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Towards the First Principles in Biology and Cancer: New Vistas in Computational Systems Biology of Cancer
These days many leading scientists argue for a new paradigm for cancer research and propose a complex systems-view of cancer supported by empirical evidence. As an example, Thea Newman (2021) has applied “the lessons learned from physical systems to a critique of reductionism in medical research, wi...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8778485/ https://www.ncbi.nlm.nih.gov/pubmed/35054414 http://dx.doi.org/10.3390/life12010021 |
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author | Prokop, Aleš |
author_facet | Prokop, Aleš |
author_sort | Prokop, Aleš |
collection | PubMed |
description | These days many leading scientists argue for a new paradigm for cancer research and propose a complex systems-view of cancer supported by empirical evidence. As an example, Thea Newman (2021) has applied “the lessons learned from physical systems to a critique of reductionism in medical research, with an emphasis on cancer”. It is the understanding of this author that the mesoscale constructs that combine the bottom-up as well as top-down approaches, are very close to the concept of emergence. The mesoscale constructs can be said to be those effective components through which the system allows itself to be understood. A short list of basic concepts related to life/biology fundamentals are first introduced to demonstrate a lack of emphasis on these matters in literature. It is imperative that physical and chemical approaches are introduced and incorporated in biology to make it more conceptually sound, quantitative, and based on the first principles. Non-equilibrium thermodynamics is the only tool currently available for making progress in this direction. A brief outline of systems biology, the discovery of emergent properties, and metabolic modeling are introduced in the second part. Then, different cancer initiation concepts are reviewed, followed by application of non-equilibrium thermodynamics in the metabolic and genomic analysis of initiation and development of cancer, stressing the endogenous network hypothesis (ENH). Finally, extension of the ENH is suggested to include a cancer niche (exogenous network hypothesis). It is expected that this will lead to a unifying systems–biology approach for a future combination of the analytical and synthetic arms of two major hypotheses of cancer models (SMT and TOFT). |
format | Online Article Text |
id | pubmed-8778485 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87784852022-01-22 Towards the First Principles in Biology and Cancer: New Vistas in Computational Systems Biology of Cancer Prokop, Aleš Life (Basel) Review These days many leading scientists argue for a new paradigm for cancer research and propose a complex systems-view of cancer supported by empirical evidence. As an example, Thea Newman (2021) has applied “the lessons learned from physical systems to a critique of reductionism in medical research, with an emphasis on cancer”. It is the understanding of this author that the mesoscale constructs that combine the bottom-up as well as top-down approaches, are very close to the concept of emergence. The mesoscale constructs can be said to be those effective components through which the system allows itself to be understood. A short list of basic concepts related to life/biology fundamentals are first introduced to demonstrate a lack of emphasis on these matters in literature. It is imperative that physical and chemical approaches are introduced and incorporated in biology to make it more conceptually sound, quantitative, and based on the first principles. Non-equilibrium thermodynamics is the only tool currently available for making progress in this direction. A brief outline of systems biology, the discovery of emergent properties, and metabolic modeling are introduced in the second part. Then, different cancer initiation concepts are reviewed, followed by application of non-equilibrium thermodynamics in the metabolic and genomic analysis of initiation and development of cancer, stressing the endogenous network hypothesis (ENH). Finally, extension of the ENH is suggested to include a cancer niche (exogenous network hypothesis). It is expected that this will lead to a unifying systems–biology approach for a future combination of the analytical and synthetic arms of two major hypotheses of cancer models (SMT and TOFT). MDPI 2021-12-23 /pmc/articles/PMC8778485/ /pubmed/35054414 http://dx.doi.org/10.3390/life12010021 Text en © 2021 by the author. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Prokop, Aleš Towards the First Principles in Biology and Cancer: New Vistas in Computational Systems Biology of Cancer |
title | Towards the First Principles in Biology and Cancer: New Vistas in Computational Systems Biology of Cancer |
title_full | Towards the First Principles in Biology and Cancer: New Vistas in Computational Systems Biology of Cancer |
title_fullStr | Towards the First Principles in Biology and Cancer: New Vistas in Computational Systems Biology of Cancer |
title_full_unstemmed | Towards the First Principles in Biology and Cancer: New Vistas in Computational Systems Biology of Cancer |
title_short | Towards the First Principles in Biology and Cancer: New Vistas in Computational Systems Biology of Cancer |
title_sort | towards the first principles in biology and cancer: new vistas in computational systems biology of cancer |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8778485/ https://www.ncbi.nlm.nih.gov/pubmed/35054414 http://dx.doi.org/10.3390/life12010021 |
work_keys_str_mv | AT prokopales towardsthefirstprinciplesinbiologyandcancernewvistasincomputationalsystemsbiologyofcancer |