Gene alterations are a major component of the landscape of tumor genomes. To assess the significance of these alterations\r\nin the development of prostate cancer, it is necessary to identify these alterations and analyze them from systems biology\r\nperspective. Here, we present a new method (EigFusion) for predicting outlier genes with potential gene rearrangement. EigFusion\r\ndemonstrated excellent performance in identifying outlier genes with potential rearrangement by testing it to synthetic and real\r\ndata to evaluate performance. EigFusion was able to identify previously unrecognized genes such as FABP5 and KCNH8 and\r\nconfirmed their association with primary and metastatic prostate samples while confirmed the metastatic specificity for other\r\ngenes such as PAH, TOP2A, and SPINK1. We performed protein network based approaches to analyze the network context of\r\npotential rearranged genes. Functional gene rearrangement Modules are constructed by integrating functional protein networks.\r\nRearranged genes showed to be highly connected to well-known altered genes in cancer such as AR, RB1, MYC, and BRCA1.\r\nFinally, using clinical outcome data of prostate cancer patients, potential rearranged genes demonstrated significant association\r\nwith prostate cancer specific death.
Loading....