ArticleMethods in molecular biology (Clifton, N.J.)2018
Phosphoproteomics-Based Profiling of Kinase Activities in Cancer Cells.
Article in Methods in molecular biology (Clifton, N.J.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 38 citations in OpenAlex.
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- Rhythmic transcription of Bmal1 stabilizes the circadian timekeeping system in mammals.Nature communications · 2022Article
- Phosphoproteomics of primary AML patient samples reveals rationale for AKT combination therapy and p53 context to overcome selinexor resistance.Cell reports · 2022Article
- Cancer-associated fibroblasts require proline synthesis by PYCR1 for the deposition of pro-tumorigenic extracellular matrix.Nature metabolism · 2022Article
- Review
- 3, 3'- (3, 5-DCPBC) Down-Regulates Multiple Phosphokinase Dependent Signal Transduction Pathways in Malignant Melanoma Cells through Specific Diminution of EGFRMolecules (Basel, Switzerland) · 2022Article
- Computational Analysis of Cholangiocarcinoma Phosphoproteomes Identifies Patient-Specific Drug Targets.Cancer research · 2021Article
- Phosphoproteomics: a valuable tool for uncovering molecular signaling in cancer cells.Expert review of proteomics · 2021Review
- Feasibility of Phosphoproteomics on Leftover Samples After RNA Extraction With Guanidinium Thiocyanate.Molecular & cellular proteomics : MCP · 2021Article
- Phosphoproteomics Meets Chemical Genetics: Approaches for Global Mapping and Deciphering the Phosphoproteome.International journal of molecular sciences · 2020Review
- Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis.International journal of molecular sciences · 2020Review
- Mass Spectrometry-Based Discovery ofMass spectrometry (Tokyo, Japan) · 2020Article
- Substrate-based kinase activity inference identifies MK2 as driver of colitis.Integrative biology : quantitative biosciences from nano to macro · 2019Article
- An Integrative Analysis of Tumor Proteomic and Phosphoproteomic Profiles to Examine the Relationships Between Kinase Activity and Phosphorylation.Molecular & cellular proteomics : MCP · 2019Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Cellular signaling, predominantly mediated by phosphorylation through protein kinases, is found to be deregulated in most cancers. Accordingly, protein kinases have been subject to intense investigations in cancer research, to understand their role in oncogenesis and to discover new therapeutic targets. Despite great advances, an understanding of kinase dysfunction in cancer is far from complete.A powerful tool to investigate phosphorylation is mass-spectrometry (MS)-based phosphoproteomics, which enables the identification of thousands of phosphorylated peptides in a single experiment. Since every phosphorylation event results from the activity of a protein kinase, high-coverage phosphoproteomics data should indirectly contain comprehensive information about the activity of protein kinases.In this chapter, we discuss the use of computational methods to predict kinase activity scores from MS-based phosphoproteomics data. We start with a short explanation of the fundamental features of the phosphoproteomics data acquisition process from the perspective of the computational analysis. Next, we briefly review the existing databases with experimentally verified kinase-substrate relationships and present a set of bioinformatic tools to discover novel kinase targets. We then introduce different methods to infer kinase activities from phosphoproteomics data and these kinase-substrate relationships. We illustrate their application with a detailed protocol of one of the methods, KSEA (Kinase Substrate Enrichment Analysis). This method is implemented in Python within the framework of the open-source Kinase Activity Toolbox (kinact), which is freely available at http://github.com/saezlab/kinact/ .
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.