Genome-wide molecular characterization of mucinous colorectal adenocarcinoma using cDNA microarray analysis

Han Sang Kim, Seung Hui Kang, Chan Hee Park, Woo Ick Yang, Hei Cheul Jeung, Hyun Cheol Chung, Jae Kyung Roh, Joong Bae Ahn, Nam Kyu Kim, Byung Soh Min, Sun Young Rha

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)717-727
Number of pages11
JournalOncology reports
Issue number3
Publication statusPublished - 2011 Mar

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research


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