Project description:ObjectivesTo establish a nomogram based on preoperative laboratory study variables using least absolute shrinkage and selection operator (LASSO) regression for differentiating combined hepatocellular cholangiocarcinoma (cHCC) from intrahepatic cholangiocarcinoma (iCCA).MethodsWe performed a retrospective analysis of iCCA and cHCC patients who underwent liver resection. Blood signatures were established using LASSO regression, and then, the clinical risk factors based on the multivariate logistic regression and blood signatures were combined to establish a nomogram for a differential preoperative diagnosis between iCCA and cHCC. The differential accuracy ability of the nomogram was determined by Harrell's index (C-index) and decision curve analysis, and the results were validated using a validation set. Furthermore, patients were categorized into two groups according to the optimal cut-off values of the nomogram-based scores, and their survival differences were assessed using Kaplan-Meier curves.ResultsA total of 587 patients who underwent curative liver resection for iCCA or cHCC between January 2008 and December 2017 at West China Hospital were enrolled in this study. The cHCC score was based on the personalized levels of the seven laboratory study variables. On multivariate logistic analysis, the independent factors for distinguishing cHCC were age, sex, biliary duct stones, and portal hypertension, all of which were incorporated into the nomogram combined with the cHCC-score. The nomogram had a good discriminating capability, with a C-index of 0.796 (95% CI, 0.752-0.840). The calibration plot for distinguishing cHCC from iCCA showed optimal agreement between the nomogram prediction and actual observation in the training and validation sets. The decision curves indicated significant clinical usefulness.ConclusionThe nomogram showed good accuracy for the differential diagnosis between iCCA and cHCC preoperatively, and therapeutic decisions would improve if it was applied in clinical practice.

Project description:Background & aimsIntrahepatic cholangiocarcinoma (ICC) is a devastating liver cancer with extremely high intra- and inter-tumoral molecular heterogeneity, partly due to its diverse cellular origins. We investigated clinical relevance and the molecular mechanisms underlying hepatocyte (HC)-driven ICC development.MethodsExpression of ICC driver genes in human diseased livers at risk for ICC development were examined. The sleeping beauty and hydrodynamic tail vein injection based Akt-NICD/YAP1 ICC model was used to investigate pathogenetic roles of SRY-box transcription factor 9 (SOX9) and yes-associated protein 1 (YAP1) in HC-driven ICC. We identified DNA methyltransferase 1 (DNMT1) as a YAP1 target, which was validated by loss- and gain-of-function studies, and its mechanism addressed by chromatin immunoprecipitation sequencing.ResultsCo-expression of AKT and Notch intracellular domain (NICD)/YAP1 in HC yielded ICC that represents 13% to 29% of clinical ICC. NICD independently regulates SOX9 and YAP1 and deletion of either, significantly delays ICC development. Yap1 or TEAD inhibition, but not Sox9 deletion, impairs HC-to-biliary epithelial cell (BEC) reprogramming. DNMT1 was discovered as a novel downstream effector of YAP1-TEAD complex that directs HC-to-BEC/ICC fate switch through the repression of HC-specific genes regulated by master regulators for HC differentiation, including hepatocyte nuclear factor 4 alpha, hepatocyte nuclear factor 1 alpha, and CCAAT/enhancer-binding protein alpha/beta. DNMT1 loss prevented NOTCH/YAP1-dependent HC-driven cholangiocarcinogenesis, and DNMT1 re-expression restored ICC development following TEAD repression. Co-expression of DNMT1 with AKT was sufficient to induce tumor development including ICC. DNMT1 was detected in a subset of HCs and dysplastic BECs in cholestatic human livers prone to ICC development.ConclusionWe identified a novel NOTCH-YAP1/TEAD-DNMT1 axis essential for HC-to-BEC/ICC conversion, which may be relevant in cholestasis-to-ICC pathogenesis in the clinic.

Project description:BACKGROUND & AIMS: Cholangiocarcinoma, the second most common liver cancer, can be classified as intrahepatic (ICC) or extrahepatic. We performed an integrative genomic analysis of ICC samples from a large series of patients. METHODS: We performed gene expression profile, high-density single nucleotide polymorphism array, and mutation analyses using formalin-fixed ICC samples from 149 patients. Associations with clinico-pathological traits and patient outcomes were examined for 119 cases. Class discovery was based on a non-negative matrix factorization algorithm and significant copy number variations (CNV) were identified by GISTIC analysis. Gene set enrichment analysis was used to identify signaling pathways activated in specific molecular classes of tumors, and to analyze their genomic overlap with hepatocellular carcinoma (HCC). RESULTS: We identified 2 main biological classes of ICC. The inflammation class (38% of ICCs) is characterized by activation of inflammatory signaling pathways, overexpression of cytokines, and STAT3 activation. The proliferation class (62%) is characterized by activation of oncogenic signaling pathways (including RAS, mitogen-activated protein kinase, and MET), DNA amplifications at 11q13.2, deletions at 14q22.1, mutations in KRAS and BRAF, and gene expression signatures previously associated with poor outcomes for patients with HCC. CNV-based clustering was able to further refine these molecular groups. We identified high-level amplifications in 5 regions, including 1p13 (9%) and 11q13.2 (4%), and several focal deletions, such as 9p21.3 (18%) and 14q22.1 (12% in coding regions for the SAV1 tumor suppressor). In a complementary approach, we identified a gene expression signature that was associated with reduced survival times of patients with ICC; this signature was enriched in the proliferation class (P<0.001). CONCLUSIONS: We used an integrative genomic analysis to identify 2 classes of ICC. The proliferation class has specific copy number alterations, many features of the poor-prognosis signatures for HCC, and is associated with worse outcome. Different classes of ICC, based on molecular features, might therefore require different treatment approaches. Gene-expression profiling was performed using formalin-fixed, paraffin-embedded intrahepatic cholangiocarcinoma tissues obtained at the time of surgical resection.

Project description:BACKGROUND & AIMS: Cholangiocarcinoma, the second most common liver cancer, can be classified as intrahepatic (ICC) or extrahepatic. We performed an integrative genomic analysis of ICC samples from a large series of patients. METHODS: We performed gene expression profile, high-density single nucleotide polymorphism array, and mutation analyses using formalin-fixed ICC samples from 149 patients. Associations with clinico-pathological traits and patient outcomes were examined for 119 cases. Class discovery was based on a non-negative matrix factorization algorithm and significant copy number variations (CNV) were identified by GISTIC analysis. Gene set enrichment analysis was used to identify signaling pathways activated in specific molecular classes of tumors, and to analyze their genomic overlap with hepatocellular carcinoma (HCC). RESULTS: We identified 2 main biological classes of ICC. The inflammation class (38% of ICCs) is characterized by activation of inflammatory signaling pathways, overexpression of cytokines, and STAT3 activation. The proliferation class (62%) is characterized by activation of oncogenic signaling pathways (including RAS, mitogen-activated protein kinase, and MET), DNA amplifications at 11q13.2, deletions at 14q22.1, mutations in KRAS and BRAF, and gene expression signatures previously associated with poor outcomes for patients with HCC. CNV-based clustering was able to further refine these molecular groups. We identified high-level amplifications in 5 regions, including 1p13 (9%) and 11q13.2 (4%), and several focal deletions, such as 9p21.3 (18%) and 14q22.1 (12% in coding regions for the SAV1 tumor suppressor). In a complementary approach, we identified a gene expression signature that was associated with reduced survival times of patients with ICC; this signature was enriched in the proliferation class (P<0.001). CONCLUSIONS: We used an integrative genomic analysis to identify 2 classes of ICC. The proliferation class has specific copy number alterations, many features of the poor-prognosis signatures for HCC, and is associated with worse outcome. Different classes of ICC, based on molecular features, might therefore require different treatment approaches.

Dataset Information

Diagnostic value of glypican-3, arginase-1 and hepatocyte paraffin antigen -1 in differentiating hepatocellular carcinoma from intrahepatic cholangiocarcinoma

Background

Methods

Results

Conclusions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets