Chip-Seq defined Genome-Wide map of TGFβ/SMAD4 targets: Implications with clinical outcome of ovarian cancer

Brian A. Kennedy, Daniel E. Deatherage, Fei Gu, Binhua Tang, Michael W Y Chan, Kenneth Nephew, Tim H M Huang, Victor X. Jin

Research output: Contribution to journalArticle

25 Citations (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 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. TGFβ stimulated SMAD4-bound loci were primarily classified as either Stimulated only (74%) or Shift (25%), 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 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 and link aberrant TGFβ/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.

Original languageEnglish
Article numbere22606
JournalPLoS One
Volume6
Issue number7
DOIs
StatePublished - 2011

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transforming growth factors
ovarian neoplasms
Transforming Growth Factors
Ovarian Neoplasms
Genes
Genome
genome
loci
Cells
Computer Simulation
genes
cell lines
Cell Line
Translational Medical Research
Data Mining
Deregulation
Gene Regulatory Networks
Chromatin Immunoprecipitation
Gene Expression Profiling
Electric network analysis

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Chip-Seq defined Genome-Wide map of TGFβ/SMAD4 targets : Implications with clinical outcome of ovarian cancer. / Kennedy, Brian A.; Deatherage, Daniel E.; Gu, Fei; Tang, Binhua; Chan, Michael W Y; Nephew, Kenneth; Huang, Tim H M; Jin, Victor X.

In: PLoS One, Vol. 6, No. 7, e22606, 2011.

Research output: Contribution to journalArticle

Kennedy, Brian A. ; Deatherage, Daniel E. ; Gu, Fei ; Tang, Binhua ; Chan, Michael W Y ; Nephew, Kenneth ; Huang, Tim H M ; Jin, Victor X. / Chip-Seq defined Genome-Wide map of TGFβ/SMAD4 targets : Implications with clinical outcome of ovarian cancer. In: PLoS One. 2011 ; Vol. 6, No. 7.
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