Integrative Prediction of Gene Function and Platinum-Free Survival from Genomic and Epigenetic Features in Ovarian Cancer

  • Kazimierz O. Wrzeszczynski
  • Vinay Varadan
  • Sitharthan Kamalakaran
  • Douglas A. Levine
  • Nevenka Dimitrova
  • Robert Lucito
Part of the Methods in Molecular Biology book series (MIMB, volume 1049)


The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to discover genes critical to the development, progression, and therapeutic resistance of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatics analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We identify changes in DNA methylation and expression specifically for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic gene function from integrative analysis of three modalities: copy number variation, DNA methylation, and gene expression. Our method (1) calculates the extent of genomic and epigenetic alterations of defined tumor suppressor and oncogenic features for the functional prediction of significant ovarian cancer gene candidates and (2) identifies the functional activity or inactivity of known tumor suppressors and oncogenes in ovarian cancer. We applied our protocol on 42 primary serous ovarian cancer samples using MOMA-ROMA representational array assays. Additionally, we provide the basis for incorporating epigenetic profiles of ovarian tumors for the purposes of platinum-free survival prediction in the context of TCGA data.

Key words

Serous ovarian cancer Copy number variation DNA methylation Representational oligonucleotide microarray analysis Methylation detection representational oligonucleotide microarray analysis Platinum-free survival 


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Copyright information

© Springer Science+Business Media, New York 2013

Authors and Affiliations

  • Kazimierz O. Wrzeszczynski
    • 1
  • Vinay Varadan
    • 2
  • Sitharthan Kamalakaran
    • 2
  • Douglas A. Levine
    • 3
  • Nevenka Dimitrova
    • 2
  • Robert Lucito
    • 4
  1. 1.Bioinformatics and Genomics, Cold Spring Harbor LaboratoryCold Spring HarborUSA
  2. 2.Philips Research North AmericaBriarcliff ManorUSA
  3. 3.Department of Surgery, Gynecology ServiceMemorial Sloan-Kettering Cancer CenterNew YorkUSA
  4. 4.Hofstra North Shore-LIJ School of MedicineHofstra UniversityHempsteadUSA

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