1
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Bordeleau ME, Audemard É, Métois A, Theret L, Lisi V, Farah A, Spinella JF, Chagraoui J, Moujaber O, Aubert L, Khakipoor B, Mallinger L, Boivin I, Mayotte N, Hajmirza A, Bonneil É, Béliveau F, Pfammatter S, Feghaly A, Boucher G, Gendron P, Thibault P, Barabé F, Lemieux S, Richard-Carpentier G, Hébert J, Lavallée VP, Roux PP, Sauvageau G. Immunotherapeutic targeting of surfaceome heterogeneity in AML. Cell Rep 2024; 43:114260. [PMID: 38838225 DOI: 10.1016/j.celrep.2024.114260] [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: 10/05/2023] [Revised: 01/29/2024] [Accepted: 05/07/2024] [Indexed: 06/07/2024] Open
Abstract
Immunotherapy remains underexploited in acute myeloid leukemia (AML) compared to other hematological malignancies. Currently, gemtuzumab ozogamicin is the only therapeutic antibody approved for this disease. Here, to identify potential targets for immunotherapeutic intervention, we analyze the surface proteome of 100 genetically diverse primary human AML specimens for the identification of cell surface proteins and conduct single-cell transcriptome analyses on a subset of these specimens to assess antigen expression at the sub-population level. Through this comprehensive effort, we successfully identify numerous antigens and markers preferentially expressed by primitive AML cells. Many identified antigens are targeted by therapeutic antibodies currently under clinical evaluation for various cancer types, highlighting the potential therapeutic value of the approach. Importantly, this initiative uncovers AML heterogeneity at the surfaceome level, identifies several antigens and potential primitive cell markers characterizing AML subgroups, and positions immunotherapy as a promising approach to target AML subgroup specificities.
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Affiliation(s)
- Marie-Eve Bordeleau
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada.
| | - Éric Audemard
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Arnaud Métois
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Louis Theret
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Véronique Lisi
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Centre Hospitalier Universitaire Sainte-Justine Research Center, Montréal, QC H3T 1C5, Canada
| | - Azer Farah
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Centre Hospitalier Universitaire Sainte-Justine Research Center, Montréal, QC H3T 1C5, Canada
| | - Jean-François Spinella
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Jalila Chagraoui
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Ossama Moujaber
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Léo Aubert
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Banafsheh Khakipoor
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Centre Hospitalier Universitaire Sainte-Justine Research Center, Montréal, QC H3T 1C5, Canada
| | - Laure Mallinger
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Isabel Boivin
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Nadine Mayotte
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Azadeh Hajmirza
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Éric Bonneil
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - François Béliveau
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Quebec Leukemia Cell Bank, Maisonneuve-Rosemont Hospital, Montréal, QC H1T 2M4, Canada
| | - Sybille Pfammatter
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Albert Feghaly
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Geneviève Boucher
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Patrick Gendron
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Pierre Thibault
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Department of Chemistry, Faculty of Arts and Science, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Frédéric Barabé
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Centre de Recherche du Centre Hospitalier Universitaire de Québec, Université Laval, Québec, QC G1V 4G2, Canada
| | - Sébastien Lemieux
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Department of Biochemistry and Molecular Medicine, Faculty of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada.
| | - Guillaume Richard-Carpentier
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2C1, Canada; Department of Medicine, Division of Medical Oncology and Hematology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada.
| | - Josée Hébert
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Quebec Leukemia Cell Bank, Maisonneuve-Rosemont Hospital, Montréal, QC H1T 2M4, Canada; Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada; Division of Hematology-Oncology, Maisonneuve-Rosemont Hospital, Montréal, QC H1T 2M4, Canada.
| | - Vincent-Philippe Lavallée
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Centre Hospitalier Universitaire Sainte-Justine Research Center, Montréal, QC H3T 1C5, Canada; Department of Pediatrics, Faculty of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada; Hematology and Oncology Division, Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC H3T 1C5, Canada.
| | - Philippe P Roux
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Department of Pathology and Cell Biology, Faculty of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada.
| | - Guy Sauvageau
- The Leucegene project at Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC H3T 1J4, Canada; Quebec Leukemia Cell Bank, Maisonneuve-Rosemont Hospital, Montréal, QC H1T 2M4, Canada; Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, QC H3T 1J4, Canada; Division of Hematology-Oncology, Maisonneuve-Rosemont Hospital, Montréal, QC H1T 2M4, Canada.
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2
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Proteogenomic analysis of acute myeloid leukemia associates relapsed disease with reprogrammed energy metabolism both in adults and children. Leukemia 2023; 37:550-559. [PMID: 36572751 PMCID: PMC9991901 DOI: 10.1038/s41375-022-01796-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 12/06/2022] [Accepted: 12/08/2022] [Indexed: 12/27/2022]
Abstract
Despite improvement of current treatment strategies and novel targeted drugs, relapse and treatment resistance largely determine the outcome for acute myeloid leukemia (AML) patients. To identify the underlying molecular characteristics, numerous studies have been aimed to decipher the genomic- and transcriptomic landscape of AML. Nevertheless, further molecular changes allowing malignant cells to escape treatment remain to be elucidated. Mass spectrometry is a powerful tool enabling detailed insights into proteomic changes that could explain AML relapse and resistance. Here, we investigated AML samples from 47 adult and 22 pediatric patients at serial time-points during disease progression using mass spectrometry-based in-depth proteomics. We show that the proteomic profile at relapse is enriched for mitochondrial ribosomal proteins and subunits of the respiratory chain complex, indicative of reprogrammed energy metabolism from diagnosis to relapse. Further, higher levels of granzymes and lower levels of the anti-inflammatory protein CR1/CD35 suggest an inflammatory signature promoting disease progression. Finally, through a proteogenomic approach, we detected novel peptides, which present a promising repertoire in the search for biomarkers and tumor-specific druggable targets. Altogether, this study highlights the importance of proteomic studies in holistic approaches to improve treatment and survival of AML patients.
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3
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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: 4] [Impact Index Per Article: 4.0] [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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4
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Netto LES, Machado LESF. Preferential redox regulation of cysteine‐based protein tyrosine phosphatases: structural and biochemical diversity. FEBS J 2022; 289:5480-5504. [DOI: 10.1111/febs.16466] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 03/20/2022] [Accepted: 04/28/2022] [Indexed: 12/30/2022]
Affiliation(s)
- Luís Eduardo S. Netto
- Departamento de Genética e Biologia Evolutiva Instituto de Biociências Universidade de São Paulo Brazil
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5
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Mirhadi S, Tam S, Li Q, Moghal N, Pham NA, Tong J, Golbourn BJ, Krieger JR, Taylor P, Li M, Weiss J, Martins-Filho SN, Raghavan V, Mamatjan Y, Khan AA, Cabanero M, Sakashita S, Huo K, Agnihotri S, Ishizawa K, Waddell TK, Zadeh G, Yasufuku K, Liu G, Shepherd FA, Moran MF, Tsao MS. Integrative analysis of non-small cell lung cancer patient-derived xenografts identifies distinct proteotypes associated with patient outcomes. Nat Commun 2022; 13:1811. [PMID: 35383171 PMCID: PMC8983714 DOI: 10.1038/s41467-022-29444-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 03/17/2022] [Indexed: 12/24/2022] Open
Abstract
Non-small cell lung cancer (NSCLC) is the leading cause of cancer deaths worldwide. Only a fraction of NSCLC harbor actionable driver mutations and there is an urgent need for patient-derived model systems that will enable the development of new targeted therapies. NSCLC and other cancers display profound proteome remodeling compared to normal tissue that is not predicted by DNA or RNA analyses. Here, we generate 137 NSCLC patient-derived xenografts (PDXs) that recapitulate the histology and molecular features of primary NSCLC. Proteome analysis of the PDX models reveals 3 adenocarcinoma and 2 squamous cell carcinoma proteotypes that are associated with different patient outcomes, protein-phosphotyrosine profiles, signatures of activated pathways and candidate targets, and in adenocarcinoma, stromal immune features. These findings portend proteome-based NSCLC classification and treatment and support the PDX resource as a viable model for the development of new targeted therapies. With non-small cell lung cancer (NSCLC) being the leading cause of cancer deaths worldwide, the development of targeted therapies remains crucial. Here, the generation and multi-omics characterization of 137 NSCLC patient-derived xenografts provides a resource for potential classifications and targets.
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Affiliation(s)
- Shideh Mirhadi
- Program in Cell Biology, Hospital for Sick Children, Toronto, ON, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Shirley Tam
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Quan Li
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Nadeem Moghal
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Nhu-An Pham
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Jiefei Tong
- Program in Cell Biology, Hospital for Sick Children, Toronto, ON, Canada
| | - Brian J Golbourn
- John G. Rangos Sr. Research Center, Children's Hospital of Pittsburgh, and Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | | | - Paul Taylor
- Program in Cell Biology, Hospital for Sick Children, Toronto, ON, Canada
| | - Ming Li
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Jessica Weiss
- Department of Biostatistics, Princess Margaret Cancer Centre, Toronto, ON, Canada
| | - Sebastiao N Martins-Filho
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Vibha Raghavan
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Yasin Mamatjan
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Aafaque A Khan
- Program in Cell Biology, Hospital for Sick Children, Toronto, ON, Canada
| | - Michael Cabanero
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Shingo Sakashita
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Kugeng Huo
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Sameer Agnihotri
- John G. Rangos Sr. Research Center, Children's Hospital of Pittsburgh, and Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kota Ishizawa
- Division of Thoracic Surgery, Toronto General Hospital, University Health Network, Toronto, ON, Canada
| | - Thomas K Waddell
- Division of Thoracic Surgery, Toronto General Hospital, University Health Network, Toronto, ON, Canada.,Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Gelareh Zadeh
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Kazuhiro Yasufuku
- Division of Thoracic Surgery, Toronto General Hospital, University Health Network, Toronto, ON, Canada.,Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Geoffrey Liu
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Medicine, Division of Medical Oncology, University of Toronto, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Frances A Shepherd
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.,Department of Medicine, Division of Medical Oncology, University of Toronto, Toronto, ON, Canada
| | - Michael F Moran
- Program in Cell Biology, Hospital for Sick Children, Toronto, ON, Canada. .,Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada. .,Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
| | - Ming-Sound Tsao
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada. .,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. .,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
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6
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Multimerin-1 and cancer: a review. Biosci Rep 2022; 42:230760. [PMID: 35132992 PMCID: PMC8881648 DOI: 10.1042/bsr20211248] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 01/29/2022] [Accepted: 02/01/2022] [Indexed: 11/21/2022] Open
Abstract
Multimerin-1 (MMRN1) is a platelet protein with a role in haemostasis and coagulation. It is also present in endothelial cells (ECs) and the extracellular matrix (ECM), where it may be involved in cell adhesion, but its molecular functions and protein–protein interactions in these cellular locations have not been studied in detail yet. In recent years, MMRN1 has been identified as a differentially expressed gene (DEG) in various cancers and it has been proposed as a possible cancer biomarker. Some evidence suggest that MMRN1 expression is regulated by methylation, protein interactions, and non-coding RNAs (ncRNAs) in different cancers. This raises the questions if a functional role of MMRN1 is being targeted during cancer development, and if MMRN1’s differential expression pattern correlates with cancer progression. As a result, it is timely to review the current state of what is known about MMRN1 to help inform future research into MMRN1’s molecular mechanisms in cancer.
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7
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Tsumagari K, Niinae T, Otaka A, Ishihama Y. Peptide probes containing a non-hydrolyzable phosphotyrosine-mimetic residue for enrichment of protein tyrosine phosphatases. Proteomics 2021; 22:e2100144. [PMID: 34714599 DOI: 10.1002/pmic.202100144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 10/25/2021] [Accepted: 10/26/2021] [Indexed: 11/07/2022]
Abstract
We developed peptide probes containing a non-hydrolyzable phosphotyrosine mimetic, 4-[difluoro(phosphono)methyl]-L-phenylalanine (F2 Pmp) for enrichment of protein tyrosine phosphatases (PTPs). We found that different F2 Pmp probes can enrich different PTPs, depending on the probe sequence. Furthermore, proteins containing a Src homology 2 (SH2) domain were enriched together. Importantly, probes containing phosphotyrosine instead of F2 Pmp failed to enrich PTPs due to dephosphorylation during the pulldown step. This enrichment approach using peptides containing F2 Pmp could be a generic tool for tyrosine phosphatome analysis without the use of antibodies. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Kazuya Tsumagari
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, 606-8501, Japan.,Center for Integrated Medical Research, Keio University School of Medicine, Tokyo, 160-8582, Japan
| | - Tomoya Niinae
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, 606-8501, Japan
| | - Akira Otaka
- Institute of Biomedical Sciences and Graduate School of Pharmaceutical Sciences, Tokushima University, Tokushima, 770-8505, Japan
| | - Yasushi Ishihama
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, 606-8501, Japan.,Laboratory of Clinical and Analytical Chemistry, National Institute of Biomedical Innovation, Health and Nutrition, Ibaraki, Osaka, 567-0085, Japan
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8
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Hernandez-Valladares M, Bruserud Ø, Selheim F. The Implementation of Mass Spectrometry-Based Proteomics Workflows in Clinical Routines of Acute Myeloid Leukemia: Applicability and Perspectives. Int J Mol Sci 2020; 21:ijms21186830. [PMID: 32957646 PMCID: PMC7556012 DOI: 10.3390/ijms21186830] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 09/10/2020] [Accepted: 09/15/2020] [Indexed: 02/08/2023] Open
Abstract
With the current reproducibility of proteome preparation workflows along with the speed and sensitivity of the mass spectrometers, the transition of the mass spectrometry (MS)-based proteomics technology from biomarker discovery to clinical implementation is under appraisal in the biomedicine community. Therefore, this technology might be implemented soon to detect well-known biomarkers in cancers and other diseases. Acute myeloid leukemia (AML) is an aggressive heterogeneous malignancy that requires intensive treatment to cure the patient. Leukemia relapse is still a major challenge even for patients who have favorable genetic abnormalities. MS-based proteomics could be of great help to both describe the proteome changes of individual patients and identify biomarkers that might encourage specific treatments or clinical strategies. Herein, we will review the advances and availability of the MS-based proteomics strategies that could already be used in clinical proteomics. However, the heterogeneity of complex diseases as AML requires consensus to recognize AML biomarkers and to establish MS-based workflows that allow their unbiased identification and quantification. Although our literature review appears promising towards the utilization of MS-based proteomics in clinical AML in a near future, major efforts are required to validate AML biomarkers and agree on clinically approved workflows.
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MESH Headings
- Biomarkers, Tumor/analysis
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/metabolism
- Computational Biology
- Humans
- Leukemia, Myeloid, Acute/diagnosis
- Leukemia, Myeloid, Acute/genetics
- Leukemia, Myeloid, Acute/metabolism
- Leukemia, Myeloid, Acute/therapy
- Mass Spectrometry/methods
- Prognosis
- Proteome/analysis
- Proteome/metabolism
- Proteomics/methods
- Robotics/instrumentation
- Robotics/methods
- Workflow
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Affiliation(s)
- Maria Hernandez-Valladares
- Department of Clinical Science, University of Bergen, 5021 Bergen, Norway
- The Proteomics Facility of the University of Bergen (PROBE), Department of Biomedicine, University of Bergen, 5009 Bergen, Norway
- Correspondence: (M.H.-V.); (Ø.B.); (F.S.); Tel.: +47-55586368 (M.H.-V.); +47-55972997 (Ø.B.); +47-55586368 (F.S.)
| | - Øystein Bruserud
- Department of Clinical Science, University of Bergen, 5021 Bergen, Norway
- Correspondence: (M.H.-V.); (Ø.B.); (F.S.); Tel.: +47-55586368 (M.H.-V.); +47-55972997 (Ø.B.); +47-55586368 (F.S.)
| | - Frode Selheim
- The Proteomics Facility of the University of Bergen (PROBE), Department of Biomedicine, University of Bergen, 5009 Bergen, Norway
- The Department of Biomedicine, University of Bergen, 5009 Bergen, Norway
- Correspondence: (M.H.-V.); (Ø.B.); (F.S.); Tel.: +47-55586368 (M.H.-V.); +47-55972997 (Ø.B.); +47-55586368 (F.S.)
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9
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van Alphen C, Cloos J, Beekhof R, Cucchi DGJ, Piersma SR, Knol JC, Henneman AA, Pham TV, van Meerloo J, Ossenkoppele GJ, Verheul HMW, Janssen JJWM, Jimenez CR. Phosphotyrosine-based Phosphoproteomics for Target Identification and Drug Response Prediction in AML Cell Lines. Mol Cell Proteomics 2020; 19:884-899. [PMID: 32102969 PMCID: PMC7196578 DOI: 10.1074/mcp.ra119.001504] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 02/05/2020] [Indexed: 12/20/2022] Open
Abstract
Acute myeloid leukemia (AML) is a clonal disorder arising from hematopoietic myeloid progenitors. Aberrantly activated tyrosine kinases (TK) are involved in leukemogenesis and are associated with poor treatment outcome. Kinase inhibitor (KI) treatment has shown promise in improving patient outcome in AML. However, inhibitor selection for patients is suboptimal.In a preclinical effort to address KI selection, we analyzed a panel of 16 AML cell lines using phosphotyrosine (pY) enrichment-based, label-free phosphoproteomics. The Integrative Inferred Kinase Activity (INKA) algorithm was used to identify hyperphosphorylated, active kinases as candidates for KI treatment, and efficacy of selected KIs was tested.Heterogeneous signaling was observed with between 241 and 2764 phosphopeptides detected per cell line. Of 4853 identified phosphopeptides with 4229 phosphosites, 4459 phosphopeptides (4430 pY) were linked to 3605 class I sites (3525 pY). INKA analysis in single cell lines successfully pinpointed driver kinases (PDGFRA, JAK2, KIT and FLT3) corresponding with activating mutations present in these cell lines. Furthermore, potential receptor tyrosine kinase (RTK) drivers, undetected by standard molecular analyses, were identified in four cell lines (FGFR1 in KG-1 and KG-1a, PDGFRA in Kasumi-3, and FLT3 in MM6). These cell lines proved highly sensitive to specific KIs. Six AML cell lines without a clear RTK driver showed evidence of MAPK1/3 activation, indicative of the presence of activating upstream RAS mutations. Importantly, FLT3 phosphorylation was demonstrated in two clinical AML samples with a FLT3 internal tandem duplication (ITD) mutation.Our data show the potential of pY-phosphoproteomics and INKA analysis to provide insight in AML TK signaling and identify hyperactive kinases as potential targets for treatment in AML cell lines. These results warrant future investigation of clinical samples to further our understanding of TK phosphorylation in relation to clinical response in the individual patient.
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Affiliation(s)
- Carolien van Alphen
- Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center; Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, OncoProteomics Laboratory, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam Department of Hematology, De Boelelaan 1117, Amsterdam, Netherlands
| | - Jacqueline Cloos
- Amsterdam UMC, Vrije Universiteit Amsterdam Department of Hematology, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pediatric Oncology, De Boelelaan 1117, Amsterdam, Netherlands
| | - Robin Beekhof
- Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center; Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, OncoProteomics Laboratory, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands
| | - David G J Cucchi
- Amsterdam UMC, Vrije Universiteit Amsterdam Department of Hematology, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pediatric Oncology, De Boelelaan 1117, Amsterdam, Netherlands
| | - Sander R Piersma
- Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center; Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, OncoProteomics Laboratory, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands
| | - Jaco C Knol
- Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center; Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, OncoProteomics Laboratory, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands
| | - Alex A Henneman
- Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center; Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, OncoProteomics Laboratory, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands
| | - Thang V Pham
- Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center; Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, OncoProteomics Laboratory, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands
| | - Johan van Meerloo
- Amsterdam UMC, Vrije Universiteit Amsterdam Department of Hematology, De Boelelaan 1117, Amsterdam, Netherlands
| | - Gert J Ossenkoppele
- Amsterdam UMC, Vrije Universiteit Amsterdam Department of Hematology, De Boelelaan 1117, Amsterdam, Netherlands
| | - Henk M W Verheul
- Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center; Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands
| | - Jeroen J W M Janssen
- Amsterdam UMC, Vrije Universiteit Amsterdam Department of Hematology, De Boelelaan 1117, Amsterdam, Netherlands
| | - Connie R Jimenez
- Amsterdam UMC, Vrije Universiteit Amsterdam, Medical Oncology, Cancer Center; Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, OncoProteomics Laboratory, Cancer Center Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands.
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10
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Aasebø E, Berven FS, Bartaula-Brevik S, Stokowy T, Hovland R, Vaudel M, Døskeland SO, McCormack E, Batth TS, Olsen JV, Bruserud Ø, Selheim F, Hernandez-Valladares M. Proteome and Phosphoproteome Changes Associated with Prognosis in Acute Myeloid Leukemia. Cancers (Basel) 2020; 12:cancers12030709. [PMID: 32192169 PMCID: PMC7140113 DOI: 10.3390/cancers12030709] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 03/05/2020] [Accepted: 03/13/2020] [Indexed: 12/12/2022] Open
Abstract
Acute myeloid leukemia (AML) is a hematological cancer that mainly affects the elderly. Although complete remission (CR) is achieved for the majority of the patients after induction and consolidation therapies, nearly two-thirds relapse within a short interval. Understanding biological factors that determine relapse has become of major clinical interest in AML. We utilized liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify the protein changes and protein phosphorylation events associated with AML relapse in primary cells from 41 AML patients at time of diagnosis. Patients were defined as relapse-free if they had not relapsed within a five-year clinical follow-up after AML diagnosis. Relapse was associated with increased expression of RNA processing proteins and decreased expression of V-ATPase proteins. We also observed an increase in phosphorylation events catalyzed by cyclin-dependent kinases (CDKs) and casein kinase 2 (CSK2). The biological relevance of the proteome findings was supported by cell proliferation assays using inhibitors of V-ATPase (bafilomycin), CSK2 (CX-4945), CDK4/6 (abemaciclib) and CDK2/7/9 (SNS-032). While bafilomycin preferentially inhibited the cells from relapse patients, the kinase inhibitors were less efficient in these cells. This suggests that therapy against the upregulated kinases could also target the factors inducing their upregulation rather than their activity. This study, therefore, presents markers that could help predict AML relapse and direct therapeutic strategies.
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Affiliation(s)
- Elise Aasebø
- Department of Clinical Science, University of Bergen, 5021 Bergen, Norway; (E.A.); (S.B.-B.); (T.S.); (M.V.); (Ø.B.)
- The Proteomics Facility of the University of Bergen (PROBE), University of Bergen, 5009 Bergen, Norway; (F.S.B.); (F.S.)
| | - Frode S. Berven
- The Proteomics Facility of the University of Bergen (PROBE), University of Bergen, 5009 Bergen, Norway; (F.S.B.); (F.S.)
- The Department of Biomedicine, University of Bergen, 5009 Bergen, Norway;
| | - Sushma Bartaula-Brevik
- Department of Clinical Science, University of Bergen, 5021 Bergen, Norway; (E.A.); (S.B.-B.); (T.S.); (M.V.); (Ø.B.)
| | - Tomasz Stokowy
- Department of Clinical Science, University of Bergen, 5021 Bergen, Norway; (E.A.); (S.B.-B.); (T.S.); (M.V.); (Ø.B.)
- Department for Medical Genetics, Haukeland University Hospital, 5021 Bergen, Norway;
| | - Randi Hovland
- Department for Medical Genetics, Haukeland University Hospital, 5021 Bergen, Norway;
- Department of Biological Sciences, University of Bergen, 5006 Bergen, Norway
| | - Marc Vaudel
- Department of Clinical Science, University of Bergen, 5021 Bergen, Norway; (E.A.); (S.B.-B.); (T.S.); (M.V.); (Ø.B.)
| | | | - Emmet McCormack
- Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, 5021 Bergen, Norway;
| | - Tanveer S. Batth
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen, Denmark; (T.S.B.); (J.V.O.)
| | - Jesper V. Olsen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen, Denmark; (T.S.B.); (J.V.O.)
| | - Øystein Bruserud
- Department of Clinical Science, University of Bergen, 5021 Bergen, Norway; (E.A.); (S.B.-B.); (T.S.); (M.V.); (Ø.B.)
| | - Frode Selheim
- The Proteomics Facility of the University of Bergen (PROBE), University of Bergen, 5009 Bergen, Norway; (F.S.B.); (F.S.)
- The Department of Biomedicine, University of Bergen, 5009 Bergen, Norway;
| | - Maria Hernandez-Valladares
- Department of Clinical Science, University of Bergen, 5021 Bergen, Norway; (E.A.); (S.B.-B.); (T.S.); (M.V.); (Ø.B.)
- The Proteomics Facility of the University of Bergen (PROBE), University of Bergen, 5009 Bergen, Norway; (F.S.B.); (F.S.)
- Correspondence: ; Tel.: +47-5558-6368
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11
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Hernandez-Valladares M, Wangen R, Berven FS, Guldbrandsen A. Protein Post-Translational Modification Crosstalk in Acute Myeloid Leukemia Calls for Action. Curr Med Chem 2019; 26:5317-5337. [PMID: 31241430 DOI: 10.2174/0929867326666190503164004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Revised: 11/23/2018] [Accepted: 02/01/2019] [Indexed: 01/24/2023]
Abstract
BACKGROUND Post-translational modification (PTM) crosstalk is a young research field. However, there is now evidence of the extraordinary characterization of the different proteoforms and their interactions in a biological environment that PTM crosstalk studies can describe. Besides gene expression and phosphorylation profiling of acute myeloid leukemia (AML) samples, the functional combination of several PTMs that might contribute to a better understanding of the complexity of the AML proteome remains to be discovered. OBJECTIVE By reviewing current workflows for the simultaneous enrichment of several PTMs and bioinformatics tools to analyze mass spectrometry (MS)-based data, our major objective is to introduce the PTM crosstalk field to the AML research community. RESULTS After an introduction to PTMs and PTM crosstalk, this review introduces several protocols for the simultaneous enrichment of PTMs. Two of them allow a simultaneous enrichment of at least three PTMs when using 0.5-2 mg of cell lysate. We have reviewed many of the bioinformatics tools used for PTM crosstalk discovery as its complex data analysis, mainly generated from MS, becomes challenging for most AML researchers. We have presented several non-AML PTM crosstalk studies throughout the review in order to show how important the characterization of PTM crosstalk becomes for the selection of disease biomarkers and therapeutic targets. CONCLUSION Herein, we have reviewed the advances and pitfalls of the emerging PTM crosstalk field and its potential contribution to unravel the heterogeneity of AML. The complexity of sample preparation and bioinformatics workflows demands a good interaction between experts of several areas.
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Affiliation(s)
- Maria Hernandez-Valladares
- Department of Clinical Science, Faculty of Medicine, University of Bergen, Jonas Lies vei 87, N-5021 Bergen, Norway.,The Proteomics Unit at the University of Bergen, Department of Biomedicine, Building for Basic Biology, Faculty of Medicine, University of Bergen, Jonas Lies vei 91, N-5009 Bergen, Norway
| | - Rebecca Wangen
- Department of Clinical Science, Faculty of Medicine, University of Bergen, Jonas Lies vei 87, N-5021 Bergen, Norway.,The Proteomics Unit at the University of Bergen, Department of Biomedicine, Building for Basic Biology, Faculty of Medicine, University of Bergen, Jonas Lies vei 91, N-5009 Bergen, Norway.,Department of Internal Medicine, Hematology Section, Haukeland University Hospital, Jonas Lies vei 65, N-5021 Bergen, Norway
| | - Frode S Berven
- The Proteomics Unit at the University of Bergen, Department of Biomedicine, Building for Basic Biology, Faculty of Medicine, University of Bergen, Jonas Lies vei 91, N-5009 Bergen, Norway
| | - Astrid Guldbrandsen
- The Proteomics Unit at the University of Bergen, Department of Biomedicine, Building for Basic Biology, Faculty of Medicine, University of Bergen, Jonas Lies vei 91, N-5009 Bergen, Norway.,Computational Biology Unit, Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Bergen, Thormøhlensgt 55, N-5008 Bergen, Norway
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12
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Quantitative Phosphoproteomic and Physiological Analyses Provide Insights into the Formation of the Variegated Leaf in Catalpa fargesii. Int J Mol Sci 2019; 20:ijms20081895. [PMID: 30999580 PMCID: PMC6514904 DOI: 10.3390/ijms20081895] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 04/11/2019] [Accepted: 04/11/2019] [Indexed: 12/29/2022] Open
Abstract
Variegated plants are valuable materials for investigating leaf color regulated mechanisms. To unveil the role of posttranslational modification in the variegated phenotype, we conducted global quantitative phosphoproteomic analysis on different leaf color sectors of Maiyuanjinqiu and the corresponding of Catalpa fargesii using Ti4+-IMAC phosphopeptide enrichment. A total of 3778 phosphorylated sites assigned to 1646 phosphoproteins were identified, and 3221 in 1434 proteins were quantified. Differential phosphoproteins (above 1.5 or below 1/1.5) in various leaf color sectors were selected for functional enrichment analyses. Gene ontology (GO) enrichment revealed that processes of photosynthesis, regulation of the generation of precursor metabolites, response to stress, homeostasis, amino acid metabolism, transport–related processes, and most of the energy metabolisms might contribute to leaf color. KEGG pathway enrichment analysis was performed based on differential phosphoproteins (DPs) in different organelles. The result showed that most enriched pathways were located in the chloroplasts and cytosol. The phosphorylation levels of glycometabolism enzymes might greatly affect leaf variegation. Measurements of fluorescence parameters and enzyme activities confirmed that protein phosphorylation could affect plant physiology by regulating enzyme activity. These results provide new clues for further study the formation mechanisms of naturally variegated phenotype.
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13
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Fang Y, Wu D, Birukov KG. Mechanosensing and Mechanoregulation of Endothelial Cell Functions. Compr Physiol 2019; 9:873-904. [PMID: 30873580 PMCID: PMC6697421 DOI: 10.1002/cphy.c180020] [Citation(s) in RCA: 107] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Vascular endothelial cells (ECs) form a semiselective barrier for macromolecules and cell elements regulated by dynamic interactions between cytoskeletal elements and cell adhesion complexes. ECs also participate in many other vital processes including innate immune reactions, vascular repair, secretion, and metabolism of bioactive molecules. Moreover, vascular ECs represent a unique cell type exposed to continuous, time-dependent mechanical forces: different patterns of shear stress imposed by blood flow in macrovasculature and by rolling blood cells in the microvasculature; circumferential cyclic stretch experienced by the arterial vascular bed caused by heart propulsions; mechanical stretch of lung microvascular endothelium at different magnitudes due to spontaneous respiration or mechanical ventilation in critically ill patients. Accumulating evidence suggests that vascular ECs contain mechanosensory complexes, which rapidly react to changes in mechanical loading, process the signal, and develop context-specific adaptive responses to rebalance the cell homeostatic state. The significance of the interactions between specific mechanical forces in the EC microenvironment together with circulating bioactive molecules in the progression and resolution of vascular pathologies including vascular injury, atherosclerosis, pulmonary edema, and acute respiratory distress syndrome has been only recently recognized. This review will summarize the current understanding of EC mechanosensory mechanisms, modulation of EC responses to humoral factors by surrounding mechanical forces (particularly the cyclic stretch), and discuss recent findings of magnitude-specific regulation of EC functions by transcriptional, posttranscriptional and epigenetic mechanisms using -omics approaches. We also discuss ongoing challenges and future opportunities in developing new therapies targeting dysregulated mechanosensing mechanisms to treat vascular diseases. © 2019 American Physiological Society. Compr Physiol 9:873-904, 2019.
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Affiliation(s)
- Yun Fang
- Department of Medicine, University of Chicago, Chicago, Illinois, USA,Correspondence to
| | - David Wu
- Department of Medicine, University of Chicago, Chicago, Illinois, USA
| | - Konstantin G. Birukov
- Department of Anesthesiology, University of Maryland Baltimore School of Medicine, Baltimore, Maryland, USA
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14
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Reimand J, Isserlin R, Voisin V, Kucera M, Tannus-Lopes C, Rostamianfar A, Wadi L, Meyer M, Wong J, Xu C, Merico D, Bader GD. Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap. Nat Protoc 2019; 14:482-517. [PMID: 30664679 PMCID: PMC6607905 DOI: 10.1038/s41596-018-0103-9] [Citation(s) in RCA: 969] [Impact Index Per Article: 193.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Pathway enrichment analysis helps researchers gain mechanistic insight into gene lists generated from genome-scale (omics) experiments. This method identifies biological pathways that are enriched in a gene list more than would be expected by chance. We explain the procedures of pathway enrichment analysis and present a practical step-by-step guide to help interpret gene lists resulting from RNA-seq and genome-sequencing experiments. The protocol comprises three major steps: definition of a gene list from omics data, determination of statistically enriched pathways, and visualization and interpretation of the results. We describe how to use this protocol with published examples of differentially expressed genes and mutated cancer genes; however, the principles can be applied to diverse types of omics data. The protocol describes innovative visualization techniques, provides comprehensive background and troubleshooting guidelines, and uses freely available and frequently updated software, including g:Profiler, Gene Set Enrichment Analysis (GSEA), Cytoscape and EnrichmentMap. The complete protocol can be performed in ~4.5 h and is designed for use by biologists with no prior bioinformatics training.
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Affiliation(s)
- Jüri Reimand
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Ruth Isserlin
- The Donnelly Centre, University of Toronto, Toronto, ON, Canada
| | | | - Mike Kucera
- The Donnelly Centre, University of Toronto, Toronto, ON, Canada
| | | | | | - Lina Wadi
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Mona Meyer
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Jeff Wong
- The Donnelly Centre, University of Toronto, Toronto, ON, Canada
| | - Changjiang Xu
- The Donnelly Centre, University of Toronto, Toronto, ON, Canada
| | - Daniele Merico
- Deep Genomics Inc., Toronto, ON, Canada
- The Centre for Applied Genomics (TCAG), The Hospital for Sick Children, Toronto, ON, Canada
| | - Gary D Bader
- The Donnelly Centre, University of Toronto, Toronto, ON, Canada.
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
- Department of Computer Science, University of Toronto, Toronto, ON, Canada.
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15
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Teyra J, Singer AU, Schmitges FW, Jaynes P, Kit Leng Lui S, Polyak MJ, Fodil N, Krieger JR, Tong J, Schwerdtfeger C, Brasher BB, Ceccarelli DFJ, Moffat J, Sicheri F, Moran MF, Gros P, Eichhorn PJA, Lenter M, Boehmelt G, Sidhu SS. Structural and Functional Characterization of Ubiquitin Variant Inhibitors of USP15. Structure 2019; 27:590-605.e5. [PMID: 30713027 DOI: 10.1016/j.str.2019.01.002] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Revised: 10/23/2018] [Accepted: 12/31/2018] [Indexed: 12/12/2022]
Abstract
The multi-domain deubiquitinase USP15 regulates diverse eukaryotic processes and has been implicated in numerous diseases. We developed ubiquitin variants (UbVs) that targeted either the catalytic domain or each of three adaptor domains in USP15, including the N-terminal DUSP domain. We also designed a linear dimer (diUbV), which targeted the DUSP and catalytic domains, and exhibited enhanced specificity and more potent inhibition of catalytic activity than either UbV alone. In cells, the UbVs inhibited the deubiquitination of two USP15 substrates, SMURF2 and TRIM25, and the diUbV inhibited the effects of USP15 on the transforming growth factor β pathway. Structural analyses revealed that three distinct UbVs bound to the catalytic domain and locked the active site in a closed, inactive conformation, and one UbV formed an unusual strand-swapped dimer and bound two DUSP domains simultaneously. These inhibitors will enable the study of USP15 function in oncology, neurology, immunology, and inflammation.
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Affiliation(s)
- Joan Teyra
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Alex U Singer
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Frank W Schmitges
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Patrick Jaynes
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Sarah Kit Leng Lui
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Maria J Polyak
- Department of Biochemistry, McGill University, Montreal, QC, Canada; Corbin Therapeutics, Montreal, QC, Canada
| | - Nassima Fodil
- Department of Biochemistry, McGill University, Montreal, QC, Canada; Corbin Therapeutics, Montreal, QC, Canada
| | - Jonathan R Krieger
- SPARC BioCentre, Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Jiefei Tong
- Cell Biology Program, The Hospital for Sick Children, 686 Bay Street, Toronto, ON M5G 0A4, Canada
| | | | - Bradley B Brasher
- Boston Biochem, a Bio-Techne Brand, 840 Memorial Drive, Cambridge, MA 02139, USA
| | - Derek F J Ceccarelli
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada
| | - Jason Moffat
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Frank Sicheri
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Michael F Moran
- SPARC BioCentre, Hospital for Sick Children, Toronto, ON M5G 0A4, Canada; Cell Biology Program, The Hospital for Sick Children, 686 Bay Street, Toronto, ON M5G 0A4, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Philippe Gros
- Department of Biochemistry, McGill University, Montreal, QC, Canada
| | - Pieter J A Eichhorn
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore; Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Martin Lenter
- Boehringer Ingelheim Pharma GmbH & Co KG, Biberach, Germany
| | | | - Sachdev S Sidhu
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada.
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16
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Forthun RB, Aasebø E, Rasinger JD, Bedringaas SL, Berven F, Selheim F, Bruserud Ø, Gjertsen BT. Phosphoprotein DIGE profiles reflect blast differentiation, cytogenetic risk stratification, FLT3/NPM1 mutations and therapy response in acute myeloid leukaemia. J Proteomics 2017; 173:32-41. [PMID: 29175091 DOI: 10.1016/j.jprot.2017.11.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Revised: 09/30/2017] [Accepted: 11/18/2017] [Indexed: 12/12/2022]
Abstract
Acute myeloid leukaemia (AML) is an aggressive blood cancer characterized by a distinct block in differentiation of myeloid progenitors, recurrent chromosomal translocations and gene mutations of which >50% involve signal transduction through dysregulated kinases and phosphatases. In search for novel protein biomarkers for disease stratification we investigated the phosphoproteome in leukaemic cells from 62 AML patients at time of diagnosis using immobilized metal-affinity chromatography, protein separation by two-dimensional differential gel electrophoresis (2D-DIGE) and mass spectrometry before validation by selected reaction monitoring (SRM). Unsupervised clustering found 27 phosphoproteins significantly discriminating patients according to leukaemic cell differentiation (French-American-British (FAB) classification), cytogenetic and mutational (FLT3, NPM1) status or response to chemotherapy. Monocytic differentiation (FAB M4-M5) correlated with enrichment of proteins involved in apoptosis (MOES, ANXA5 and EFHD2). TALDO, a protein associated with thrombocytopenia if down-regulated, was elevated in patients with wild type NPM1 compared to patients with NPM1 mutation. This study demonstrates the potential of quantitative proteomics in AML classification and risk stratification. BIOLOGICAL SIGNIFICANCE Patients diagnosed with AML are currently categorized according to cellular morphology, cytogenetic alterations and mutations, although the majority of these cellular and genetic alterations have no or unsolved impact on therapy selection or prognosis. We therefore explored the phosphoproteome for abundance changes associated with traditional classifiers to unravel patterns that could stratify patients at the protein level. MOES, ANXA5 and EFHD2 were confirmed by SRM to be correlated to monocytic differentiation, whilst TALDO was elevated in NPM1 wild type patients.
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Affiliation(s)
- Rakel Brendsdal Forthun
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
| | - Elise Aasebø
- Department of Biomedicine, Proteomic Unit, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway; Department of Clinical Science, Leukemia Research Group, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
| | | | - Siv Lise Bedringaas
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
| | - Frode Berven
- Department of Biomedicine, Proteomic Unit, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
| | - Frode Selheim
- Department of Biomedicine, Proteomic Unit, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
| | - Øystein Bruserud
- Department of Clinical Science, Leukemia Research Group, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway; Department of Internal Medicine, Hematology Section, Haukeland University Hospital, Bergen, Norway
| | - Bjørn Tore Gjertsen
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway; Department of Internal Medicine, Hematology Section, Haukeland University Hospital, Bergen, Norway.
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17
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Hernandez-Valladares M, Vaudel M, Selheim F, Berven F, Bruserud Ø. Proteogenomics approaches for studying cancer biology and their potential in the identification of acute myeloid leukemia biomarkers. Expert Rev Proteomics 2017; 14:649-663. [DOI: 10.1080/14789450.2017.1352474] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Affiliation(s)
- Maria Hernandez-Valladares
- Department of Clinical Science, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
- Proteomics Unit, Department of Biomedicine, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
| | - Marc Vaudel
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Frode Selheim
- Proteomics Unit, Department of Biomedicine, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
| | - Frode Berven
- Proteomics Unit, Department of Biomedicine, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
| | - Øystein Bruserud
- Department of Clinical Science, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
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