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J Proteome Res. 2017 Feb 3;16(2):421-432. doi: 10.1021/acs.jproteome.6b00505. Epub 2016 Dec 15.

CanProVar 2.0: An Updated Database of Human Cancer Proteome Variation.

Zhang M1,2, Wang B1, Xu J1, Wang X, Xie L2, Zhang B, Li Y1,2,3, Li J1,2.

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Department of Bioinformatics & Biostatistics, School of Life Science and Biotechnology, Shanghai Jiao Tong University , Shanghai 200240, China.
Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology , Shanghai 201203, China.
Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences , Shanghai 200031, China.


Identification and annotation of the mutations involved in oncogenesis and tumor progression are crucial for both cancer biology and clinical applications. Previously, we developed a public resource CanProVar, a human cancer proteome variation database for storing and querying single amino acid alterations in the human cancers. Since the publication of CanProVar, extensive cancer genomics efforts have revealed the enormous genomic complexity of various types of human cancers. Thus, there is an overwhelming need for comprehensive annotation of the genomic alterations at the protein level and making such knowledge easily accessible. Here, we describe CanProVar 2.0, a significantly expanded version of CanProVar, in which the amount of cancer-related variations and noncancer specific variations was increased by about 10-fold as compared to the previous version. To facilitate the interpretation of the variations, we added to the database functional data on potential impact of the cancer-related variations on 3D protein interaction and on the differential expression of the variant-bearing proteins between cancer and normal samples. The web interface allows for flexible queries based on gene or protein IDs, cancer types, chromosome locations, or pathways. An integrated protein sequence database containing variations that can be directly used for proteomics database searching can be downloaded.


cancer; database; proteome; variation

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