Final Report Summary - TICE (TRANSCRIPTOMICS IN CANCER EPIDEMIOLOGY)
So far the TICE project has given two important results. First, based on blood samples taken at time of diagnosis and from random controls we could show that the gene expression informed us about the disease status. In fact, it is possible to create a list of 50 genes that could act as a test for breast cancer on the same level as a single reader mammogram. A major obstacle for the use of such a test could be the effect of stress in breast cancer patient. Maybe the test is more of a stress test comparing gene expression patterns in stressed breast cancer patients with healthy women without stress. Methodological studies are ongoing to test this interesting hypothesis.
Secondly, the analyses of the prospective gene expression patterns have been even more demanding. The prospective design depends on exposure information and gene expression analyses from blood samples collected in the years before diagnosis. The hypothesis was that certain genes should show significant changes in breast cancer patient compared to the controls. Based on standard statistical procedures it has been difficult to find single genes that have significant changes in the years before diagnosis. With a shift of perspective to groups of genes expressing the same time related patterns, we could show that there are differences in the shape of the curve groups over time dependent on the extent of the and the setting of the diagnosis, screening versus clinical detection. The ability to discriminate between groups of cases will be further analyzed.
The TICE project has resulted in several methodological papers ranging from technical, statistical, design related and mathematical issues. Major challenges have been to change the standard way of analyses and realize that gene expression is neither exposures nor outcomes, but a dynamic intermediate marker of both carcinogenesis and exposures. The translational potential of the study was not foreseen.
The conclusion of the project is that the overall objectives were fulfilled. Gene expression can be analysed in the setting of epidemiology or as we named it – systems epidemiology.