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Tannir, Nizar

0000-0001-5559-8060

Mayo Clinic

The University of Texas MD Anderson Cancer Center

Citations 12

DNA methylation signature to define cell ontogeny of renal cell carcinomas.
Zhang, Jianping , Tamboli, Pheroze, Allanick, Frederick, Khayat, David, Wood, Christopher G. , Malouf, Gabriel G. , Su, Xiaoping , Ho, Thai H. , Lu, Yue , Raynal, Noël J.‐M. , Karam, Jose Antonio , Mouawad, Roger , Jelı́nek, Jaroslav , Tannir, Nizar

Journal of Clinical Oncology | February 24, 2017 | Volume: 34 | Issue: 2_suppl | Pages: 536-536

10.1200/jco.2016.34.2_suppl.536 Get It

536 Background: DNA methylation is a heritable covalent modification that is developmentally regulated and is critical in tissue-type definition. Although genotype-phenotype correlations have been described for different subtypes of renal cell carcinoma (RCC), it is unknown if DNA methylation profiles correlate with morphological or ontology based phenotypes. Here we test the hypothesis that DNA methylation signatures can discriminate between putative precursor cells in the nephron. Methods: We performed deep profiling of DNA methylation in diverse histopathological RCC subtypes and validated DNA methylation and transcriptome signatures in The Cancer Genome Atlas Clear Cell and Chromophobe Renal Cell Carcinoma Datasets. Results: Our data provide the first mapping of methylome epi-signature and indicates that RCC subtypes can be grouped into two major epi-clusters: C1 which encompasses clear cell RCC, papillary RCC, mucinous and spindle cell carcinomas and translocation RCC; C2 which comprises oncocytoma and chromophobe RCC. Interestingly, C1 epi-cluster displayed three fold more hypermethylation as compared to C2 epi-cluster. Of note, differentially methylated regions between C1 and C2 epi-clusters occur in gene bodies and intergenic regions, instead of gene promoters. Transcriptome analysis of C1 epi-cluster suggests a functional convergence on Polycomb targets, whereas C2 epi-cluster displays DNA methylation defects. Furthermore, we find that our epigenetic ontogeny signature is associated with worse outcomes of patients with clear-cell RCC. Conclusions: Taken together, our data defines the epi-clusters that can discriminate between distinct RCC subtypes and for the first time, to our knowledge, define the epigenetic basis for proximal versus distal tubule derived kidney tumors.
DNA Methylation Signature Reveals Cell Ontogeny of Renal Cell Carcinomas
Malouf, Gabriel G. , Zhang, Jianping , Creighton, Chad J. , Ho, Thai H. , Lu, Yue , Raynal, Noël J.‐M. , Tamboli, Pheroze, Allanick, Frederick, Spano, Jean-Philippe, Khayat, David, Wood, Christopher G. , Su, Xiaoping , Karam, Jose Antonio , Mouawad, Roger , Jelı́nek, Jaroslav , Tannir, Nizar , Ho, Thai

Clinical Cancer Research | June 2, 2016 | Volume: 22 | Issue: 24 | Pages: 6236-6246

10.1158/1078-0432.ccr-15-1217 Get It

Abstract Purpose: DNA methylation is a heritable covalent modification that is developmentally regulated and is critical in tissue-type definition. Although genotype–phenotype correlations have been described for different subtypes of renal cell carcinoma (RCC), it is unknown if DNA methylation profiles correlate with morphological or ontology based phenotypes. Here, we test the hypothesis that DNA methylation signatures can discriminate between putative precursor cells in the nephron. Experimental Designs: We performed deep profiling of DNA methylation and transcriptome in diverse histopathological RCC subtypes and validated DNA methylation in an independent dataset as well as in The Cancer Genome Atlas Clear Cell and Chromophobe Renal Cell Carcinoma Datasets. Results: Our data provide the first mapping of methylome epi-signature and indicate that RCC subtypes can be grouped into two major epi-clusters: C1, which encompasses clear-cell RCC, papillary RCC, mucinous and spindle cell carcinomas and translocation RCC; C2, which comprises oncocytoma and chromophobe RCC. Interestingly, C1 epi-cluster displayed 3-fold more hypermethylation as compared with C2 epi-cluster. Of note, differentially methylated regions between C1 and C2 epi-clusters occur in gene bodies and intergenic regions, instead of gene promoters. Transcriptome analysis of C1 epi-cluster suggests a functional convergence on Polycomb targets, whereas C2 epi-cluster displays DNA methylation defects. Furthermore, we find that our epigenetic ontogeny signature is associated with worse outcomes of patients with clear-cell RCC. Conclusions: Our data define the epi-clusters that can discriminate between distinct RCC subtypes and for the first time define the epigenetic basis for proximal versus distal tubule derived kidney tumors. Clin Cancer Res; 22(24); 6236–46. ©2016 AACR.