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Comprehensive Map of the Regulated Cell Death Signaling Network: A Powerful Analytical Tool for Studying Diseases
The processes leading to, or avoiding cell death are widely studied, because of their frequent perturbation in various diseases. Cell death occurs in three highly interconnected steps: Initiation, signaling and execution. We used a systems biology approach to gather information about all known modes...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226067/ https://www.ncbi.nlm.nih.gov/pubmed/32316560 http://dx.doi.org/10.3390/cancers12040990 |
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author | Ravel, Jean-Marie Monraz Gomez, L. Cristobal Sompairac, Nicolas Calzone, Laurence Zhivotovsky, Boris Kroemer, Guido Barillot, Emmanuel Zinovyev, Andrei Kuperstein, Inna |
author_facet | Ravel, Jean-Marie Monraz Gomez, L. Cristobal Sompairac, Nicolas Calzone, Laurence Zhivotovsky, Boris Kroemer, Guido Barillot, Emmanuel Zinovyev, Andrei Kuperstein, Inna |
author_sort | Ravel, Jean-Marie |
collection | PubMed |
description | The processes leading to, or avoiding cell death are widely studied, because of their frequent perturbation in various diseases. Cell death occurs in three highly interconnected steps: Initiation, signaling and execution. We used a systems biology approach to gather information about all known modes of regulated cell death (RCD). Based on the experimental data retrieved from literature by manual curation, we graphically depicted the biological processes involved in RCD in the form of a seamless comprehensive signaling network map. The molecular mechanisms of each RCD mode are represented in detail. The RCD network map is divided into 26 functional modules that can be visualized contextually in the whole seamless network, as well as in individual diagrams. The resource is freely available and accessible via several web platforms for map navigation, data integration, and analysis. The RCD network map was employed for interpreting the functional differences in cell death regulation between Alzheimer’s disease and non-small cell lung cancer based on gene expression data that allowed emphasizing the molecular mechanisms underlying the inverse comorbidity between the two pathologies. In addition, the map was used for the analysis of genomic and transcriptomic data from ovarian cancer patients that provided RCD map-based signatures of four distinct tumor subtypes and highlighted the difference in regulations of cell death molecular mechanisms. |
format | Online Article Text |
id | pubmed-7226067 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72260672020-05-18 Comprehensive Map of the Regulated Cell Death Signaling Network: A Powerful Analytical Tool for Studying Diseases Ravel, Jean-Marie Monraz Gomez, L. Cristobal Sompairac, Nicolas Calzone, Laurence Zhivotovsky, Boris Kroemer, Guido Barillot, Emmanuel Zinovyev, Andrei Kuperstein, Inna Cancers (Basel) Article The processes leading to, or avoiding cell death are widely studied, because of their frequent perturbation in various diseases. Cell death occurs in three highly interconnected steps: Initiation, signaling and execution. We used a systems biology approach to gather information about all known modes of regulated cell death (RCD). Based on the experimental data retrieved from literature by manual curation, we graphically depicted the biological processes involved in RCD in the form of a seamless comprehensive signaling network map. The molecular mechanisms of each RCD mode are represented in detail. The RCD network map is divided into 26 functional modules that can be visualized contextually in the whole seamless network, as well as in individual diagrams. The resource is freely available and accessible via several web platforms for map navigation, data integration, and analysis. The RCD network map was employed for interpreting the functional differences in cell death regulation between Alzheimer’s disease and non-small cell lung cancer based on gene expression data that allowed emphasizing the molecular mechanisms underlying the inverse comorbidity between the two pathologies. In addition, the map was used for the analysis of genomic and transcriptomic data from ovarian cancer patients that provided RCD map-based signatures of four distinct tumor subtypes and highlighted the difference in regulations of cell death molecular mechanisms. MDPI 2020-04-17 /pmc/articles/PMC7226067/ /pubmed/32316560 http://dx.doi.org/10.3390/cancers12040990 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ravel, Jean-Marie Monraz Gomez, L. Cristobal Sompairac, Nicolas Calzone, Laurence Zhivotovsky, Boris Kroemer, Guido Barillot, Emmanuel Zinovyev, Andrei Kuperstein, Inna Comprehensive Map of the Regulated Cell Death Signaling Network: A Powerful Analytical Tool for Studying Diseases |
title | Comprehensive Map of the Regulated Cell Death Signaling Network: A Powerful Analytical Tool for Studying Diseases |
title_full | Comprehensive Map of the Regulated Cell Death Signaling Network: A Powerful Analytical Tool for Studying Diseases |
title_fullStr | Comprehensive Map of the Regulated Cell Death Signaling Network: A Powerful Analytical Tool for Studying Diseases |
title_full_unstemmed | Comprehensive Map of the Regulated Cell Death Signaling Network: A Powerful Analytical Tool for Studying Diseases |
title_short | Comprehensive Map of the Regulated Cell Death Signaling Network: A Powerful Analytical Tool for Studying Diseases |
title_sort | comprehensive map of the regulated cell death signaling network: a powerful analytical tool for studying diseases |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226067/ https://www.ncbi.nlm.nih.gov/pubmed/32316560 http://dx.doi.org/10.3390/cancers12040990 |
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