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Series GSE113005 Query DataSets for GSE113005
Status Public on Sep 01, 2019
Title Transcriptomics-based drug repurposing approach identifies novel drugs against sorafenib-resistant hepatocellular carcinoma
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary Hepatocellular carcinoma (HCC) is frequently diagnosed in patients with late-stage disease who are ineligible for curative surgical therapies. Furthermore, the majority of patients become resistant to sorafenib. Recently, computational methods for drug repurposing have shown great promise to accelerate the discovery of new uses for existing drugs. In order to identify novel drugs for use against sorafenib resistant (SR)-HCC, we employed a transcriptomics-based drug repurposing method termed connectivity mapping. We conducted a comprehensive analysis of available in vitro and in vivo gene signatures of (SR)-HCC, and generated our own in vitro model using the Huh7 HCC cell line. We compared coverage of SR-HCC gene signatures across seven patient-derived HCC gene expression datasets, and observed that patients harboring the Huh7 SR-HCC gene signature had significantly reduced survival. Utilizing the Huh7 SR-HCC gene signature, we applied connectivity mapping to drug-induced gene expression profiles (n= 3,740 drugs) in the HepG2 HCC cell line from the LINCS database in order to find drugs that could oppose sorafenib resistance. We validated the use of two non-receptor tyrosine kinase inhibitors, dasatinib and fostamatinib, to reduce viability of sorafenib-resistant HCC cells and confirmed up-regulated activity of Src family kinases, the targets of dasatinib, in our SR-HCC models. We prospectively validated predicted gene expression changes in fostamatinib treated Huh7-SR via RNA-seq analysis.
 
Overall design Gene expression profiles of Huh7-SR hepatocellular carcinoma cells resistant to sorafenib were generated by RNAseq (Illumina HiSeq 4000) following treatment with fostamatinib and vehicle control.
 
Contributor(s) Regan-Fendt KE, Li D, Ghoshal K
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Submission date Apr 11, 2018
Last update date Sep 03, 2019
Contact name Kelly Regan
E-mail(s) kelly.regan@osumc.edu
Organization name The Ohio State Univ
Department Biomedical Informatics
Street address 1800 Cannon Drive
City Columbus
State/province Ohio
ZIP/Postal code 43206
Country USA
 
Platforms (1)
GPL20301 Illumina HiSeq 4000 (Homo sapiens)
Samples (6)
GSM3093315 DMSO_1
GSM3093316 DMSO_2
GSM3093317 DMSO_3
Relations
BioProject PRJNA449722
SRA SRP139603

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Supplementary file Size Download File type/resource
GSE113005_RAW.tar 1.0 Mb (http)(custom) TAR (of TXT)
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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