Dear colleagues:
I am currently analyzing a quite interesting dataset consisting of 40 Affymetrix HG-U133 Plus 2.0 arrays. The material hybridized to the chips comes from human biopsy samples taken at the beginning and after surgery (so it is a paired design) in patients who have been randomized to two different treatments before surgery. The design is as follows:
Total of 20 patients undergoing the same type of surgery randomized to receive either drug A or drug B; from each patient a biopsy was taken at the beginning a one at the end of surgery.
The factor I am interesting in is "drug", the factor heavily co-influencing gene expression is the time that elapsed between biopsy 1 and biopsy 2 in the same patient. Unfortunately and despite randomization, the group receiving drug A was "more morbid" than the group receiving drug B. As a consequence, the surgeon had more trouble with patients in group A (longer surgery times for the same procedure) than those in group B. We have collected a number of physiological parameters, which are all significant different between group A and group B, so there is an immediate effect seen between treatments, even after correction for the different surgery time.

The question I am trying to answer is whether or not the drugs induce a different transcriptional state in group A and B. Filtering out the drug effect proved to be quite difficult (the differences  -if any - may indeed be subtle but important for the outcome) as the surgery effect is overwhelming (due to the large inflammatory response).

I tried ANOVA models (paired design, i.e. 2 groups, before/after surgery), and I also analyzed my data using two-class time course problem (with two timepoints) in SAM 2.0. The gene list I obtain is characterized by quite large q-values. This may reflect the large variability one observes when using human tissue samples but obviously may also tell me there is no difference in the transcriptomic response between the two drugs.

While RT-PCR analysis ot the interesting transcripts is being done, I'd like to ask whether there is any other alternative method I can use to verify the list of "differentially regul. genes". Importantly, I need to be able to account for the individual surgery times (which unfortunately vary between 2 and 4 or more hours) as a confounding variable.

Thank you very much in advance for any idea.
Kind regards,
ELIANA

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Dr. Eliana Lucchinetti, PhD
University Hospital Zurich
Rämistrasse 100
CH-8091 Zurich (Switzerland)

phone: +41 44 255 3921
fax: +41 44 255 4409
e-mail: eliana.lucchinetti@usz.ch




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