[High throughput screening and analysis of prostate cancer-related genes through mining databases].

Abstract

BACKGROUND & OBJECTIVE:

Investigation of differentially expressed genes in prostate cancer tissues may help to understand the molecular mechanism of prostate cancer and provide diagnostic markers or new targets for therapy. The Cancer Genome Anatomy Project (CGAP) public database provides an unprecedented opportunity for cancer researchers to mine genes differentially expressed in cancer tissues by bioinformatic methods. This study was to explore the feasibility of incorporating the Internet-available Serial Analysis of Gene Expression (SAGE) and cDNA databases to find human prostate cancer-related genes.

METHODS:

SAGE digital gene expression displayer (DGED) and cDNA DGED were used to analyze differentially expressed (>5 folds) genes in malignant prostate tissues compared with normal prostate tissues. The SAGE tags were filtered by their confidence and our 3 criteria. To test the confidence of tags of virtual digital analysis for gene identification, the modified GLGI (generation of longer cDNA fragments from SAGE tags for gene identification) was used to get the cDNA 3' end downstream of 20 tags. Main functions of all candidate genes and their relations to prostate cancer were annotated.

RESULTS:

Fifty-three differentially expressed genes were screened out by SAGE DGED, 26 of them were up-regulated and 27 were down-regulated in prostate cancer; 28 differentially expressed genes were got by cDNA DGED, 15 of them were up-regulated and 13 were down-regulated in prostate cancer.

CONCLUSION:

Reasonable use of public databases by the Internet-available tools is a simple, effective approach to get cancer-related genes, and might provide useful clues for further investigation although the results require experimental validation.

• Authors: Gang Wu, Liang Peng, Feng-Shuo Jin, Qian-Sheng Li
• Journal: Ai zheng = Aizheng = Chinese journal of cancer (Ai Zheng) Vol. 25 Issue 5 Pg. 645-50 (May 2006) China
• PMID: 16687091 (Publication Type: English Abstract, Journal Article, Research Support, Non-U.S. Gov't)

Chemical References

• DNA, Complementary

Topics

• DNA, Complementary (analysis, genetics)
• Databases, Genetic
• Expressed Sequence Tags
• Gene Expression Profiling (methods)
• Gene Expression Regulation, Neoplastic
• Humans
• Male
• Prostatic Neoplasms (genetics)
• Software