Application of next-generation sequencing to analysis of TGFβ/SMAD4 targets in ovarian cancer

Russell Bonneville, Kenneth Nephew, Victor X. Jin

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

Deregulation of the transforming growth factor-β (TGFβ) signaling pathway in epithelial ovarian cancer has been reported, but the precise mechanism underlying disrupted TGFβ signaling in the disease remains unclear. We performed chromatin immunoprecipitation followed by sequencing (ChIP-seq) to investigate genome-wide screening of TGFβ-induced SMAD4 binding in epithelial ovarian cancer. Following TGFβ stimulation of the A2780 epithelial ovarian cancer cell line, we identifi ed 2,362 SMAD4 binding loci and 318 differentially expressed SMAD4 target genes. Comprehensive examination of SMAD4-bound loci revealed four distinct binding patterns. TGFβ-stimulated SMAD4-bound loci were primarily classifi ed as either Stimulated Only or Shift, indicating that TGFβ stimulation alters SMAD4 binding patterns in epithelial ovarian cancer cells. Furthermore, based on gene regulatory network analysis, we determined that the TGFβ-induced, SMAD4- dependent regulatory network was strikingly different in ovarian cancer compared to normal cells. Importantly, the TGFβ/SMAD4 target genes identifi ed in the A2780 epithelial ovarian cancer cell line were predictive of patient survival, based on in silico mining of publically available patient databases. In conclusion, our data highlight the utility of next-generation sequencing technology to identify genome-wide SMAD4 target genes in epithelial ovarian cancer and link aberrant TGFβ/SMAD signaling to ovarian tumorigenesis. Furthermore, the identifi ed SMAD4 binding loci, combined with gene expression profi ling 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.

Original languageEnglish (US)
Title of host publicationNext Generation Sequencing in Cancer Research: Volume 1: Decoding the Cancer Genome
PublisherSpringer New York
Pages119-135
Number of pages17
ISBN (Print)9781461476450, 9781461476443
DOIs
StatePublished - Jan 1 2013

Fingerprint

Transforming Growth Factors
Ovarian Neoplasms
Computer Simulation
Genes
Genome
Cell Line
Translational Medical Research
Data Mining
Gene Regulatory Networks
Chromatin Immunoprecipitation
Ovarian epithelial cancer
Carcinogenesis
Databases
Technology
Gene Expression
Survival

Keywords

  • ChIP-seq
  • Epithelial ovarian cancer
  • Gene signatures
  • TGFβ/SMAD

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Bonneville, R., Nephew, K., & Jin, V. X. (2013). Application of next-generation sequencing to analysis of TGFβ/SMAD4 targets in ovarian cancer. In Next Generation Sequencing in Cancer Research: Volume 1: Decoding the Cancer Genome (pp. 119-135). Springer New York. https://doi.org/10.1007/978-1-4614-7645-0_6

Application of next-generation sequencing to analysis of TGFβ/SMAD4 targets in ovarian cancer. / Bonneville, Russell; Nephew, Kenneth; Jin, Victor X.

Next Generation Sequencing in Cancer Research: Volume 1: Decoding the Cancer Genome. Springer New York, 2013. p. 119-135.

Research output: Chapter in Book/Report/Conference proceedingChapter

Bonneville, R, Nephew, K & Jin, VX 2013, Application of next-generation sequencing to analysis of TGFβ/SMAD4 targets in ovarian cancer. in Next Generation Sequencing in Cancer Research: Volume 1: Decoding the Cancer Genome. Springer New York, pp. 119-135. https://doi.org/10.1007/978-1-4614-7645-0_6
Bonneville R, Nephew K, Jin VX. Application of next-generation sequencing to analysis of TGFβ/SMAD4 targets in ovarian cancer. In Next Generation Sequencing in Cancer Research: Volume 1: Decoding the Cancer Genome. Springer New York. 2013. p. 119-135 https://doi.org/10.1007/978-1-4614-7645-0_6
Bonneville, Russell ; Nephew, Kenneth ; Jin, Victor X. / Application of next-generation sequencing to analysis of TGFβ/SMAD4 targets in ovarian cancer. Next Generation Sequencing in Cancer Research: Volume 1: Decoding the Cancer Genome. Springer New York, 2013. pp. 119-135
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