Heterogeneity in cancer dynamics: A convex formulation to dissect dynamic trajectories and infer LTV models of networked systems

Roel Dobbe, Young Hwan Chang, James Korkola, Joe Gray, Claire Tomlin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Breast cancer tumors have inherently heterogeneous cell types that respond differently to treatments. Although there is a wealth of studies describing canonical cell signaling networks, little is known about how these networks operate in different cancer cells and treatments. This paper proposes a method to split a set of responses gathered from experiments on different cancer cells up into common and specific components. The key to this retrieval is the derivation of a linear timevarying model of the shared dynamics among the different cell lines. A convex optimization problem is derived that retrieves both the model and the common and specific responses without a priori information. The method is tested on synthetic data, and verifies known facts when tested on a biological data set with protein expression data from breast cancer experiments. The technique can be used to analyze specific responses to understand what treatments can be combined to persistently treat a heterogeneous cancer tumor. The linear time-varying model sheds light on how proteins interact over time.

Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4398-4403
Number of pages6
Volume2015-July
ISBN (Print)9781479986842
DOIs
StatePublished - Jul 28 2015
Event2015 American Control Conference, ACC 2015 - Chicago, United States
Duration: Jul 1 2015Jul 3 2015

Other

Other2015 American Control Conference, ACC 2015
CountryUnited States
CityChicago
Period7/1/157/3/15

Fingerprint

Cells
Trajectories
Tumors
Cell signaling
Proteins
Convex optimization
Experiments

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Dobbe, R., Chang, Y. H., Korkola, J., Gray, J., & Tomlin, C. (2015). Heterogeneity in cancer dynamics: A convex formulation to dissect dynamic trajectories and infer LTV models of networked systems. In Proceedings of the American Control Conference (Vol. 2015-July, pp. 4398-4403). [7172021] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2015.7172021

Heterogeneity in cancer dynamics : A convex formulation to dissect dynamic trajectories and infer LTV models of networked systems. / Dobbe, Roel; Chang, Young Hwan; Korkola, James; Gray, Joe; Tomlin, Claire.

Proceedings of the American Control Conference. Vol. 2015-July Institute of Electrical and Electronics Engineers Inc., 2015. p. 4398-4403 7172021.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Dobbe, R, Chang, YH, Korkola, J, Gray, J & Tomlin, C 2015, Heterogeneity in cancer dynamics: A convex formulation to dissect dynamic trajectories and infer LTV models of networked systems. in Proceedings of the American Control Conference. vol. 2015-July, 7172021, Institute of Electrical and Electronics Engineers Inc., pp. 4398-4403, 2015 American Control Conference, ACC 2015, Chicago, United States, 7/1/15. https://doi.org/10.1109/ACC.2015.7172021
Dobbe R, Chang YH, Korkola J, Gray J, Tomlin C. Heterogeneity in cancer dynamics: A convex formulation to dissect dynamic trajectories and infer LTV models of networked systems. In Proceedings of the American Control Conference. Vol. 2015-July. Institute of Electrical and Electronics Engineers Inc. 2015. p. 4398-4403. 7172021 https://doi.org/10.1109/ACC.2015.7172021
Dobbe, Roel ; Chang, Young Hwan ; Korkola, James ; Gray, Joe ; Tomlin, Claire. / Heterogeneity in cancer dynamics : A convex formulation to dissect dynamic trajectories and infer LTV models of networked systems. Proceedings of the American Control Conference. Vol. 2015-July Institute of Electrical and Electronics Engineers Inc., 2015. pp. 4398-4403
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