Gene expression profiling in kidney cancer: Combining differential expression and chromosomal and pathway analyses

Kyle A. Furge, Eric J. Kort, Ximing J Yang, Walter M. Stadler, Hyung Kim, Bin Tean Teh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The high-throughput gene expression profiling by microarray analysis has enabled researchers to compare the relative expression levels of thousands of genes in diseases, including cancer. By identifying how these genes cluster in different carcinomas, these profiling techniques can improve the accuracy of classifying subtypes of tumors and their prognoses and could help determine which therapy is appropriate for each patient with cancer. These efforts aim to provide more effective personalized medicine. To reach this goal, the analysis of microarray data has also evolved and become more sophisticated and complex. Herein, using kidney cancer as an example, we demonstrate the use of microarray data for different bases of analysis, ie, direct differential expression, deduced chromosomal alteration, and pathways signature. We believe combining these will enhance the value of microarray studies and will better serve the goals we try to achieve using these data.

Original languageEnglish (US)
Pages (from-to)227-231
Number of pages5
JournalClinical Genitourinary Cancer
Volume5
Issue number3
DOIs
StatePublished - Jan 1 2006

Keywords

  • Clinical implications
  • Diagnosis
  • Microarray analysis
  • Prognosis

ASJC Scopus subject areas

  • Oncology
  • Urology

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