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 |
Appears in Collections: | Elements Staff Publications |
Show full item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
10_1038_srep22811.pdf | 3.38 MB | Adobe PDF | OPEN | None | View/Download |
This item is licensed under a Creative Commons License