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Next-generation sequencing of translocation renal cell carcinoma reveals novel RNA splicing partners and frequent mutations of chromatin-remodeling genes.

ABSTRACT: PURPOSE:MITF/TFE translocation renal cell carcinoma (TRCC) is a rare subtype of kidney cancer. Its incidence and the genome-wide characterization of its genetic origin have not been fully elucidated. EXPERIMENTAL DESIGN:We performed RNA and exome sequencing on an exploratory set of TRCC (n = 7), and validated our findings using The Cancer Genome Atlas (TCGA) clear-cell RCC (ccRCC) dataset (n = 460). RESULTS:Using the TCGA dataset, we identified seven TRCC (1.5%) cases and determined their genomic profile. We discovered three novel partners of MITF/TFE (LUC7L3, KHSRP, and KHDRBS2) that are involved in RNA splicing. TRCC displayed a unique gene expression signature as compared with other RCC types, and showed activation of MITF, the transforming growth factor ?1 and the PI3K complex targets. Genes differentially spliced between TRCC and other RCC types were enriched for MITF and ID2 targets. Exome sequencing of TRCC revealed a distinct mutational spectrum as compared with ccRCC, with frequent mutations in chromatin-remodeling genes (six of eight cases, three of which were from the TCGA). In two cases, we identified mutations in INO80D, an ATP-dependent chromatin-remodeling gene, previously shown to control the amplitude of the S phase. Knockdown of INO80D decreased cell proliferation in a novel cell line bearing LUC7L3-TFE3 translocation. CONCLUSIONS:This genome-wide study defines the incidence of TRCC within a ccRCC-directed project and expands the genomic spectrum of TRCC by identifying novel MITF/TFE partners involved in RNA splicing and frequent mutations in chromatin-remodeling genes.

SUBMITTER: Malouf GG

PROVIDER: S-EPMC4167829 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Next-generation sequencing of translocation renal cell carcinoma reveals novel RNA splicing partners and frequent mutations of chromatin-remodeling genes.

Malouf Gabriel G GG Su Xiaoping X Yao Hui H Gao Jianjun J Xiong Liangwen L He Qiuming Q Compérat Eva E Couturier Jérôme J Molinié Vincent V Escudier Bernard B Camparo Philippe P Doss Denaha J DJ Thompson Erika J EJ Khayat David D Wood Christopher G CG Yu Willie W Teh Bin T BT Weinstein John J Tannir Nizar M NM

Clinical cancer research : an official journal of the American Association for Cancer Research 20140604 15

<h4>Purpose</h4>MITF/TFE translocation renal cell carcinoma (TRCC) is a rare subtype of kidney cancer. Its incidence and the genome-wide characterization of its genetic origin have not been fully elucidated.<h4>Experimental design</h4>We performed RNA and exome sequencing on an exploratory set of TRCC (n = 7), and validated our findings using The Cancer Genome Atlas (TCGA) clear-cell RCC (ccRCC) dataset (n = 460).<h4>Results</h4>Using the TCGA dataset, we identified seven TRCC (1.5%) cases and d ...[more]

PMID: 24899691

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Project description:Purpose: The goals of this study are using whole-exome and RNA sequencing technologies on 63 cases with TFE3-tRCC to explore the molecular characteristics of TFE3-tRCC and provide potential effective therapeutic strategies Methods: Total RNA was isolated from each sample (63 tumor samples and 14 paired adjacent normal samples) using Qiagen RNeasy formalin-fixed paraffin-embedded (FFPE) Kit (Qiagen, Hilden, Germany). Strand-specific RNA sequencing libraries were generated using the Whole RNA-seq Lib Prep kit for Illumina (ABclonal, China). Final libraries were sequenced at the Novogene Bioinformatics Institute (Beijing, China) on an Illumina Hiseq X10 platform by a 150bp paired-end reads. The raw RNA-sequencing reads were filtered by FastQC, Reads were aligned using STAR v2.7.0f with default parameters to the Ensembl human genome assembly GRCh37. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions: Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

Dataset Information

Next-generation sequencing of translocation renal cell carcinoma reveals novel RNA splicing partners and frequent mutations of chromatin-remodeling genes.

Publications

Next-generation sequencing of translocation renal cell carcinoma reveals novel RNA splicing partners and frequent mutations of chromatin-remodeling genes.

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