Dissecting cell fate dynamics in pediatric glioblastoma through the lens of complex systems and cellular cybernetics.
Artificial intelligence
Attractors
Cancer
Cellular decision-making
Complex systems
Computational medicine
Cybernetics
Epigenetics
Networks
Systems oncology
Journal
Biological cybernetics
ISSN: 1432-0770
Titre abrégé: Biol Cybern
Pays: Germany
ID NLM: 7502533
Informations de publication
Date de publication:
08 2022
08 2022
Historique:
received:
25
08
2021
accepted:
04
05
2022
pubmed:
10
6
2022
medline:
20
7
2022
entrez:
9
6
2022
Statut:
ppublish
Résumé
Cancers are complex dynamic ecosystems. Reductionist approaches to science are inadequate in characterizing their self-organized patterns and collective emergent behaviors. Since current approaches to single-cell analysis in cancer systems rely primarily on single time-point multiomics, many of the temporal features and causal adaptive behaviors in cancer dynamics are vastly ignored. As such, tools and concepts from the interdisciplinary paradigm of complex systems theory are introduced herein to decode the cellular cybernetics of cancer differentiation dynamics and behavioral patterns. An intuition for the attractors and complex networks underlying cancer processes such as cell fate decision-making, multiscale pattern formation systems, and epigenetic state-transitions is developed. The applications of complex systems physics in paving targeted therapies and causal pattern discovery in precision oncology are discussed. Pediatric high-grade gliomas are discussed as a model-system to demonstrate that cancers are complex adaptive systems, in which the emergence and selection of heterogeneous cellular states and phenotypic plasticity are driven by complex multiscale network dynamics. In specific, pediatric glioblastoma (GBM) is used as a proof-of-concept model to illustrate the applications of the complex systems framework in understanding GBM cell fate decisions and decoding their adaptive cellular dynamics. The scope of these tools in forecasting cancer cell fate dynamics in the emerging field of computational oncology and patient-centered systems medicine is highlighted.
Identifiants
pubmed: 35678918
doi: 10.1007/s00422-022-00935-8
pii: 10.1007/s00422-022-00935-8
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
407-445Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
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