Meta-analysis of colorectal cancer gene expression profiling studies identifies consistently reported candidate biomarkers

Cancer Epidemiol Biomarkers Prev. 2008 Mar;17(3):543-52. doi: 10.1158/1055-9965.EPI-07-2615.


Purpose: Elucidation of candidate colorectal cancer biomarkers often begins by comparing the expression profiles of cancerous and normal tissue by performing gene expression profiling. Although many such studies have been done, the resulting lists of differentially expressed genes tend to be inconsistent with each other, suggesting that there are some false positives and false negatives. One solution is to take the intersection of the lists from independent studies. However, often times, the statistical significance of the observed intersection are not assessed.

Methods: Recently, we developed a meta-analysis method that ranked differentially expressed genes in thyroid cancer based on the intersection among studies, total sample sizes, average fold change, and direction of differential expression. We applied an improved version of the method to 25 independent colorectal cancer profiling studies that compared cancer versus normal, adenoma versus normal, and cancer versus adenoma to highlight genes that were consistently reported as differentially expressed at a statistically significant frequency.

Results: We observed that some genes were consistently reported as differentially expressed with a statistically significant frequency (P < 0.05) in cancer versus normal and adenoma versus normal comparisons but not in the cancer versus adenoma comparison.

Conclusion: Our meta-analysis method identified genes that were consistently reported as differentially expressed. A review of some of the candidates revealed genes described previously as having diagnostic and/or prognostic value as well as novel candidate biomarkers. The genes presented here will aid in the identification of highly sensitive and specific biomarkers in colorectal cancer.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / analysis*
  • Colorectal Neoplasms / genetics*
  • Gene Expression Profiling*
  • Gene Expression Regulation, Neoplastic
  • Humans


  • Biomarkers, Tumor