Literature DB >> 31814417

Systematic Comparison of Label-Free, SILAC, and TMT Techniques to Study Early Adaption toward Inhibition of EGFR Signaling in the Colorectal Cancer Cell Line DiFi.

Markus Stepath, Birgit Zülch1, Abdelouahid Maghnouj, Karin Schork, Michael Turewicz, Martin Eisenacher, Stephan Hahn, Barbara Sitek, Thilo Bracht.   

Abstract

We evaluated the quantification strategies label-free (LF), stable isotope labeling by amino acids in cell culture (SILAC), and tandem mass tags (TMT) and their performance in quantification of proteins and phosphosites (p-sites) to identify the most powerful approach for monitoring cellular signaling. We analyzed the epidermal growth factor receptor (EGFR) signaling network, which plays an essential role in colorectal cancer, and studied its dynamics within 24 h upon treatment with the EGFR-blocking antibody cetuximab, representing the first cellular adaption toward therapy. LF achieved superior coverage but was outperformed by label-based approaches regarding technical variability, especially for quantification of p-sites. TMT showed the lowest coverage and most missing values. We found that its performance considerably decreases when experimental replicates are distributed over several TMT plexes. SILAC showed the highest precision and outstanding performance for quantification of p-sites, rendering it the method of choice for analyzing cellular signaling in cell culture models. On the protein level, we observed only little regulation upon cetuximab treatment, whereas a great fraction of p-sites was significantly regulated. These dynamics represented an initial downregulation of the MAPK pathway, which was partially rescued as early as 24 h after treatment. We identified upregulation and signaling via ERBB3 as well as calcium and cAMP signaling as possible mechanisms bypassing the blockage of EGFR.

Entities:  

Keywords:  ERBB3; MAPK; SILAC; TMT; adaptive mechanism; anti-EGFR therapy; cetuximab; colorectal cancer; label-free; phosphoproteomics

Mesh:

Substances:

Year:  2020        PMID: 31814417     DOI: 10.1021/acs.jproteome.9b00701

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  6 in total

Review 1.  Phosphoproteomics: a valuable tool for uncovering molecular signaling in cancer cells.

Authors:  Jacqueline S Gerritsen; Forest M White
Journal:  Expert Rev Proteomics       Date:  2021-09-16       Impact factor: 4.250

2.  A comprehensive SARS-CoV-2-human protein-protein interactome reveals COVID-19 pathobiology and potential host therapeutic targets.

Authors:  Yadi Zhou; Yuan Liu; Shagun Gupta; Mauricio I Paramo; Yuan Hou; Chengsheng Mao; Yuan Luo; Julius Judd; Shayne Wierbowski; Marta Bertolotti; Mriganka Nerkar; Lara Jehi; Nir Drayman; Vlad Nicolaescu; Haley Gula; Savaş Tay; Glenn Randall; Peihui Wang; John T Lis; Cédric Feschotte; Serpil C Erzurum; Feixiong Cheng; Haiyuan Yu
Journal:  Nat Biotechnol       Date:  2022-10-10       Impact factor: 68.164

3.  HarmonizR enables data harmonization across independent proteomic datasets with appropriate handling of missing values.

Authors:  Hannah Voß; Simon Schlumbohm; Philip Barwikowski; Marcus Wurlitzer; Matthias Dottermusch; Philipp Neumann; Hartmut Schlüter; Julia E Neumann; Christoph Krisp
Journal:  Nat Commun       Date:  2022-06-20       Impact factor: 17.694

4.  A comprehensive SARS-CoV-2-human protein-protein interactome network identifies pathobiology and host-targeting therapies for COVID-19.

Authors:  Yadi Zhou; Yuan Liu; Shagun Gupta; Mauricio I Paramo; Yuan Hou; Chengsheng Mao; Yuan Luo; Julius Judd; Shayne Wierbowski; Marta Bertolotti; Mriganka Nerkar; Lara Jehi; Nir Drayman; Vlad Nicolaescu; Haley Gula; Savaş Tay; Glenn Randall; John T Lis; Cédric Feschotte; Serpil C Erzurum; Feixiong Cheng; Haiyuan Yu
Journal:  Res Sq       Date:  2022-06-07

5.  Comparative Evaluation of MaxQuant and Proteome Discoverer MS1-Based Protein Quantification Tools.

Authors:  Antonio Palomba; Marcello Abbondio; Giovanni Fiorito; Sergio Uzzau; Daniela Pagnozzi; Alessandro Tanca
Journal:  J Proteome Res       Date:  2021-05-26       Impact factor: 4.466

6.  MS-Based in Situ Proteomics Reveals AMPylation of Host Proteins during Bacterial Infection.

Authors:  Theresa Rauh; Sophie Brameyer; Pavel Kielkowski; Kirsten Jung; Stephan A Sieber
Journal:  ACS Infect Dis       Date:  2020-12-01       Impact factor: 5.578

  6 in total

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