Quantification and analysis of combination drug synergy in high-throughput transcriptome studies

Zeynep H. Gümüş; Fernando Siso-Nada; Ada Gjyrezi; Paul McDonagh; Iya Khali; Paraskevi Giannakakou; Harel Weinstein

doi:10.1109/BIBE.2010.46

Quantification and analysis of combination drug synergy in high-throughput transcriptome studies

Zeynep H. Gümüş
, Fernando Siso-Nada
, Ada Gjyrezi
, Paul McDonagh
, Iya Khali
, Paraskevi Giannakakou
, Harel Weinstein

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

We present an integrated experimental and computational approach designed to identify the key cellular components that either contribute to or drive therapeutic synergy of drug combinations with anticancer activity. The approach includes (i) quantification of drug synergy in high throughput transcriptome experiments, (ii) data-driven reverse engineering and forward simulation technology to develop an in silico model predictive of drug synergy, and (iii) utilization of databases of interaction and functional information in hypothesis generation that are validated experimentally in a final step (iv). The goal is to develop an integrated framework that aids in understanding the mechanistic details of drug synergy to design better combination drugs. We illustrate this approach with an application to the analysis of transcriptome changes in cells exposed to the synergistic anticancer drug combination of farnesyl transferase inhibitors (FTIs) combined with taxanes.

Original language	English
Title of host publication	10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010
Pages	238-243
Number of pages	6
DOIs	https://doi.org/10.1109/BIBE.2010.46
State	Published - 2010
Externally published	Yes
Event	10th IEEE International Conference on Bioinformatics and Bioengineering, BIBE-2010 - Philadelphia, PA, United States Duration: 31 May 2010 → 3 Jun 2010

Publication series

Name	10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010

Conference

Conference	10th IEEE International Conference on Bioinformatics and Bioengineering, BIBE-2010
Country/Territory	United States
City	Philadelphia, PA
Period	31/05/10 → 3/06/10

Keywords

Combination index
Drug synergy
Ovarian cancer
Reverse engineering
Transcriptome

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10.1109/BIBE.2010.46

Cite this

Gümüş, Z. H., Siso-Nada, F., Gjyrezi, A., McDonagh, P., Khali, I., Giannakakou, P., & Weinstein, H. (2010). Quantification and analysis of combination drug synergy in high-throughput transcriptome studies. In 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010 (pp. 238-243). Article 5521684 (10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010). https://doi.org/10.1109/BIBE.2010.46

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title = "Quantification and analysis of combination drug synergy in high-throughput transcriptome studies",

abstract = "We present an integrated experimental and computational approach designed to identify the key cellular components that either contribute to or drive therapeutic synergy of drug combinations with anticancer activity. The approach includes (i) quantification of drug synergy in high throughput transcriptome experiments, (ii) data-driven reverse engineering and forward simulation technology to develop an in silico model predictive of drug synergy, and (iii) utilization of databases of interaction and functional information in hypothesis generation that are validated experimentally in a final step (iv). The goal is to develop an integrated framework that aids in understanding the mechanistic details of drug synergy to design better combination drugs. We illustrate this approach with an application to the analysis of transcriptome changes in cells exposed to the synergistic anticancer drug combination of farnesyl transferase inhibitors (FTIs) combined with taxanes.",

keywords = "Combination index, Drug synergy, Ovarian cancer, Reverse engineering, Transcriptome",

author = "G{\"u}m{\"u}{\c s}, \{Zeynep H.\} and Fernando Siso-Nada and Ada Gjyrezi and Paul McDonagh and Iya Khali and Paraskevi Giannakakou and Harel Weinstein",

year = "2010",

doi = "10.1109/BIBE.2010.46",

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isbn = "9780769540832",

series = "10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010",

pages = "238--243",

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note = "10th IEEE International Conference on Bioinformatics and Bioengineering, BIBE-2010 ; Conference date: 31-05-2010 Through 03-06-2010",

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Gümüş, ZH, Siso-Nada, F, Gjyrezi, A, McDonagh, P, Khali, I, Giannakakou, P & Weinstein, H 2010, Quantification and analysis of combination drug synergy in high-throughput transcriptome studies. in 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010., 5521684, 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010, pp. 238-243, 10th IEEE International Conference on Bioinformatics and Bioengineering, BIBE-2010, Philadelphia, PA, United States, 31/05/10. https://doi.org/10.1109/BIBE.2010.46

Quantification and analysis of combination drug synergy in high-throughput transcriptome studies. / Gümüş, Zeynep H.; Siso-Nada, Fernando; Gjyrezi, Ada et al.
10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010. 2010. p. 238-243 5521684 (10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Gümüş, Zeynep H.

AU - Siso-Nada, Fernando

AU - Gjyrezi, Ada

AU - McDonagh, Paul

AU - Khali, Iya

AU - Giannakakou, Paraskevi

AU - Weinstein, Harel

PY - 2010

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AB - We present an integrated experimental and computational approach designed to identify the key cellular components that either contribute to or drive therapeutic synergy of drug combinations with anticancer activity. The approach includes (i) quantification of drug synergy in high throughput transcriptome experiments, (ii) data-driven reverse engineering and forward simulation technology to develop an in silico model predictive of drug synergy, and (iii) utilization of databases of interaction and functional information in hypothesis generation that are validated experimentally in a final step (iv). The goal is to develop an integrated framework that aids in understanding the mechanistic details of drug synergy to design better combination drugs. We illustrate this approach with an application to the analysis of transcriptome changes in cells exposed to the synergistic anticancer drug combination of farnesyl transferase inhibitors (FTIs) combined with taxanes.

KW - Combination index

KW - Drug synergy

KW - Ovarian cancer

KW - Reverse engineering

KW - Transcriptome

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BT - 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010

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Gümüş ZH, Siso-Nada F, Gjyrezi A, McDonagh P, Khali I, Giannakakou P et al. Quantification and analysis of combination drug synergy in high-throughput transcriptome studies. In 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010. 2010. p. 238-243. 5521684. (10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010). doi: 10.1109/BIBE.2010.46

Quantification and analysis of combination drug synergy in high-throughput transcriptome studies

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Keywords

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