Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling by array of cis-Apc+/Delta716/Smad4+/- mouse liver vs C57BL/6N mouse liver

ABSTRACT: cis-Apc+/Delta716/Smad4+/- mice spontaneously develop multiple invasive intestinal carcinomas due to loss of heterozygosity and manifest symptoms associated with cancer cachexia within four months of age. To investigate the role of the liver in cachexia pathophysiology, we compared the transcriptomes of cachexia and control mouse livers. We isolated total RNA from livers of four C57BL/6N mice and four cis-Apc+/Delta716/Smad4+/- mice. Total RNA samples were then employed to perform microarray analysis (Agilent SurePrint G3 Mouse GE 8x60K Microarray).

INSTRUMENT(S): Agilent Microarray Scanner

ORGANISM(S): Mus musculus

SUBMITTER: Masahiro Aoki

PROVIDER: E-MTAB-11771 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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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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Transcription profiling by array of cis-Apc+/Delta716/Smad4+/- mouse liver vs C57BL/6N mouse liver

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