to quickly assess protein levels to enable routine rapid profiling of proteins with differential abundance and functional activation may be used as adjuncts to aid in therapy selection and to provide additional prognostic insights.
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Affiliation(s)
- Fieke W. Hoff
- Department of Pediatric Oncology/Hematology, Beatrix Children’s Hospital, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Chenyue W. Hu
- Department of Bioengineering, Rice University, Houston, TX, USA
| | - Amina A. Qutub
- Department of Bioengineering, Rice University, Houston, TX, USA
| | - Eveline S. J. M. de Bont
- Department of Pediatric Oncology/Hematology, Beatrix Children’s Hospital, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Terzah M. Horton
- Department of Pediatrics, Baylor College of Medicine, Texas Children’s Cancer Center, Houston, TX, USA
- Co-senior author
| | - Steven M. Kornblau
- Department of Leukemia, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
- Co-senior author
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19
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Liu T, Yao Y, Zhang G, Wang Y, Deng B, Song J, Li X, Han F, Xiao X, Yang J, Xia L, Li YJ, Plachynta M, Zhang M, Yan C, Mu S, Luo H, Zacksenhaus E, Hao X, Ben-David Y. A screen for Fli-1 transcriptional modulators identifies PKC agonists that induce erythroid to megakaryocytic differentiation and suppress leukemogenesis. Oncotarget 2017; 8:16728-16743. [PMID: 28052010 PMCID: PMC5369997 DOI: 10.18632/oncotarget.14377] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2016] [Accepted: 12/07/2016] [Indexed: 11/25/2022] Open
Abstract
The ETS-related transcription factor Fli-1 affects many developmental programs including erythroid and megakaryocytic differentiation, and is frequently de-regulated in cancer. Fli-1 was initially isolated following retrovirus insertional mutagenesis screens for leukemic initiator genes, and accordingly, inhibition of this transcription factor can suppress leukemia through induction of erythroid differentiation. To search for modulators of Fli-1, we hereby performed repurposing drug screens with compounds isolated from Chinese medicinal plants. We identified agents that can transcriptionally activate or inhibit a Fli-1 reporter. Remarkably, agents that increased Fli-1 transcriptional activity conferred a strong anti-cancer activity upon Fli-1-expressing leukemic cells in culture. As opposed to drugs that suppress Fli1 activity and lead to erythroid differentiation, growth suppression by these new Fli-1 transactivating compounds involved erythroid to megakaryocytic conversion (EMC). The identified compounds are structurally related to diterpene family of small molecules, which are known agonists of protein kinase C (PKC). In accordance, these PKC agonists (PKCAs) induced PKC phosphorylation leading to activation of the mitogen-activated protein kinase (MAPK) pathway, increased cell attachment and EMC, whereas pharmacological inhibition of PKC or MAPK diminished the effect of our PKCAs. Moreover, in a mouse model of leukemia initiated by Fli-1 activation, the PKCA compounds exhibited strong anti-cancer activity, which was accompanied by increased presence of CD41/CD61 positive megakaryocytic cells in leukemic spleens. Thus, PKC agonists offer a novel approach to combat Fli-1-induced leukemia, and possibly other cancers,by inducing EMC in part through over-activation of the PKC-MAPK-Fli-1 pathway.
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Affiliation(s)
- Tangjingjun Liu
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China.,State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang, China
| | - Yao Yao
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China.,State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang, China
| | - Gang Zhang
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China
| | - Ye Wang
- College of Ecology, Lishui University, Zhejiang, China
| | - Bin Deng
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China
| | - Jialei Song
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China.,The Laboratory of Cell Biochemistry and Topogenic Regulation, College of Bioengineering and Faculty of Sciences, Chongqing University, Chongqing, China
| | - Xiaogang Li
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China
| | - Fei Han
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China
| | - Xiao Xiao
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China.,State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang, China
| | - Jue Yang
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China
| | - Lei Xia
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China.,School of Pharmaceutical Sciences, Guizhou University, Guizhou, China
| | - You-Jun Li
- Department of Anatomy, Norman Bethune College of Medicine, Jilin University, Changchun, China
| | - Maksym Plachynta
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China
| | - Mu Zhang
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China
| | - Chen Yan
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China
| | - Shuzhen Mu
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China.,State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang, China
| | - Heng Luo
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China.,State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang, China
| | - Eldad Zacksenhaus
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Division of Advanced Diagnostics, Toronto General Research Institute-University Health Network, Toronto, Ontario, Canada
| | - Xiaojiang Hao
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China.,School of Pharmaceutical Sciences, Guizhou University, Guizhou, China.,State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang, China
| | - Yaacov Ben-David
- Department of Biology and Chemistry, The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences, Guizhou, China.,State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang, China
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20
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Butler JS, Qiu YH, Zhang N, Yoo SY, Coombes KR, Dent SYR, Kornblau SM. Low expression of ASH2L protein correlates with a favorable outcome in acute myeloid leukemia. Leuk Lymphoma 2016; 58:1207-1218. [PMID: 28185526 DOI: 10.1080/10428194.2016.1235272] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
ASH2L encodes a trithorax group protein that is a core component of all characterized mammalian histone H3K4 methyltransferase complexes, including mixed lineage leukemia (MLL) complexes. ASH2L protein levels in primary leukemia patient samples have not yet been defined. We analyzed ASH2L protein expression in 511 primary AML patient samples using reverse phase protein array (RPPA) technology. We discovered that ASH2L expression is significantly increased in a subset of patients carrying fms-related tyrosine kinase 3 (FLT3) mutations. Furthermore, we observed that low levels of ASH2L are associated with increased overall survival. We also compared ASH2L levels to the expression of 230 proteins previously analyzed on this array. ASH2L expression was inversely correlated with 32 proteins, mostly involved in cell adhesion and cell cycle inhibition, while a positive correlation was observed for 50 proteins, many of which promote cell proliferation. Together, these results indicate that a lower level of ASH2L protein is beneficial to AML patients.
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Affiliation(s)
- Jill S Butler
- a Department of Epigenetics and Molecular Carcinogenesis , The University of Texas MD Anderson Cancer Center , Science Park , Smithville , TX , USA.,b Center for Cancer Epigenetics, The University of Texas MD Anderson Cancer Center , Houston , TX , USA
| | - Yi Hua Qiu
- c Division of Molecular Hematology, Department of Leukemia , The University of Texas MD Anderson Cancer Center , Houston , TX , USA
| | | | - Suk-Young Yoo
- e Department of Bioinformatics and Computational Biology , The University of Texas MD Anderson Cancer Center , Houston , TX , USA
| | - Kevin R Coombes
- f Department of Biomedical Informatics , The Ohio State University College of Medicine , Columbus , OH , USA
| | - Sharon Y R Dent
- a Department of Epigenetics and Molecular Carcinogenesis , The University of Texas MD Anderson Cancer Center , Science Park , Smithville , TX , USA.,b Center for Cancer Epigenetics, The University of Texas MD Anderson Cancer Center , Houston , TX , USA
| | - Steven M Kornblau
- c Division of Molecular Hematology, Department of Leukemia , The University of Texas MD Anderson Cancer Center , Houston , TX , USA
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21
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A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis. PLoS Comput Biol 2016; 12:e1004890. [PMID: 27351836 PMCID: PMC4924788 DOI: 10.1371/journal.pcbi.1004890] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2015] [Accepted: 03/31/2016] [Indexed: 11/19/2022] Open
Abstract
Acute Myeloid Leukemia (AML) is a fatal hematological cancer. The genetic abnormalities underlying AML are extremely heterogeneous among patients, making prognosis and treatment selection very difficult. While clinical proteomics data has the potential to improve prognosis accuracy, thus far, the quantitative means to do so have yet to be developed. Here we report the results and insights gained from the DREAM 9 Acute Myeloid Prediction Outcome Prediction Challenge (AML-OPC), a crowdsourcing effort designed to promote the development of quantitative methods for AML prognosis prediction. We identify the most accurate and robust models in predicting patient response to therapy, remission duration, and overall survival. We further investigate patient response to therapy, a clinically actionable prediction, and find that patients that are classified as resistant to therapy are harder to predict than responsive patients across the 31 models submitted to the challenge. The top two performing models, which held a high sensitivity to these patients, substantially utilized the proteomics data to make predictions. Using these models, we also identify which signaling proteins were useful in predicting patient therapeutic response.
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22
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van der Sligte NE, Kampen KR, ter Elst A, Scherpen FJG, Meeuwsen-de Boer TGJ, Guryev V, van Leeuwen FN, Kornblau SM, de Bont ESJM. Essential role for cyclic-AMP responsive element binding protein 1 (CREB) in the survival of acute lymphoblastic leukemia. Oncotarget 2016; 6:14970-81. [PMID: 26008971 PMCID: PMC4558129 DOI: 10.18632/oncotarget.3911] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2015] [Accepted: 04/24/2015] [Indexed: 01/27/2023] Open
Abstract
Acute lymphoblastic leukemia (ALL) relapse remains a leading cause of cancer related death in children, therefore, new therapeutic options are needed. Recently, we showed that a peptide derived from Cyclic-AMP Responsive Element Binding Protein (CREB) was highly phosphorylated in pediatric leukemias. In this study, we determined CREB phosphorylation and mRNA levels showing that CREB expression was significantly higher in ALL compared to normal bone marrow (phosphorylation: P < 0.0001, mRNA: P = 0.004). High CREB and phospho-CREB expression was correlated with a lower median overall survival in a cohort of 140 adult ALL patients. ShRNA mediated knockdown of CREB in ALL cell lines blocked leukemic cell growth by inducing cell cycle arrest and apoptosis. Gene expression array analysis showed downregulation of CREB target genes regulating cell proliferation and glucose metabolism and upregulation of apoptosis inducing genes. Similar to CREB knockdown, the CREB inhibitor KG-501 decreased leukemic cell viability and induced apoptosis in ALL cell lines, as well as primary T-ALL samples, with cases showing high phospho-CREB levels being more sensitive than those with lower phospho-CREB levels. Together, these in vitro findings support an important role for CREB in the survival of ALL cells and identify this transcription factor as a potential target for treatment.
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Affiliation(s)
- Naomi E van der Sligte
- Division of Pediatric Oncology/Hematology, Department of Pediatrics, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Kim R Kampen
- Division of Pediatric Oncology/Hematology, Department of Pediatrics, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Arja ter Elst
- Division of Pediatric Oncology/Hematology, Department of Pediatrics, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Frank J G Scherpen
- Division of Pediatric Oncology/Hematology, Department of Pediatrics, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Tiny G J Meeuwsen-de Boer
- Division of Pediatric Oncology/Hematology, Department of Pediatrics, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Victor Guryev
- European Research Institute for The Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Frank N van Leeuwen
- Laboratory of Pediatric Oncology, Department of Pediatrics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Steven M Kornblau
- Department of Leukemia, The University of Texas, MD Anderson Cancer Center, Houston, Texas, United States of America
| | - Eveline S J M de Bont
- Division of Pediatric Oncology/Hematology, Department of Pediatrics, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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23
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Benito JM, Godfrey L, Kojima K, Hogdal L, Wunderlich M, Geng H, Marzo I, Harutyunyan KG, Golfman L, North P, Kerry J, Ballabio E, Chonghaile TN, Gonzalo O, Qiu Y, Jeremias I, Debose L, O'Brien E, Ma H, Zhou P, Jacamo R, Park E, Coombes KR, Zhang N, Thomas DA, O'Brien S, Kantarjian HM, Leverson JD, Kornblau SM, Andreeff M, Müschen M, Zweidler-McKay PA, Mulloy JC, Letai A, Milne TA, Konopleva M. MLL-Rearranged Acute Lymphoblastic Leukemias Activate BCL-2 through H3K79 Methylation and Are Sensitive to the BCL-2-Specific Antagonist ABT-199. Cell Rep 2015; 13:2715-27. [PMID: 26711339 PMCID: PMC4700051 DOI: 10.1016/j.celrep.2015.12.003] [Citation(s) in RCA: 104] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2015] [Revised: 10/21/2015] [Accepted: 11/19/2015] [Indexed: 12/25/2022] Open
Abstract
Targeted therapies designed to exploit specific molecular pathways in aggressive cancers are an exciting area of current research. Mixed Lineage Leukemia (MLL) mutations such as the t(4;11) translocation cause aggressive leukemias that are refractory to conventional treatment. The t(4;11) translocation produces an MLL/AF4 fusion protein that activates key target genes through both epigenetic and transcriptional elongation mechanisms. In this study, we show that t(4;11) patient cells express high levels of BCL-2 and are highly sensitive to treatment with the BCL-2-specific BH3 mimetic ABT-199. We demonstrate that MLL/AF4 specifically upregulates the BCL-2 gene but not other BCL-2 family members via DOT1L-mediated H3K79me2/3. We use this information to show that a t(4;11) cell line is sensitive to a combination of ABT-199 and DOT1L inhibitors. In addition, ABT-199 synergizes with standard induction-type therapy in a xenotransplant model, advocating for the introduction of ABT-199 into therapeutic regimens for MLL-rearranged leukemias.
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Affiliation(s)
- Juliana M Benito
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Laura Godfrey
- Weatherall Institute of Molecular Medicine, Molecular Haematology Unit, NIHR Oxford Biomedical Research Centre Programme, University of Oxford, Headington, Oxford OX3 9DS, UK
| | - Kensuke Kojima
- Division of Hematology, Respiratory Medicine and Oncology, Department of Internal Medicine, Faculty of Medicine, Saga University, Saga 840-8502, Japan
| | - Leah Hogdal
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Mark Wunderlich
- Cancer and Blood Diseases Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Huimin Geng
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Isabel Marzo
- Department of Biochemistry, Molecular and Cell Biology, University of Zaragoza, 50018 Zaragoza, Spain
| | - Karine G Harutyunyan
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Leonard Golfman
- Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Phillip North
- Weatherall Institute of Molecular Medicine, Molecular Haematology Unit, NIHR Oxford Biomedical Research Centre Programme, University of Oxford, Headington, Oxford OX3 9DS, UK
| | - Jon Kerry
- Weatherall Institute of Molecular Medicine, Molecular Haematology Unit, NIHR Oxford Biomedical Research Centre Programme, University of Oxford, Headington, Oxford OX3 9DS, UK
| | - Erica Ballabio
- Weatherall Institute of Molecular Medicine, Molecular Haematology Unit, NIHR Oxford Biomedical Research Centre Programme, University of Oxford, Headington, Oxford OX3 9DS, UK
| | - Triona Ní Chonghaile
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, York House, Dublin 2, Ireland
| | - Oscar Gonzalo
- Department of Biochemistry, Molecular and Cell Biology, University of Zaragoza, 50018 Zaragoza, Spain
| | - Yihua Qiu
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Irmela Jeremias
- German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany
| | - LaKiesha Debose
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Eric O'Brien
- Cancer and Blood Diseases Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Helen Ma
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Ping Zhou
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Rodrigo Jacamo
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Eugene Park
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Kevin R Coombes
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Nianxiang Zhang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Deborah A Thomas
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Susan O'Brien
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Hagop M Kantarjian
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Joel D Leverson
- Department of Oncology Development, AbbVie Inc., North Chicago, IL 60064, USA
| | - Steven M Kornblau
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Michael Andreeff
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Markus Müschen
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Patrick A Zweidler-McKay
- Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - James C Mulloy
- Cancer and Blood Diseases Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Anthony Letai
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Thomas A Milne
- Weatherall Institute of Molecular Medicine, Molecular Haematology Unit, NIHR Oxford Biomedical Research Centre Programme, University of Oxford, Headington, Oxford OX3 9DS, UK.
| | - Marina Konopleva
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
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24
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MN1-Fli1 oncofusion transforms murine hematopoietic progenitor cells into acute megakaryoblastic leukemia cells. Oncogenesis 2015; 4:e179. [PMID: 26690545 PMCID: PMC4688398 DOI: 10.1038/oncsis.2015.41] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2015] [Revised: 10/20/2015] [Accepted: 11/09/2015] [Indexed: 11/08/2022] Open
Abstract
Long-term outcome of acute megakaryoblastic leukemia (AMKL) patients without Down's syndrome remains poor. Founding mutations and chimeric oncogenes characterize various AMKL subtypes. However, for around one third of all cases the underlying mechanisms of AMKL leukemogenesis are still largely unknown. Recently, an in-frame fusion of meningeoma 1-friend leukemia virus integration 1 (MN1-Fli1) gene was detected in a child with AMKL. We intended to investigate the potential role of this oncofusion in leukemogenesis of acute myeloid leukemia. Strikingly, expression of MN1-Fli1 in murine hematopoietic progenitor cells was sufficient to induce leukemic transformation generating immature myeloid cells with cytomorphology and expression of surface markers typical for AMKL. Systematic structure function analyses revealed FLS and 3'ETS domains of Fli1 as decisive domains for the AMKL phenotype. Our data highlight an important role of MN1-Fli1 in AMKL leukemogenesis and provide a basis for research assessing the value of this oncofusion as a future diagnostic marker and/or therapeutic target in AMKL patients.
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25
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Nishida Y, Maeda A, Chachad D, Ishizawa J, Qiu YH, Kornblau SM, Kimura S, Andreeff M, Kojima K. Preclinical activity of the novel B-cell-specific Moloney murine leukemia virus integration site 1 inhibitor PTC-209 in acute myeloid leukemia: Implications for leukemia therapy. Cancer Sci 2015; 106:1705-13. [PMID: 26450753 PMCID: PMC4714665 DOI: 10.1111/cas.12833] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2015] [Revised: 10/02/2015] [Accepted: 10/06/2015] [Indexed: 12/11/2022] Open
Abstract
Curing patients with acute myeloid leukemia (AML) remains a therapeutic challenge. The polycomb complex protein B-cell-specific Moloney murine leukemia virus integration site 1 (BMI-1) is required for the self-renewal and maintenance of leukemia stem cells. We investigated the prognostic significance of BMI-1 in AML and the effects of a novel small molecule selective inhibitor of BMI-1, PTC-209. BMI-1 protein expression was determined in 511 newly diagnosed AML patients together with 207 other proteins using reverse-phase protein array technology. Patients with unfavorable cytogenetics according to Southwest Oncology Group criteria had higher levels of BMI-1 compared to those with favorable (P = 0.0006) or intermediate cytogenetics (P = 0.0061), and patients with higher levels of BMI-1 had worse overall survival (55.3 weeks vs. 42.8 weeks, P = 0.046). Treatment with PTC-209 reduced protein level of BMI-1 and its downstream target mono-ubiquitinated histone H2A and triggered several molecular events consistent with the induction of apoptosis, this is, loss of mitochondrial membrane potential, caspase-3 cleavage, BAX activation, and phosphatidylserine externalization. PTC-209 induced apoptosis in patient-derived CD34(+)CD38(low/-) AML cells and, less prominently, in CD34(-) differentiated AML cells. BMI-1 reduction by PTC-209 directly correlated with apoptosis induction in CD34(+) primary AML cells (r = 0.71, P = 0.022). However, basal BMI-1 expression was not a determinant of AML sensitivity. BMI-1 inhibition, which targets a primitive AML cell population, might offer a novel therapeutic strategy for AML.
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Affiliation(s)
- Yuki Nishida
- Division of Medicine, Department of Hematology, Respiratory Medicine and Oncology, Saga University, Saga, Japan
| | - Aya Maeda
- Division of Medicine, Department of Hematology, Respiratory Medicine and Oncology, Saga University, Saga, Japan
| | - Dhruv Chachad
- Section of Molecular Hematology and Therapy, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jo Ishizawa
- Section of Molecular Hematology and Therapy, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Yi Hua Qiu
- Section of Molecular Hematology and Therapy, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Steven M Kornblau
- Section of Molecular Hematology and Therapy, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Shinya Kimura
- Division of Medicine, Department of Hematology, Respiratory Medicine and Oncology, Saga University, Saga, Japan
| | - Michael Andreeff
- Section of Molecular Hematology and Therapy, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Kensuke Kojima
- Division of Medicine, Department of Hematology, Respiratory Medicine and Oncology, Saga University, Saga, Japan.,Section of Molecular Hematology and Therapy, Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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26
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Song W, Zhang T, Li W, Mu R, Zhang L, Li Y, Jin B, Wang N, Li A, Cui J. Overexpression of Fli-1 is associated with adverse prognosis of endometrial cancer. Cancer Invest 2015; 33:469-75. [PMID: 26305602 DOI: 10.3109/07357907.2015.1069831] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
This study aimed to investigate the expression of Friend leukemia virus integration 1 (Fli-1) and its correlation with the prognosis of endometrial cancer (EC). Thirty-two EC tissue samples were evaluated for Fli-1 expression using immunohistochemistry. Fli-1 showed significantly high expression in EC cells, followed by hyperplasia cells, and was negative in adjacent normal tissues. The high expression of Fli-1 was significantly associated with a high differentiation grade, mutated P53 expression, and histological subtype (p < .05). Downregulation of Fli-1 in AN3CN cells using RNA interference inhibited cell clone formation and proliferation but did not affect apoptosis and migration of the cells. This study provides the first evidence that Fli-1 expression gradually increases in parallel with disease progression, and its overexpression might predict poor prognosis in EC.
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Affiliation(s)
- Wei Song
- a Cancer Center, the First Hospital of Jilin University , Changchun , China
| | - Tianyang Zhang
- a Cancer Center, the First Hospital of Jilin University , Changchun , China
| | - Wei Li
- a Cancer Center, the First Hospital of Jilin University , Changchun , China
| | - Rui Mu
- b Institute of Basic Medical Sciences , National Center of Biomedical Analysis , Beijing , China
| | - Lingyi Zhang
- c Obstetrics and Gynecology , the Second Hospital of Jilin University , Changchun , China
| | - Yan Li
- a Cancer Center, the First Hospital of Jilin University , Changchun , China
| | - Baofeng Jin
- b Institute of Basic Medical Sciences , National Center of Biomedical Analysis , Beijing , China
| | - Na Wang
- b Institute of Basic Medical Sciences , National Center of Biomedical Analysis , Beijing , China
| | - Ailing Li
- b Institute of Basic Medical Sciences , National Center of Biomedical Analysis , Beijing , China
| | - Jiuwei Cui
- a Cancer Center, the First Hospital of Jilin University , Changchun , China
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27
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PKR inhibits the DNA damage response, and is associated with poor survival in AML and accelerated leukemia in NHD13 mice. Blood 2015. [PMID: 26202421 DOI: 10.1182/blood-2015-03-635227] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Increased expression of the interferon-inducible double-stranded RNA-activated protein kinase (PKR) has been reported in acute leukemia and solid tumors, but the role of PKR has been unclear. Now, our results indicate that high PKR expression in CD34(+) cells of acute myeloid leukemia (AML) patients correlates with worse survival and shortened remission duration. Significantly, we find that PKR has a novel and previously unrecognized nuclear function to inhibit DNA damage response signaling and double-strand break repair. Nuclear PKR antagonizes ataxia-telangiectasia mutated (ATM) activation by a mechanism dependent on protein phosphatase 2A activity. Thus, inhibition of PKR expression or activity promotes ATM activation, γ-H2AX formation, and phosphorylation of NBS1 following ionizing irradiation. PKR transgenic but not PKR null mice demonstrate a mutator phenotype characterized by radiation-induced and age-associated genomic instability that was partially reversed by short-term pharmacologic PKR inhibition. Furthermore, the age-associated accumulation of somatic mutations that occurs in the Nup98-HOXD13 (NHD13) mouse model of leukemia progression was significantly elevated by co-expression of a PKR transgene, whereas knockout of PKR expression or pharmacologic inhibition of PKR activity reduced the frequency of spontaneous mutations in vivo. Thus, PKR cooperated with the NHD13 transgene to accelerate leukemia progression and shorten survival. Taken together, these results indicate that increased nuclear PKR has an oncogenic function that promotes the accumulation of potentially deleterious mutations. Thus, PKR inhibition may be a therapeutically useful strategy to prevent leukemia progression or relapse, and improve clinical outcomes.
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28
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Cole A, Wang Z, Coyaud E, Voisin V, Gronda M, Jitkova Y, Mattson R, Hurren R, Babovic S, Maclean N, Restall I, Wang X, Jeyaraju DV, Sukhai MA, Prabha S, Bashir S, Ramakrishnan A, Leung E, Qia YH, Zhang N, Combes KR, Ketela T, Lin F, Houry WA, Aman A, Al-Awar R, Zheng W, Wienholds E, Xu CJ, Dick J, Wang JCY, Moffat J, Minden MD, Eaves CJ, Bader GD, Hao Z, Kornblau SM, Raught B, Schimmer AD. Inhibition of the Mitochondrial Protease ClpP as a Therapeutic Strategy for Human Acute Myeloid Leukemia. Cancer Cell 2015; 27:864-76. [PMID: 26058080 PMCID: PMC4461837 DOI: 10.1016/j.ccell.2015.05.004] [Citation(s) in RCA: 240] [Impact Index Per Article: 26.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2014] [Revised: 02/06/2015] [Accepted: 05/07/2015] [Indexed: 12/15/2022]
Abstract
From an shRNA screen, we identified ClpP as a member of the mitochondrial proteome whose knockdown reduced the viability of K562 leukemic cells. Expression of this mitochondrial protease that has structural similarity to the cytoplasmic proteosome is increased in leukemic cells from approximately half of all patients with AML. Genetic or chemical inhibition of ClpP killed cells from both human AML cell lines and primary samples in which the cells showed elevated ClpP expression but did not affect their normal counterparts. Importantly, Clpp knockout mice were viable with normal hematopoiesis. Mechanistically, we found that ClpP interacts with mitochondrial respiratory chain proteins and metabolic enzymes, and knockdown of ClpP in leukemic cells inhibited oxidative phosphorylation and mitochondrial metabolism.
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Affiliation(s)
- Alicia Cole
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Zezhou Wang
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Etienne Coyaud
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Veronique Voisin
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Marcela Gronda
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Yulia Jitkova
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Rachel Mattson
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Rose Hurren
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Sonja Babovic
- Terry Fox Laboratory, British Columbia Cancer Agency and University of British Columbia, Vancouver, BC V5Z 1L3, Canada
| | - Neil Maclean
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Ian Restall
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Xiaoming Wang
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | | | | | - Swayam Prabha
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Shaheena Bashir
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | | | - Elisa Leung
- Department of Biochemistry, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Yi Hua Qia
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Nianxian Zhang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Kevin R Combes
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Troy Ketela
- Department of Molecular Genetics, Donnelly Centre for Cellular and Biomolecular Research, Toronto, ON M5S 3E1, Canada
| | - Fengshu Lin
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Walid A Houry
- Department of Biochemistry, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Ahmed Aman
- Drug Discovery Program, Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada
| | - Rima Al-Awar
- Drug Discovery Program, Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada; Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Wei Zheng
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD 20892, USA
| | - Erno Wienholds
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada; Department of Medicine, University of Toronto, Toronto, ON M5G 2C4, Canada
| | - Chang Jiang Xu
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - John Dick
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada; Department of Medicine, University of Toronto, Toronto, ON M5G 2C4, Canada
| | - Jean C Y Wang
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada; Department of Medicine, University of Toronto, Toronto, ON M5G 2C4, Canada
| | - Jason Moffat
- Department of Molecular Genetics, Donnelly Centre for Cellular and Biomolecular Research, Toronto, ON M5S 3E1, Canada
| | - Mark D Minden
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada; Department of Medicine, University of Toronto, Toronto, ON M5G 2C4, Canada
| | - Connie J Eaves
- Terry Fox Laboratory, British Columbia Cancer Agency and University of British Columbia, Vancouver, BC V5Z 1L3, Canada
| | - Gary D Bader
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Zhenyue Hao
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Steven M Kornblau
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Brian Raught
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada
| | - Aaron D Schimmer
- Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada; Department of Medicine, University of Toronto, Toronto, ON M5G 2C4, Canada.
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29
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Wang W, Tang G, Cortes JE, Liu H, Ai D, Yin CC, Li S, Khoury JD, Bueso-Ramos C, Medeiros LJ, Hu S. Chromosomal rearrangement involving 11q23 locus in chronic myelogenous leukemia: a rare phenomenon frequently associated with disease progression and poor prognosis. J Hematol Oncol 2015; 8:32. [PMID: 25888368 PMCID: PMC4396174 DOI: 10.1186/s13045-015-0128-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2015] [Accepted: 03/10/2015] [Indexed: 12/20/2022] Open
Abstract
Background Progression of chronic myelogenous leukemia (CML) is frequently accompanied by cytogenetic evolution, commonly unbalanced chromosomal changes, such as an extra copy of Philadelphia chromosome (Ph), +8, and i(17)(q10). Balanced chromosomal translocations typically found in de novo acute myeloid leukemia occur occasionally in CML, such as inv(3)/t(3;3), t(8;21), t(15;17), and inv(16). Translocations involving the 11q23, a relatively common genetic abnormality in acute leukemia, have been seldom reported in CML. In this study, we explored the prevalence and prognostic role of 11q23 in CML. Methods We searched our pathology archives for CML cases diagnosed in our institution from 1998 to present. Cases with 11q23 rearrangements were retrieved. The corresponding clinicopathological data were reviewed. Results A total of 2,012 cases of CML with available karyotypes were identified. Ten (0.5%) CML cases had 11q23 rearrangement in Ph-positive cells, including 4 cases of t(9;11), 2 cases of t(11;19), and 1 case each of t(2;11), t(4;11), t(6;11), and t(4;9;11). Eight cases (80%) had other concurrent chromosomal abnormalities. There were 6 men and 4 women with a median age of 50 years (range, 21–70 years) at time of initial diagnosis of CML. 11q23 rearrangement occurred after a median period of 12.5 months (range, 0–172 months): 1 patient in chronic phase, 2 in accelerated phase, and 7 in blast phase. Eight of ten patients died after a median follow-up of 16.5 months (range, 8–186 months) following the initial diagnosis of CML, and a median of 6.7 months (range, 0.8–16.6 months) after the emergence of 11q23 rearrangement. The remaining two patients had complete remission at the last follow-up, 50.2 and 6.9 months, respectively. In addition, we also identified a case with 11q23/t(11;17) in Ph-negative cells in a patient with a history of CML. MLL involvement was tested by fluorescence in situ hybridization in 10 cases, and 7 cases (70%) were positive. Conclusions In summary, chromosomal rearrangements involving 11q23 are rare in CML, frequently occurring in blast phase, and are often associated with other cytogenetic abnormalities. These patients had a low response rate to tyrosine kinase inhibitors and a poor prognosis.
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Affiliation(s)
- Wei Wang
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - Guilin Tang
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - Jorge E Cortes
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - Hui Liu
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - Di Ai
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - C Cameron Yin
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - Shaoying Li
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - Joseph D Khoury
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - Carlos Bueso-Ramos
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - L Jeffrey Medeiros
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
| | - Shimin Hu
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
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STAT activation status differentiates leukemogenic from non-leukemogenic stem cells in AML and is suppressed by arsenic in t(6;9)-positive AML. Genes Cancer 2015; 5:378-92. [PMID: 25568664 PMCID: PMC4279436 DOI: 10.18632/genesandcancer.39] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2014] [Accepted: 10/19/2014] [Indexed: 01/13/2023] Open
Abstract
Acute myeloid leukemia (AML) is characterized by an aberrant self-renewal of hematopoietic stem cells (HSC) and a block in differentiation. The major therapeutic challenge is the characterization of the leukemic stem cell as a target for the eradication of the disease. Until now the biology of AML-associated fusion proteins (AAFPs), such as the t(15;17)-PML/RARα, t(8;21)-RUNX1/RUNX1T1 and t(6;9)-DEK/NUP214, all able to induce AML in mice, was investigated in different models and genetic backgrounds, not directly comparable to each other. To avoid the bias of different techniques and models we expressed these three AML-inducing oncogenes in an identical genetic background and compared their influence on the HSC compartment in vitro and in vivo. These AAFPs exerted differential effects on HSCs and PML/RARα, similar to DEK/NUP214, induced a leukemic phenotype from a small subpopulation of HSCs with a surface marker pattern of long-term HSC and characterized by activated STAT3 and 5. In contrast the established AML occurred from mature populations in the bone marrow. The activation of STAT5 by PML/RARα and DEK/NUP214 was confirmed in t(15;17)(PML/RARα) and t(6;9)(DEK/NUP214)-positive patients as compared to normal CD34+ cells. The activation of STAT5 was reduced upon the exposure to Arsenic which was accompanied by apoptosis in both PML/RARα- and DEK/NUP214-positive leukemic cells. These findings indicate that in AML the activation of STATs plays a decisive role in the biology of the leukemic stem cell. Furthermore we establish exposure to arsenic as a novel concept for the treatment of this high risk t(6;9)-positive AML.
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McGee SF, Kornblau SM, Qiu Y, Look AT, Zhang N, Yoo SY, Coombes KR, Kentsis A. Biological properties of ligand-dependent activation of the MET receptor kinase in acute myeloid leukemia. Leukemia 2014; 29:1218-21. [PMID: 25541150 DOI: 10.1038/leu.2014.348] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- S F McGee
- 1] Department of Medicine, Mount Sinai St Luke's-Roosevelt Hospital Center, New York, NY, USA [2] Molecular Pharmacology and Chemistry Program, Sloan Kettering Institute, New York, NY, USA
| | - S M Kornblau
- Department of Leukemia, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Y Qiu
- Department of Leukemia, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - A T Look
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - N Zhang
- Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - S-Y Yoo
- Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - K R Coombes
- Departmentt of Biomedical Informatics, Ohio State University College of Medicine, Columbus, OH, USA
| | - A Kentsis
- 1] Molecular Pharmacology and Chemistry Program, Sloan Kettering Institute, New York, NY, USA [2] Department of Pediatrics, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, Cornell University, New York, NY, USA
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Rolland T, Taşan M, Charloteaux B, Pevzner SJ, Zhong Q, Sahni N, Yi S, Lemmens I, Fontanillo C, Mosca R, Kamburov A, Ghiassian SD, Yang X, Ghamsari L, Balcha D, Begg BE, Braun P, Brehme M, Broly MP, Carvunis AR, Convery-Zupan D, Corominas R, Coulombe-Huntington J, Dann E, Dreze M, Dricot A, Fan C, Franzosa E, Gebreab F, Gutierrez BJ, Hardy MF, Jin M, Kang S, Kiros R, Lin GN, Luck K, MacWilliams A, Menche J, Murray RR, Palagi A, Poulin MM, Rambout X, Rasla J, Reichert P, Romero V, Ruyssinck E, Sahalie JM, Scholz A, Shah AA, Sharma A, Shen Y, Spirohn K, Tam S, Tejeda AO, Wanamaker SA, Twizere JC, Vega K, Walsh J, Cusick ME, Xia Y, Barabási AL, Iakoucheva LM, Aloy P, De Las Rivas J, Tavernier J, Calderwood MA, Hill DE, Hao T, Roth FP, Vidal M. A proteome-scale map of the human interactome network. Cell 2014; 159:1212-1226. [PMID: 25416956 PMCID: PMC4266588 DOI: 10.1016/j.cell.2014.10.050] [Citation(s) in RCA: 913] [Impact Index Per Article: 91.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Revised: 10/21/2014] [Accepted: 10/30/2014] [Indexed: 12/12/2022]
Abstract
Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ?14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ?30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a "broader" human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help "connect the dots" of the genomic revolution.
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Affiliation(s)
- Thomas Rolland
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Murat Taşan
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Departments of Molecular Genetics and Computer Science, University of Toronto, Toronto, ON M5S 3E1, Canada; Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada
| | - Benoit Charloteaux
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Samuel J Pevzner
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Boston University School of Medicine, Boston, MA 02118, USA
| | - Quan Zhong
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Sciences, Wright State University, Dayton, OH 45435, USA
| | - Nidhi Sahni
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Song Yi
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Irma Lemmens
- Department of Medical Protein Research, VIB, 9000 Ghent, Belgium
| | - Celia Fontanillo
- Cancer Research Center (Centro de Investigación del Cancer), University of Salamanca and Consejo Superior de Investigaciones Científicas, Salamanca 37008, Spain
| | - Roberto Mosca
- Joint IRB-BSC Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain
| | - Atanas Kamburov
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Susan D Ghiassian
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Center for Complex Network Research (CCNR) and Department of Physics, Northeastern University, Boston, MA 02115, USA
| | - Xinping Yang
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Lila Ghamsari
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Dawit Balcha
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Bridget E Begg
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Pascal Braun
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Marc Brehme
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Martin P Broly
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Anne-Ruxandra Carvunis
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Dan Convery-Zupan
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Roser Corominas
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | - Jasmin Coulombe-Huntington
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Bioengineering, McGill University, Montreal, QC H3A 0C3, Canada
| | - Elizabeth Dann
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Matija Dreze
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Amélie Dricot
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Changyu Fan
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Eric Franzosa
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Bioengineering, McGill University, Montreal, QC H3A 0C3, Canada
| | - Fana Gebreab
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Bryan J Gutierrez
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Madeleine F Hardy
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Mike Jin
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Shuli Kang
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | - Ruth Kiros
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Guan Ning Lin
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | - Katja Luck
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Andrew MacWilliams
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Jörg Menche
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Center for Complex Network Research (CCNR) and Department of Physics, Northeastern University, Boston, MA 02115, USA
| | - Ryan R Murray
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Alexandre Palagi
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Matthew M Poulin
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Xavier Rambout
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Protein Signaling and Interactions Lab, GIGA-R, University of Liege, 4000 Liege, Belgium
| | - John Rasla
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Patrick Reichert
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Viviana Romero
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Elien Ruyssinck
- Department of Medical Protein Research, VIB, 9000 Ghent, Belgium
| | - Julie M Sahalie
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Annemarie Scholz
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Akash A Shah
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Amitabh Sharma
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Center for Complex Network Research (CCNR) and Department of Physics, Northeastern University, Boston, MA 02115, USA
| | - Yun Shen
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Kerstin Spirohn
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Stanley Tam
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Alexander O Tejeda
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Shelly A Wanamaker
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Jean-Claude Twizere
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Protein Signaling and Interactions Lab, GIGA-R, University of Liege, 4000 Liege, Belgium
| | - Kerwin Vega
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Jennifer Walsh
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Michael E Cusick
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Yu Xia
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Bioengineering, McGill University, Montreal, QC H3A 0C3, Canada
| | - Albert-László Barabási
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Center for Complex Network Research (CCNR) and Department of Physics, Northeastern University, Boston, MA 02115, USA; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Lilia M Iakoucheva
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | - Patrick Aloy
- Joint IRB-BSC Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona 08010, Spain
| | - Javier De Las Rivas
- Cancer Research Center (Centro de Investigación del Cancer), University of Salamanca and Consejo Superior de Investigaciones Científicas, Salamanca 37008, Spain
| | - Jan Tavernier
- Department of Medical Protein Research, VIB, 9000 Ghent, Belgium
| | - Michael A Calderwood
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - David E Hill
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Tong Hao
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Frederick P Roth
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Departments of Molecular Genetics and Computer Science, University of Toronto, Toronto, ON M5S 3E1, Canada; Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada; Canadian Institute for Advanced Research, Toronto M5G 1Z8, Canada.
| | - Marc Vidal
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
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Widespread genetic epistasis among cancer genes. Nat Commun 2014; 5:4828. [PMID: 25407795 DOI: 10.1038/ncomms5828] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2013] [Accepted: 07/28/2014] [Indexed: 12/17/2022] Open
Abstract
Quantitative genetic epistasis has been hypothesized to be an important factor in the development and progression of complex diseases. Cancers in particular are driven by the accumulation of mutations that may act epistatically during the course of the disease. However, as cancer mutations are uncovered at an unprecedented rate, determining which combinations of genetic alterations interact to produce cancer phenotypes remains a challenge. Here we show that by using combinatorial RNAi screening in cell culture, dense and often previously undetermined interactions among cancer genes were revealed by assessing gene pairs that are frequently co-altered in primary breast cancers. These interacting gene pairs are significantly associated with survival time when co-altered in patients, indicating that genetic interaction mapping may be leveraged to improve risk assessment. As many of these interacting gene pairs involve known drug targets, personalized treatment regimens may be improved by overlaying genetic interactions with mutational profiling.
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The ets transcription factor Fli-1 in development, cancer and disease. Oncogene 2014; 34:2022-31. [PMID: 24909161 PMCID: PMC5028196 DOI: 10.1038/onc.2014.162] [Citation(s) in RCA: 94] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2014] [Revised: 05/03/2014] [Accepted: 05/04/2014] [Indexed: 12/13/2022]
Abstract
Friend Leukemia Virus Induced erythroleukemia-1 (Fli-1), an ETS transcription factor, was isolated a quarter century ago through a retrovirus mutagenesis screen. Fli-1 has since been recognized to play critical roles in normal development and homeostasis. For example, it transcriptionally regulates genes that drive normal hematopoiesis and vasculogenesis. Indeed, Fli-1 is one of 10 key regulators of hematopoietic stem/progenitor cell maintenance and differentiation. Aberrant expression of Fli-1 also underlies a number of virally induced leukemias, including Friend virus-induced erythroleukemia and various types of human cancers, and it is the target of chromosomal translocations in childhood Ewing’s sarcoma. Abnormal expression of Fli-1 is important in the aetiology of auto-immune diseases such as Systemic Lupus Erythematosus (SLE) and Systemic Sclerosis (SSc). These studies establish Fli-1 as a strong candidate for drug development. Despite difficulties in targeting transcription factors, recent studies identified small molecule inhibitors for Fli-1. Here we review past and ongoing research on Fli-1 with emphasis on its mechanistic function in autoimmune disease and malignant transformation. The significance of identifying Fli-1 inhibitors and their clinical applications for treatment of disease and cancer with deregulated Fli-1 expression are discussed.
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35
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Been RA, Linden MA, Hager CJ, DeCoursin KJ, Abrahante JE, Landman SR, Steinbach M, Sarver AL, Largaespada DA, Starr TK. Genetic signature of histiocytic sarcoma revealed by a sleeping beauty transposon genetic screen in mice. PLoS One 2014; 9:e97280. [PMID: 24827933 PMCID: PMC4020815 DOI: 10.1371/journal.pone.0097280] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2013] [Accepted: 04/18/2014] [Indexed: 02/06/2023] Open
Abstract
Histiocytic sarcoma is a rare, aggressive neoplasm that responds poorly to therapy. Histiocytic sarcoma is thought to arise from macrophage precursor cells via genetic changes that are largely undefined. To improve our understanding of the etiology of histiocytic sarcoma we conducted a forward genetic screen in mice using the Sleeping Beauty transposon as a mutagen to identify genetic drivers of histiocytic sarcoma. Sleeping Beauty mutagenesis was targeted to myeloid lineage cells using the Lysozyme2 promoter. Mice with activated Sleeping Beauty mutagenesis had significantly shortened lifespan and the majority of these mice developed tumors resembling human histiocytic sarcoma. Analysis of transposon insertions identified 27 common insertion sites containing 28 candidate cancer genes. Several of these genes are known drivers of hematological neoplasms, like Raf1, Fli1, and Mitf, while others are well-known cancer genes, including Nf1, Myc, Jak2, and Pten. Importantly, several new potential drivers of histiocytic sarcoma were identified and could serve as targets for therapy for histiocytic sarcoma patients.
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Affiliation(s)
- Raha A. Been
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, United States of America
- College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, United States of America
- Department of Comparative and Molecular Biosciences, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Michael A. Linden
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Courtney J. Hager
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Krista J. DeCoursin
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Juan E. Abrahante
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, United States of America
- Obstetrics, Gynecology, and Women's Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Sean R. Landman
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Michael Steinbach
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Aaron L. Sarver
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - David A. Largaespada
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, United States of America
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Timothy K. Starr
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, United States of America
- Obstetrics, Gynecology, and Women's Health, University of Minnesota, Minneapolis, Minnesota, United States of America
- Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, Minnesota, United States of America
- * E-mail:
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36
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Konopleva MY, Walter RB, Faderl SH, Jabbour EJ, Zeng Z, Borthakur G, Huang X, Kadia TM, Ruvolo PP, Feliu JB, Lu H, Debose L, Burger JA, Andreeff M, Liu W, Baggerly KA, Kornblau SM, Doyle LA, Estey EH, Kantarjian HM. Preclinical and early clinical evaluation of the oral AKT inhibitor, MK-2206, for the treatment of acute myelogenous leukemia. Clin Cancer Res 2014; 20:2226-35. [PMID: 24583795 PMCID: PMC3989412 DOI: 10.1158/1078-0432.ccr-13-1978] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
PURPOSE Recent studies suggested that AKT activation might confer poor prognosis in acute myelogenous leukemia (AML), providing the rationale for therapeutic targeting of this signaling pathway. We, therefore, explored the preclinical and clinical anti-AML activity of an oral AKT inhibitor, MK-2206. Experimental Methods: We first studied the effects of MK-2206 in human AML cell lines and primary AML specimens in vitro. Subsequently, we conducted a phase II trial of MK-2206 (200 mg weekly) in adults requiring second salvage therapy for relapsed/refractory AML, and assessed target inhibition via reverse phase protein array (RPPA). RESULTS In preclinical studies, MK-2206 dose-dependently inhibited growth and induced apoptosis in AML cell lines and primary AML blasts. We then treated 19 patients with MK-2206 but, among 18 evaluable participants, observed only 1 (95% confidence interval, 0%-17%) response (complete remission with incomplete platelet count recovery), leading to early study termination. The most common grade 3/4 drug-related toxicity was a pruritic rash in 6 of 18 patients. Nevertheless, despite the use of MK-2206 at maximum tolerated doses, RPPA analyses indicated only modest decreases in Ser473 AKT (median 28%; range, 12%-45%) and limited inhibition of downstream targets. CONCLUSIONS Although preclinical activity of MK-2206 can be demonstrated, this inhibitor has insufficient clinical antileukemia activity when given alone at tolerated doses, and alternative approaches to block AKT signaling should be explored.
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MESH Headings
- Acute Disease
- Administration, Oral
- Adult
- Aged
- Aged, 80 and over
- Apoptosis/drug effects
- Cell Cycle/drug effects
- Cell Line, Tumor
- Cell Proliferation/drug effects
- Dose-Response Relationship, Drug
- Drug Evaluation, Preclinical
- Exanthema/chemically induced
- Female
- HL-60 Cells
- Heterocyclic Compounds, 3-Ring/administration & dosage
- Heterocyclic Compounds, 3-Ring/adverse effects
- Heterocyclic Compounds, 3-Ring/therapeutic use
- Humans
- Immunoblotting
- Leukemia, Myeloid/drug therapy
- Leukemia, Myeloid/metabolism
- Leukemia, Myeloid/pathology
- Male
- Middle Aged
- Proto-Oncogene Proteins c-akt/antagonists & inhibitors
- Proto-Oncogene Proteins c-akt/metabolism
- Pruritus/chemically induced
- Salvage Therapy/methods
- Treatment Outcome
- U937 Cells
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Affiliation(s)
- Marina Y. Konopleva
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Roland B. Walter
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Division of Hematology/Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Stefan H. Faderl
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Elias J. Jabbour
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Zhihong Zeng
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Gautam Borthakur
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xuelin Huang
- Division of Quantitative Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Tapan M. Kadia
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Peter P. Ruvolo
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jennie B. Feliu
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Hongbo Lu
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - LaKiesha Debose
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jan A. Burger
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Michael Andreeff
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Wenbin Liu
- Division of Quantitative Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Keith A. Baggerly
- Division of Quantitative Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Steven M. Kornblau
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Elihu H. Estey
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Division of Hematology/Department of Medicine, University of Washington, Seattle, WA, USA
| | - Hagop M. Kantarjian
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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37
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Pierceall WE, Kornblau SM, Carlson NE, Huang X, Blake N, Lena R, Elashoff M, Konopleva M, Cardone MH, Andreeff M. BH3 profiling discriminates response to cytarabine-based treatment of acute myelogenous leukemia. Mol Cancer Ther 2013; 12:2940-9. [PMID: 24092807 DOI: 10.1158/1535-7163.mct-13-0692] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
As acute myelogenous leukemia (AML) patient response to cytarabine-based standard-of-care treatment is variable, stratification into subgroups by biomarker-predicted response may lead to improved clinical outcomes. Here, we assess cell mitochondrial depolarization to proapoptotic signaling BH3-only peptides as a surrogate for the function of Bcl-2 family proteins to address clinical response to cytarabine-based therapy in patients with AML (N = 62). Peripheral blood mononuclear cell (PBMC) or bone marrow aspirate specimens were obtained from newly diagnosed patients with AML, viably preserved, and assayed by flow cytometry following BH3 profile assay with individual BH3 peptides. Mann-Whitney analysis indicates biomarker correlation with response to induction therapy: Notably, BIM priming was highly significant (P = 2 × 10(-6)) with a compelling sensitivity/specificity profile [area under curve (AUC) = 0.83; 95% confidence interval (CI), 0.73-0.94; P = 2 × 10(-10)]. Multivariate analysis indicates improved profiles for BIM readout + patient age (AUC = 0.89; 95% CI, 0.81-0.97) and BIM + patient age + cytogenetic status (AUC = 0.91; 95% CI, 0.83-0.98). When patients were stratified by cytogenetic status, BIM readout was significant for both intermediate (P = 0.0017; AUC = 0.88; 95% CI, 0.71-1.04) and unfavorable (P = 0.023; AUC = 0.79; 95% CI, 0.58-1.00) risk groups, demonstrating predictive power independent of cytogenetics. Additional analyses of secondary clinical endpoints displayed correlation between overall survival (P = 0.037) and event-free survival (P = 0.044) when patients were stratified into tertiles by BIM peptide response. Taken together, these results highlight the potential utility of BH3 profiling in personalized diagnostics of AML by offering actionable information for patient management decisions.
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Affiliation(s)
- William E Pierceall
- Corresponding Authors: Michael Andreeff, University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 448, Houston, TX 77054.
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38
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Pierce A, Whetton AD, Meyer S, Ravandi-Kashani F, Borthakur G, Coombes KR, Zhang N, Kornblau S. Transglutaminase 2 expression in acute myeloid leukemia: association with adhesion molecule expression and leukemic blast motility. Proteomics 2013; 13:2216-2224. [PMID: 23576428 DOI: 10.1002/pmic.201200471] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2012] [Revised: 03/11/2013] [Accepted: 03/26/2013] [Indexed: 11/09/2022]
Abstract
Acute myeloid leukemia (AML) is a heterogenous disease with differential oncogene association, outcome and treatment regimens. Treatment strategies for AML have improved outcome but despite increased molecular biological information AML is still associated with poor prognosis. Proteomic analysis on the effects of a range of leukemogenic oncogenes showed that the protein transglutaminase 2 (TG2) is expressed at greater levels as a consequence of oncogenic transformation. Further analysis of this observation was performed with 511 AML samples using reverse phase proteomic arrays, demonstrating that TG2 expression was higher at relapse than diagnosis in many cases. In addition elevated TG2 expression correlated with increased expression of numerous adhesion proteins and many apoptosis regulating proteins, two processes related to leukemogenesis. TG2 has previously been linked to drug resistance in cancer and given the negative correlation between TG2 levels and peripheral blasts observed increased TG2 levels may lead to the protection of the leukemic stem cell due to increased adhesion/reduced motility. TG2 may therefore form part of a network of proteins that define poor outcome in AML patients and potentially offer a target to sensitize AML stem cells to drug treatment.
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Affiliation(s)
- Andrew Pierce
- Stem Cell and Leukaemia Proteomics Laboratory, Manchester Academic Health Science Centre, Wolfson Molecular Imaging Centre, The University of Manchester, Manchester, UK
| | - Anthony D Whetton
- Stem Cell and Leukaemia Proteomics Laboratory, Manchester Academic Health Science Centre, Wolfson Molecular Imaging Centre, The University of Manchester, Manchester, UK
| | - Stefan Meyer
- Stem Cell and Leukaemia Proteomics Laboratory, Manchester Academic Health Science Centre, Wolfson Molecular Imaging Centre, The University of Manchester, Manchester, UK
| | - Farhad Ravandi-Kashani
- Department of Leukemia, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Gautam Borthakur
- Department of Leukemia, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Kevin R Coombes
- Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Nianxiang Zhang
- Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Steven Kornblau
- Department of Leukemia, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
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39
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Wertheim GBW, Hexner E, Bagg A. Molecular-based classification of acute myeloid leukemia and its role in directing rational therapy: personalized medicine for profoundly promiscuous proliferations. Mol Diagn Ther 2013. [PMID: 23184342 DOI: 10.1007/s40291-012-0009-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Acute myeloid leukemia (AML) is not a single pathologic entity but represents a heterogeneous group of malignancies. This heterogeneity is exemplified by the variable clinical outcomes that are observed in patients with AML, and it is largely the result of diverse mutations within the leukemic cells. These mutations range from relatively large genetic alterations, such as gains, losses, and translocations of chromosomes, to single nucleotide changes. Detection of many of these mutations is required for accurate diagnosis, prognosis, and treatment of patients with AML. As such, many testing modalities have been developed and are currently employed in clinical laboratories to ascertain mutational status at prognostically and therapeutically critical loci. The assays include those that specifically identify large chromosomal alterations, such as conventional metaphase analysis and fluorescence in situ hybridization, and methods that are geared more toward analysis of small mutations, such as PCR with allele-specific oligonucleotide primers. Furthermore, newer tests, including array analysis and next-generation sequencing, which can simultaneously probe numerous molecular aberrancies within tumor cells, are likely to become commonplace in AML diagnostics. Each testing method clearly has advantages and disadvantages, an understanding of which should influence the choice of test in various clinical circumstances. To aid such understanding, this review discusses both genetic mutations in AML and the clinical tests-including their pros and cons-that may be used to probe these abnormalities. Additionally, we highlight the significance of genetic testing by describing cases in which results of genetic testing significantly influence clinical management of patients with AML.
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Affiliation(s)
- Gerald B W Wertheim
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
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40
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Kojima K, Kornblau SM, Ruvolo V, Dilip A, Duvvuri S, Davis RE, Zhang M, Wang Z, Coombes KR, Zhang N, Qiu YH, Burks JK, Kantarjian H, Shacham S, Kauffman M, Andreeff M. Prognostic impact and targeting of CRM1 in acute myeloid leukemia. Blood 2013; 121:4166-74. [PMID: 23564911 PMCID: PMC3656451 DOI: 10.1182/blood-2012-08-447581] [Citation(s) in RCA: 164] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2012] [Accepted: 03/28/2013] [Indexed: 11/20/2022] Open
Abstract
Chromosomal region maintenance 1 (CRM1) is a nuclear export receptor recognizing proteins bearing a leucine-rich nuclear export signal. CRM1 is involved in nuclear export of tumor suppressors such as p53. We investigated the prognostic significance of CRM1 in acute myeloid leukemia (AML) and effects of a novel small-molecule selective inhibitor of CRM1. CRM1 protein expression was determined in 511 newly diagnosed AML patients and was correlated with mouse double minute 2 (MDM2) and p53 levels. High CRM1 expression was associated with short survival of patients and remained an adverse prognostic factor in multivariate analysis. CRM1 inhibitor KPT-185 induced mainly full-length p53 and apoptosis in a p53-dependent manner, whereas inhibition of proliferation was p53 independent. Patient samples with p53 mutations showed low sensitivity to KPT-185. Nuclear retention of p53 induced by CRM1 inhibition synergized with increased levels of p53 induced by MDM2 inhibition in apoptosis induction. KPT-185 and Nutlin-3a, alone and in combination, induced synergistic apoptosis in patient-derived CD34(+)/CD38(-) AML, but not in normal progenitor cells. Data suggest that CRM1 exerts an antiapoptotic function and is highly prognostic in AML. We propose a novel combinatorial approach for the therapy of AML, aimed at maximal activation of p53-mediated apoptosis by concomitant MDM2 and CRM1 inhibition.
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MESH Headings
- Acrylates/therapeutic use
- Antineoplastic Agents/therapeutic use
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/physiology
- Cells, Cultured
- Drug Evaluation, Preclinical
- Drug Resistance, Neoplasm/genetics
- Female
- HL-60 Cells
- Humans
- Karyopherins/antagonists & inhibitors
- Karyopherins/genetics
- Karyopherins/physiology
- Leukemia, Myeloid, Acute/diagnosis
- Leukemia, Myeloid, Acute/drug therapy
- Leukemia, Myeloid, Acute/genetics
- Male
- Molecular Targeted Therapy
- Prognosis
- Receptors, Cytoplasmic and Nuclear/antagonists & inhibitors
- Receptors, Cytoplasmic and Nuclear/genetics
- Receptors, Cytoplasmic and Nuclear/physiology
- Triazoles/therapeutic use
- Tumor Suppressor Protein p53/genetics
- Tumor Suppressor Protein p53/metabolism
- Tumor Suppressor Protein p53/physiology
- U937 Cells
- Exportin 1 Protein
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Affiliation(s)
- Kensuke Kojima
- Section of Molecular Hematology and Therapy, Department of Leukemia, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA.
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41
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York H, Kornblau SM, Qutub AA. Network analysis of reverse phase protein expression data: characterizing protein signatures in acute myeloid leukemia cytogenetic categories t(8;21) and inv(16). Proteomics 2012; 12:2084-93. [PMID: 22623292 DOI: 10.1002/pmic.201100491] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Acute myeloid leukemia (AML) patients present with cancerous cells originating from bone marrow. Proteomic data on AML patient cells provides critical information on the key molecules associated with the disease. Here, we introduce a new computational approach to identify complex patterns in protein signaling from reverse phase protein array data. We analyzed the expression of 203 proteins in cells taken from AML patients. Dominant overlapping protein networks between subtypes of AML patients were characterized computationally, through a paired t-test approach looking at relative protein expression. In the first application of this method, we compared recurrent cytogenetic abnormalities inv(16) and t(8;21), both affecting core-binding factor (CBFβ), to normal CD34(+) cells and to each other. Six hundred seventy-eight sets of proteins were identified as significantly different in both inv(16) and t(8;21) compared to controls, at the Bonferroni number, α < 2.44 × 10(-6) . We strengthened our predictions by comparing results to those obtained using lasso regression analysis. Signaling networks were constructed from the protein pairs that were significantly different in the t-test and lasso regression analysis. Predicted networks were also compared to known networks from public protein-protein interaction and signaling databases. By characterizing unique "protein signatures" through this rapid computational analysis, and placing them in the context of canonical biological networks, we identify signaling pathways distinct to subcategories of AML patients.
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Affiliation(s)
- Heather York
- Department of Bioengineering, Rice University, Houston, TX, USA
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42
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ERG and FLI1 binding sites demarcate targets for aberrant epigenetic regulation by AML1-ETO in acute myeloid leukemia. Blood 2012; 120:4038-48. [PMID: 22983443 DOI: 10.1182/blood-2012-05-429050] [Citation(s) in RCA: 87] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
ERG and FLI1 are closely related members of the ETS family of transcription factors and have been identified as essential factors for the function and maintenance of normal hematopoietic stem cells. Here genome-wide analysis revealed that both ERG and FLI1 occupy similar genomic regions as AML1-ETO in t(8;21) AMLs and identified ERG/FLI1 as proteins that facilitate binding of oncofusion protein complexes. In addition, we demonstrate that ERG and FLI1 bind the RUNX1 promoter and that shRNA-mediated silencing of ERG leads to reduced expression of RUNX1 and AML1-ETO, consistent with a role of ERG in transcriptional activation of these proteins. Finally, we identify H3 acetylation as the epigenetic mark preferentially associated with ETS factor binding. This intimate connection between ERG/FLI1 binding and H3 acetylation implies that one of the molecular strategies of oncofusion proteins, such as AML1-ETO and PML-RAR-α, involves the targeting of histone deacetylase activities to ERG/FLI1 bound hematopoietic regulatory sites. Together, these results highlight the dual importance of ETS factors in t(8;21) leukemogenesis, both as transcriptional regulators of the oncofusion protein itself as well as proteins that facilitate AML1-ETO binding.
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43
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Concomitant inhibition of DNA methyltransferase and BCL-2 protein function synergistically induce mitochondrial apoptosis in acute myelogenous leukemia cells. Ann Hematol 2012; 91:1861-70. [PMID: 22893484 DOI: 10.1007/s00277-012-1537-8] [Citation(s) in RCA: 121] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2012] [Accepted: 07/23/2012] [Indexed: 01/12/2023]
Abstract
DNA methylation and BLC-2 are potential therapeutic targets in acute myeloid leukemia (AML). We investigated pharmacologic interaction between the DNA methyltransferase inhibitor 5-azacytidine (5-AZA) and the BCL-2 inhibitor ABT-737. Increased BCL-2 expression determined by reverse phase protein analysis was associated with poor survival in AML patients with unfavorable cytogenetics (n = 195). We found that 5-AZA, which itself has modest apoptotic activity, acts synergistically with ABT-737 to induce apoptosis. The 5-AZA/ABT-737 combination enhanced mitochondrial outer membrane permeabilization, as evidenced by effective conformational activation of BAX and ∆ψ(m) loss. Although absence of p53 limited apoptotic activities of 5-AZA and ABT-737 as single agents, the combination synergistically induced apoptosis independent of p53 expression. 5-AZA down-regulated MCL-1, known to mediate resistance to ABT-737, in a p53-independent manner. The 5-AZA/ABT-737 combination synergistically induced apoptosis in AML cells in seven of eight patients. 5-AZA significantly reduced MCL-1 levels in two of three samples examined. Our data provide a molecular rationale for this combination strategy in AML therapy.
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