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Nucleic Acids Research Advance Access published online on November 9, 2009
Nucleic Acids Research, doi:10.1093/nar/gkp933
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© The Author(s) 2009. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Database Issue

dbDEPC: a database of Differentially Expressed Proteins in human Cancers

Hong Li1,2, Ying He1,2, Guohui Ding1, Chuan Wang1, Lu Xie2,* and Yixue Li1,2,*

1Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031 and 2Shanghai Center for Bioinformation Technology, Shanghai 200235, P. R. China

*To whom correspondence should be addressed. Tel: +86 21 61313672; Fax: +86 21 54065058; Email: xielu{at}scbit.org

Correspondence may also be addressed to Yixue Li. Tel: +86 21 61313672; Fax: +86 21 54065058; Email: yxli{at}sibs.ac.cn

Received August 13, 2009. Revised September 23, 2009. Accepted October 11, 2009.

Cancer-related investigations have long been in the limelight of biomedical research. Years of effort from scientists and doctors worldwide have generated large amounts of data at the genome, transcriptome, proteome and even metabolome level, and DNA and RNA cancer signature databases have been established. Here we present a database of differentially expressed proteins in human cancers (dbDEPC), with the goal of collecting curated cancer proteomics data, providing a resource for information on protein-level expression changes, and exploring protein profile differences among different cancers. dbDEPC currently contains 1803 proteins differentially expressed in 15 cancers, curated from 65 mass spectrometry (MS) experiments in peer-reviewed publications. In addition to MS experiments, low-throughput experiment data from the same literatures and cancer-associated genes from external databases were also integrated to provide some validation information. Furthermore, dbDEPC associates differential proteins with important structural variations in the human genome, such as copy number variations or single nucleotide polymorphisms, which might be helpful for explaining changes in protein expression at the DNA level. Data in dbDEPC can be queried by protein identifier, description or sequence; the retrieved protein entry provides the differential expression pattern seen in cancers, along with detailed annotations. dbDEPC is expected to be a reference database for cancer signatures at the protein level. This database is provided at http://dbdepc.biosino.org/index/.

The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.


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