ArticleAdvances in bioinformatics2012
Detecting cancer outlier genes with potential rearrangement using gene expression data and biological networks.
Article in Advances in bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 19 citations in OpenAlex.
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- Fatty acid-binding protein 5 predicts poor prognosis in patients with uveal melanoma.Oncology letters · 2020Article
- Clinical relevance of gene expression in localized and metastatic prostate cancer exemplified by FABP5.World journal of urology · 2020Article
- Detection and analysis of stable and flexible genes towards a genome signature framework in cancer.Bioinformation · 2019Article
- Altered epidermal fatty acid-binding protein expression in hepatocellular carcinoma predicts unfavorable outcomes.Cancer management and research · 2018Article
- Fatty acid-binding protein 5 function in hepatocellular carcinoma through induction of epithelial-mesenchymal transition.Cancer medicine · 2017Article
- Genetic ablation of the fatty acid-binding protein FABP5 suppresses HER2-induced mammary tumorigenesis.Cancer research · 2013Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene alterations are a major component of the landscape of tumor genomes. To assess the significance of these alterations in the development of prostate cancer, it is necessary to identify these alterations and analyze them from systems biology perspective. Here, we present a new method (EigFusion) for predicting outlier genes with potential gene rearrangement. EigFusion demonstrated excellent performance in identifying outlier genes with potential rearrangement by testing it to synthetic and real data to evaluate performance. EigFusion was able to identify previously unrecognized genes such as FABP5 and KCNH8 and confirmed their association with primary and metastatic prostate samples while confirmed the metastatic specificity for other genes such as PAH, TOP2A, and SPINK1. We performed protein network based approaches to analyze the network context of potential rearranged genes. Functional gene rearrangement Modules are constructed by integrating functional protein networks. Rearranged genes showed to be highly connected to well-known altered genes in cancer such as AR, RB1, MYC, and BRCA1. Finally, using clinical outcome data of prostate cancer patients, potential rearranged genes demonstrated significant association with prostate cancer specific death.
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Registered trials
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