[BioC] Comparing normal versus tumor specimens from different studies

[rcaloger]

Hi,

I am involved in the identification of new breast tumor associated 
antigens (TAA) suitable for molecular imaging and vaccination.

The main issue, for the kind of TAAs, is their relative low expression 
in normal tissue and high expression in tumor specimens. Although I have 
made some in house microarray experiments on tumor specimens I would 
like to take advantage of breast cancer studies and mammary gland normal 
tissue, both available in GEO.

 The question  I would like to address is the identification of genes 
that behave differently between normal and tumor specimens (low 
expression in normal samples and high in tumor specimens) but the main 
point is that the two experiments were performed in different labs, 
different samples, different preparation procedures, etc.

I read the paper from Gentleman et al. On the Synthesis of Microarray 
Experiments <http://www.bepress.com/bioconductor/paper8> (September 30, 
2005) which suggests the use of Random Error Model (REM) to integrate 
different studies.  However, my situation is different from the 
conventional data integration where two different studies, e.g. 
comprising different tumor histotypes, need to be integrated. In my case 
the comparison is made between normal and tumor samples coming from 
different studies. Therefore, it is not clear to me if  modeling normal 
and tumor samples using the REM approach proposed in Gentleman will be 
helpful also in the identification of genes that behave differently in 
normal and tumor specimens.

I will be very pleased to receive any comment and suggestion.
Raffaele


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Prof. Raffaele A. Calogero
Bioinformatics and Genomics Unit
Dipartimento di Scienze Cliniche e Biologiche
c/o Az. Ospedaliera S. Luigi
Regione Gonzole 10, Orbassano
10043 Torino
tel.   ++39 0116705420
Lab.   ++39 0116705408
Fax    ++39 0119038639
Mobile ++39 3333827080
email: raffaele.calogero at unito.it
www:   www.bioinformatica.unito.it