Please use this identifier to cite or link to this item:
https://doi.org/10.1038/srep18658
DC Field | Value | |
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dc.title | Predicting chemotherapeutic drug combinations through gene network profiling | |
dc.contributor.author | Nguyen, Thi Thuy Trang | |
dc.contributor.author | Chua, Jacqueline Kia Kee | |
dc.contributor.author | Seah, Kwi Shan | |
dc.contributor.author | Koo, Seok Hwee | |
dc.contributor.author | Yee, Jie Yin | |
dc.contributor.author | Yang, Eugene Guorong | |
dc.contributor.author | Lim, Kim Kiat | |
dc.contributor.author | Pang, Shermaine Yu Wen | |
dc.contributor.author | Yuen, Audrey | |
dc.contributor.author | Zhang, Louxin | |
dc.contributor.author | Ang, Wee Han | |
dc.contributor.author | Dymock, Brian | |
dc.contributor.author | Lee, Edmund Jon Deoon | |
dc.contributor.author | Chen, Ee Sin | |
dc.date.accessioned | 2022-07-21T01:44:41Z | |
dc.date.available | 2022-07-21T01:44:41Z | |
dc.date.issued | 2016-01-21 | |
dc.identifier.citation | Nguyen, Thi Thuy Trang, Chua, Jacqueline Kia Kee, Seah, Kwi Shan, Koo, Seok Hwee, Yee, Jie Yin, Yang, Eugene Guorong, Lim, Kim Kiat, Pang, Shermaine Yu Wen, Yuen, Audrey, Zhang, Louxin, Ang, Wee Han, Dymock, Brian, Lee, Edmund Jon Deoon, Chen, Ee Sin (2016-01-21). Predicting chemotherapeutic drug combinations through gene network profiling. SCIENTIFIC REPORTS 6 (1). ScholarBank@NUS Repository. https://doi.org/10.1038/srep18658 | |
dc.identifier.issn | 2045-2322 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/228983 | |
dc.description.abstract | Contemporary chemotherapeutic treatments incorporate the use of several agents in combination. However, selecting the most appropriate drugs for such therapy is not necessarily an easy or straightforward task. Here, we describe a targeted approach that can facilitate the reliable selection of chemotherapeutic drug combinations through the interrogation of drug-resistance gene networks. Our method employed single-cell eukaryote fission yeast (Schizosaccharomyces pombe) as a model of proliferating cells to delineate a drug resistance gene network using a synthetic lethality workflow. Using the results of a previous unbiased screen, we assessed the genetic overlap of doxorubicin with six other drugs harboring varied mechanisms of action. Using this fission yeast model, drug-specific ontological sub-classifications were identified through the computation of relative hypersensitivities. We found that human gastric adenocarcinoma cells can be sensitized to doxorubicin by concomitant treatment with cisplatin, an intra-DNA strand crosslinking agent, and suberoylanilide hydroxamic acid, a histone deacetylase inhibitor. Our findings point to the utility of fission yeast as a model and the differential targeting of a conserved gene interaction network when screening for successful chemotherapeutic drug combinations for human cells. | |
dc.language.iso | en | |
dc.publisher | NATURE PUBLISHING GROUP | |
dc.source | Elements | |
dc.subject | Science & Technology | |
dc.subject | Multidisciplinary Sciences | |
dc.subject | Science & Technology - Other Topics | |
dc.subject | HISTONE DEACETYLASE INHIBITOR | |
dc.subject | DNA-DAMAGE CHECKPOINT | |
dc.subject | FISSION YEAST | |
dc.subject | HOMOLOGOUS RECOMBINATION | |
dc.subject | SUBUNIT-E | |
dc.subject | CANCER | |
dc.subject | PROTEIN | |
dc.subject | REPAIR | |
dc.subject | RESISTANCE | |
dc.subject | FITNESS | |
dc.type | Article | |
dc.date.updated | 2022-07-20T10:57:11Z | |
dc.contributor.department | MATHEMATICS | |
dc.contributor.department | BIOCHEMISTRY | |
dc.contributor.department | PHARMACY | |
dc.contributor.department | PHARMACOLOGY | |
dc.description.doi | 10.1038/srep18658 | |
dc.description.sourcetitle | SCIENTIFIC REPORTS | |
dc.description.volume | 6 | |
dc.description.issue | 1 | |
dc.description.place | UNITED KINGDOM | |
dc.published.state | Published | |
Appears in Collections: | Staff Publications Elements |
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Predicting chemotherapeutic drug combinations through gene network profiling.pdf | 1.53 MB | Adobe PDF | OPEN | None | View/Download |
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