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Cutillas PR. Targeted In-Depth Quantification of Signaling Using Label-Free Mass Spectrometry. Methods Enzymol 2016; 585:245-268. [PMID: 28109432 DOI: 10.1016/bs.mie.2016.09.021] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Protein phosphorylation encodes information on the activity of kinase-driven signaling pathways that regulate cell biology. This chapter discusses an approach, named TIQUAS (targeted in-depth quantification of signaling), to quantify cell signaling comprehensively and without bias. The workflow-based on mass spectrometry (MS) and computational science-consists of targeting the analysis of phosphopeptides previously identified by shotgun liquid chromatography tandem MS (LC-MS/MS) across the samples that are being compared. TIQUAS therefore takes advantage of concepts derived from both targeted (data-independent) and data-dependent acquisition methods; phosphorylation sites are quantified in all experimental samples regardless of whether or not these phosphopeptides were identified by MS/MS in all runs. As a result, datasets are obtained containing quantitative information on several thousand phosphorylation sites in as many samples and replicates as required in the experimental design, and these rich datasets are devoid of a significant number of missing data points. This chapter discussed the biochemical, analytical, and computational procedures required to apply the approach and for obtaining a biological interpretation of the data in the context of our understanding of cell signaling regulation and kinase-substrate relationships.
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Affiliation(s)
- P R Cutillas
- Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, London, United Kingdom.
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Shi T, Niepel M, McDermott JE, Gao Y, Nicora CD, Chrisler WB, Markillie LM, Petyuk VA, Smith RD, Rodland KD, Sorger PK, Qian WJ, Wiley HS. Conservation of protein abundance patterns reveals the regulatory architecture of the EGFR-MAPK pathway. Sci Signal 2016; 9:rs6. [PMID: 27405981 DOI: 10.1126/scisignal.aaf0891] [Citation(s) in RCA: 95] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Various genetic mutations associated with cancer are known to alter cell signaling, but it is not clear whether they dysregulate signaling pathways by altering the abundance of pathway proteins. Using a combination of RNA sequencing and ultrasensitive targeted proteomics, we defined the primary components-16 core proteins and 10 feedback regulators-of the epidermal growth factor receptor (EGFR)-mitogen-activated protein kinase (MAPK) pathway in normal human mammary epithelial cells and then quantified their absolute abundance across a panel of normal and breast cancer cell lines as well as fibroblasts. We found that core pathway proteins were present at very similar concentrations across all cell types, with a variance similar to that of proteins previously shown to display conserved abundances across species. In contrast, EGFR and transcriptionally controlled feedback regulators were present at highly variable concentrations. The absolute abundance of most core proteins was between 50,000 and 70,000 copies per cell, but the adaptors SOS1, SOS2, and GAB1 were found at far lower amounts (2000 to 5000 copies per cell). MAPK signaling showed saturation in all cells between 3000 and 10,000 occupied EGFRs, consistent with the idea that adaptors limit signaling. Our results suggest that the relative stoichiometry of core MAPK pathway proteins is very similar across different cell types, with cell-specific differences mostly restricted to variable amounts of feedback regulators and receptors. The low abundance of adaptors relative to EGFR could be responsible for previous observations that only a fraction of total cell surface EGFR is capable of rapid endocytosis, high-affinity binding, and mitogenic signaling.
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Affiliation(s)
- Tujin Shi
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Mario Niepel
- HMS LINCS Center and Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Jason E McDermott
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Yuqian Gao
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Carrie D Nicora
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - William B Chrisler
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Lye M Markillie
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352 USA
| | - Vladislav A Petyuk
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA. Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352 USA
| | - Karin D Rodland
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Peter K Sorger
- HMS LINCS Center and Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - H Steven Wiley
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352 USA.
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Timms JF, Hale OJ, Cramer R. Advances in mass spectrometry-based cancer research and analysis: from cancer proteomics to clinical diagnostics. Expert Rev Proteomics 2016; 13:593-607. [DOI: 10.1080/14789450.2016.1182431] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Kulbe H, Iorio F, Chakravarty P, Milagre CS, Moore R, Thompson RG, Everitt G, Canosa M, Montoya A, Drygin D, Braicu I, Sehouli J, Saez-Rodriguez J, Cutillas PR, Balkwill FR. Integrated transcriptomic and proteomic analysis identifies protein kinase CK2 as a key signaling node in an inflammatory cytokine network in ovarian cancer cells. Oncotarget 2016; 7:15648-61. [PMID: 26871292 PMCID: PMC4941267 DOI: 10.18632/oncotarget.7255] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Accepted: 01/26/2016] [Indexed: 01/07/2023] Open
Abstract
We previously showed how key pathways in cancer-related inflammation and Notch signaling are part of an autocrine malignant cell network in ovarian cancer. This network, which we named the "TNF network", has paracrine actions within the tumor microenvironment, influencing angiogenesis and the immune cell infiltrate.The aim of this study was to identify critical regulators in the signaling pathways of the TNF network in ovarian cancer cells that might be therapeutic targets. To achieve our aim, we used a systems biology approach, combining data from phospho-proteomic mass spectrometry and gene expression array analysis. Among the potential therapeutic kinase targets identified was the protein kinase Casein kinase II (CK2).Knockdown of CK2 expression in malignant cells by siRNA or treatment with the specific CK2 inhibitor CX-4945 significantly decreased Notch signaling and reduced constitutive cytokine release in ovarian cancer cell lines that expressed the TNF network as well as malignant cells isolated from high grade serous ovarian cancer ascites. The expression of the same cytokines was also inhibited after treatment with CX-4945 in a 3D organotypic model. CK2 inhibition was associated with concomitant inhibition of proliferative activity, reduced angiogenesis and experimental peritoneal ovarian tumor growth.In conclusion, we have identified kinases, particularly CK2, associated with the TNF network that may play a central role in sustaining the cytokine network and/or mediating its effects in ovarian cancer.
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Affiliation(s)
- Hagen Kulbe
- Centre for Cancer and Inflammation, Barts Cancer Institute, Queen Mary University of London, London, UK
- Department of Gynecology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Francesco Iorio
- European Molecular Biology Laboratory – European Bioinformatics Institute, EMBL-EBI, Cambridge, UK
- Cancer Genome Project, Wellcome Trust Sanger Institute, Cambridge, UK
| | | | - Carla S. Milagre
- Centre for Cancer and Inflammation, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Robert Moore
- Centre for Cancer and Inflammation, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Richard G. Thompson
- Centre for Cancer and Inflammation, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Gemma Everitt
- Centre for Cancer and Inflammation, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Monica Canosa
- Centre for Cancer and Inflammation, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Alexander Montoya
- Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | | | - Ioana Braicu
- Tumorbank Ovarian Cancer Network, Department of Gynecology, Charité Universitätsmedizin Berlin, Berlin, Germany
- Department of Gynecology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Jalid Sehouli
- Tumorbank Ovarian Cancer Network, Department of Gynecology, Charité Universitätsmedizin Berlin, Berlin, Germany
- Department of Gynecology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Julio Saez-Rodriguez
- European Molecular Biology Laboratory – European Bioinformatics Institute, EMBL-EBI, Cambridge, UK
| | - Pedro R. Cutillas
- Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Frances R. Balkwill
- Centre for Cancer and Inflammation, Barts Cancer Institute, Queen Mary University of London, London, UK
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Locard-Paulet M, Pible O, Gonzalez de Peredo A, Alpha-Bazin B, Almunia C, Burlet-Schiltz O, Armengaud J. Clinical implications of recent advances in proteogenomics. Expert Rev Proteomics 2016; 13:185-99. [DOI: 10.1586/14789450.2016.1132169] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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Terfve CDA, Wilkes EH, Casado P, Cutillas PR, Saez-Rodriguez J. Large-scale models of signal propagation in human cells derived from discovery phosphoproteomic data. Nat Commun 2015; 6:8033. [PMID: 26354681 PMCID: PMC4579397 DOI: 10.1038/ncomms9033] [Citation(s) in RCA: 66] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2015] [Accepted: 07/09/2015] [Indexed: 12/27/2022] Open
Abstract
Mass spectrometry is widely used to probe the proteome and its modifications in an untargeted manner, with unrivalled coverage. Applied to phosphoproteomics, it has tremendous potential to interrogate phospho-signalling and its therapeutic implications. However, this task is complicated by issues of undersampling of the phosphoproteome and challenges stemming from its high-content but low-sample-throughput nature. Hence, methods using such data to reconstruct signalling networks have been limited to restricted data sets and insights (for example, groups of kinases likely to be active in a sample). We propose a new method to handle high-content discovery phosphoproteomics data on perturbation by putting it in the context of kinase/phosphatase-substrate knowledge, from which we derive and train logic models. We show, on a data set obtained through perturbations of cancer cells with small-molecule inhibitors, that this method can study the targets and effects of kinase inhibitors, and reconcile insights obtained from multiple data sets, a common issue with these data. Phosphoproteomics can offer significant insight into cell signalling and how signalling is modified in response to perturbations. Here the authors develop a new tool for the analysis of high-content phosphoproteomics in the context of kinase/phosphatase-substrate knowledge, which is used to train logic models.
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Affiliation(s)
- Camille D A Terfve
- European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Edmund H Wilkes
- Integrative Cell Signalling and Proteomics, Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London EC1M 6BQ, UK
| | - Pedro Casado
- Integrative Cell Signalling and Proteomics, Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London EC1M 6BQ, UK
| | - Pedro R Cutillas
- Integrative Cell Signalling and Proteomics, Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London EC1M 6BQ, UK
| | - Julio Saez-Rodriguez
- European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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