CSIOVDB: a microarray gene expression database of epithelial ovarian cancer subtype
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Tuan Zea Tan1, He Yang1, Jieru Ye1, Jeffrey Low2, Mahesh Choolani2, David Shao Peng Tan1,2,3, Jean-Paul Thiery1,4,5, Ruby Yun-Ju Huang1,2,5,6
1Cancer Science Institute of Singapore, National University of Singapore, Center for Translational Medicine, Singapore 117599
2Department of Obstetrics and Gynecology, National University Health System, Singapore 119228
3Department of Haematology-Oncology, National University Hospital, Singapore 119074
4Institute of Molecular and Cell Biology, A*STAR, Proteos, Singapore 138673
5Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596
6Department of Anatomy, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596
Ruby Yun-Ju Huang, e-mail: firstname.lastname@example.org
Jean-Paul Thiery, e-mail: email@example.com
Keywords: ovarian cancer, microarray gene expression, molecular subtype, database
Received: July 16, 2015 Accepted: October 04, 2015 Published: November 07, 2015
Databases pertaining to various diseases provide valuable resources on particular genes of interest but lack the molecular subtype and epithelial-mesenchymal transition status. CSIOVDB is a transcriptomic microarray database of 3,431 human ovarian cancers, including carcinoma of the ovary, fallopian tube, and peritoneum, and metastasis to the ovary. The database also comprises stroma and ovarian surface epithelium from normal ovary tissue, as well as over 400 early-stage ovarian cancers. This unique database presents the molecular subtype and epithelial-mesenchymal transition status for each ovarian cancer sample, with major ovarian cancer histologies (clear cell, endometrioid, mucinous, low-grade serous, serous) represented. Clinico-pathological parameters available include tumor grade, surgical debulking status, clinical response and age. The database has 1,868 and 1,516 samples with information pertaining to overall and disease-free survival rates, respectively. The database also provides integration with the copy number, DNA methylation and mutation data from TCGA. CSIOVDB seeks to provide a resource for biomarker and therapeutic target exploration for ovarian cancer research.
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