Analysis of Genes Differentially Expressed in a Human Ovarian Cancer Model

Abstract

The objectives of this study are to: (1) analyze gene expression in a model of human ovarian carcinogenesis from a benign to a malignant phenotype in organotypic culture and (2) to confirm gene expression patterns by RNA analysis. Sufficient RNA for microarray analysis has been isolated and purified and we changed from cDNA arrays to oligonucleotide arrays. All RNAs from one cell line (96.9.18) have queried the Affymetrix human U133 A and B chips in triplicate. All RNAs from the second cell line (1.24.96) have queried the Affymetrix U133A plus chip in triplicate. Data mining is underway by the Bioinformatics Core at Wayne State University. Analysis of the queries of the U133 A and B chips indicate that 231 genes are differentially expressed between benign and malignant cells when data transformation is done by ANOVA at p-<0.1 with an expression level of >1.2-fold change. Quantitative real time polymerase chain reaction validated the expression levels of all genes tested. About 60% of the genes we have identified have previously been shown to be dysregulated in cancer and about 50% of those have been shown to be dysregulated in ovarian cancer thus validating our model.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2004
Accession Number
ADA428851

Entities

People

  • Wayne D. Lancaster

Organizations

  • Wayne State University

Tags

DTIC Thesaurus Topics

  • Cancer
  • Cell Line
  • Cells
  • Chain Reactions
  • Chemical Reactions
  • Data Analysis
  • Data Mining
  • Data Sets
  • Dna Microarrays
  • Gene Expression
  • Health Services
  • Information Science
  • Microarray Analysis
  • Neoplasms
  • Ovarian Cancer
  • Polymerase Chain Reaction
  • Schools

Fields of Study

  • Biology

Readers

  • Molecular and genetic basis of cancer.
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference