Please use this identifier to cite or link to this item: https://doi.org/10.1038/srep22811
Title: A systematic study on drug-response associated genes using baseline gene expressions of the Cancer Cell Line Encyclopedia
Authors: Liu, X
Yang, J 
Zhang, Y
Fang, Y
Wang, F
Wang, J
Zheng, X
Yang, J
Keywords: antineoplastic agent
pharmacological biomarker
age
cell cycle
chemistry
drug resistance
female
gene expression regulation
gene regulatory network
genetics
human
male
Neoplasms
sex difference
systems biology
tumor cell line
Age Factors
Antineoplastic Agents
Biomarkers, Pharmacological
Cell Cycle
Cell Line, Tumor
Drug Resistance, Neoplasm
Female
Gene Expression Regulation
Gene Regulatory Networks
Humans
Male
Neoplasms
Sex Factors
Systems Biology
Issue Date: 2016
Publisher: Nature Publishing Group
Citation: Liu, X, Yang, J, Zhang, Y, Fang, Y, Wang, F, Wang, J, Zheng, X, Yang, J (2016). A systematic study on drug-response associated genes using baseline gene expressions of the Cancer Cell Line Encyclopedia. Scientific Reports 6 : 22811. ScholarBank@NUS Repository. https://doi.org/10.1038/srep22811
Rights: Attribution 4.0 International
Abstract: We have studied drug-response associated (DRA) gene expressions by applying a systems biology framework to the Cancer Cell Line Encyclopedia data. More than 4,000 genes are inferred to be DRA for at least one drug, while the number of DRA genes for each drug varies dramatically from almost 0 to 1,226. Functional enrichment analysis shows that the DRA genes are significantly enriched in genes associated with cell cycle and plasma membrane. Moreover, there might be two patterns of DRA genes between genders. There are significantly shared DRA genes between male and female for most drugs, while very little DRA genes tend to be shared between the two genders for a few drugs targeting sex-specific cancers (e.g., PD-0332991 for breast cancer and ovarian cancer). Our analyses also show substantial difference for DRA genes between young and old samples, suggesting the necessity of considering the age effects for personalized medicine in cancers. Lastly, differential module and key driver analyses confirm cell cycle related modules as top differential ones for drug sensitivity. The analyses also reveal the role of TSPO, TP53, and many other immune or cell cycle related genes as important key drivers for DRA network modules. These key drivers provide new drug targets to improve the sensitivity of cancer therapy.
Source Title: Scientific Reports
URI: https://scholarbank.nus.edu.sg/handle/10635/182494
ISSN: 2045-2322
DOI: 10.1038/srep22811
Rights: Attribution 4.0 International
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