Su, Xiaoping

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.

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.

Abstract Early-phase trials targeting the T-cell inhibitory molecule programmed cell death ligand 1 (PD-L1) have shown clinical efficacy in cancer. This study was undertaken to determine whether PD-L1 is overexpressed in triple-negative breast cancer (TNBC) and to investigate the loss of PTEN as a mechanism of PD-L1 regulation. The Cancer Genome Atlas (TCGA) RNA sequencing data showed significantly greater expression of the PD-L1 gene in TNBC (n = 120) compared with non-TNBC (n = 716; P < 0.001). Breast tumor tissue microarrays were evaluated for PD-L1 expression, which was present in 19% (20 of 105) of TNBC specimens. PD-L1+ tumors had greater CD8+ T-cell infiltrate than PD-L1− tumors (688 cells/mm vs. 263 cells/mm; P < 0.0001). To determine the effect of PTEN loss on PD-L1 expression, stable cell lines were generated using PTEN short hairpin RNA (shRNA). PTEN knockdown led to significantly higher cell-surface PD-L1 expression and PD-L1 transcripts, suggesting transcriptional regulation. Moreover, phosphoinositide 3-kinase (PI3K) pathway inhibition using the AKT inhibitor MK-2206 or rapamycin resulted in decreased PD-L1 expression, further linking PTEN and PI3K signaling to PD-L1 regulation. Coculture experiments were performed to determine the functional effect of altered PD-L1 expression. Increased PD-L1 cell surface expression by tumor cells induced by PTEN loss led to decreased T-cell proliferation and increased apoptosis. PD-L1 is expressed in 20% of TNBCs, suggesting PD-L1 as a therapeutic target in TNBCs. Because PTEN loss is one mechanism regulating PD-L1 expression, agents targeting the PI3K pathway may increase the antitumor adaptive immune responses. Cancer Immunol Res; 2(4); 361–70. ©2014 AACR.