| scimedweb@mail.com 2005-09-24, 2:11 pm |
| Molecular characterization of breast cancer cell lines by a low density
microarray.
by Fran=E7oise de Longueville (*), Marc Lacroix (*), Anna-Maria Barbuto,
Vincent Bertholet, Dominique Gallo, Denis Larsimont, Laurence Marcq,
Nathalie Zammatteo, Sophie Boffe, Guy Leclercq and Jose Remacle
(*): equal contributions
Institut Jules Bordet Institute, Bruxelles (Brussels) and Eppendorf
Array Technologies (EAT), Namur, Belgique (Belgium)
in International Journal of Oncology (2005) 27, 881-892
http://www.geocities.com/m.lacroix/ijo1.htm
We designed a low density microarray carrying 132 DNA capture sequences
highly specific for genes known to be differentially expressed among
breast tumors and BCC lines or associated with specific tumor
properties (hormone sensitivity, cell cycle alteration, proteolysis,
adhesion, etc). We analyzed gene expression in 11 BCC lines among which
6 had already been extensively studied (BT-474, Hs578T, MCF-7,
MDA-MB-231, MDA-MB-453, T-47D) and 5 were still poorly characterized
(Evsa-T, IBEP-1, IBEP-2, IBEP-3, KPL-1). Some data obtained were
verified or extended by real-time polymerase chain reaction,
Northern-blotting, Western blotting, immunohistochemistry and cell
growth studies. Clustering analysis of the low-density microarray data
allowed the sorting of BCC lines into two classes and supported a major
discriminatory role for ER-alpha, confirming data from previous
studies. A few genes that are highly and specifically expressed in one
cell line were identified such as MGB1 / SCGB2A2 (mammaglobin /
secretoglobin family 2A, member 2) in Evsa-T cells, and PIP / GCDFP15
(prolactin-inducible protein / gross cystic disease fluid protein-15 )
in MDA-MB-453 BCC, suggesting an apocrine origin for these latter
cells. Two BCC lines (IBEP-1 and IBEP-3) that had been previously
characterized as ER-alpha-negative, were classified by the low density
microarray among ER-alpha-positive lines (MCF-7, T-47D, IBEP-2, BT-474,
KPL-1) and were indeed confirmed as receptor-positive (at both mRNA and
protein levels) and hormone-responsive cells. In conclusion, our
results support the use of a low density microarray approach in cases
where the cost and exhaustiveness of high density microarrays may
constitute a drawback; for instance, in obtaining a rapid phenotype
evaluation in cell populations freshly isolated from breast tumors.
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