CSIOVDB: a microarray gene expression database of epithelial ovarian cancer subtype

Area of Science:

• Genomics
• Cancer Biology
• Bioinformatics

Background:

• Existing disease databases often lack crucial molecular subtype and epithelial-mesenchymal transition (EMT) status for ovarian cancers.
• Ovarian cancer research requires integrated datasets that combine transcriptomic information with clinical and molecular data.

Purpose of the Study:

• To introduce the Cancer Systems Immunobiology Ovarian Database (CSIOVDB), a novel transcriptomic microarray database for ovarian cancer.
• To provide a comprehensive resource for ovarian cancer research, including molecular subtypes, EMT status, and survival data.
• To facilitate the exploration of biomarkers and therapeutic targets in ovarian cancer.

Main Methods:

• Compilation of transcriptomic microarray data from 3,431 human ovarian cancers, including various histologies and normal ovarian tissues.
• Inclusion of clinico-pathological parameters such as tumor grade, surgical debulking status, clinical response, and patient age.
• Integration of copy number, DNA methylation, and mutation data from The Cancer Genome Atlas (TCGA).

Main Results:

• CSIOVDB contains data for 3,431 ovarian cancer samples, encompassing major histologies and early-stage cancers.
• The database provides molecular subtype and EMT status for each sample, alongside survival data for 1,868 (overall) and 1,516 (disease-free) samples.
• Integrated genomic data from TCGA enhances the utility of CSIOVDB for multi-omic analyses.

Conclusions:

• CSIOVDB is a unique and valuable resource for ovarian cancer research, offering integrated transcriptomic, molecular, and clinical data.
• The database supports the identification of novel biomarkers and therapeutic targets by providing detailed molecular and clinical information.
• This comprehensive dataset will advance our understanding of ovarian cancer heterogeneity and progression.