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April 9, 2006
New Frontiers in Self-Deception
One of the big uses for human gene chips has been the search for biomarkers: genes that are up- or down-regulated in disease states. The hope is that gene expression changes will be the early warning signs of diseases, and could also help refine their diagnosis beyond what can be done by traditional means.
Cancer is the obvioius place to start. As I've said in the past, there's no one disease by that name - just thousands of broadly similar diseases that we don't adequately distinguish between. We'll have to get down to the genetic and protein-expression levels to see the important differences. The process has already begun, as a look at the Iressa story shows.
Nothing good comes easy, though, and the field may have gotten ahead of itself. That's what a new paper in PNAS maintains, anyway. The authors, from the Weizmann Institute in Israel, point out that the various predictive gene lists proposed for different kinds of cancers have a lot of disquieting problems. For one thing, the lists for the same types of cancer don't seem to overlap very much. And in those cases, if you take the two and switch them (applying one group's list to the other group's patients) their success rates fall sharply.
The problems remain after all attempts to massage them away. Some possible reasons for them might be the different gene chips technologies used by different groups or different methods of analyzing the data, but these don't seem to be nearly enough to account for all the trouble. A bigger problem is the dependence of the results of these studies on the particular patients who were entered into them. There seems to be a major problem with unstable results based on the training set used to generate the lists.
This latest paper lays this out in mathematical terms, and the results aren't real pretty. The published gene lists were derived from dozens, or at most a couple of hundred patients. But in order to have an overlap of at least 50% between two lists of candidate marker genes, with a confidence of 95%, the authors calculate that the number of patients needs to be in the low thousands. The existing proposals are almost certainly completely inadequate. The search goes on, but it just got harder, and a lot more expensive.
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