Affiliations: 2nd Department of Medicine, Semmelweis University,
Budapest, Hungary | Joint Research Laboratory of the Hungarian Academy of
Sciences and the Semmelweis University for Pediatrics and Nephrology, 1st
Department of Paediatrics, Semmelweis University Budapest, Hungary | EGIS Pharmaceuticals Ltd. Medical Department,
Budapest, Hungary | Hungarian Academy of Science, Molecular Medicine
Research Unit, Budapest, Hungary
Note: [] Corresponding author: Orsolya Galamb, 2nd Department of Medicine
Semmelweis University, 1088 Budapest, Szentkirályi str. 46, Hungary.
Tel.: +36 1 266 09 26; Fax: +361 266 08 16; E-mail: [email protected]
Abstract: Gene expression analysis of colon biopsies using high-density
oligonucleotide microarrays can contribute to the understanding of local
pathophysiological alterations and to functional classification of adenoma (15
samples), colorectal carcinomas (CRC) (15) and inflammatory bowel diseases
(IBD) (14). Total RNA was extracted, amplified and biotinylated from frozen
colonic biopsies. Genome-wide gene expression profile was evaluated by
HGU133plus2 microarrays and verified by RT-PCR. We applied two independent
methods for data normalization and used PAM for feature selection. Leave
one-out stepwise discriminant analysis was performed. Top validated genes
included collagenIVα1, lipocalin-2, calumenin, aquaporin-8 genes in CRC;
CD44, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and
ATP-binding casette-A8 genes in adenoma; and lipocalin-2, ubiquitin D and
IFITM2 genes in IBD. Best differentiating markers between Ulcerative colitis
and Crohn's disease were cyclin-G2; tripartite motif-containing-31; TNFR
shedding aminopeptidase regulator-1 and AMICA. The discriminant analysis was
able to classify the samples in overall 96.2% using 7 discriminatory genes
(indoleamine-pyrrole-2,3-dioxygenase, ectodermal-neural cortex, TIMP3,
fucosyltransferase-8, collectin sub-family member 12, carboxypeptidase D, and
transglutaminase-2). Using routine biopsy samples we successfully performed
whole genomic microarray analysis to identify discriminative signatures. Our
results provide further insight into the pathophysiological background of
colonic diseases. The results set up data warehouse which can be mined
further.
