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. 2010 Dec;89(3):227-35.
doi: 10.1016/j.yexmp.2010.08.007. Epub 2010 Sep 9.

Differential gene expression profiling of cultured neu-transformed versus spontaneously-transformed rat cholangiocytes and of corresponding cholangiocarcinomas

Affiliations

Differential gene expression profiling of cultured neu-transformed versus spontaneously-transformed rat cholangiocytes and of corresponding cholangiocarcinomas

Catherine I Dumur et al. Exp Mol Pathol. 2010 Dec.

Abstract

Previously, we described an orthotopic cholangiocarcinoma model based on bile duct inoculation of spontaneously-transformed low grade malignant rat BDE1 cholangiocytes (BDEsp cells) compared to high grade malignant erbB-2/neu- transformed BDE1 cholangiocytes (BDEneu cells) into the livers of syngeneic rats, which closely mimics clinical features of early versus advanced stages of the human cancer. We now used gene expression microarray together with quantitative real-time RT-PCR to profile genes differentially expressed in highly tumorigenic BDEneu cells and corresponding tumors compared to less aggressive tumorigenic BDEsp cells and tumors. Genes identified as being commonly overexpressed in parent BDEneu cells, tumors, and in a BDEneu tumor-derived cholangiocarcinoma cell line included Sox17, Krt20, Erbb2, and Sphk1 when respectively compared to BDEsp cells, tumors, and tumor-derived BDEsp cholangiocarcinoma cells. Muc1 was also prominently overexpressed in BDEneu cells and tumor-derived cholangiocarcinoma cells over that expressed in corresponding BDEsp cell lines. Periostin and tenascin-C, which were produced exclusively by cholangiocarcinoma-associated fibroblastic cells, were each significantly overexpressed in BDEneu tumors compared to BDEsp tumors. Interestingly, amphiregulin was representative of a gene found to be significantly underexpressed in vitro in BDEneu cells compared to BDEsp cells, but significantly overexpressed in BDEneu tumors compared to BDEsp tumors, and correlated with BDEneu cholangiocarcinoma progression in vivo. Our data support a unique animal model that recapitulates important molecular features of human cholangiocarcinoma progression, and may serve as a potentially powerful preclinical platform for identifying and rapidly testing novel molecular targeting strategies for cholangiocarcinoma therapy and/or prevention.

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Conflict of interest statement

Conflicts of Interest: None

Figures

Figure 1
Figure 1
Two-dimensional hierarchical clustering of samples and genes using Pearson’s (centered) correlation and average linkage, based on (A) 4,711 probe sets that were significantly different (q < 0.05) between BDEneu and BDEsp cultured cell lines, (B) 3,090 probe sets that were significantly different (q < 0.05) between BDEneu liver tumors and peritoneal metastases compared to non-metastatic BDEsp liver tumors, and (C) 4,711 probe sets that were significantly different between BDEneu and BDEsp cell lines used to cluster all of the samples: BDEsp cell line (blue box), BDEneu cell line (orange box), BDEsp tumors (pink box), and BDEneu tumors (brown box). The 1,497 common probe sets for cells in tumors are indicated by gray sidebars, whereas the discordant probe sets are indicated by black sidebars. Each of the colored rows in the individual heat maps show the relative expression for that specific gene in the separate specimen samples (columns). The relative gene expression levels are plotted according to the color scale at the bottom of each heat map, where red and green respectively indicate the relative extents of gene overexpression or underexpression compared to the median intensity across all samples.
Figure 2
Figure 2
Regression analysis of selectively analyzed genes, plotting their fold increases relative to expressed levels in BDEsp tumor against BDEneu liver tumor wet weight. Tumors of progressively increased wet weight were harvested from the livers of syngeneic rats at days 10, 15, and 25 after bile duct inoculation of the BDEneu cells. Pearson’s correlations to tumor wet weight are indicated for each analyzed gene. Note that correlation to tumor weight is not linear, but is best-fit by a logarithmic regression curve.
Figure 3
Figure 3
QRT-PCR validation of selected genes. (A) Significantly affected genes between BDEneu compared to BDEsp cell lines, and (B) between BDEneu compared to BDEsp tumors. Pearson’s correlations between QRT-PCR and microarray measurements are indicated for each gene. Asterisks: unpaired two-tailed t-test BDEneu versus BDEsp samples, * p-value < 0.05; ** p-value < 0.0005. When asterisks are not shown, no significant difference was observed. Error bars represent SD.
Figure 4
Figure 4
Bar chart representation of genes (Postn and Tnc) belonging to the extracellular matrix gene ontology classification whose expression is differentially altered in BDEneu liver tumors compared with BDEsp liver tumors. Fold changes for each BDE tumor type (BDEspT, BDEneuT at 10 days and at 25 days) are calculated against their respective parent BDE cell line (BDEspC and BDEneuC). Asterisks: unpaired two-tailed t-test BDEneu tumors versus BDEsp tumors, * p-value < 0.05; ** p-value < 0.005. Error bars represent SD. N.S.=not significant.
Figure 5
Figure 5
QRT-PCR analysis of differential gene expression of select genes in parent BDEneuC and tumor-derived BDEneu-TDE cell lines compared to parent BDEspC and tumor-derived BDEsp-TDE and BDEsp-TDF cell lines. Note that representative Western blot banding profiles for ErbB2, caveolin 1, and periostin conform with corresponding QRT-PCR data.

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