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Leveraging the Epigenomic Landscape to identify Histology-Specific Master transcription factors and to functionally annotate risk loci in renal cell carcinoma

ABSTRACT: We performed histone (ChIP-seq, the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq), and RNA sequencing (RNA-seq) on 42 fresh frozen RCC tumor samples (24 ccRCC, 6 pRCC, 12 chRCC). We integrated 153 unique data sets to gain a holistic view of gene regulation in RCC subtypes and 50 candidate histology-specific master transcription factors (TF) to define RCC histologic subtypes. We also integrated RCC GWAS risk SNPs with H3K27ac ChIP-seq and ATAC-seq data and revealed that risk variants were significantly enriched in allelically imbalanced peaks

ORGANISM(S): Homo sapiens

PROVIDER: GSE188486 | GEO | 2022/11/01

REPOSITORIES: GEO

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Project description:We investigated the expression profiles of microRNAs (miRNA) in 26 renal cell carcinoma (RCC) FFPE tissues (3 chRCC, 5 papRCC and 18 ccRCC), 4 urothelial cell carcinomas of the upper urinary tract (UT-UCs) and 20 normal kidneys by using the miRCURY LNA™ 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 tumours compared to the normal kidney tissues. Overall, 126 miRNAs (29%) showed increased expression and 303 miRNAs (69.8%) had decreased expression in RCCs and UT-UCs vs. the normal kidneys. Specifically, 374, 420, 421 and 409 miRNAs were 90% consistently down-regulated in ccRCC, papRCC, chRCC and UT-UC, respectively. Unsupervised two-way hierarchical clustering (HCL) with Euclidian distance accurately discriminated between RCC and UT-UC. Apart from one chRCC sample that was clustered with ccRCCs, HCL also managed to successfully classify the 3 RCC subtypes among them. Furthermore, it showed that ccRCC is more closely related to papRCC and that both are distinct from chRCC or UT-UC. Ninety-four miRNAs were co-upregulated among ccRCC, papRCC and chRCC; and 11, 44 and 24 miRNAs were specifically up-regulated in each one of the three RCC subtypes (ccRCC, chRCC and papRCC), respectively. On the other hand, 222 miRNAs were co-down-regulated in the three RCC subtypes, whereas 16, 18 and 5 miRNAs were specifically down-regulated in ccRCC, chRCC and papRCC, respectively. When the DE miRNAs in each RCC subtype were combined with those in UT-UC, we identified 89 and 206 miRNAs, respectively, that were up- and down-regulated in all tumor types. miRNA profiling can distinguish between RCC and UT-UC as well as among distinct RCC subtypes. Our data validicate that miRNA expression tends to be down-regulated in RCC versus the normal kidney tissue.

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Leveraging the Epigenomic Landscape to identify Histology-Specific Master transcription factors and to functionally annotate risk loci in renal cell carcinoma

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