Cargando…
Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability
One of the most aggressive forms of breast cancer is inflammatory breast cancer (IBC), whose lack of tumour mass also makes a prompt diagnosis difficult. Moreover, genomic differences between common breast cancers and IBC have not been completely assessed, thus substantially limiting the identificat...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5673205/ https://www.ncbi.nlm.nih.gov/pubmed/29108005 http://dx.doi.org/10.1371/journal.pone.0186353 |
_version_ | 1783276562609602560 |
---|---|
author | Wakai, Ryouji Ishitsuka, Masayuki Kishimoto, Toshihiko Ochiai, Tomoshiro Nacher, Jose C. |
author_facet | Wakai, Ryouji Ishitsuka, Masayuki Kishimoto, Toshihiko Ochiai, Tomoshiro Nacher, Jose C. |
author_sort | Wakai, Ryouji |
collection | PubMed |
description | One of the most aggressive forms of breast cancer is inflammatory breast cancer (IBC), whose lack of tumour mass also makes a prompt diagnosis difficult. Moreover, genomic differences between common breast cancers and IBC have not been completely assessed, thus substantially limiting the identification of biomarkers unique to IBC. Here, we developed a novel statistical analysis of gene expression profiles corresponding to microdissected IBC, non-IBC (nIBC) and normal samples that enabled us to identify a set of genes significantly associated with a specific disease state. Second, by using advanced methods based on controllability network theory, we identified a set of critical control proteins that uniquely and structurally control the entire proteome. By mapping high change variance genes in protein interaction networks, we found that a large statistically significant fraction of genes whose variance changed significantly between normal and IBC and nIBC disease states were among the set of critical control proteins. Moreover, this analysis identified the overlapping genes with the highest statistical significance; these genes may assist in developing future biomarkers and determining drug targets to disrupt the molecular pathways driving carcinogenesis in IBC. |
format | Online Article Text |
id | pubmed-5673205 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-56732052017-11-18 Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability Wakai, Ryouji Ishitsuka, Masayuki Kishimoto, Toshihiko Ochiai, Tomoshiro Nacher, Jose C. PLoS One Research Article One of the most aggressive forms of breast cancer is inflammatory breast cancer (IBC), whose lack of tumour mass also makes a prompt diagnosis difficult. Moreover, genomic differences between common breast cancers and IBC have not been completely assessed, thus substantially limiting the identification of biomarkers unique to IBC. Here, we developed a novel statistical analysis of gene expression profiles corresponding to microdissected IBC, non-IBC (nIBC) and normal samples that enabled us to identify a set of genes significantly associated with a specific disease state. Second, by using advanced methods based on controllability network theory, we identified a set of critical control proteins that uniquely and structurally control the entire proteome. By mapping high change variance genes in protein interaction networks, we found that a large statistically significant fraction of genes whose variance changed significantly between normal and IBC and nIBC disease states were among the set of critical control proteins. Moreover, this analysis identified the overlapping genes with the highest statistical significance; these genes may assist in developing future biomarkers and determining drug targets to disrupt the molecular pathways driving carcinogenesis in IBC. Public Library of Science 2017-11-06 /pmc/articles/PMC5673205/ /pubmed/29108005 http://dx.doi.org/10.1371/journal.pone.0186353 Text en © 2017 Wakai et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Wakai, Ryouji Ishitsuka, Masayuki Kishimoto, Toshihiko Ochiai, Tomoshiro Nacher, Jose C. Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability |
title | Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability |
title_full | Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability |
title_fullStr | Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability |
title_full_unstemmed | Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability |
title_short | Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability |
title_sort | identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5673205/ https://www.ncbi.nlm.nih.gov/pubmed/29108005 http://dx.doi.org/10.1371/journal.pone.0186353 |
work_keys_str_mv | AT wakairyouji identificationofgenesandcriticalcontrolproteinsassociatedwithinflammatorybreastcancerusingnetworkcontrollability AT ishitsukamasayuki identificationofgenesandcriticalcontrolproteinsassociatedwithinflammatorybreastcancerusingnetworkcontrollability AT kishimototoshihiko identificationofgenesandcriticalcontrolproteinsassociatedwithinflammatorybreastcancerusingnetworkcontrollability AT ochiaitomoshiro identificationofgenesandcriticalcontrolproteinsassociatedwithinflammatorybreastcancerusingnetworkcontrollability AT nacherjosec identificationofgenesandcriticalcontrolproteinsassociatedwithinflammatorybreastcancerusingnetworkcontrollability |