Independent Component Analysis Uncovers the Landscape of the Bladder Tumor Transcriptome and Reveals Insights into Luminal and Basal Subtypes

570 QH301-705.5 Carcinogenesis Cell Survival [SDV]Life Sciences [q-bio] 610 03 medical and health sciences Databases, Genetic Humans Neoplasm Invasiveness Biology (General) Càncer -- Aspectes genètics -- Informàtica 0303 health sciences Gene Expression Profiling Muscles Reproducibility of Results Cell Differentiation Càncer -- Aspectes moleculars -- Informàtica 3. Good health [SDV] Life Sciences [q-bio] Gene Expression Regulation, Neoplastic PPAR gamma Urinary Bladder Neoplasms Disease Progression Urothelium Transcriptome Algorithms Genes, Neoplasm
DOI: 10.1016/j.celrep.2014.10.035 Publication Date: 2014-11-16T20:33:52Z
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.
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