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PMID: 19393097 Published · epublish English Journal Article

PrognoScan: a new database for meta-analysis of the prognostic value of genes.

BMC medical genomics ·Vol. 2 ·2009-04-24 ·Pages 18

Mizuno H, Kitada K, Nakai K, Sarai A

Abstract

In cancer research, the association between a gene and clinical outcome suggests the underlying etiology of the disease and consequently can motivate further studies. The recent availability of published cancer microarray datasets with clinical annotation provides the opportunity for linking gene expression to prognosis. However, the data are not easy to access and analyze without an effective analysis platform. To take advantage of public resources in full, a database named "PrognoScan" has been developed. This is 1) a large collection of publicly available cancer microarray datasets with clinical annotation, as well as 2) a tool for assessing the biological relationship between gene expression and prognosis. PrognoScan employs the minimum P-value approach for grouping patients for survival analysis that finds the optimal cutpoint in continuous gene expression measurement without prior biological knowledge or assumption and, as a result, enables systematic meta-analysis of multiple datasets. PrognoScan provides a powerful platform for evaluating potential tumor markers and therapeutic targets and would accelerate cancer research. The database is publicly accessible at http://gibk21.bse.kyutech.ac.jp/PrognoScan/index.html.

Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Mizuno Hideaki
Pharmaceutical Technology Department, Kamakura Research Laboratories, Chugai Pharmaceutical Co Ltd, Kamakura, Kanagawa, Japan. [email protected]
Kitada Kunio
Nakai Kenta
Sarai Akinori
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Article Info
Journal
BMC medical genomics
Abbr.
BMC Med Genomics
ISSN
1755-8794
DOI
10.1186/1755-8794-2-18
Email
[email protected]
Published
2009-04-24
Epub
2009-00-24
Pages
18
Language
English
Region
England
NLM ID
101319628
PMCID
PMC2689870
External Links
PubMed source DOI: 10.1186/1755-8794-2-18 PMC Full Text View journal details
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