[BioC] Comparing normal versus tumor specimens from different studies
raffaele.calogero at unito.it
Tue Jul 18 10:14:24 CEST 2006
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.
Prof. Raffaele A. Calogero
Bioinformatics and Genomics Unit
Dipartimento di Scienze Cliniche e Biologiche
c/o Az. Ospedaliera S. Luigi
Regione Gonzole 10, Orbassano
tel. ++39 0116705420
Lab. ++39 0116705408
Fax ++39 0119038639
Mobile ++39 3333827080
email: raffaele.calogero at unito.it
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