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Abstract
Flow cytometry is a laser-based technology generating a scattered and a fluorescent light signal that enables rapid analysis of the size and granularity of a particle or single cell. In addition, it offers the opportunity to phenotypically characterize and collect the cell with the use of a variety of fluorescent reagents. These reagents include but are not limited to fluorochrome-conjugated antibodies, fluorescent expressing protein-, viability-, and DNA-binding dyes. Major developments in reagents, electronics, and software within the last 30 years have greatly expanded the ability to combine up to 50 antibodies in one single tube. However, these advances also harbor technical risks and interpretation issues in the identification of certain cell populations which will be summarized in this viewpoint article. It will further provide an overview of different potential applications of flow cytometry in research and its possibilities to be used in the clinic.
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Ren AH, Diamandis EP, Kulasingam V. Uncovering the Depths of the Human Proteome: Antibody-based Technologies for Ultrasensitive Multiplexed Protein Detection and Quantification. Mol Cell Proteomics 2021; 20:100155. [PMID: 34597790 PMCID: PMC9357438 DOI: 10.1016/j.mcpro.2021.100155] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 09/01/2021] [Accepted: 09/25/2021] [Indexed: 12/20/2022] Open
Abstract
Probing the human proteome in tissues and biofluids such as plasma is attractive for biomarker and drug target discovery. Recent breakthroughs in multiplex, antibody-based, proteomics technologies now enable the simultaneous quantification of thousands of proteins at as low as sub fg/ml concentrations with remarkable dynamic ranges of up to 10-log. We herein provide a comprehensive guide to the methodologies, performance, technical comparisons, advantages, and disadvantages of established and emerging technologies for the multiplexed ultrasensitive measurement of proteins. Gaining holistic knowledge on these innovations is crucial for choosing the right multiplexed proteomics tool for applications at hand to critically complement traditional proteomics methods. This can bring researchers closer than ever before to elucidating the intricate inner workings and cross talk that spans multitude of proteins in disease mechanisms.
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Affiliation(s)
- Annie H Ren
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada; Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada
| | - Eleftherios P Diamandis
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada; Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada; Department of Clinical Biochemistry, University Health Network, Toronto, Canada
| | - Vathany Kulasingam
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada; Department of Clinical Biochemistry, University Health Network, Toronto, Canada.
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3
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Noh KW, Buettner R, Klein S. Shifting Gears in Precision Oncology-Challenges and Opportunities of Integrative Data Analysis. Biomolecules 2021; 11:biom11091310. [PMID: 34572523 PMCID: PMC8465238 DOI: 10.3390/biom11091310] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 08/26/2021] [Accepted: 09/01/2021] [Indexed: 02/07/2023] Open
Abstract
For decades, research relating to modification of host immunity towards antitumor response activation has been ongoing, with the breakthrough discovery of immune-checkpoint blockers. Several biomarkers with potential predictive value have been reported in recent studies for these novel therapies. However, with the plethora of therapeutic options existing for a given cancer entity, modern oncology is now being confronted with multifactorial interpretation to devise “the best therapy” for the individual patient. Into the bargain come the multiverse guidelines for established and emerging diagnostic biomarkers, as well as the complex interplay between cancer cells and tumor microenvironment, provoking immense challenges in the therapy decision-making process. Through this review, we present various molecular diagnostic modalities and techniques, such as genomics, immunohistochemistry and quantitative image analysis, which have the potential of becoming powerful tools in the development of an optimal treatment regime when analogized with patient characteristics. We will summarize the underlying complexities of these methods and shed light upon the necessary considerations and requirements for data integration. It is our hope to provide compelling evidence to emphasize on the need for inclusion of integrative data analysis in modern cancer therapy, and thereupon paving a path towards precision medicine and better patient outcomes.
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Affiliation(s)
- Ka-Won Noh
- Institute for Pathology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany; (K.-W.N.); (R.B.)
| | - Reinhard Buettner
- Institute for Pathology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany; (K.-W.N.); (R.B.)
| | - Sebastian Klein
- Gerhard-Domagk-Institute of Pathology, University Hospital Münster, 48149 Münster, Germany
- Correspondence: ; Tel.: +49-251-83-57670
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4
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Dunphy K, Dowling P, Bazou D, O’Gorman P. Current Methods of Post-Translational Modification Analysis and Their Applications in Blood Cancers. Cancers (Basel) 2021; 13:1930. [PMID: 33923680 PMCID: PMC8072572 DOI: 10.3390/cancers13081930] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 04/04/2021] [Accepted: 04/14/2021] [Indexed: 12/12/2022] Open
Abstract
Post-translational modifications (PTMs) add a layer of complexity to the proteome through the addition of biochemical moieties to specific residues of proteins, altering their structure, function and/or localization. Mass spectrometry (MS)-based techniques are at the forefront of PTM analysis due to their ability to detect large numbers of modified proteins with a high level of sensitivity and specificity. The low stoichiometry of modified peptides means fractionation and enrichment techniques are often performed prior to MS to improve detection yields. Immuno-based techniques remain popular, with improvements in the quality of commercially available modification-specific antibodies facilitating the detection of modified proteins with high affinity. PTM-focused studies on blood cancers have provided information on altered cellular processes, including cell signaling, apoptosis and transcriptional regulation, that contribute to the malignant phenotype. Furthermore, the mechanism of action of many blood cancer therapies, such as kinase inhibitors, involves inhibiting or modulating protein modifications. Continued optimization of protocols and techniques for PTM analysis in blood cancer will undoubtedly lead to novel insights into mechanisms of malignant transformation, proliferation, and survival, in addition to the identification of novel biomarkers and therapeutic targets. This review discusses techniques used for PTM analysis and their applications in blood cancer research.
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Affiliation(s)
- Katie Dunphy
- Department of Biology, National University of Ireland, W23 F2K8 Maynooth, Ireland; (K.D.); (P.D.)
| | - Paul Dowling
- Department of Biology, National University of Ireland, W23 F2K8 Maynooth, Ireland; (K.D.); (P.D.)
| | - Despina Bazou
- Department of Haematology, Mater Misericordiae University Hospital, D07 WKW8 Dublin, Ireland;
| | - Peter O’Gorman
- Department of Haematology, Mater Misericordiae University Hospital, D07 WKW8 Dublin, Ireland;
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Coarfa C, Grimm SL, Rajapakshe K, Perera D, Lu HY, Wang X, Christensen KR, Mo Q, Edwards DP, Huang S. Reverse-Phase Protein Array: Technology, Application, Data Processing, and Integration. J Biomol Tech 2021; 32:15-29. [PMID: 34025221 DOI: 10.7171/jbt.21-3202-001] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Reverse-phase protein array (RPPA) is a high-throughput antibody-based targeted proteomics platform that can quantify hundreds of proteins in thousands of samples derived from tissue or cell lysates, serum, plasma, or other body fluids. Protein samples are robotically arrayed as microspots on nitrocellulose-coated glass slides. Each slide is probed with a specific antibody that can detect levels of total protein expression or post-translational modifications, such as phosphorylation as a measure of protein activity. Here we describe workflow protocols and software tools that we have developed and optimized for RPPA in a core facility setting that includes sample preparation, microarray mapping and printing of protein samples, antibody labeling, slide scanning, image analysis, data normalization and quality control, data reporting, statistical analysis, and management of data. Our RPPA platform currently analyzes ∼240 validated antibodies that primarily detect proteins in signaling pathways and cellular processes that are important in cancer biology. This is a robust technology that has proven to be of value for both validation and discovery proteomic research and integration with other omics data sets.
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Affiliation(s)
- Cristian Coarfa
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA.,Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA; and.,Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Sandra L Grimm
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA
| | - Kimal Rajapakshe
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA
| | - Dimuthu Perera
- Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Hsin-Yi Lu
- Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Xuan Wang
- Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Kurt R Christensen
- Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Qianxing Mo
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA; and
| | - Dean P Edwards
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA.,Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA; and.,Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Shixia Huang
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA.,Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA; and.,Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
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6
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Oh JW, Oh YJ, Han S, Her NG, Nam DH. High-Content Analysis-Based Sensitivity Prediction and Novel Therapeutics Screening for c-Met-Addicted Glioblastoma. Cancers (Basel) 2021; 13:cancers13030372. [PMID: 33498427 PMCID: PMC7864197 DOI: 10.3390/cancers13030372] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 01/16/2021] [Accepted: 01/17/2021] [Indexed: 12/23/2022] Open
Abstract
Simple Summary Real-time ex vivo drug testing tailors individual therapeutics based on predicted drug responses. Most technologies to date rely on conventional drug screening that provides low confidence data. Here, we present high-content analysis-based drug testing of glioblastoma patients to identify the right glioblastoma patients for a given drug. This generates multi-parameter biomarker and phenotype readouts providing a better reliability of the assay. Additionally, we showed a high-content drug repurposing screen and defined a new c-Met-inhibiting function of the CDK4/6 inhibitor Abemaciclib. Large-scale high throughput screening results demonstrate that Abemaciclib sensitivity in glioblastoma patients is highly correlated with the c-Met inhibitors sensitivity, further supporting the accuracy of the platform and important new clinical implications regarding multiple functions of Abemaciclib. Abstract (1) Background: Recent advances in precision oncology research rely on indicating specific genetic alterations associated with treatment sensitivity. Developing ex vivo systems to identify cancer patients who will respond to a specific drug remains important. (2) Methods: cells from 12 patients with glioblastoma were isolated, cultured, and subjected to high-content screening. Multi-parameter analyses assessed the c-Met level, cell viability, apoptosis, cell motility, and migration. A drug repurposing screen and large-scale drug sensitivity screening data across 59 cancer cell lines and patient-derived cells were obtained from 125 glioblastoma samples. (3) Results: High-content analysis of patient-derived cells provided robust and accurate drug responses to c-Met-targeted agents. Only the cells of one glioblastoma patient (PDC6) showed elevated c-Met level and high susceptibility to the c-Met inhibitors. Multi-parameter image analysis also reflected a decreased c-Met expression and reduced cell growth and motility by a c-Met-targeting antibody. In addition, a drug repurposing screen identified Abemaciclib as a distinct CDK4/6 inhibitor with a potent c-Met-inhibitory function. Consistent with this, we present large-scale drug sensitivity screening data showing that the Abemaciclib response correlates with the response to c-Met inhibitors. (4) Conclusions: Our study provides a new insight into high-content screening platforms supporting drug sensitivity prediction and novel therapeutics screening.
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Affiliation(s)
- Jeong-Woo Oh
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea; (J.-W.O.); (Y.J.O.)
- Department of Health Sciences & Technology, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul 06351, Korea
| | - Yun Jeong Oh
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea; (J.-W.O.); (Y.J.O.)
| | - Suji Han
- Research Institute, National Cancer Center, Goyang 10408, Korea;
| | - Nam-Gu Her
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea; (J.-W.O.); (Y.J.O.)
- R&D Center, AIMEDBIO Inc., Seoul 15835, Korea
- Correspondence: (N.-G.H.); (D.-H.N.); Tel.: +82-2-6285-0827
| | - Do-Hyun Nam
- Institute for Refractory Cancer Research, Samsung Medical Center, Seoul 06351, Korea; (J.-W.O.); (Y.J.O.)
- Department of Health Sciences & Technology, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul 06351, Korea
- Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University, Seoul 06351, Korea
- Correspondence: (N.-G.H.); (D.-H.N.); Tel.: +82-2-6285-0827
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7
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Coarfa C, Grimm SL, Rajapakshe K, Perera D, Lu HY, Wang X, Christensen KR, Mo Q, Edwards DP, Huang S. Reverse-Phase Protein Array: Technology, Application, Data Processing, and Integration. J Biomol Tech 2021:jbt.2021-3202-001. [PMID: 33584151 DOI: 10.7171/jbt.2021-3202-001] [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] [Indexed: 11/20/2022]
Abstract
Reverse-phase protein array (RPPA) is a high-throughput antibody-based targeted proteomics platform that can quantify hundreds of proteins in thousands of samples derived from tissue or cell lysates, serum, plasma, or other body fluids. Protein samples are robotically arrayed as microspots on nitrocellulose-coated glass slides. Each slide is probed with a specific antibody that can detect levels of total protein expression or post-translational modifications, such as phosphorylation as a measure of protein activity. Here we describe workflow protocols and software tools that we have developed and optimized for RPPA in a core facility setting that includes sample preparation, microarray mapping and printing of protein samples, antibody labeling, slide scanning, image analysis, data normalization and quality control, data reporting, statistical analysis, and management of data. Our RPPA platform currently analyzes ∼240 validated antibodies that primarily detect proteins in signaling pathways and cellular processes that are important in cancer biology. This is a robust technology that has proven to be of value for both validation and discovery proteomic research and integration with other omics data sets.
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Affiliation(s)
- Cristian Coarfa
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA; and
- Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Sandra L Grimm
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA
| | - Kimal Rajapakshe
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA
| | - Dimuthu Perera
- Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Hsin-Yi Lu
- Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Xuan Wang
- Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Kurt R Christensen
- Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Qianxing Mo
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA; and
| | - Dean P Edwards
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA; and
- Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
| | - Shixia Huang
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA; and
- Advanced Technology Cores/Office of Research, Baylor College of Medicine, Houston, Texas, USA
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8
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Byron A, Bernhardt S, Ouine B, Cartier A, Macleod KG, Carragher NO, Sibut V, Korf U, Serrels B, de Koning L. Integrative analysis of multi-platform reverse-phase protein array data for the pharmacodynamic assessment of response to targeted therapies. Sci Rep 2020; 10:21985. [PMID: 33319783 PMCID: PMC7738515 DOI: 10.1038/s41598-020-77335-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 03/11/2020] [Indexed: 12/30/2022] Open
Abstract
Reverse-phase protein array (RPPA) technology uses panels of high-specificity antibodies to measure proteins and protein post-translational modifications in cells and tissues. The approach offers sensitive and precise quantification of large numbers of samples and has thus found applications in the analysis of clinical and pre-clinical samples. For effective integration into drug development and clinical practice, robust assays with consistent results are essential. Leveraging a collaborative RPPA model, we set out to assess the variability between three different RPPA platforms using distinct instrument set-ups and workflows. Employing multiple RPPA-based approaches operated across distinct laboratories, we characterised a range of human breast cancer cells and their protein-level responses to two clinically relevant cancer drugs. We integrated multi-platform RPPA data and used unsupervised learning to identify protein expression and phosphorylation signatures that were not dependent on RPPA platform and analysis workflow. Our findings indicate that proteomic analyses of cancer cell lines using different RPPA platforms can identify concordant profiles of response to pharmacological inhibition, including when using different antibodies to measure the same target antigens. These results highlight the robustness and the reproducibility of RPPA technology and its capacity to identify protein markers of disease or response to therapy.
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Affiliation(s)
- Adam Byron
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XR, UK.
| | - Stephan Bernhardt
- Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Pfizer Pharma GmbH, Berlin, Germany
| | - Bérèngere Ouine
- Department of Translational Research, Institut Curie, PSL Research University, 26 rue d'Ulm, 75005, Paris, France
| | - Aurélie Cartier
- Department of Translational Research, Institut Curie, PSL Research University, 26 rue d'Ulm, 75005, Paris, France
- Sederma, Le Perray-en-Yvelines, France
| | - Kenneth G Macleod
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XR, UK
| | - Neil O Carragher
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XR, UK
| | - Vonick Sibut
- U900 INSERM, Institut Curie, PSL Research University, Paris, France
- U1236 INSERM, Faculté de Médecine, Université de Rennes 1, Rennes, France
| | - Ulrike Korf
- Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Bryan Serrels
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XR, UK
- NanoString Technologies, Inc., Seattle, WA, USA
| | - Leanne de Koning
- Department of Translational Research, Institut Curie, PSL Research University, 26 rue d'Ulm, 75005, Paris, France.
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9
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Wahjudi LW, Bernhardt S, Abnaof K, Horak P, Kreutzfeldt S, Heining C, Borgoni S, Becki C, Berg D, Richter D, Hutter B, Uhrig S, Pfütze K, Leichsenring J, Glimm H, Brors B, von Kalle C, Stenzinger A, Korf U, Fröhling S, Wiemann S. Integrating proteomics into precision oncology. Int J Cancer 2020; 148:1438-1451. [PMID: 32949162 DOI: 10.1002/ijc.33301] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 09/03/2020] [Accepted: 09/07/2020] [Indexed: 12/13/2022]
Abstract
DNA sequencing and RNA sequencing are increasingly applied in precision oncology, where molecular tumor boards evaluate the actionability of genetic events in individual tumors to guide targeted treatment. To work toward an additional level of patient characterization, we assessed the abundance and activity of 27 proteins in 134 patients whose tumors had previously undergone whole-exome and RNA sequencing within the Molecularly Aided Stratification for Tumor Eradication Research (MASTER) program of National Center for Tumor Diseases, Heidelberg. Proteomic and phosphoproteomic targets were selected to reflect the most relevant therapeutic baskets in MASTER. Among six different therapeutic baskets, the proteomic data supported treatment recommendations that were based on DNA and RNA analyses in 10% to 57% and frequently suggested alternative treatment options. In several cases, protein activities explained the patients' clinical course and provided potential explanations for treatment failure. Our study indicates that the integrative analysis of DNA, RNA and protein data may refine therapeutic stratification of individual patients and, thus, holds potential to increase the success rate of precision cancer therapy. Prospective validation studies are needed to advance the integration of proteomic analysis into precision oncology.
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Affiliation(s)
- Leonie W Wahjudi
- Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stephan Bernhardt
- Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Khalid Abnaof
- Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Peter Horak
- Division of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany.,German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Simon Kreutzfeldt
- Division of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany.,German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Christoph Heining
- Department of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Dresden, Dresden, Germany.,German Cancer Consortium (DKTK), Dresden, Germany.,Center for Personalized Oncology, National Center for Tumour Diseases (NCT) Dresden and University Hospital Carl Gustav Carus Dresden at TU Dresden, Dresden, Germany
| | - Simone Borgoni
- Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Biosciences, University Heidelberg, Heidelberg, Germany
| | - Corinna Becki
- Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniela Berg
- Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniela Richter
- Department of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Dresden, Dresden, Germany.,German Cancer Consortium (DKTK), Dresden, Germany
| | - Barbara Hutter
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Applied Bioinformatics, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| | - Sebastian Uhrig
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Faculty of Biosciences, University Heidelberg, Heidelberg, Germany.,Division of Applied Bioinformatics, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| | - Katrin Pfütze
- Division of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany.,German Cancer Consortium (DKTK), Heidelberg, Germany
| | | | - Hanno Glimm
- Department of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Dresden, Dresden, Germany.,Translational Functional Cancer Genomics, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany.,German Cancer Consortium (DKTK), Dresden, Germany.,Center for Personalized Oncology, National Center for Tumour Diseases (NCT) Dresden and University Hospital Carl Gustav Carus Dresden at TU Dresden, Dresden, Germany
| | - Benedikt Brors
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Division of Applied Bioinformatics, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| | - Christof von Kalle
- Division of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Translational Functional Cancer Genomics, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Albrecht Stenzinger
- German Cancer Consortium (DKTK), Heidelberg, Germany.,Institute of Pathology, University Heidelberg, Heidelberg, Germany
| | - Ulrike Korf
- Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stefan Fröhling
- Division of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany.,German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Stefan Wiemann
- Division of Molecular Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, Germany.,German Cancer Consortium (DKTK), Heidelberg, Germany
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10
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Francescangeli F, Contavalli P, De Angelis ML, Careccia S, Signore M, Haas TL, Salaris F, Baiocchi M, Boe A, Giuliani A, Tcheremenskaia O, Pagliuca A, Guardiola O, Minchiotti G, Colace L, Ciardi A, D'Andrea V, La Torre F, Medema J, De Maria R, Zeuner A. A pre-existing population of ZEB2 + quiescent cells with stemness and mesenchymal features dictate chemoresistance in colorectal cancer. JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH : CR 2020; 39:2. [PMID: 31910865 PMCID: PMC6947904 DOI: 10.1186/s13046-019-1505-4] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 12/12/2019] [Indexed: 12/28/2022]
Abstract
Background Quiescent/slow cycling cells have been identified in several tumors and correlated with therapy resistance. However, the features of chemoresistant populations and the molecular factors linking quiescence to chemoresistance are largely unknown. Methods A population of chemoresistant quiescent/slow cycling cells was isolated through PKH26 staining (which allows to separate cells on the basis of their proliferation rate) from colorectal cancer (CRC) xenografts and subjected to global gene expression and pathway activation analyses. Factors expressed by the quiescent/slow cycling population were analyzed through lentiviral overexpression approaches for their ability to induce a dormant chemoresistant state both in vitro and in mouse xenografts. The correlation between quiescence-associated factors, CRC consensus molecular subtype and cancer prognosis was analyzed in large patient datasets. Results Untreated colorectal tumors contain a population of quiescent/slow cycling cells with stem cell features (quiescent cancer stem cells, QCSCs) characterized by a predetermined mesenchymal-like chemoresistant phenotype. QCSCs expressed increased levels of ZEB2, a transcription factor involved in stem cell plasticity and epithelial-mesenchymal transition (EMT), and of antiapototic factors pCRAF and pASK1. ZEB2 overexpression upregulated pCRAF/pASK1 levels resulting in increased chemoresistance, enrichment of cells with stemness/EMT traits and proliferative slowdown of tumor xenografts. In parallel, chemotherapy treatment of tumor xenografts induced the prevalence of QCSCs with a stemness/EMT phenotype and activation of the ZEB2/pCRAF/pASK1 axis, resulting in a chemotherapy-unresponsive state. In CRC patients, increased ZEB2 levels correlated with worse relapse-free survival and were strongly associated to the consensus molecular subtype 4 (CMS4) characterized by dismal prognosis, decreased proliferative rates and upregulation of EMT genes. Conclusions These results show that chemotherapy-naive tumors contain a cell population characterized by a coordinated program of chemoresistance, quiescence, stemness and EMT. Such population becomes prevalent upon drug treatment and is responsible for chemotherapy resistance, thus representing a key target for more effective therapeutic approaches.
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Affiliation(s)
- Federica Francescangeli
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - Paola Contavalli
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - Maria Laura De Angelis
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - Silvia Careccia
- Institute of General Pathology, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168, Rome, Italy
| | - Michele Signore
- RPPA Unit, Proteomics Area, Core Facilities, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - Tobias Longin Haas
- Institute of General Pathology, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168, Rome, Italy.,Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy
| | - Federico Salaris
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - Marta Baiocchi
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - Alessandra Boe
- Core Facilities, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - Alessandro Giuliani
- Environment and Health Department, Istituto Superiore di Sanita, Viale Regina Elena 299, 00161, Rome, Italy
| | - Olga Tcheremenskaia
- Environment and Health Department, Istituto Superiore di Sanita, Viale Regina Elena 299, 00161, Rome, Italy
| | - Alfredo Pagliuca
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy
| | - Ombretta Guardiola
- Stem Cell Fate Laboratory, Institute of Genetics and Biophysics "A. Buzzati Traverso", CNR,Via Pietro Castellino 111, 80131, Naples, Italy
| | - Gabriella Minchiotti
- Stem Cell Fate Laboratory, Institute of Genetics and Biophysics "A. Buzzati Traverso", CNR,Via Pietro Castellino 111, 80131, Naples, Italy
| | - Lidia Colace
- Department of Surgical Sciences, Policlinico Umberto I/Sapienza University of Rome, Viale del Policlinico 155, 00161, Rome, Italy
| | - Antonio Ciardi
- Department of Surgery "Pietro Valdoni", Policlinico Umberto I/Sapienza University of Rome, via Lancisi 2, 00161, Rome, Italy
| | - Vito D'Andrea
- Department of Surgical Sciences, Policlinico Umberto I/Sapienza University of Rome, Viale del Policlinico 155, 00161, Rome, Italy
| | - Filippo La Torre
- Surgical Sciences and Emergency Department, Policlinico Umberto I/Sapienza University of Rome, Viale del Policlinico 155, 00161, Rome, Italy
| | - JanPaul Medema
- Laboratory for Experimental Oncology and Radiobiology, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam, Academic Medical Center, Meibergdreef 9, 1105, AZ, Amsterdam, The Netherlands
| | - Ruggero De Maria
- Institute of General Pathology, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168, Rome, Italy. .,Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo Agostino Gemelli 8, 00168, Rome, Italy.
| | - Ann Zeuner
- Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161, Rome, Italy.
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11
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Betancourt LH, Szasz AM, Kuras M, Rodriguez Murillo J, Sugihara Y, Pla I, Horvath Z, Pawłowski K, Rezeli M, Miharada K, Gil J, Eriksson J, Appelqvist R, Miliotis T, Baldetorp B, Ingvar C, Olsson H, Lundgren L, Horvatovich P, Welinder C, Wieslander E, Kwon HJ, Malm J, Nemeth IB, Jönsson G, Fenyö D, Sanchez A, Marko-Varga G. The Hidden Story of Heterogeneous B-raf V600E Mutation Quantitative Protein Expression in Metastatic Melanoma-Association with Clinical Outcome and Tumor Phenotypes. Cancers (Basel) 2019; 11:E1981. [PMID: 31835364 PMCID: PMC6966659 DOI: 10.3390/cancers11121981] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 11/23/2019] [Accepted: 12/03/2019] [Indexed: 02/07/2023] Open
Abstract
In comparison to other human cancer types, malignant melanoma exhibits the greatest amount of heterogeneity. After DNA-based detection of the BRAF V600E mutation in melanoma patients, targeted inhibitor treatment is the current recommendation. This approach, however, does not take the abundance of the therapeutic target, i.e., the B-raf V600E protein, into consideration. As shown by immunohistochemistry, the protein expression profiles of metastatic melanomas clearly reveal the existence of inter- and intra-tumor variability. Nevertheless, the technique is only semi-quantitative. To quantitate the mutant protein there is a fundamental need for more precise techniques that are aimed at defining the currently non-existent link between the levels of the target protein and subsequent drug efficacy. Using cutting-edge mass spectrometry combined with DNA and mRNA sequencing, the mutated B-raf protein within metastatic tumors was quantitated for the first time. B-raf V600E protein analysis revealed a subjacent layer of heterogeneity for mutation-positive metastatic melanomas. These were characterized into two distinct groups with different tumor morphologies, protein profiles and patient clinical outcomes. This study provides evidence that a higher level of expression in the mutated protein is associated with a more aggressive tumor progression. Our study design, comprised of surgical isolation of tumors, histopathological characterization, tissue biobanking, and protein analysis, may enable the eventual delineation of patient responders/non-responders and subsequent therapy for malignant melanoma.
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Affiliation(s)
- Lazaro Hiram Betancourt
- Clinical Protein Science & Imaging, Biomedical Centre, Department of Biomedical, Engineering, Lund University, BMC D13, 221 84 Lund, Sweden; (L.H.B.); (Z.H.); (M.R.); (J.G.); (J.E.); (R.A.); (G.M.-V.)
| | - A. Marcell Szasz
- Clinical Protein Science & Imaging, Biomedical Centre, Department of Biomedical, Engineering, Lund University, BMC D13, 221 84 Lund, Sweden; (L.H.B.); (Z.H.); (M.R.); (J.G.); (J.E.); (R.A.); (G.M.-V.)
- Cancer Center, Semmelweis University, Budapest 1083, Hungary
| | - Magdalena Kuras
- Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 205 02 Malmö, Sweden; (M.K.); (I.P.); (K.P.); (J.M.); (A.S.)
| | - Jimmy Rodriguez Murillo
- Division of Physiological Chemistry I, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-17 177 Stockholm, Sweden; (J.R.M.); (Y.S.)
| | - Yutaka Sugihara
- Division of Physiological Chemistry I, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-17 177 Stockholm, Sweden; (J.R.M.); (Y.S.)
| | - Indira Pla
- Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 205 02 Malmö, Sweden; (M.K.); (I.P.); (K.P.); (J.M.); (A.S.)
| | - Zsolt Horvath
- Clinical Protein Science & Imaging, Biomedical Centre, Department of Biomedical, Engineering, Lund University, BMC D13, 221 84 Lund, Sweden; (L.H.B.); (Z.H.); (M.R.); (J.G.); (J.E.); (R.A.); (G.M.-V.)
| | - Krzysztof Pawłowski
- Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 205 02 Malmö, Sweden; (M.K.); (I.P.); (K.P.); (J.M.); (A.S.)
- Department of Biochemistry and Microbiology, Warsaw University of Life Sciences, 02-787 Warsaw, Poland
| | - Melinda Rezeli
- Clinical Protein Science & Imaging, Biomedical Centre, Department of Biomedical, Engineering, Lund University, BMC D13, 221 84 Lund, Sweden; (L.H.B.); (Z.H.); (M.R.); (J.G.); (J.E.); (R.A.); (G.M.-V.)
| | - Kenichi Miharada
- Department of Molecular Medicine and Gene Therapy, Lund Stem Cell Center, Lund University, BMC A12, Sölvegatan 17, 221 84 Lund, Sweden;
| | - Jeovanis Gil
- Clinical Protein Science & Imaging, Biomedical Centre, Department of Biomedical, Engineering, Lund University, BMC D13, 221 84 Lund, Sweden; (L.H.B.); (Z.H.); (M.R.); (J.G.); (J.E.); (R.A.); (G.M.-V.)
| | - Jonatan Eriksson
- Clinical Protein Science & Imaging, Biomedical Centre, Department of Biomedical, Engineering, Lund University, BMC D13, 221 84 Lund, Sweden; (L.H.B.); (Z.H.); (M.R.); (J.G.); (J.E.); (R.A.); (G.M.-V.)
| | - Roger Appelqvist
- Clinical Protein Science & Imaging, Biomedical Centre, Department of Biomedical, Engineering, Lund University, BMC D13, 221 84 Lund, Sweden; (L.H.B.); (Z.H.); (M.R.); (J.G.); (J.E.); (R.A.); (G.M.-V.)
| | - Tasso Miliotis
- Translational Science, Cardiovascular Renal and Metabolism, IMED Biotech Unit, AstraZeneca, 431 50 Gothenburg, Sweden;
| | - Bo Baldetorp
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, 221 85 Lund, Sweden; (B.B.); (H.O.); (L.L.); (C.W.); (E.W.); (G.J.)
| | - Christian Ingvar
- Department of Surgery, Clinical Sciences, Lund University, Skåne University Hospital, 222 42 Lund, Sweden;
| | - Håkan Olsson
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, 221 85 Lund, Sweden; (B.B.); (H.O.); (L.L.); (C.W.); (E.W.); (G.J.)
| | - Lotta Lundgren
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, 221 85 Lund, Sweden; (B.B.); (H.O.); (L.L.); (C.W.); (E.W.); (G.J.)
| | - Peter Horvatovich
- Department of Analytical Biochemistry, Faculty of Science and Engineering, University of Groningen, 9712 CP Groningen, The Netherlands;
| | - Charlotte Welinder
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, 221 85 Lund, Sweden; (B.B.); (H.O.); (L.L.); (C.W.); (E.W.); (G.J.)
| | - Elisabet Wieslander
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, 221 85 Lund, Sweden; (B.B.); (H.O.); (L.L.); (C.W.); (E.W.); (G.J.)
| | - Ho Jeong Kwon
- Department of Biotechnology, Yonsei University, Seoul 03722, Korea;
| | - Johan Malm
- Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 205 02 Malmö, Sweden; (M.K.); (I.P.); (K.P.); (J.M.); (A.S.)
| | - Istvan Balazs Nemeth
- Department of Dermatology and Allergology, University of Szeged, H-6720 Szeged, Hungary;
| | - Göran Jönsson
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Lund University, 221 85 Lund, Sweden; (B.B.); (H.O.); (L.L.); (C.W.); (E.W.); (G.J.)
| | - David Fenyö
- Institute for Systems Genetics, NYU School of Medicine, 550 1st Ave, New York, NY 10016, USA;
| | - Aniel Sanchez
- Section for Clinical Chemistry, Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 205 02 Malmö, Sweden; (M.K.); (I.P.); (K.P.); (J.M.); (A.S.)
| | - György Marko-Varga
- Clinical Protein Science & Imaging, Biomedical Centre, Department of Biomedical, Engineering, Lund University, BMC D13, 221 84 Lund, Sweden; (L.H.B.); (Z.H.); (M.R.); (J.G.); (J.E.); (R.A.); (G.M.-V.)
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12
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Werner H, Sarfstein R, Bruchim I. Investigational IGF1R inhibitors in early stage clinical trials for cancer therapy. Expert Opin Investig Drugs 2019; 28:1101-1112. [PMID: 31731883 DOI: 10.1080/13543784.2019.1694660] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Introduction: The insulin-like growth factors (IGFs) are a family of secreted peptide hormones with important roles in different cellular and organism functions. The biological activities of the IGFs are mediated by the IGF1 receptor (IGF1R), a cell surface, tyrosine kinase-containing heterotetramer that is linked to numerous cytoplasmic signaling cascades. The IGF1R displays potent antiapoptotic, pro-survival capacities and plays a key role in malignant transformation. Research has identified the IGF1R as a candidate therapeutic target in cancer.Areas covered: We offer a synopsis of ongoing efforts to target the IGF axis for therapeutic purposes. Our review includes a digest of early experimental work that led to the identification of IGF1R as a candidate therapeutic target in oncology.Expert opinion: Targeting of the IGF axis has yielded disappointing results in phase III trials, but it is important to learn from this to improve future trials in a rational manner. The potential of anti-IGF1R antibodies and small molecular weight inhibitors, alone or in combination with chemotherapy or other biological agents, should be investigated further in randomized studies. Moreover, the implementation of predictive biomarkers for patient selection will improve the outcome of future trials. Emerging personalized medicine could have a major impact on IGF1R targeting.
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Affiliation(s)
- Haim Werner
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,Yoran Institute for Human Genome Research, Tel Aviv University, Tel Aviv, Israel
| | - Rive Sarfstein
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Ilan Bruchim
- Gynecologic Oncology Division, Hillel Yaffe Medical Center, Technion Institute of Technology, Haifa, Israel
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