Genome-wide molecular characterization of mucinous colorectal adenocarcinoma using cDNA microarray analysis.
Han Sang Kim ; Seung Hui Kang ; Sun Young Rha ; Byung Soh Min ; Nam Kyu Kim ; Joong Bae Ahn ; Jae Kyung Roh ; Hyun Cheol Chung ; Hei Cheul Jeung ; Woo Ick Yang ; Chan Hee Park
Oncology Reports, Vol.25(3) : 717~727, 2011
Mucinous colorectal carcinoma exhibits distinct clinicopathological features compared to non-mucinous colorectal carcinoma. Previous studies have discovered several molecular genetic features in mucinous colorectal carcinomas, but have limitations as they are confined to a small number of molecules. To understand the mucinous colorectal carcinoma system, this study was designed to identify genes that are differentially expressed in mucinous colorectal carcinoma compared to non-mucinous colorectal carcinoma using cDNA microarrays. cDNA microarray experiments were performed using human cDNA 17k chips with 25 mucinous and 27 non-mucinous cancer tissues. Differentially expressed genes (DEGs) were determined by Welch's t-test and more accurate classifiers were selected from the DEGs using the prediction analysis for microarrays (PAM) software package. Array results were validated using quantitative real-time RT-PCR. The identified gene set was functionally investigated through in silico analysis. Sixty-two DEGs were identified and the 50 highest ranking genes could be used to accurately classify mucinous and non-mucinous colorectal carcinomas. The identified gene set included up-regulated TFF1 (4-fold), AGR2 (3.3-fold), FSCN1 (2.2-fold), CD44 (1.5-fold) and down-regulated SLC26A3 (0.2-fold) in MC. TFF1, AGR2 and SLC26A3 were validated by quantitative real-time RT-PCR. The functions of these DEGs were related to tumorigenesis (14 genes), cell cycle progression (6 genes), invasion (2 genes), anti-apoptosis (7 genes), cell adhesion and proliferation (5 genes) and carbohydrate metabolism (3 genes). We suggest that MC has distinct molecular characteristics from NMC and therefore, that the expression signatures of DEGs may improve the understanding of molecular pathogenesis and clinical behaviors in MC.