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BITS2007 Meeting
BITS2007 Meeting

26-28 April 2007 Napoli, Italy

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Identifying networks of estrogen-responsive genes in breast cancer cells
Estrogens regulate a variety of physiological processes in human 
body. In the genomic
pathway, they act through transcription factors, ERs, which 
recognize either specific
nucleotide sequences, EREs, or other proteins already bound to 
DNA. The
transcriptional result (activation or repression) is determined by 
type of co-factor
complexes recruited locally, which in turn is gene- and cell 
type-specific. This
raises a key question: which is the syntax of these complexes 
recruitment? Or, with
the traditional words of biology, how are these genes regulated? An 
answer would be
of great interest in medicine, as endocrine therapies are widely 
employed in breast
cancer treatment. Indeed, anti-estrogenic therapies fail in 40% 
cases, likely due to
the cellular context which may convert the action of estrogenic 
antagonists into an
agonistic one. Expression data from microarray experiments show 
patterns which
suggest a selective co-regulation of the estrogen-responsive genes, 
e.g. repressed
vs. stimulated genes, and early vs. late responders. We collected and 
available genome-wide data in order to classify the myriad of 
genes functionally, a valuable first step towards an understanding of 
the molecular
syntax and hence a better molecular therapy.

We built a database of genes which are unambiguously 
up/down-regulate at different
kinetics (early, intermediate, late, or unknown) after estrogen 
stimulation, in
immortalized breast cancer cells and mainly considering micro-arrays 
expression data.
Each gene has been given a score which reflects number of 
independent experiments and
experimental assessment of ERE presence. The database, EREGLON, 
also contains
additional information such as 5'-flanking regions and number of ERE 
elements found
in their (-2000,+500) DNA regions with a computational tool 
(Lazzarato et al.
Bioinformatics, 2003). Afterwards, we used a combination of DNA 
sequence analyses in
order to assess features of down-regulated, as compared to 
up-regulated, genes'
5'-flanking regions of the different classes of genes stored in 
EREGLON. In addition
to the traditional approaches based both on alignment matrices and 
algorithms, we employed a method that combines phylogenetic 
conservation with motif
over-representation (Cora` et al. BCM Bioinformatics, 2004). 

We obtained two distinctive collections of overrepresented motifs, 
out of highly
conserved and aligned 15kb-upstream regions of those genes 
possessing a mouse
orthologue. The upstream regions of early up-regulated genes 
remarkably differ from
the ones of early down-regulated genes. We are extending our 
comparison to all gene
lists, including late vs. early for both regulation classes. A screening 
of the
(-2000,+500) DNA regions for TATA box presence with a hidden 
Markov model (Frith et
al., 2001), revealed that the percentage of TATA+ genes is 
noticeably higher within
the up-regulated set as compared to both down-regulated and 
random control ones.
Besides, we found 30% of the down regulated genes and 43% of 
up-regulated ones can be
classified as TATA+ promoters according to a published study, 
where, over 9,010 core
promoter sequences in human genome, the ones with TATA box are 
20.5% as compared to
13% in randomized sequences (Jin et al. BCM Bioinformatics, 2006). 
We are validating
our results with the RIKEN database. Our final goal is to infer 
combinations of factors to be tested in-vivo by biomolecular tools. 
Responsiveness to
estrogens and anti-estrogens in real tumors shall be included in 
EREGLON, for the
comparison between clinical and model data must provide a valuable 
insight into
breast cancer pathogenesis. The fully integrated database may 
become a publicly
accessible resource.
Id: 116
Place: Napoli, Italy
Centro Congressi "Federico II"
Via Partenope 36
Starting date:
-- not yet scheduled --   
Duration: 01h00'
Contribution type: Poster
Primary Authors: ALTOBELLI, Gioia (Department of Oncological Sciences, University of Turin; Complex Systems in Molecular Biology and Medicine, University of Turin)
Co-Authors: CASELLE, Michele (Department of Theoretical Physics, University of Turin; Complex Systems in Molecular Biology and Medicine, University of Turin)
DE BORTOLI, Michele (Department of Oncological Sciences, University of Turin; Complex Systems in Molecular Biology and Medicine, University of Turin)
Presenters: ALTOBELLI, Gioia
Included in session: Poster Session
Included in track: Gene expression and system biology | Last modified 08 July 2009 10:35 |

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