Expression Profiling of Cell Lines Expressing Regulated NF2 Transcripts

Abstract

Expression profiling is a powerful novel technique to examine changes in the expression of a large number of genes at the same time. Parallel analysis of gene expression reflects the changing view of signaling pathways towards signaling networks that have multiple and complex feedback and feed forward loops. Different phenotypic states of a cell can be translated into specific gene expression signatures. Expression profiling is not restricted to known genes, but changes in the expression of genes without known function can also be detected. As a complement to yeast two-hybrid studies we proposed using gene expression profiling to determine changes in gene expression as a function of NF2 expression in schwannoma cells. The strength of our approach is that we will not use tissues from patients, but will concentrate on cell lines in which NF2 expression can be controlled through the Tet/On system. We have now generated several cell lines that express NF2 in a regulated fashion. The parent lines are RT4 schwannoma cells and mouse embryonic fibroblasts. A time course for NF2 expression has been established. A total of four cell lines have been tested on microarrays to detect expression changes. Surprisingly, no changes common to expression of isoform 1 and 2 have been detected so far. We are currently in the process of repeating the experiments with slightly altered conditions to enhance the reliability of the detected expression changes.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2002
Accession Number
ADA411281

Entities

People

  • Stefan M. Pulst

Organizations

  • Cedars-Sinai Medical Center

Tags

DTIC Thesaurus Topics

  • Biomedical Research
  • Cell Line
  • Cells
  • Classification
  • Dna Microarrays
  • Electronic Mail
  • Feedback
  • Fibroblasts
  • Gene Expression
  • Genetic Phenomena
  • Genetic Variation
  • Mutations
  • Nervous System Diseases
  • Security

Fields of Study

  • Biology

Readers

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