Dataset Information

Molecular Genetic Classification of clear-cell Renal Cell Carcinoma (ccRCC) based on the Gene Expression Profiling of Tumors and Tumorgrafts deficient for BAP1 or PBRM1

ABSTRACT: Renal cell carcinoma (RCC) exhibits some unusual features and genes commonly mutated in cancer are rarely mutated in clear-cell RCC (ccRCC), the most common type. The most prevalent genetic alteration in ccRCC is the inactivation of the tumor suppressor gene VHL. Using whole-genome and exome sequencing we discovered BAP1 as a novel tumor suppressor in ccRCC that shows little overlap with mutations in PBRM1, another recent tumor suppressor. Whereas VHL was mutated in 81% of the patients (142/176), PBRM1 was lost in 58% and BAP1 in 15% of the patients analyzed. All these tumor suppressor genes are located in chromosome 3p, which is partially or completely lost in most ccRCC patients. However, BAP1 but not PBRM1 loss was associated with higher Fuhrman grade and, therefore, poorer outcome. Xenograft tumors (tumorgrafts) implanted orthotopically in mice exhibited similar gene expression profiling to corresponding primary tumors. Gene expression profiling of tumors and tumorgrafts displayed different signatures for BAP1- and PBRM1-deficient samples. Thus, after inactivation of VHL, the acquisition of a mutation in BAP1 or PBRM1 defines a different program that might alter the fate of the patient. Our results establish the foundation for an integrated pathological and molecular genetic classification of about 70% of ccRCC patients, paving the way for subtype-specific treatments exploiting genetic vulnerabilities.

ORGANISM(S): Homo sapiens

PROVIDER: GSE36895 | GEO | 2012/06/10

SECONDARY ACCESSION(S): PRJNA157021

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Patients with loss-of-function mutations of the von Hippel Lindau gene (“VHL-patients”) often develop clear cell renal cell carcinoma (ccRCC). Using archived, formalin-fixed, paraffin-embedded (FFPE) samples and a cohort of eight cases, we sought to determine global proteome alterations that distinguish ccRCC tissue from adjacent, non-malignant kidney tissue in VHL-patients. Our quantitative proteomic analysis clearly discriminated tumor and non-malignant tissue, yielding comparable proteome profiles for the eight ccRCC cases. Limma statistics was used to identify significantly dysregulated proteins in ccRCC. Functional classification of these proteins highlighted a decrease in proteins involved in the tricarboxylic acid cycle and an increase in proteins involved in glycolysis. This profile possibly represents a proteomic fingerprint of the “Warburg effect”, which is a molecular hallmark of ccRCC. Furthermore, we observed an increase in proteins involved in extracellular matrix organization. Of particular note were opposing alterations of Xaa-Pro Aminopeptidases-1 and -2 (XPNPEP-1 and -2): a strong decrease of XPNPEP-2 in ccRCC was accompanied by a strong increase of the related protease XPNPEP-1. In both cases, we corroborated the proteomic results by immunohistochemical analysis of ccRCC and adjacent, non-malignant kidney tissue of VHL patients. To functionally investigate the role of XPNPEP-1 in ccRCC, we performed small-hairpin RNA mediated XPNPEP-1 expression silencing in 786-O ccRCC cells harboring a mutated VHL gene. We found that XPNPEP-1 expression suppresses cellular proliferation and migration. These results suggest that XPNPEP-1 is rather an anti-target in VHL-driven ccRCC. Generally, we present one of the first proteomic profiling studies of ccRCC in VHL patients, comparing normal and tumor tissue, which are both deficient for the VHL tumor suppressor. Methodologically, our work further validates the robustness of using FFPE material for quantitative proteomics.

Dataset Information

Molecular Genetic Classification of clear-cell Renal Cell Carcinoma (ccRCC) based on the Gene Expression Profiling of Tumors and Tumorgrafts deficient for BAP1 or PBRM1

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets