Distal cholangiocarcinoma (dCCA) is a rare type of CCA in Asia, even in Opisthorchis viverrini-prevalent Northeastern Thailand. The clinical ambiguity and imprecision of diagnosis surrounding this malignancy result in high mortality due often to advanced/metastatic disease on presentation. We aim to identify a prognostic factor that can improve the performance stratification and influence the outcome of dCCA patients after curative resection. A total of 79 patients who underwent curative-intended surgery for dCCA was enrolled. Possible risk factors for survival were analyzed with log-rank test, and independent factors with Cox regression model. dCCA patients were staged and classified according to the 8th edition the American Joint Committee on Cancer (AJCC) Staging Manual. Results were then compared with the revised classification employing the prognostic factor identified from multivariate analysis. Multivariate analysis revealed that growth pattern (p < 0.01) and distant metastasis (p = 0.012) were independent factors. Growth patterns comprise intraductal (ID), periductal infiltrating (PI), mass-forming (MF), and mixed types. When dCCA patients were grouped into those having good and poor outcomes (with and without ID components, respectively). The survival outcomes significantly differed among patients with and without ID components, which was better than with the 8th AJCC staging system in our cohort. Furthermore, Chi-square test showed that patterns without ID components (PI, MF, PI + MF) correlated with lymph node and distant metastasis. Therefore, classification of dCCA patients after curative-intended surgical resection based on growth pattern provides additional beneficial information for the prediction of survival in dCCA patients.

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AimThis study aims to improve the classification performance of the eighth American Joint Committee on Cancer (AJCC) staging system for perihilar cholangiocarcinoma (pCCA) by proposing the Khon Kaen University (KKU) staging system developed in cholangiocarcinoma-prevalent Northeast Thailand.MethodFour hundred eighty-eight patients with pCCA who underwent partial hepatectomy between 2002 and 2017 at the Srinagarind Hospital, Faculty of Medicine, Khon Kaen University, Thailand, were included. Overall survival (OS) related to clinicopathological features was analyzed using the Kaplan–Meier method. Logrank test was performed in univariate analysis to compare OS data of clinicopathological features to determine risk factors for poor survival. Significant features were further analyzed by multivariate analysis (Cox regression) to identify prognostic factors which were then employed to modify the eighth AJCC staging system.ResultsMultivariate analysis showed that growth pattern (HR = 4.67–19.72, p < 0.001), moderately and poorly differentiated histological grades (HR = 2.31–4.99, p < 0.05 and 0.001, respectively), lymph node metastasis N1 and N2 (HR = 1.37 and 2.18, p < 0.05 and 0.01, respectively), and distant metastasis (HR = 2.11, p < 0.001) were independent factors when compared to their respective reference groups. There was a clear separation of patients with pCCA into KKU stage: I [OS = 116 months (mo.)], II (OS = 46 mo.), IIIA (OS = 24 mo.), IIIB (11 mo.), IVA (OS = 7 mo.), and IVB (OS = 6 mo.).ConclusionThe new staging system was based on the incorporation of growth patterns to modify the eighth AJCC staging system. The classification performance demonstrated that the KKU staging system was able to classify and distinctly separate patients with pCCA into those with good and poor outcomes. It was also able to improve the stratification performance and discriminative ability of different stages of pCCA classification better than the eighth AJCC staging system. Hence, the KKU staging system is proposed as an alternative model to augment the accuracy of survival prognostication and treatment performance for patients with pCCA.

Background/Aim: Diabetes mellitus (DM) is an established risk for hepatocellular carcinoma (HCC), with unclarified mechanisms. This study investigated the effects of hyperglycemia on O-GlcNacylation in hepatocytes and its associations with hepatocarcinogenesis. Materials and Methods: Mouse and human HCC cell lines were used in an in vitro model of hyperglycemia. Western blotting was used to determine the effects of high glucose on O-GlcNacylation in HCC cells. Twenty 4-week-old C3H/HeNJcl mice were randomized into four groups: non-DM control, non-DM plus diethylnitrosamine (DEN), DM, and DM plus DEN. DM was induced using intraperitoneal injection of a single high dose of streptozotocin. DEN was used to induce HCC. All mice were euthanized at week 16 after DM induction, and the liver tissues were histologically examined using hematoxylin and eosin, and immunohistochemistry. Results: High glucose increased O-GlcNacylated proteins in mouse and human HCC cell lines compared with those cultured at normal glucose concentration. Mice with hyperglycemia or DEN treatment had increased O-GlcNacylated proteins in hepatocytes. No gross tumors were evident at the end of the experiment but hepatic morbidity was observed. Mice with hyperglycemia and DEN treatment showed greater histological morbidity in their livers, i.e. increased nuclear size, hepatocellular swelling and sinusoidal dilatation, compared with mice in the DM group or treated with DEN alone. Conclusion: Hyperglycemia increased O-GlcNAcylation in both in vitro and animal models. Increased O-GlcNAcylated proteins may be associated with hepatic histological morbidities which then promote HCC development in carcinogen-induced tumorigenesis.

Patients with distal cholangiocarcinoma (dCCA) generally have poor outcomes because of late presentation and diagnosis. Therefore, prognostic factors for predicting outcomes are essential to improve therapeutic strategies and quality of life. Tumor-infiltrating lymphocytes (TILs) have been reported as a prognostic predictor in several cancers. However, their role in dCCA is still unclear. This study aimed to evaluate the association of TILs with outcome in patients with dCCA. Fifty-two patients were evaluated for the percentage rate of TILs in their cancers, and a median TIL level was used to divide the patients into two groups. Survival, multivariate, and correlation analyses were performed to determine the prognostic factors. Results showed that a low TIL level was associated with poor survival. Multivariate analysis revealed TILs as an independent factor for poor outcome. Moreover, TILs were markedly correlated with growth patterns, and both were applied to classify patients with dCCA. Subgroups of TILs with growth pattern incorporation improved stratification performance in separating good from poor patient outcomes. This study suggested that TILs could be a prognostic factor for predicting survival and for clustering patients with dCCA to improve prognostication capability. This finding may be incorporated into a new staging system for stratifying dCCA in Thailand.