CanProVar: a Human Cancer Proteome Variation Database
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Identification and annotation of mutated genes or proteins involved in oncogenesis and tumor progression are crucial for both cancer biology and clinical applications. We have developed a human Cancer Proteome Variation Database (CanProVar) by integrating information on protein sequence variations from various public resources, with a focus on cancer-related variations (crVAR). We have also built a user-friendly interface for querying the database. The current version of CanProVar comprises 8,570 crVARs in 2,921 proteins derived from existing genome variation databases and recently published large-scale cancer genome resequencing studies. It also includes 41,541 non-cancer specific variations (ncsVARs) in 30,322 proteins derived from the dbSNP database. CanProVar provides quick access to known crVARs in protein sequences along with related cancer samples, relevant publications, data sources, and functional information such as Gene Ontology (GO) annotations for the proteins, protein domains in which the variation occurs, and protein interaction partners with crVARs. CanProVar also helps reveal functional characteristics of crVARs and proteins bearing these variations. Our analysis showed that crVARs were enriched in certain protein domains. We also showed that proteins bearing crVARs were more likely to interact with each other in the protein interaction network. CanProVar can be accessed from http://bioinfo.vanderbilt.edu/canprovar.
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Kuras M, Betancourt L, Hong R, Szadai L, Rodriguez J, Horvatovich P Cancers (Basel). 2025; 17(5).
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Integration of proteomics profiling data to facilitate discovery of cancer neoantigens: a survey.
Luo S, Peng H, Shi Y, Cai J, Zhang S, Shao N Brief Bioinform. 2025; 26(2).
PMID: 40052441 PMC: 11886573. DOI: 10.1093/bib/bbaf087.
Rao R, Gulfishan M, Kim M, Kashyap M Methods Mol Biol. 2024; 2859:211-237.
PMID: 39436604 DOI: 10.1007/978-1-0716-4152-1_12.
Cancer pharmacoinformatics: Databases and analytical tools.
Kamble P, Nagar P, Bhakhar K, Garg P, Sobhia M, Naidu S Funct Integr Genomics. 2024; 24(5):166.
PMID: 39294509 DOI: 10.1007/s10142-024-01445-5.
Genome interpretation using in silico predictors of variant impact.
Katsonis P, Wilhelm K, Williams A, Lichtarge O Hum Genet. 2022; 141(10):1549-1577.
PMID: 35488922 PMC: 9055222. DOI: 10.1007/s00439-022-02457-6.