Hello everyone.
As I am far away from being an expert in biostatistics and get confused by it easily (I will do some training in the next year and hopefully get better at it), I would like to ask for advice.

The study setup is the following:

Data all is gene expression data generated by qPCR

We wanted to elude the effects of a compound on the carcinogenic process in rats, so there are two major groups: rats that recived the compound, and rats that recieve a control diet.
To induce carcinogenesis, rats recieved a hormone. We recieved tumors as well as tissue that was not a tumor yet despite recieving the hormone (of which we do not know if it is really normal, or in a pre malignent state).

So we have 2 major groups, with 3 minor groups in each groups (number of samples in brackets):

A) Control diet
  1. Normal tissue, no hormone treatment (19)
  2. Normal or pre malignet tissue, with hormone treatment (10)
  3. Tumor tissue, with hormone treatment (16)

B) Compound diet
  1. Normal tissue, no hormone treatment (9)
  2. Normal or pre malignet tissue, with hormone treatment (8)
  3. Tumor tissue, with hormone treatment (7)

So far, we are using 2-way-Anova grouped analysis in Prism 5 for statistical analysis, but we are not convinced that this is the right way to go since we want to compare a lot of things here:
1. Effect of the diet (with or without compound)
2. Effect of carcinogenesis (normal or Tumor)
3. Effect of the hormone (normal/pre malignent that recieved the hormone and tumors)

We are comaring 3 things here, so we should use 3-way anova, but 2 of the variables are somehow connected (for the hormone treatment we have 2 groups).
I read that for 3-way anova you need to have 3 independant variables.

I would be very gratefull for advice.
If I forgot to mention something, please let me know.

Best wishes and thank you very much!
Makenshi