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 language | English (US) |
|---|---|
| Title of host publication | Proceedings of the American Control Conference |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 4398-4403 |
| Number of pages | 6 |
| Volume | 2015-July |
| ISBN (Print) | 9781479986842 |
| DOIs | |
| State | Published - Jul 28 2015 |
| Event | 2015 American Control Conference, ACC 2015 - Chicago, United States Duration: Jul 1 2015 → Jul 3 2015 |
Other
| Other | 2015 American Control Conference, ACC 2015 |
|---|---|
| Country | United States |
| City | Chicago |
| Period | 7/1/15 → 7/3/15 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
Cite this
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 proceeding › Conference contribution
}
TY - GEN
T1 - Heterogeneity in cancer dynamics
T2 - A convex formulation to dissect dynamic trajectories and infer LTV models of networked systems
AU - Dobbe, Roel
AU - Chang, Young Hwan
AU - Korkola, James
AU - Gray, Joe
AU - Tomlin, Claire
PY - 2015/7/28
Y1 - 2015/7/28
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84940920035&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84940920035&partnerID=8YFLogxK
U2 - 10.1109/ACC.2015.7172021
DO - 10.1109/ACC.2015.7172021
M3 - Conference contribution
AN - SCOPUS:84940920035
SN - 9781479986842
VL - 2015-July
SP - 4398
EP - 4403
BT - Proceedings of the American Control Conference
PB - Institute of Electrical and Electronics Engineers Inc.
ER -