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Prospects and challenges of cancer systems medicine: from genes to disease networks
It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowl...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769701/ https://www.ncbi.nlm.nih.gov/pubmed/34471925 http://dx.doi.org/10.1093/bib/bbab343 |
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author | Karimi, Mohammad Reza Karimi, Amir Hossein Abolmaali, Shamsozoha Sadeghi, Mehdi Schmitz, Ulf |
author_facet | Karimi, Mohammad Reza Karimi, Amir Hossein Abolmaali, Shamsozoha Sadeghi, Mehdi Schmitz, Ulf |
author_sort | Karimi, Mohammad Reza |
collection | PubMed |
description | It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches. |
format | Online Article Text |
id | pubmed-8769701 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-87697012022-01-20 Prospects and challenges of cancer systems medicine: from genes to disease networks Karimi, Mohammad Reza Karimi, Amir Hossein Abolmaali, Shamsozoha Sadeghi, Mehdi Schmitz, Ulf Brief Bioinform Review It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches. Oxford University Press 2021-09-01 /pmc/articles/PMC8769701/ /pubmed/34471925 http://dx.doi.org/10.1093/bib/bbab343 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Karimi, Mohammad Reza Karimi, Amir Hossein Abolmaali, Shamsozoha Sadeghi, Mehdi Schmitz, Ulf Prospects and challenges of cancer systems medicine: from genes to disease networks |
title | Prospects and challenges of cancer systems medicine: from genes to disease networks |
title_full | Prospects and challenges of cancer systems medicine: from genes to disease networks |
title_fullStr | Prospects and challenges of cancer systems medicine: from genes to disease networks |
title_full_unstemmed | Prospects and challenges of cancer systems medicine: from genes to disease networks |
title_short | Prospects and challenges of cancer systems medicine: from genes to disease networks |
title_sort | prospects and challenges of cancer systems medicine: from genes to disease networks |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769701/ https://www.ncbi.nlm.nih.gov/pubmed/34471925 http://dx.doi.org/10.1093/bib/bbab343 |
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