Adjuvant chemotherapy is required for cholangiocarcinoma (CCA) patients after surgical treatment. Gemcitabine and gemcitabine plus cisplatin are considered the appropriate regimen; however, the response spectrum to chemotherapy differs between patients. Thus, the present study aims to evaluate the response pattern of individual CCA patients by using an in vitro method, histoculture drug response assay (HDRA), to predict the chemosensitivity of individual patients in a prospective study. Moreover, we also investigate the expression of gemcitabine and cisplatin sensitivity factors in CCA tissues in the same cases. Based on the dose response curve, 1000 and 1500 μg/ml of gemcitabine were used as the testing concentrations. For cisplatin, concentrations of 20 and 25 μg/ml were selected for testing and for the combination regimen, 1000 μg/ml of gemcitabine and 20 μg/ml of cisplatin were chosen. The median %IR of each drug was measured as the cut-off to categorize the response pattern into response and non-response groups. In addition, we compared the effectiveness of the chemotherapy regimens between gemcitabine alone and gemcitabine plus cisplatin. The %IR of the combination of gemcitabine and cisplatin was significantly higher than gemcitabine alone. The relationship between the expression level of gemcitabine and cisplatin sensitive factors and the individual response pattern as well as clinicopathological data of CCA patients were analyzed. The results indicated that a low expression of the gemcitabine sensitive factor hENT-1 was significantly associated with the non-response group in vitro (p = 0.002). Moreover, the low expression of hENT-1 was also significantly associated with advanced stages CCA in the patients (p = 0.025). A low expression of MT and ERCC1 was significantly correlated with the response group in the in vitro experiments (p = 0.015 and p = 0.037 for MT and ERCC1, respectively). Therefore, HDRA may serve as an aid to selecting chemotherapy, and the expression of hNET-1, MT and ERCC1 may serve as biomarkers for predicting chemotherapy success.