I have long used a data integration approach to obtain a global picture of eukaryotic cell-cycle regulation. The cell cycle is a popular research topic in part because of its importance for cancer research. I thus recently compared microarray expression data on the human cell cycle to genes with mutations that have been causally implicated in various forms of cancer.
From the Cancer Genome Project website, I downloaded a list of 353 human genes that are implicated in cancer. Using the identifier mapping file from STRING, I was able to automatically map 338 of these genes to the set of human genes from Ensembl that I used in earlier cell-cycle studies. 295 of the 338 genes were present on the microarrays used in the cell-cycle expression study by Whitfield et al. (2002). However, only 23 of these are among the 600 periodically expressed genes identified in the reanalysis by Jensen et al. (2006). The many numbers are illustrated in the diagram below:
By random chance, 295*600/12097 = 15 of the 295 genes would be expected to be periodically expressed, and the enrichment is thus only a bit over 1.5 fold. Although this enrichment is statistically significantly (P < 3%, Fisher’s exact test), the correlation is clearly not strong enough to allow prediction of novel cancer genes.
My step was to look at the evolutionary conservation of the 23 periodically expressed cancer genes. Only 12 of them belong to an orthologous group. Half of them do thus not appear to have orthologs in budding yeast, fission yeast, or Arabidopsis thaliana. Only three periodically expressed cancer genes have orthologs in all of these organisms. One of these genes is periodically expressed onlt in human, one in human and fission yeast, and one in all four organisms (a histone subunit).
In summary, it seems that one cannot say much about cancer based on cell-cycle mRNA expression data. This is perhaps not surprising considering that the transcriptional regulation does not seem to vary much between cancer cells and normal cells.