ObjectiveTo study the abnormal biological pathways of intrahepatic cholangiocarcinoma (ICC) from the transcriptomics level and identify genes associated with the prognosis of ICC.MethodsThe differentially expressed genes were screened by t test and fold change method, then KEGG functional enrichment analysis was performed on related genes. The STRING database was applied to construct protein interaction network and find the hub nodes of the network by calculating the degree, betweenness, and closeness of each node. Kaplan-Meier survival analysis was performed using log-rank test to identify prognostic genes related to ICC.ResultsAll of 1 134 differentially expressed genes were overlapped in 3 datasets, which were mainly involved in 15 pathways, including DNA replication, cell cycle, drug metabolism, RNA transport, etc. signaling pathways and amino acid synthesis. According to protein interaction network analysis, TAF1, GRB2, E2F4, HNF4A, MYC, and TP53 genes were hub nodes. As GRB2 and TP53 genes were also the death related genes of ICC, it was found that patients with lower GRB2 gene expression had a better overall survival than those with higher GRB2 gene expression (P=0.040 9), while patients with lower TP53 had a worse overall survival than those with higher TP53 gene expression (P=0.027 3), which were also verified in the TCGA database.ConclusionsThe abnormal cell metabolism is notably related to the tumorigenesis of ICC. TAF1, GRB2, E2F4, HNF4A, MYC, and TP53 are the key genes in the carcinogenesis and progression of ICC. Expressions of GRB2 and TP53 genes are associated with the prognosis of ICC.
ObjectiveTo understand the current progress in the application of artificial intelligence (AI) technology in intrahepatic cholangiocarcinoma (ICC). MethodA systematic review was conducted on recent domestic and international research literature regarding AI applications in ICC, with a focus on radiomics and deep learning (DL). ResultsICC is a critical subtype of primary liver cancer characterized by high malignancy and mortality. We systematically reviewed the current status and prospects of AI-based approaches in preoperative diagnosis, treatment guidance, and prognosis prediction for ICC. ConclusionsDespite the progress made by AI in the field of ICC, it still faces challenges such as model accuracy, data integration, and clinical application. With technological advancements and deeper research, AI is expected to play a more significant role in ICC prevention and treatment. Interdisciplinary collaboration will also drive sustainable progress in this domain.
ObjectiveTo explore the clinical, imaging, and pathological features of patients with synchronous double primary hepatocellular carcinoma and intrahepatic cholangiocarcinoma (sdpHCC-ICC), to enhance our understanding of the disease and reduce the rate of misdiagnosis and missed diagnosis.MethodsThe clinical, imaging, and pathological data of patients who were histologically confirmed as sdpHCC-ICC in West China Hospital of Sichuan University between January 1st 2014 and December 31st 2018 were studied retrospectively.ResultsA total of 11 patients with sdpHCC-ICC were screened for the study, of which 10 were male and 1 was female. The median age of patients was 55.6 years (ranged from 47 to 73 years). Eight patients were chronically infected with hepatitis B virus. Both increased alpha-fetoprotein and carbohydrate antigen 19-9 were observed in 8 patients. Contrast enhanced CT was performed in 8 cases, color doppler ultrasound in 4 cases, enhanced MRI in 3 cases, and contrast-enhanced ultrasound in 1 case. Among them, one solitary lesion was found in 2 patients, and two or more lesions were observed in 9 patients. Most of the patients had typical imaging performance of hepatocellular carcinoma (HCC): 8 patients showed strong enhancement of HCC during the hepatic arterial phase and progressive hyper-attenuation on venous and delayed phases, 1 patient showed peripheral rim enhancement in the arterial phase of intrahepatic cholangiocarcinoma (ICC) in another lesion could be observed at the same time. None of the 11 patients with sdpHCC-ICC was diagnosed accurately before operation. All patients underwent surgical treatment. HCC lesions were distributed in all parts of the liver, while ICC lesions were located in the right lobe of the liver in 10 cases. The median diameter of HCC and ICC was 3.5 cm and 2.1 cm, respectively. All of them were confirmed by hematoxylin-eosin staining and immunohistochemistry.ConclusionsThe clinical characteristics of sdpHCC-ICC are usually atypical. It is difficult to make an accurate preoperative diagnosis. Tumor markers may be valuable to the diagnosis of sdpHCC-ICC. The definite diagnosis of sdpHCC-ICC depends on pathological examination.
ObjectiveTo detect the expressions of takeda G protein-coupled receptor 5 (TGR5) and mortalin protein 75 in the tissues of patients with intrahepatic cholangiocarcinoma (ICC), and to explore their relationship with prognosis.MethodsA total of 94 ICC patients who were admitted to Anyang District Hospital and received surgical treatment from March 2015 to March 2018 were selected as the research objects. The expressions of TGR5 and mortalin protein 75 in ICC cancer tissues and adjacent tissues were detected by immunohistochemistry and Western blot (WB). The relationship between the expressions of TGR5 and mortalin protein 75 in ICC cancer tissues and clinicopathological parameters and prognosis was analyzed. Multivariate Cox proportional hazards regression was used to analyze the risk factors of poor prognosis in patients with ICC. ROC curve was used to analyze the diagnostic value of TGR5 and mortalin protein 75 for poor prognosis in patients with ICC.ResultsImmunohistochemical results showed that the positive expression rates of TGR5 and mortalin protein 75 in cancer tissues were significantly higher than those in adjacenttissues (P<0.05). WB results showed that the protein expression levels of TGR5 and mortalin protein 75 in cancer tissues were significantly higher than those in adjacent tissues (P<0.05). The expression of TGR5 protein in cancer tissues of ICC patients was correlated with gender, tumor diameter, degree of differentiation, TNM staging, satellite focus, and liver cirrhosis (P<0.05). The expression of mortalin protein 75 was correlated with tumor diameter, TNM staging, nerve involvement, satellite focus, and liver cirrhosis (P<0.05). There were significant differences in gender, tumor diameter, TNM staging, microvascular invasion, satellite focus, liver cirrhosis, and the expressions of TGR5 and mortalin protein 75 between the poor prognosis group and the good prognosis group (P<0.05). The cumulative 3-year overall survival rate of TGR5 positive patients (32.00%) was significantly lower than that of TGR5 negative patients (63.16%), χ2=6.228, P=0.013; the cumulative 3-year overall survival rate of mortalin protein 75 positive patients (32.91%) was significantly lower than that of mortalin protein 75 negative patients (66.67%), χ2=6.079, P=0.014. Multivariate Cox proportional hazards regression analysis showed that the positive expression of TGR5 and mortalin protein 75, TNM Ⅲ+Ⅳphase, satellite focus, and cirrhosis were risk factors for poor prognosis in ICC patients (P<0.05). ROC results showed that when the expression level of TGR5 was 0.932 as the cut-off value, its AUC in the diagnosis of poor prognosis of ICC patients was 0.783, the sensitivity was 72.4%, the specificity was 72.2%; when the expression level of mortalin protein 75 was 0.756 as the cut-off value, its AUC in the diagnosis of poor prognosis of ICC patients was 0.805, the sensitivity was 84.4%, the specificity was 63.9%; the AUC of combined diagnosis of TGR5 and mortalin protein 75 was 0.884, the sensitivity was 79.3%, the specificity was 83.3%.ConclusionsThe high expressions of TGR5 and mortalin protein 75 in cancer tissues of ICC patients are associated with poor prognosis, and they are risk factors for poor prognosis. The combined detection of TGR5 and mortalin protein 75 has a certain value in predicting poor prognosis, and can be used as potential biological indicators.
ObjectiveTo develop and validate a nomogram for predicting the cancer-specific survival in patients with intrahepatic cholangiocarcinoma (ICC) after hepatectomy. MethodsSuitable patient cases were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Nomograms were established based on the independent prognostic factors identified by COX and Lasso regression models. The performance of the nomograms was validated internally and externally by using the concordance index (c-index), calibration plot, and decision curve analysis. ResultsThe multi factor COX regression results showed that: age, gender, T stage, tumor grade, tumour diameter and number of positive lymph nodes were independent prognostic predictors for cancer-specific survival (CSS) in ICC patients. Nomogram predicting CSS had a c-index of 0.66 (95%CI 0.64 to 0.69) in the training cohort and 0.67 (95%CI 0.63 to 0.72) in the internal validation cohort. The 1-, 3- and 5-year areas under the curve (AUC) of nomogram were 0.68, 0.74 and 0.75 in the training cohort respectively. In the validation cohort, the 1-, 3- and 5-year AUC of nomogram were 0.69, 0.68 and 0.71, respectively. ConclusionThe prediction model constructed based on six factors, including age, gender, pathological stage, T-stage, tumour diameter and number of positive lymph nodes, shows good prediction accuracy.