Unraveling non-genetic heterogeneity in cancer with dynamical models and computational tools

Pillai, M and Hojel, E and Jolly, MK and Goyal, Y (2023) Unraveling non-genetic heterogeneity in cancer with dynamical models and computational tools. In: Nature Computational Science, 3 (4). pp. 301-313.

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Abstract

Individual cells within an otherwise genetically homogenous population constantly undergo fluctuations in their molecular state, giving rise to non-genetic heterogeneity. Such diversity is being increasingly implicated in cancer therapy resistance and metastasis. Identifying the origins of non-genetic heterogeneity is therefore crucial for making clinical breakthroughs. We discuss with examples how dynamical models and computational tools have provided critical multiscale insights into the nature and consequences of non-genetic heterogeneity in cancer. We demonstrate how mechanistic modeling has been pivotal in establishing key concepts underlying non-genetic diversity at various biological scales, from population dynamics to gene regulatory networks. We discuss advances in single-cell longitudinal profiling techniques to reveal patterns of non-genetic heterogeneity, highlighting the ongoing efforts and challenges in statistical frameworks to robustly interpret such multimodal datasets. Moving forward, we stress the need for data-driven statistical and mechanistically motivated dynamical frameworks to come together to develop predictive cancer models and inform therapeutic strategies. © 2023, Springer Nature America, Inc.

Item Type:	Journal Article
Publication:	Nature Computational Science
Publisher:	Springer Nature
Additional Information:	The copyright of this article belongs to Springer Nature.
Keywords:	Computational methods; Diseases; Cancer therapy; Computational tools; Dynamical modeling; Gene regulatory networks; Genetic heterogeneities; Genetics diversities; Individual cells; Mechanistic models; Modelling tools; Molecular state; Population dynamics
Department/Centre:	Division of Interdisciplinary Sciences > Centre for Biosystems Science and Engineering
Date Deposited:	14 Jun 2023 09:36
Last Modified:	14 Jun 2023 09:36
URI:	https://eprints.iisc.ac.in/id/eprint/81879

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