| Literature DB >> 25456126 |
Anne Biton1, Isabelle Bernard-Pierrot2, Yinjun Lou2, Clémentine Krucker2, Elodie Chapeaublanc2, Carlota Rubio-Pérez3, Nuria López-Bigas4, Aurélie Kamoun2, Yann Neuzillet5, Pierre Gestraud6, Luca Grieco6, Sandra Rebouissou2, Aurélien de Reyniès7, Simone Benhamou8, Thierry Lebret9, Jennifer Southgate10, Emmanuel Barillot6, Yves Allory11, Andrei Zinovyev6, François Radvanyi12.
Abstract
Extracting relevant information from large-scale data offers unprecedented opportunities in cancerology. We applied independent component analysis (ICA) to bladder cancer transcriptome data sets and interpreted the components using gene enrichment analysis and tumor-associated molecular, clinicopathological, and processing information. We identified components associated with biological processes of tumor cells or the tumor microenvironment, and other components revealed technical biases. Applying ICA to nine cancer types identified cancer-shared and bladder-cancer-specific components. We characterized the luminal and basal-like subtypes of muscle-invasive bladder cancers according to the components identified. The study of the urothelial differentiation component, specific to the luminal subtypes, showed that a molecular urothelial differentiation program was maintained even in those luminal tumors that had lost morphological differentiation. Study of the genomic alterations associated with this component coupled with functional studies revealed a protumorigenic role for PPARG in luminal tumors. Our results support the inclusion of ICA in the exploitation of multiscale data sets.Entities:
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Year: 2014 PMID: 25456126 DOI: 10.1016/j.celrep.2014.10.035
Source DB: PubMed Journal: Cell Rep Impact factor: 9.423