Dataset Information

Early loss of mitochondrial complex I and rewiring of glutathione metabolism in renal oncocytoma.

ABSTRACT: Renal oncocytomas are benign tumors characterized by a marked accumulation of mitochondria. We report a combined exome, transcriptome, and metabolome analysis of these tumors. Joint analysis of the nuclear and mitochondrial (mtDNA) genomes reveals loss-of-function mtDNA mutations occurring at high variant allele fractions, consistent with positive selection, in genes encoding complex I as the most frequent genetic events. A subset of these tumors also exhibits chromosome 1 loss and/or cyclin D1 overexpression, suggesting they follow complex I loss. Transcriptome data revealed that many pathways previously reported to be altered in renal oncocytoma were simply differentially expressed in the tumor's cell of origin, the distal nephron, compared with other nephron segments. Using a heuristic approach to account for cell-of-origin bias we uncovered strong expression alterations in the gamma-glutamyl cycle, including glutathione synthesis (increased GCLC) and glutathione degradation. Moreover, the most striking changes in metabolite profiling were elevations in oxidized and reduced glutathione as well as ?-glutamyl-cysteine and cysteinyl-glycine, dipeptide intermediates in glutathione biosynthesis, and recycling, respectively. Biosynthesis of glutathione appears adaptive as blockade of GCLC impairs viability in cells cultured with a complex I inhibitor. Our data suggest that loss-of-function mutations in complex I are a candidate driver event in renal oncocytoma that is followed by frequent loss of chromosome 1, cyclin D1 overexpression, and adaptive up-regulation of glutathione biosynthesis.

SUBMITTER: Gopal RK

PROVIDER: S-EPMC6142220 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Early loss of mitochondrial complex I and rewiring of glutathione metabolism in renal oncocytoma.

Gopal Raj K RK Calvo Sarah E SE Shih Angela R AR Chaves Frances L FL McGuone Declan D Mick Eran E Pierce Kerry A KA Li Yang Y Garofalo Andrea A Van Allen Eliezer M EM Clish Clary B CB Oliva Esther E Mootha Vamsi K VK

Proceedings of the National Academy of Sciences of the United States of America 20180618 27

Renal oncocytomas are benign tumors characterized by a marked accumulation of mitochondria. We report a combined exome, transcriptome, and metabolome analysis of these tumors. Joint analysis of the nuclear and mitochondrial (mtDNA) genomes reveals loss-of-function mtDNA mutations occurring at high variant allele fractions, consistent with positive selection, in genes encoding complex I as the most frequent genetic events. A subset of these tumors also exhibits chromosome 1 loss and/or cyclin D1 ...[more]

PMID: 29915083

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Project description:Background: While subtyping of the majority of malignant chromophobe renal cell carcinoma (cRCC) and benign renal oncocytoma (rO) is possible on morphology alone, additional histochemical, immunohistochemical or molecular investigations are required in a subset of cases. As currently used histochemical and immunohistological stains as well as genetic aberrations show considerable overlap in both tumors, additional techniques are required for differential diagnostics. Mass spectrometry imaging (MSI) combining the detection of multiple peptides with information about their localization in tissue may be a suitable technology to overcome this diagnostic challenge. Patients and Methods: Formalin-fixed paraffin embedded (FFPE) tissue specimens from cRCC (n=71) and rO (n=64) were analyzed by MSI. Data were classified by linear discriminant analysis (LDA), classification and regression trees (CART), k-nearest neighbors (KNN), support vector machine (SVM), and random forest (RF) algorithm with internal cross validation and visualized by t-distributed stochastic neighbor embedding (t-SNE). Most important variables for classification were identified and the classification algorithm was optimized. Results: Applying different machine learning algorithms on all m/z peaks, classification accuracy between cRCC and rO was 85%, 82%, 84%, 77% and 64% for RF, SVM, KNN, CART and LDA. Under the assumption that a reduction of m/z peaks would lead to improved classification accuracy, m/z peaks were ranked based on their variable importance. Reduction to six most important m/z peaks resulted in improved accuracy of 89%, 85%, 85% and 85% for RF, SVM, KNN, and LDA and remained at the level of 77% for CART. t-SNE showed clear separation of cRCC and rO after algorithm improvement. Conclusion: In summary, we acquired MSI data on FFPE tissue specimens of cRCC and rO, performed classification and detected most relevant biomarkers for the differential diagnosis of both diseases. MSI data might be a useful adjunct method in the differential diagnosis of cRCC and rO.

Dataset Information

Early loss of mitochondrial complex I and rewiring of glutathione metabolism in renal oncocytoma.

Publications

Early loss of mitochondrial complex I and rewiring of glutathione metabolism in renal oncocytoma.

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