Cargando…
Profiling the interactome of protein kinase C ζ by proteomics and bioinformatics
BACKGROUND: Protein kinase C ζ (PKCζ), an isoform of the atypical protein kinase C, is a pivotal regulator in cancer. However, the molecular and cellular mechanisms whereby PKCζ regulates tumorigenesis and metastasis are still not fully understood. In this study, proteomics and bioinformatics analys...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5828088/ https://www.ncbi.nlm.nih.gov/pubmed/29491746 http://dx.doi.org/10.1186/s12953-018-0134-8 |
_version_ | 1783302572183912448 |
---|---|
author | Hou, Chunyu Li, Yuan Liu, Huiqin Dang, Mengjiao Qin, Guoxuan Zhang, Ning Chen, Ruibing |
author_facet | Hou, Chunyu Li, Yuan Liu, Huiqin Dang, Mengjiao Qin, Guoxuan Zhang, Ning Chen, Ruibing |
author_sort | Hou, Chunyu |
collection | PubMed |
description | BACKGROUND: Protein kinase C ζ (PKCζ), an isoform of the atypical protein kinase C, is a pivotal regulator in cancer. However, the molecular and cellular mechanisms whereby PKCζ regulates tumorigenesis and metastasis are still not fully understood. In this study, proteomics and bioinformatics analyses were performed to establish a protein-protein interaction (PPI) network associated with PKCζ, laying a stepping stone to further understand the diverse biological roles of PKCζ. METHODS: Protein complexes associated with PKCζ were purified by co-immunoprecipitation from breast cancer cell MDA-MB-231 and identified by LC-MS/MS. Two biological replicates and two technical replicates were analyzed. The observed proteins were filtered using the CRAPome database to eliminate the potential false positives. The proteomics identification results were combined with PPI database search to construct the interactome network. Gene ontology (GO) and pathway analysis were performed by PANTHER database and DAVID. Next, the interaction between PKCζ and protein phosphatase 2 catalytic subunit alpha (PPP2CA) was validated by co-immunoprecipitation, Western blotting and immunofluorescence. Furthermore, the TCGA database and the COSMIC database were used to analyze the expressions of these two proteins in clinical samples. RESULTS: The PKCζ centered PPI network containing 178 nodes and 1225 connections was built. Network analysis showed that the identified proteins were significantly associated with several key signaling pathways regulating cancer related cellular processes. CONCLUSIONS: Through combining the proteomics and bioinformatics analyses, a PKCζ centered PPI network was constructed, providing a more complete picture regarding the biological roles of PKCζ in both cancer regulation and other aspects of cellular biology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12953-018-0134-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5828088 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58280882018-02-28 Profiling the interactome of protein kinase C ζ by proteomics and bioinformatics Hou, Chunyu Li, Yuan Liu, Huiqin Dang, Mengjiao Qin, Guoxuan Zhang, Ning Chen, Ruibing Proteome Sci Research BACKGROUND: Protein kinase C ζ (PKCζ), an isoform of the atypical protein kinase C, is a pivotal regulator in cancer. However, the molecular and cellular mechanisms whereby PKCζ regulates tumorigenesis and metastasis are still not fully understood. In this study, proteomics and bioinformatics analyses were performed to establish a protein-protein interaction (PPI) network associated with PKCζ, laying a stepping stone to further understand the diverse biological roles of PKCζ. METHODS: Protein complexes associated with PKCζ were purified by co-immunoprecipitation from breast cancer cell MDA-MB-231 and identified by LC-MS/MS. Two biological replicates and two technical replicates were analyzed. The observed proteins were filtered using the CRAPome database to eliminate the potential false positives. The proteomics identification results were combined with PPI database search to construct the interactome network. Gene ontology (GO) and pathway analysis were performed by PANTHER database and DAVID. Next, the interaction between PKCζ and protein phosphatase 2 catalytic subunit alpha (PPP2CA) was validated by co-immunoprecipitation, Western blotting and immunofluorescence. Furthermore, the TCGA database and the COSMIC database were used to analyze the expressions of these two proteins in clinical samples. RESULTS: The PKCζ centered PPI network containing 178 nodes and 1225 connections was built. Network analysis showed that the identified proteins were significantly associated with several key signaling pathways regulating cancer related cellular processes. CONCLUSIONS: Through combining the proteomics and bioinformatics analyses, a PKCζ centered PPI network was constructed, providing a more complete picture regarding the biological roles of PKCζ in both cancer regulation and other aspects of cellular biology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12953-018-0134-8) contains supplementary material, which is available to authorized users. BioMed Central 2018-02-26 /pmc/articles/PMC5828088/ /pubmed/29491746 http://dx.doi.org/10.1186/s12953-018-0134-8 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Hou, Chunyu Li, Yuan Liu, Huiqin Dang, Mengjiao Qin, Guoxuan Zhang, Ning Chen, Ruibing Profiling the interactome of protein kinase C ζ by proteomics and bioinformatics |
title | Profiling the interactome of protein kinase C ζ by proteomics and bioinformatics |
title_full | Profiling the interactome of protein kinase C ζ by proteomics and bioinformatics |
title_fullStr | Profiling the interactome of protein kinase C ζ by proteomics and bioinformatics |
title_full_unstemmed | Profiling the interactome of protein kinase C ζ by proteomics and bioinformatics |
title_short | Profiling the interactome of protein kinase C ζ by proteomics and bioinformatics |
title_sort | profiling the interactome of protein kinase c ζ by proteomics and bioinformatics |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5828088/ https://www.ncbi.nlm.nih.gov/pubmed/29491746 http://dx.doi.org/10.1186/s12953-018-0134-8 |
work_keys_str_mv | AT houchunyu profilingtheinteractomeofproteinkinaseczbyproteomicsandbioinformatics AT liyuan profilingtheinteractomeofproteinkinaseczbyproteomicsandbioinformatics AT liuhuiqin profilingtheinteractomeofproteinkinaseczbyproteomicsandbioinformatics AT dangmengjiao profilingtheinteractomeofproteinkinaseczbyproteomicsandbioinformatics AT qinguoxuan profilingtheinteractomeofproteinkinaseczbyproteomicsandbioinformatics AT zhangning profilingtheinteractomeofproteinkinaseczbyproteomicsandbioinformatics AT chenruibing profilingtheinteractomeofproteinkinaseczbyproteomicsandbioinformatics |