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
AUTHORS (20)
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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CITATIONS (180)
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