Dataset Information

The Molecular Taxonomy of Primary Prostate Cancer.

ABSTRACT: There is substantial heterogeneity among primary prostate cancers, evident in the spectrum of molecular abnormalities and its variable clinical course. As part of The Cancer Genome Atlas (TCGA), we present a comprehensive molecular analysis of 333 primary prostate carcinomas. Our results revealed a molecular taxonomy in which 74% of these tumors fell into one of seven subtypes defined by specific gene fusions (ERG, ETV1/4, and FLI1) or mutations (SPOP, FOXA1, and IDH1). Epigenetic profiles showed substantial heterogeneity, including an IDH1 mutant subset with a methylator phenotype. Androgen receptor (AR) activity varied widely and in a subtype-specific manner, with SPOP and FOXA1 mutant tumors having the highest levels of AR-induced transcripts. 25% of the prostate cancers had a presumed actionable lesion in the PI3K or MAPK signaling pathways, and DNA repair genes were inactivated in 19%. Our analysis reveals molecular heterogeneity among primary prostate cancers, as well as potentially actionable molecular defects.

SUBMITTER: Cancer Genome Atlas Research Network

PROVIDER: S-EPMC4695400 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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The Molecular Taxonomy of Primary Prostate Cancer.

Cell 20151101 4

There is substantial heterogeneity among primary prostate cancers, evident in the spectrum of molecular abnormalities and its variable clinical course. As part of The Cancer Genome Atlas (TCGA), we present a comprehensive molecular analysis of 333 primary prostate carcinomas. Our results revealed a molecular taxonomy in which 74% of these tumors fell into one of seven subtypes defined by specific gene fusions (ERG, ETV1/4, and FLI1) or mutations (SPOP, FOXA1, and IDH1). Epigenetic profiles showe ...[more]

PMID: 26544944

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Project description:Even though urothelial cancer (UC) is the fourth common tumor type among males, progress in treatment development has been deficient. Pathological assessment provides the urologists with only a broad classification, complicated by frequent disagreement among pathologist and the co-existence of different grading systems. Consequently, there is a great need for an objective, reproducible and biologically relevant classification system to make treatment more efficient. In the present investigation we present a molecular taxonomy for UC stratification based on integrated genomics. We used gene expression profiles from 308 UC to define seven molecular subtypes using step-by-step partitions and a bootstrap approach. Results were validated in three independent and publically available data sets. The subtypes differ significantly with respect to expression of cell cycle genes, of receptor tyrosine kinases particularity FGFR3, ERBB2 (HER2), and EGFR, of an FGFR3 associated gene expression signature, of cytokaratins, and of cell adhesion genes. The subtypes also differ significantly with respect to FGFR3, PIK3CA, and TP53 mutations. The expression of key proteins was validated by IHC on TMA. A further inspection indicated that the subtypes could be reduced to four major types of UC; Urobasal/D-driven, Genomically unstable/E-driven, Evolved urobasal, and Basal/SCC like, with characteristic and highly divergent molecular phenotypes. We show that the molecular subtypes cut across pathological classification and that tumors classified as one subtype maintain their characteristic molecular phenotype irrespective of pathological stage and grade. Available data from the Drugbank database and the Cochrane central registry of controlled trials indicate that susceptibility to specific drugs is more likely to be associated with the molecular stratification than with pathological classification. The presented molecular taxonomy stratifies UC into subtypes with distinct molecular phenotypes and biological properties. We anticipate that the molecular taxonomy will be a useful tool in future clinical investigations. Total RNA from fresh-frozen resection samples of 308 urothelial carcinomas was hybridized to the Illumina HumanHT-12 V3.0 expression beadchip arrays (Illumina Inc) at the SCIBLU Genomics Centre at Lund University Sweden (http://www.lth.se/sciblu). Supplementary files: GSE32894_non-normalized_308UCsamples.txt file = Raw intensity values for 308 UC (urothelial tumor) samples subjected only to background correction. GSE32894_reps_normals_preprocess*.txt files = Descriptive details and non-normalized data for technical replicates and normal samples that were used only in the preprocessing of the data. This dataset partly overlaps with Series GSE32549. Names of the overlapping sample names are the same, but the title of each sample is unique to the hybridization.

Dataset Information

The Molecular Taxonomy of Primary Prostate Cancer.

Publications

The Molecular Taxonomy of Primary Prostate Cancer.

Similar Datasets

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