Skip to content

Advertisement

  • Poster Presentation
  • Open Access

Development of a rapid screening approach for candidate gene sets in cancer

  • 1,
  • 2,
  • 1,
  • 1,
  • 3,
  • 2,
  • 1 and
  • 1
Breast Cancer Research20057 (Suppl 2) :P4.20

https://doi.org/10.1186/bcr1150

  • Published:

Keywords

  • Melanoma
  • Melanoma Cell Line
  • Marker Gene Expression
  • Cancer Diagnostics
  • Line Point

Background

During the past decade, microarray-based gene expression analysis gave rise to a large number of candidate genes for the diagnostics and therapy of cancer. Bioinformatic approaches delivered gene sets, the expression patterns of which were predictive for certain cancer phenotypes. A synergy between these advances and the development of screening tools for a rapid and reliable screening of marker gene expression represents an important step towards an improved treatment of cancer.

Methods

For the semiquantitative expression screening of 11 candidate genes for drug resistance in melanoma, we combined multiplex RT-PCR (mRT-PCR) with subsequent microfluidic fragment analysis.

Results

The functionality of this approach was demonstrated by low interexperimental variations of amplicon quantities after endpoint analysis. Applied to RNA samples derived from drug-sensitive and drug-resistant melanoma cell lines, mRT-PCR delivered results qualitatively concordant with data obtained from northern blot analyses and array analyses. A preliminary screen of four additional melanoma cell lines points to IL1B, APOD, and CYR61 as interesting candidates for drug-resistance associated genes. First tests using an automated on-chip electrophoresis platform indicate the applicability of this approach for high-throughput measurements.

Conclusion

mRT-PCR combined with on-chip electrophoresis reveals a rapid and easy-to-handle method for candidate gene set evaluation from limited amounts of mRNA. Using gene sets indicative for different tumor phenotypes, this procedure may represent an alternative for future cancer diagnostics.

Authors’ Affiliations

(1)
Molecular Genome Analysis, Deutsches Krebsforschungszentrum, Heidelberg, Germany
(2)
Agilent Technologies, Waldbronn, Germany
(3)
Maxim Biotech, San Francisco, California, USA

Copyright

© BioMed Central 2005

Advertisement