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

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. Access through your institution Buy or subscribe This is a preview of subscription content,

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about institutional subscriptions * Read our FAQs * Contact customer support SIMILAR CONTENT BEING VIEWED BY OTHERS SINGLE-CELL TRANSCRIPTOMICS IN CANCER: COMPUTATIONAL CHALLENGES AND

OPPORTUNITIES Article Open access 15 September 2020 INTEGRATING GENETIC AND NON-GENETIC DETERMINANTS OF CANCER EVOLUTION BY SINGLE-CELL MULTI-OMICS Article 17 August 2020 DELINEATING THE

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(2005). Google Scholar  * Purvis, J. E. et al. p53 dynamics control cell fate. _Science_ 336, 1440–1444 (2012). Google Scholar  Download references ACKNOWLEDGEMENTS We thank the members of

the Goyal and Jolly labs for helpful discussions. We thank K. Kiani and I. Mellis for their critical reading of the manuscript. The Goyal lab thanks R. Valadka at Northwestern University for

his prompt and unwavering support in setting up the lab space. M.P. was supported by grants to Y.G. including the Career Award at the Scientific Interface from BWF (1020614.01) and start-up

funds from Northwestern University, and KVPY Fellowship (Department of Science and Technology, Government of India). E.H. acknowledges support from the Career Award at the Scientific

Interface from BWF (1020614.01) and Northwestern University’s Biomedical Engineering Department for the BME Summer Undergraduate Research Grant Award (SURA). E.H. thanks E. Hojel and M.

Hojel for the support and encouragement to pursue her passions. M.K.J. acknowledges support from Ramanujan Fellowship awarded by the Science and Engineering Research Board, Department of

Science and Technology, Government of India (SB/S2/RJN-049/2018), and from the InfoSys Foundation, Bangalore. Y.G. acknowledges support from the Career Award at the Scientific Interface from

BWF (1020614.01), start-up funds from Northwestern University, and a grant (10063150.01) from Research Catalyst Program from the McCormick School of Engineering at Northwestern University.

AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA Maalavika Pillai, Emilia

Hojel & Yogesh Goyal * Center for Synthetic Biology, Northwestern University, Chicago, IL, USA Maalavika Pillai, Emilia Hojel & Yogesh Goyal * Robert H. Lurie Comprehensive Cancer

Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA Maalavika Pillai & Yogesh Goyal * Centre for BioSystems Science and Engineering, Indian Institute of

Science, Bangalore, India Maalavika Pillai & Mohit Kumar Jolly * Department of Biomedical Engineering, Northwestern University McCormick School of Engineering, Evanston, IL, USA Emilia

Hojel & Yogesh Goyal Authors * Maalavika Pillai View author publications You can also search for this author inPubMed Google Scholar * Emilia Hojel View author publications You can also

search for this author inPubMed Google Scholar * Mohit Kumar Jolly View author publications You can also search for this author inPubMed Google Scholar * Yogesh Goyal View author

publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS M.K.J. and Y.G. conceived the project, wrote the first draft of the manuscript and contributed to

figure design. M.P. revised the initial draft, contributed to figure design, and prepared the boxes and the table. E.H. contributed to the figure, box and table design and literature survey.

All authors contributed to revisions. CORRESPONDING AUTHORS Correspondence to Mohit Kumar Jolly or Yogesh Goyal. ETHICS DECLARATIONS COMPETING INTERESTS Y.G. received consultancy fee from

the Schmidt Science Fellows and the Rhodes Trust. The other authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Nature Computational Science_ thanks Gábor Balázsi

and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Ananya Rastogi and Kaitlin McCardle, in collaboration with the _Nature

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permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Pillai, M., Hojel, E., Jolly, M.K. _et al._ Unraveling non-genetic heterogeneity in cancer with dynamical models and computational tools.

_Nat Comput Sci_ 3, 301–313 (2023). https://doi.org/10.1038/s43588-023-00427-0 Download citation * Received: 30 March 2022 * Accepted: 03 March 2023 * Published: 24 April 2023 * Issue Date:

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