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GENT: gene expression database of normal and tumor tissues
Gwangsik Shin1, Tae-Wook Kang, Sungjin Yang
1Department of Bio and Information Technology, Graduate School, Chungbuk National University, 410 Seongbong-ro, Heungdeok-gu, Cheongju, Chungbuk, 361-763.
Cancer Informatics
|June 23, 2011
Summary
The Gene Expression database of Normal and Tumor tissues (GENT) aids cancer outlier profile analysis. Its large sample size facilitates identifying genes over-expressed in specific patient subsets for target discovery and validation.
Area of Science:
- Genomics
- Bioinformatics
- Cancer Research
Background:
- Oncogenes like ERBB2 and EGFR are over-expressed in a subset of cancer patients.
- Cancer outlier profile analysis computationally identifies gene expression outliers.
- Large sample size databases are crucial for identifying genes over-expressed in patient subsets.
Purpose of the Study:
- To introduce the Gene Expression database of Normal and Tumor tissues (GENT) as a resource for cancer research.
- To facilitate the identification of cancer outliers and genes over-expressed in specific patient subsets.
- To support cancer target discovery and validation through comprehensive gene expression data.
Main Methods:
- GENT is a web-accessible database containing gene expression patterns from diverse human cancer and normal tissues.
- Data comprises over 40,000 samples profiled on Affymetrix U133A or U133plus2 platforms from public resources.
- Includes gene expression patterns for nearly 1,000 human cancer cell lines, with data classified by clinical information.
Main Results:
- The large sample size of GENT (>24,300 for U133plus2, >16,400 for U133A) enhances the identification of cancer outliers.
- Provides gene expression patterns across various human tissues and cancer cell lines.
- Enables retrieval of gene expression data classified by detailed clinical information.
Conclusions:
- GENT's extensive sample size offers a significant advantage for identifying cancer outliers.
- The integrated cancer cell line expression data is valuable for in vitro target validation.
- GENT serves as a valuable resource for cancer researchers from target discovery to validation.
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