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Dynamic reprogramming of DNA methylation in SETD2-deregulated renal cell carcinoma.

ABSTRACT: Clear cell renal cell carcinomas (ccRCCs) harbor frequent mutations in epigenetic modifiers including SETD2, the H3K36me3 writer. We profiled DNA methylation (5mC) across the genome in cell line-based models of SETD2 inactivation and SETD2 mutant primary tumors because 5mC has been linked to H3K36me3 and is therapeutically targetable. SETD2 depleted cell line models (long-term and acute) exhibited a DNA hypermethylation phenotype coinciding with ectopic gains in H3K36me3 centered across intergenic regions adjacent to low expressing genes, which became upregulated upon dysregulation of the epigenome. Poised enhancers of developmental genes were prominent hypermethylation targets. SETD2 mutant primary ccRCCs, papillary renal cell carcinomas, and lung adenocarcinomas all demonstrated a DNA hypermethylation phenotype that segregated tumors by SETD2 genotype and advanced grade. These findings collectively demonstrate that SETD2 mutations drive tumorigenesis by coordinated disruption of the epigenome and transcriptome,and they have important implications for future therapeutic strategies targeting chromatin regulator mutant tumors.

SUBMITTER: Tiedemann RL

PROVIDER: S-EPMC4811507 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Dynamic reprogramming of DNA methylation in SETD2-deregulated renal cell carcinoma.

Tiedemann Rochelle L RL Hlady Ryan A RA Hanavan Paul D PD Lake Douglas F DF Tibes Raoul R Lee Jeong-Heon JH Choi Jeong-Hyeon JH Ho Thai H TH Robertson Keith D KD

Oncotarget 20160101 2

Clear cell renal cell carcinomas (ccRCCs) harbor frequent mutations in epigenetic modifiers including SETD2, the H3K36me3 writer. We profiled DNA methylation (5mC) across the genome in cell line-based models of SETD2 inactivation and SETD2 mutant primary tumors because 5mC has been linked to H3K36me3 and is therapeutically targetable. SETD2 depleted cell line models (long-term and acute) exhibited a DNA hypermethylation phenotype coinciding with ectopic gains in H3K36me3 centered across intergen ...[more]

PMID: 26646321

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Project description:Inactivating mutations in the SETD2 gene, encoding for a nonredundant histone H3 methyltransferase and regulator of transcription, is a frequent molecular feature in clear cell renal cell carcinomas (ccRCC). SETD2 deficiency is associated with recurrence of ccRCC and bears low prognostic values. Targeting autophagy, a conserved catabolic process with critical functions in maintenance of cellular homeostasis and cell conservation under stress condition, is emerging as a potential therapeutic strategy to combat ccRCC. Epigenetics-based pathways are now appreciated as key components in the regulation of autophagy. However, whether loss of function in the SETD2 histone modifying enzyme occurring in ccRCC cells may impact on their ability to undergo autophagy remained to be explored. Here, we report that SETD2 deficiency in RCC cells is associated with the aberrant accumulation of both free ATG12 and of an additional ATG12-containing complex, distinct from the ATG5-ATG12 complex. Rescue of SETD2 functions in the SETD2 deficiency in RCC cells, or reduction of SETD2 expression level in RCC cells wild type for this enzyme, demonstrates that SETD2 deficiency in RCC is directly involved in the acquisition of these alterations in the autophagic process. Furthermore, we revealed that deficiency in SETD2, known regulator of alternative splicing, is associated with increased expression of a short ATG12 spliced isoform at the depend of the canonical long ATG12 isoform in RCC cells. The defect in the ATG12-dependent conjugation system was found to be associated with a decrease autophagic flux, in accord with the role for this ubiquitin-like protein conjugation system in autophagosome formation and expansion. Finally, we report that SETD2 and ATG12 gene expression levels are associated with favorable respective unfavorable prognosis in ccRCC patients. Collectively, our findings bring further argument for considering the SETD2 gene status of ccRCC tumors, when therapeutic interventions, such as targeting the autophagic process, are considered to combat these kidney cancers.

Project description:BackgroundClear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cancer and is associated with poor prognosis if metastasized. Up to one third of patients with local disease at diagnosis will develop metastasis after nephrectomy, and there is a need for new molecular markers to identify patients with high risk of tumor progression. In the present study, we performed genome-wide promoter DNA methylation analysis at diagnosis to identify DNA methylation profiles associated with risk for progress.MethodDiagnostic tissue samples from 115 ccRCC patients were analysed by Illumina HumanMethylation450K arrays and methylation status of 155,931 promoter associated CpGs were related to genetic aberrations, gene expression and clinicopathological parameters.ResultsThe ccRCC samples separated into two clusters (cluster A/B) based on genome-wide promoter methylation status. The samples in these clusters differed in tumor diameter (p < 0.001), TNM stage (p < 0.001), morphological grade (p < 0.001), and patients outcome (5 year cancer specific survival (pCSS5yr) p < 0.001 and cumulative incidence of progress (pCIP5yr) p < 0.001. An integrated genomic and epigenomic analysis in the ccRCCs, revealed significant correlations between the total number of genetic aberrations and total number of hypermethylated CpGs (R = 0.435, p < 0.001), and predicted mitotic age (R = 0.407, p < 0.001). We identified a promoter methylation classifier (PMC) panel consisting of 172 differently methylated CpGs accompanying progress of disease. Classifying non-metastatic patients using the PMC panel showed that PMC high tumors had a worse prognosis compared with the PMC low tumors (pCIP5yr 38% vs. 8%, p = 0.001), which was confirmed in non-metastatic ccRCCs in the publically available TCGA-KIRC dataset (pCIP5yr 39% vs. 16%, p < 0.001).ConclusionDNA methylation analysis at diagnosis in ccRCC has the potential to improve outcome-prediction in non-metastatic patients at diagnosis.

Project description:We investigated the expression profiles of microRNAs (miRNA) in 27 renal cell carcinoma (RCC) FFPE tissues (3 chRCC, 5 papRCC and 18 ccRCC), 4 upper urinary tract-urothelial cell carcinomas of the renal pelvis-ureter (UUT-UCCs) and 20 normal kidneys by using the miRCURY LNAM-bM-^DM-" microRNA Array, 6th gen (Exiqon, Woburn MA), containing capture probes that target all miRNAs for all species registered in the miRBASE version 16.0. Real-time PCR (qRT-PCR) using appropriate endogenous controls was performed in order to validate the microarray results of the 27 most differentially expressed (DE) miRNAs. We identified 434 miRNAs that were significantly deregulated in all kidney tumours compared to the normal tissues. A total of 126 miRNAs (29%) had increased expression while 303 (69.8%) had decreased expression in RCC. Out of the 434 DE miRNAs, we detected 94 co-up-regulated and 218 co-down-regulated microRNAs among chRCC, papRCC and ccRCC. Of these, 89 and 203 were co-up- and co-down-regulated between RCCs and UUT-UCCs, respectively. We detected 11, 44 and 24 up-regulated miRNAs, which were specific for ccRCC, chRCC and papRCC, respectively. Moreover, 19, 18 and 8 miRNAs were uniquelly down-regulated in ccRCC, chRCC and papRCC, respectively. We also detected 89 and 203 co-up- and co-down-regulated miRNAs between kidney cancer and UUT-UCCs. Five miRNAs were up-regulated specifically in renal tumours and 49 in UUT-UCCs, whereas 15 miRNAs were down-regulated specifically in renal tumours and 89 in UUT-UCCs, respectively. Our data validicate that expression of miRNAs tends to be down-regulated renal cell carcinomas compared with normal kidney. We used 18 ccRCC, 3 chRCC, 5 papRCC, 4 UUT-UCC, 1 undifferentiated carcinoma and 19 normal tissue samples for miRNA profiling. Total RNA (0.5 M-BM-5g) from each sample and reference was labeled with Hy3M-bM-^DM-" fluorescent label, using the miRCURY LNAM-bM-^DM-" microRNA Hi-Power Labeling Kit (Exiqon, Woburn MA). The Hy3M-bM-^DM-\"-labeled samples were hybridized to the miRCURY LNAM-bM-^DM-" microRNA Array, 6th gen (Exiqon, Woburn MA), using an Agilent hybridization SureHyb chamber and gasket slide kits. After hybridization, the microarray slides were scanned at 10 M-NM-<m using the High-Resolution Microarray Scanner (Agilent Technologies) and stored in an ozone free environment. The image analysis was carried out using the ImaGene 8.0 software (BioDiscovery, Inc., USA). Raw microarray data were filtered, background corrected and quantile normalizated. Normalized data were further extracted, pre-processed and sorted with Microsoft ExcelM-BM-.. MicroRNAs were considered to be significantly differentially expressed if they obtained a p-value<0.05 and a FDRM-bM-^IM-$0.05.

Dataset Information

Dynamic reprogramming of DNA methylation in SETD2-deregulated renal cell carcinoma.

Publications

Dynamic reprogramming of DNA methylation in SETD2-deregulated renal cell carcinoma.

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