title: Utilizingsignature-score to identify oncogenic pathways of cholangiocarcinoma.
abstract: Extracting maximal information from gene signature sets (GSSs) via microarray-based transcriptional profiling involves assigning function to up and down regulated genes. Here we present a novel sample scoring method called Signature-score (S-score) which can be used to quantify the expression pattern of tumor samples from previously identified gene signature sets. A simulation result demonstrated an improved accuracy and robustness by S-score method comparing with other scoring methods. By applying the S-score method to cholangiocarcinoma (CAC), an aggressive hepatic cancer that arises from bile ducts cells, we identified enriched oncogenic pathways in two large CAC data sets. Thirteen pathways were enriched in CAC compared with normal liver and bile duct. Moreover, using S-score, we were able to dissect correlations between CAC-associated oncogenic pathways and Gene Ontology function. Two major oncogenic clusters and associated functions were identified. Cluster 1, which included beta-catenin and Ras, showed a positive correlation with the cell cycle, while cluster 2, which included TGF-beta, cytokeratin 19 and EpCAM was inversely correlated with immune function. We also used S-score to identify pathways that are differentially expressed in CAC and hepatocellular carcinoma (HCC), the more common subtype of liver cancer. Our results demonstrate the utility and effectiveness ofS-score in assigning functional roles to tumor-associated gene signature sets and in identifying potential therapeutic targets for specific liver cancer subtypes.
authors.affiliation: Greehey Children's Cancer Research Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
authors.forename: Tzu-Hung
authors.initials: TH
authors.lastname: Hsiao
authors.forename: Hung-I Harry
authors.initials: HI
authors.lastname: Chen
authors.forename: Jo-Yang
authors.initials: JY
authors.lastname: Lu
authors.forename: Pei-Ying
authors.initials: PY
authors.lastname: Lin
authors.forename: Charles
authors.initials: C
authors.lastname: Keller
authors.forename: Sarah
authors.initials: S
authors.lastname: Comerford
authors.forename: Gail E
authors.initials: GE
authors.lastname: Tomlinson
authors.forename: Yidong
authors.initials: Y
authors.lastname: Chen
keywords: S-score method; gene signature set; pathway analysis; tumor classification
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