Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics

Rapid advancements in high-throughput omics technologies and experimental protocols have led to the generation of vast amounts of scale-specific biomolecular data on cancer that now populates several online databases and resources. Cancer systems biology models built using this data have the potenti...

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Autores principales:	Mahnoor Naseer Gondal, Safee Ullah Chaudhary
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	multi-scale cancer modeling personalized cancer therapeutics cancer systems biology data-driven oncology in silico cancer systems oncology predictive systems oncology Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/9eb5590fc0d64978a50fa2b6d5907043
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spelling	oai:doaj.org-article:9eb5590fc0d64978a50fa2b6d59070432021-11-30T18:12:08ZNavigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics2234-943X10.3389/fonc.2021.712505https://doaj.org/article/9eb5590fc0d64978a50fa2b6d59070432021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fonc.2021.712505/fullhttps://doaj.org/toc/2234-943XRapid advancements in high-throughput omics technologies and experimental protocols have led to the generation of vast amounts of scale-specific biomolecular data on cancer that now populates several online databases and resources. Cancer systems biology models built using this data have the potential to provide specific insights into complex multifactorial aberrations underpinning tumor initiation, development, and metastasis. Furthermore, the annotation of these single- and multi-scale models with patient data can additionally assist in designing personalized therapeutic interventions as well as aid in clinical decision-making. Here, we have systematically reviewed the emergence and evolution of (i) repositories with scale-specific and multi-scale biomolecular cancer data, (ii) systems biology models developed using this data, (iii) associated simulation software for the development of personalized cancer therapeutics, and (iv) translational attempts to pipeline multi-scale panomics data for data-driven in silico clinical oncology. The review concludes that the absence of a generic, zero-code, panomics-based multi-scale modeling pipeline and associated software framework, impedes the development and seamless deployment of personalized in silico multi-scale models in clinical settings.Mahnoor Naseer GondalMahnoor Naseer GondalSafee Ullah ChaudharyFrontiers Media S.A.articlemulti-scale cancer modelingpersonalized cancer therapeuticscancer systems biologydata-driven oncologyin silico cancer systems oncologypredictive systems oncologyNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENFrontiers in Oncology, Vol 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	multi-scale cancer modeling personalized cancer therapeutics cancer systems biology data-driven oncology in silico cancer systems oncology predictive systems oncology Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	multi-scale cancer modeling personalized cancer therapeutics cancer systems biology data-driven oncology in silico cancer systems oncology predictive systems oncology Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Mahnoor Naseer Gondal Mahnoor Naseer Gondal Safee Ullah Chaudhary Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics
description	Rapid advancements in high-throughput omics technologies and experimental protocols have led to the generation of vast amounts of scale-specific biomolecular data on cancer that now populates several online databases and resources. Cancer systems biology models built using this data have the potential to provide specific insights into complex multifactorial aberrations underpinning tumor initiation, development, and metastasis. Furthermore, the annotation of these single- and multi-scale models with patient data can additionally assist in designing personalized therapeutic interventions as well as aid in clinical decision-making. Here, we have systematically reviewed the emergence and evolution of (i) repositories with scale-specific and multi-scale biomolecular cancer data, (ii) systems biology models developed using this data, (iii) associated simulation software for the development of personalized cancer therapeutics, and (iv) translational attempts to pipeline multi-scale panomics data for data-driven in silico clinical oncology. The review concludes that the absence of a generic, zero-code, panomics-based multi-scale modeling pipeline and associated software framework, impedes the development and seamless deployment of personalized in silico multi-scale models in clinical settings.
format	article
author	Mahnoor Naseer Gondal Mahnoor Naseer Gondal Safee Ullah Chaudhary
author_facet	Mahnoor Naseer Gondal Mahnoor Naseer Gondal Safee Ullah Chaudhary
author_sort	Mahnoor Naseer Gondal
title	Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics
title_short	Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics
title_full	Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics
title_fullStr	Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics
title_full_unstemmed	Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics
title_sort	navigating multi-scale cancer systems biology towards model-driven clinical oncology and its applications in personalized therapeutics
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/9eb5590fc0d64978a50fa2b6d5907043
work_keys_str_mv	AT mahnoornaseergondal navigatingmultiscalecancersystemsbiologytowardsmodeldrivenclinicaloncologyanditsapplicationsinpersonalizedtherapeutics AT mahnoornaseergondal navigatingmultiscalecancersystemsbiologytowardsmodeldrivenclinicaloncologyanditsapplicationsinpersonalizedtherapeutics AT safeeullahchaudhary navigatingmultiscalecancersystemsbiologytowardsmodeldrivenclinicaloncologyanditsapplicationsinpersonalizedtherapeutics
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Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics

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