Literature DB >> 32865326

Lowering Sample Requirements to Study Tyrosine Kinase Signaling Using Phosphoproteomics with the TMT Calibrator Approach.

Bin Fang1, Victoria Izumi1, Lily L Remsing Rix1, Eric Welsh1, Ian Pike2, Gary W Reuther1, Eric B Haura1, Uwe Rix1, John M Koomen1.   

Abstract

Analysis of tyrosine kinase signaling is critical for the development of targeted cancer therapy. Currently, immunoprecipitation of phosphotyrosine (pY) peptides prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS) is used to profile tyrosine kinase substrates. A typical protocol requests 10 mg of total protein from ≈108 cells or 50-100 mg of tissue. Large sample requirements can be cost prohibitive or not feasible for certain experiments. Sample multiplexing using chemical labeling reduces the protein amount required for each sample, and newer approaches use a material-rich reference channel as a calibrator to trigger detection and quantification for smaller samples. Here, it is demonstrated that the tandem mass tag (TMT) calibrator approach reduces the sample input for pY profiling tenfold (to ≈1 mg total protein per sample from 107 cells grown in one plate), while maintaining the depth of pY proteome sampling and the biological content of the experiment. Data are available through PRIDE (PXD019764 for label-free and PXD018952 for TMT). This strategy opens more opportunities for pY profiling of large sample cohorts and samples with limited protein quantity such as immune cells, xenograft models, and human tumors.
© 2020 Wiley-VCH GmbH.

Entities:  

Keywords:  cancer signaling; phosphotyrosine; sample reduction; tandem mass tag

Year:  2020        PMID: 32865326      PMCID: PMC7771371          DOI: 10.1002/pmic.202000116

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  23 in total

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10.  The PRIDE database and related tools and resources in 2019: improving support for quantification data.

Authors:  Yasset Perez-Riverol; Attila Csordas; Jingwen Bai; Manuel Bernal-Llinares; Suresh Hewapathirana; Deepti J Kundu; Avinash Inuganti; Johannes Griss; Gerhard Mayer; Martin Eisenacher; Enrique Pérez; Julian Uszkoreit; Julianus Pfeuffer; Timo Sachsenberg; Sule Yilmaz; Shivani Tiwary; Jürgen Cox; Enrique Audain; Mathias Walzer; Andrew F Jarnuczak; Tobias Ternent; Alvis Brazma; Juan Antonio Vizcaíno
Journal:  Nucleic Acids Res       Date:  2019-01-08       Impact factor: 16.971

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