A novel predictive equation for potential diagnosis of cholangiocarcinoma

Cholangiocarcinoma (CCA) is the second most common-primary liver cancer. The difficulties in diagnosis limit successful treatment of CCA. At present, histological investigation is the standard diagnosis for CCA. However, there are some poor-defined tumor tissues which cannot be definitively diagnosed by general histopathology. As molecular signatures can define molecular phenotypes related to diagnosis, prognosis, or treatment outcome, and CCA is the second most common cancer found after hepatocellularcarcinoma (HCC), the aim of this study was to develop a predictive model which differentiates CCA from HCC and normal liver tissues. An in-house PCR array containing 176 putative CCA marker genes was tested with the training set tissues of 20 CCA and 10 HCC cases. The molecular signature of CCA revealed the prominent expression of genes involved in cell adhesion and cell movement, whereas HCC showed elevated expression of genes related to cell proliferation/differentiation and metabolisms. A total of 69 genes differentially expressed in CCA and HCC were optimized statistically to formulate a diagnostic equation which distinguished CCA cases from HCC cases. Finally, a four-gene diagnostic equation (CLDN4, HOXB7, TMSB4 and TTR) was formulated and then successfully validated using real-time PCR in an independent testing set of 68 CCA samples and 77 non-CCA controls. Discrimination analysis showed that a combination of these genes could be used as a diagnostic marker for CCA with better diagnostic parameters with high sensitivity and specificity than using a single gene marker or the usual serum markers (CA19-9 and CEA). This new combination marker may help physicians to identify CCA in liver tissues when the histopathology is uncertain.