Abstract

The Cancer Genome Atlas (TCGA) and other large-scale genomic data pipelines have been integral to the current understanding of the molecular events underlying renal cell carcinoma (RCC). These data networks have focused mostly on primary RCC, which often demonstrates indolent behavior. However, metastatic disease is the major cause of mortality associated with RCC and data sets examining metastatic tumors are sparse. Therefore, a more comprehensive analysis of gene expression and DNA methylome profiling of metastatic RCC in addition to primary RCC and normal kidney was performed. Integrative analysis of the methylome and transcriptome identified over 30 RCC-specific genes whose mRNA expression inversely correlated with promoter methylation, including several known targets of hypoxia inducible factors. Notably, genes encoding several metabolism-related proteins were identified as differentially regulated via methylation including hexokinase 2, aldolase C, stearoyl-CoA desaturase, and estrogen-related receptor-γ (ESRRG), which has a known role in the regulation of nuclear-encoded mitochondrial metabolism genes. Several gene expression changes could portend prognosis in the TCGA cohort. Mechanistically, ESRRG loss occurs via DNA methylation and histone repressive silencing mediated by the polycomb repressor complex 2. Restoration of ESRRG in RCC lines suppresses migratory and invasive phenotypes independently of its canonical role in mitochondrial metabolism. IMPLICATIONS: Collectively, these data provide significant insight into the biology of aggressive RCC and demonstrate a novel role for DNA methylation in the promotion of HIF signaling and invasive phenotypes in renal cancer.

Highlights

  • Insight into the biologic basis of renal cancer has greatly benefitted from large-scale data sets such as The Cancer Genome Atlas (TCGA)

  • We identified several genes silenced via promoter methylation and whose loss was correlated with worsened prognosis through subsequent analysis of the TCGA cohort

  • Principal component analysis (PCA) of transcriptomic data demonstrated that metastatic tumor samples clustered together (Supplementary Fig. S1)

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Summary

Introduction

Insight into the biologic basis of renal cancer has greatly benefitted from large-scale data sets such as The Cancer Genome Atlas (TCGA). These data have confirmed the high prevalence of tumor-initiating events such as alterations in the VHL tumor. Note: Supplementary data for this article are available at Molecular Cancer Research Online (http://mcr.aacrjournals.org/). Nam and D.S. Chandrashekar contributed to this article. Current address for C.B. Livi: Agilent Technologies, Santa Clara, CA

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