Dataset Information

Ena-DATASET-CHARITE-28-09-2015-14:05:54:879-543 - samples

ABSTRACT: This dataset contains RNA sequencing raw data from four parental tumors that were used for classification of gene expression subtypes (Verhaak, Cancer Cell 2010) using ssGSEA.

PROVIDER: EGAD00001001627 | EGA |

REPOSITORIES: EGA

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Publications

Prognostic Relevance of Tumor Purity and Interaction with MGMT Methylation in Glioblastoma.

Schulze Heuling Eva E Knab Felix F Radke Josefine J Eskilsson Eskil E Martinez-Ledesma Emmanuel E Koch Arend A Czabanka Marcus M Dieterich Christoph C Verhaak Roel G RG Harms Christoph C Euskirchen Philipp P

Molecular cancer research : MCR 20170201 5

Promoter methylation status of O-6-methylguanine-DNA methyltransferase (MGMT), a DNA repair enzyme, is a critical biomarker in glioblastoma (GBM), as treatment decisions and clinical trial inclusion rely on its accurate assessment. However, interpretation of results is complicated by poor interassay reproducibility as well as a weak correlation between methylation status and expression levels of MGMT. This study systematically investigates the influence of tumor purity on tissue subjected to MGM ...[more]

PMID: 28148826

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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.

Dataset Information

Ena-DATASET-CHARITE-28-09-2015-14:05:54:879-543 - samples

Publications

Prognostic Relevance of Tumor Purity and Interaction with MGMT Methylation in Glioblastoma.

Similar Datasets

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