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Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and SMAD4 Y95 Mutation Transcriptomes

ABSTRACT: Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of Y95 phosphorylation on SMAD4-mediated transcription in response to TGF-b signals. The goals of this study are to compare transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis Methods: mRNA profiles of HaCaT parental and SMAD4 KO cells stably expressing wild-type SMAD4 (WT), Y95E or Y95F mutant, and GFP (as control) under with or without TGF-b were generated by deep sequencing, using Illumina HiSeq X Ten. qRT–PCR validation was performed using TaqMan and SYBR Green assays Conclusions: hierarchical clustering of the global gene expression profiles of TGF-β treated cells revealed that wild-type-SMAD4- and Y95F-mutant-rescued SMAD4-null cells were highly similar to the parental HaCaT cells, whereas GFP- and Y95E-mutant-rescued cells formed a separate cluster

ORGANISM(S): Homo sapiens

PROVIDER: GSE121188 | GEO | 2018/10/22

REPOSITORIES: GEO

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Project description:Deregulation of the transforming growth factor-? (TGF?) signaling pathway in epithelial ovarian cancer has been reported, but the precise mechanism underlying disrupted TGF? signaling in the disease remains unclear. We performed chromatin immunoprecipitation followed by sequencing (ChIP-seq) to investigate genome-wide screening of TGF?-induced SMAD4 binding in epithelial ovarian cancer. Following TGF? stimulation of the A2780 epithelial ovarian cancer cell line, we identified 2,362 SMAD4 binding loci and 318 differentially expressed SMAD4 target genes. Comprehensive examination of SMAD4-bound loci, revealed four distinct binding patterns: 1) Basal; 2) Shift; 3) Stimulated Only; 4) Unstimulated Only. SMAD4-bound loci were primarily classified as either Stimulated only (74%) or Shift (25%), indicating that TGF?-stimulation alters SMAD4 binding patterns in epithelial ovarian cancer cells compared to normal epithelial cells. Furthermore, based on gene regulatory network analysis, we determined that the TGF?-induced SMAD4-dependent regulatory network was strikingly different in ovarian cancer compared to normal cells. Importantly, the TGF?/SMAD4 target genes identified in the A2780 epithelial ovarian cancer cell line were predictive of patient survival, based on in silico mining of publically available patient data bases. In conclusion, our data highlight the utility of next generation sequencing technology to identify genome-wide SMAD4 target genes in epithelial ovarian cancer. The results link aberrant TGF?/SMAD signaling to ovarian tumorigenesis. Furthermore, the identified SMAD4 binding loci, combined with gene expression profiling and in silico data mining of patient cohorts, may provide a powerful approach to determine potential gene signatures with biological and future translational research in ovarian and other cancers. ChIP-Seq: 1 control lane. 4 unstimulated lanes 4 stimulated lanes Gene expression: 3 technical replicates each of SMAD4 stimulated and SMAD4 unstimulated cells

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Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and SMAD4 Y95 Mutation Transcriptomes

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