Genome Research · 2013 · 59 citations · 48 references
Life SciencesBioinformaticsOncologyCancer GeneticsMolecular OncologyProteomicsCancer ProteomicsProtein IdentificationProtein LocalizationSubcellular ProteomicsProtein Subcellular LocalizationProtein Subcellular Localization PredictionProteome-wide Localization AnalysisSubcellular Localization PredictionSubcellular Protein DistributionSubcellular Protein LocalizationSubcellular Proteome MappingWestern Blotting
Several studies have sought systematically to identify protein subcellular locations, but an even larger task is to map which of these proteins conditionally relocates in disease (the mislocalizome). Here, we report an integrative computational framework for mapping conditional location and mislocation of proteins on a proteome-wide scale, called a conditional location predictor (CoLP). Using CoLP, we mapped the locations of over 10,000 proteins in normal human brain and in glioma. The prediction showed 0.9 accuracy using 100 location tests of 20 randomly selected proteins. Of the 10,000 proteins, over 150 have a strong likelihood of mislocation under glioma, which is striking considering that few mislocation events have been identified in this disease previously. Using immunofluorescence and Western blotting in both primary cells and tissues, we successfully experimentally confirmed 15 mislocations. The most common type of mislocation occurs between the endoplasmic reticulum and the nucleus; for example, for RNF138, TLX3, and NFRKB. In particular, we found that the gene for the mislocating protein GFRA4 had a nonsynonymous point mutation in exon 2. Moreover, redirection of GFRA4 to its normal location, the plasma membrane, led to marked reductions in phospho-STAT3 and proliferation of glioma cells. This framework has the potential to track changes in protein location in many human diseases.
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