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Edgetic perturbation signatures represent known and novel cancer biomarkers
Isoform switching is a recently characterized hallmark of cancer, and often translates to the loss or gain of domains mediating protein interactions and thus, the re-wiring of the interactome. Recent computational tools leverage domain-domain interaction data to resolve the condition-specific intera...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062722/ https://www.ncbi.nlm.nih.gov/pubmed/32152446 http://dx.doi.org/10.1038/s41598-020-61422-3 |
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author | Kataka, Evans Zaucha, Jan Frishman, Goar Ruepp, Andreas Frishman, Dmitrij |
author_facet | Kataka, Evans Zaucha, Jan Frishman, Goar Ruepp, Andreas Frishman, Dmitrij |
author_sort | Kataka, Evans |
collection | PubMed |
description | Isoform switching is a recently characterized hallmark of cancer, and often translates to the loss or gain of domains mediating protein interactions and thus, the re-wiring of the interactome. Recent computational tools leverage domain-domain interaction data to resolve the condition-specific interaction networks from RNA-Seq data accounting for the domain content of the primary transcripts expressed. Here, we used The Cancer Genome Atlas RNA-Seq datasets to generate 642 patient-specific pairs of interactomes corresponding to both the tumor and the healthy tissues across 13 cancer types. The comparison of these interactomes provided a list of patient-specific edgetic perturbations of the interactomes associated with the cancerous state. We found that among the identified perturbations, select sets are robustly shared between patients at the multi-cancer, cancer-specific and cancer sub-type specific levels. Interestingly, the majority of the alterations do not directly involve significantly mutated genes, nevertheless, they strongly correlate with patient survival. The findings (available at EdgeExplorer: “http://webclu.bio.wzw.tum.de/EdgeExplorer”) are a new source of potential biomarkers for classifying cancer types and the proteins we identified are potential anti-cancer therapy targets. |
format | Online Article Text |
id | pubmed-7062722 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70627222020-03-18 Edgetic perturbation signatures represent known and novel cancer biomarkers Kataka, Evans Zaucha, Jan Frishman, Goar Ruepp, Andreas Frishman, Dmitrij Sci Rep Article Isoform switching is a recently characterized hallmark of cancer, and often translates to the loss or gain of domains mediating protein interactions and thus, the re-wiring of the interactome. Recent computational tools leverage domain-domain interaction data to resolve the condition-specific interaction networks from RNA-Seq data accounting for the domain content of the primary transcripts expressed. Here, we used The Cancer Genome Atlas RNA-Seq datasets to generate 642 patient-specific pairs of interactomes corresponding to both the tumor and the healthy tissues across 13 cancer types. The comparison of these interactomes provided a list of patient-specific edgetic perturbations of the interactomes associated with the cancerous state. We found that among the identified perturbations, select sets are robustly shared between patients at the multi-cancer, cancer-specific and cancer sub-type specific levels. Interestingly, the majority of the alterations do not directly involve significantly mutated genes, nevertheless, they strongly correlate with patient survival. The findings (available at EdgeExplorer: “http://webclu.bio.wzw.tum.de/EdgeExplorer”) are a new source of potential biomarkers for classifying cancer types and the proteins we identified are potential anti-cancer therapy targets. Nature Publishing Group UK 2020-03-09 /pmc/articles/PMC7062722/ /pubmed/32152446 http://dx.doi.org/10.1038/s41598-020-61422-3 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Kataka, Evans Zaucha, Jan Frishman, Goar Ruepp, Andreas Frishman, Dmitrij Edgetic perturbation signatures represent known and novel cancer biomarkers |
title | Edgetic perturbation signatures represent known and novel cancer biomarkers |
title_full | Edgetic perturbation signatures represent known and novel cancer biomarkers |
title_fullStr | Edgetic perturbation signatures represent known and novel cancer biomarkers |
title_full_unstemmed | Edgetic perturbation signatures represent known and novel cancer biomarkers |
title_short | Edgetic perturbation signatures represent known and novel cancer biomarkers |
title_sort | edgetic perturbation signatures represent known and novel cancer biomarkers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062722/ https://www.ncbi.nlm.nih.gov/pubmed/32152446 http://dx.doi.org/10.1038/s41598-020-61422-3 |
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