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AuthorLambrou, George I.
AuthorVichos, Kleanthis
AuthorKoutsouris, Dimitrios
AuthorZaravinos, Apostolos
Available date2021-02-21T07:24:13Z
Publication Date2021-02-18
Publication NameApplied Sciences
Identifierhttp://dx.doi.org/10.3390/app11041785
CitationLambrou, G.I.; Vichos, K.; Koutsouris, D.; Zaravinos, A. Identification of Co-Deregulated Genes in Urinary Bladder Cancer Using High-Throughput Methodologies. Appl. Sci. 2021, 11, 1785. https://doi.org/10.3390/app11041785
URIhttp://hdl.handle.net/10576/17752
AbstractUrinary bladder cancer (UBC) is the second most common urogenital solid tumor and the eleventh in the rank among all types of solid tumors. Although several oncogenes and tumor suppressors are known to be implicated in the disease, the list of candidate prognostic markers has recently expanded, as a result of the power of new high-throughput methodologies. The prognosis and therapy of UBC have progressed greatly during the last years. However, a majority of the different tumor subtypes still relapses, manifesting poor prognosis. Here, we identified gene expression patterns being common across different histological phenotypes of UBC. Such an approach could be useful in the discovery of prognostic and therapeutic targets able to be applied in the majority of the tumor’s subtypes.
Languageen
PublisherMDPI
Subjecturinary bladder cancer
microarray
common gene expression
unsupervised machine learning algorithms
TitleIdentification of Co-Deregulated Genes in Urinary Bladder Cancer Using High-Throughput Methodologies
TypeArticle
Issue Number4
Volume Number11
ESSN2076-3417


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