Differentially expressed gene profiles of intrahepatic cholangiocarcinoma, hepatocellular carcinoma, and combined hepatocellular-cholangiocarcinoma by integrated microarray analysis

Molecular subtypes of intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinoma (iCCA) presents in two clinically distinct subtypes: large duct (LD-iCCA) and small duct (SD-iCCA). These subtypes exhibit significant molecular, genetic, and histopathological differences that impact patient prognosis and treatment responsiveness. This review advocates for a subtype-specific approach to iCCA research and clinical management, including tailored therapeutic strategies that consider distinct genetic profiles and tumor microenvironments. Current therapeutic approaches hold promise, yet efficacy varies by subtype. Additionally, subtype-specific molecular diagnostics, including DNA methylation-based classifiers and transcriptomic sequencing, have shown potential in refining iCCA subclassification, thereby guiding precision medicine efforts. This article outlines existing clinical trials, key research trajectories, and future directions for developing more effective subtype-adapted therapies for iCCA.

Identification of Candidate Hub Genes and Drug Targets for Cholangiocarcinoma via Juhua (Chrysanthemum Morifolium) Bioactivity and Molecular Docking: A Bioinformatics Approach

Background

Cholangiocarcinoma (CHOL) is a malignancy with poor clinical outcomes and limited treatment options. While extensive research has investigated genetic and signaling pathways in CHOL, the molecular mechanisms underlying disease pathogenesis remain incompletely understood. A key hurdle has been the lack of a systematic, multi-omic approach to illuminate causal relationships between genetic variants and CHOL risk.

Results

We integrated gene expression, co-expression network, and Mendelian randomization analyses to elucidate molecular drivers of CHOL. Gene set enrichment of differentially expressed genes from CHOL tumor samples identified enrichment in cancer-related biological processes. Weighted gene co-expression network analysis identified modules highly correlated with CHOL, including genes involved in cell cycle regulation, transcription, and proteolysis. Integrating these data with targets of the herbal formula Juhua, which shows anti-CHOL activity, pinpointed four candidate hub genes (CDK5, CDK7, CTSB, MAP2K2). Molecular docking revealed interactions between Juhua constituents and these hub genes. Mendelian randomization analysis of genetic variants implicated CCL2, CD5, CXCL6, CXCL9, HGF, IL10, IL10RA, IL18, IL24, IL2RB, IL6, IL8, SIRT2 and SLAMF1 as causally associated with CHOL.

Conclusion

Our multi-omic analysis provides new insight into molecular underpinnings of CHOL and identifies candidate disease drivers, signaling pathways and herbal targets for further validation. This systematic approach established a framework for illuminating causal links between genetics, molecular mechanisms and disease pathogenesis, with potential to accelerate drug and biomarker development for CHOL.

Differentiating HCC from ICC and prediction of ICC grade based on MRI deep-radiomics: Using lesions and their extended regions

PURPOSE

This study aimed to evaluate the ability of MRI-based intratumoral and peritumoral radiomics features of liver tumors to differentiate between hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) and to predict ICC differentiation.

METHODS

This study retrospectively collected 87 HCC patients and 75 ICC patients who were confirmed pathologically. The standard region of interest (ROI) of the lesion drawn by the radiologist manually shrank inward and expanded outward to form multiple ROI extended regions. A three-step feature selection method was used to select important radiomics features and convolution features from extended regions. The predictive performance of several machine learning classifiers on dominant feature sets was compared. The extended region performance was assessed by area under the curve (AUC), specificity, sensitivity, F1-score and accuracy.

RESULTS

The performance of the model is further improved by incorporating convolution features. Compared with the standard ROI, the extended region obtained better prediction performance, among which 6 mm extended region had the best prediction ability (Classification: AUC = 0.96, F1-score = 0.94, Accuracy: 0.94; Grading: AUC = 0.94, F1-score = 0.93, Accuracy = 0.89).

CONCLUSION

Larger extended region and fusion features can improve tumor predictive performance and have potential value in tumor radiology.

A multi-parameter intrahepatic cholangiocarcinoma scoring system based on modified contrast-enhanced ultrasound LI-RADS M criteria for differentiating intrahepatic cholangiocarcinoma from hepatocellular carcinoma

PURPOSE

To develop a multi-parameter intrahepatic cholangiocarcinoma (ICC) scoring system and compare its diagnostic performance with contrast-enhanced ultrasound (CEUS) liver imaging reporting and data system M (LR-M) criteria for differentiating ICC from hepatocellular carcinoma (HCC).

METHODS

This retrospective study enrolled 62 high-risk patients with ICCs and 62 high-risk patients with matched HCCs between January 2022 and December 2022 from two institutions. The CEUS LR-M criteria was modified by adjusting the early wash-out onset (within 45 s) and the marked wash-out (within 3 min). Then, a multi-parameter ICC scoring system was established based on clinical features, B-mode ultrasound features, and modified LR-M criteria.

RESULT

We found that elevated CA 19-9 (OR=12.647), lesion boundary (OR=11.601), peripheral rim-like arterial phase hyperenhancement (OR=23.654), early wash-out onset (OR=7.211), and marked wash-out (OR=19.605) were positive predictors of ICC, whereas elevated alpha-fetoprotein (OR=0.078) was a negative predictor. Based on these findings, an ICC scoring system was established. Compared with the modified LR-M and LR-M criteria, the ICC scoring system showed the highest area under the curve (0.911 vs. 0.831 and 0.750, both p<0.05) and specificity (0.935 vs. 0.774 and 0.565, both p<0.05). Moreover, the numbers of HCCs categorized as LR-M decreased from 27 (43.5%) to 14 (22.6%) and 4 (6.5%) using the modified LR-M criteria and ICC scoring system, respectively.

CONCLUSION

The modified LR-M criteria-based multi-parameter ICC scoring system had the highest specificity for diagnosing ICC and reduced the number of HCC cases diagnosed as LR-M category.

Combined Hepatocellular-Cholangiocarcinoma: Biology, Diagnosis, and Management

BACKGROUND

Combined hepatocellular-cholangiocarcinoma (cHCC-iCCA) is a rare type of primary liver cancer displaying characteristics of both hepatocytic and cholangiocytic differentiation.

SUMMARY

Because of its aggressive nature, patients with cHCC-iCCA exhibit a poorer prognosis than those with HCC. Surgical resection and liver transplantation may be considered curative treatment approaches; however, only a minority of patients are eligible at the time of diagnosis, and postoperative recurrence rates are high. For cases that are not eligible for surgery, locoregional and systemic therapy are often administered based on treatment protocols applied for HCC or iCCA. Owing to the rarity of this cancer, there are still no established standard treatment protocols; therefore, the choice of therapy is often personalized and guided by the suspected predominant component. Further, the genomic and molecular heterogeneity of cHCC-iCCA can severely compromise the efficacy of the available therapies.

KEY MESSAGES

In the present review, we summarize the latest advances in cHCC-iCCA and attempt to clarify its terminology and molecular biology. We provide an overview of the etiology of cHCC-iCCA and present new insights into the molecular pathology of this disease that could contribute to further studies aiming to improve the patient outcomes through new systemic therapies.

The heterogeneity of signaling pathways and drug responses in intrahepatic cholangiocarcinoma with distinct genetic mutations

Intrahepatic cholangiocarcinoma (ICC) is the second most common malignancy among primary liver cancers, with an increasing overall incidence and poor prognosis. The intertumoral and intratumoral heterogeneity of ICC makes it difficult to find efficient drug therapies. Therefore, it is essential to identify tumor suppressor genes and oncogenes that induce ICC formation and progression. Here, we performed CRISPR/Cas9-mediated genome-wide screening in a liver-specific Smad4/Pten knockout mouse model (Smad4co/co;Ptenco/co;Alb-Cre, abbreviated as SPC), which normally generates ICC after 6 months, and detected that mutations in Trp53, Fbxw7, Inppl1, Tgfbr2, or Cul3 markedly accelerated ICC formation. To illustrate the potential mechanisms, we conducted transcriptome sequencing and found that multiple receptor tyrosine kinases were activated, which mainly upregulated the PI3K pathway to induce cell proliferation. Remarkably, the Cul3 mutation stimulated cancer progression mainly by altering the immune microenvironment, whereas other mutations promoted the cell cycle. Moreover, Fbxw7, Inppl1, Tgfbr2, and Trp53 also affect inflammatory responses, apelin signaling, mitotic spindles, ribosome biogenesis, and nucleocytoplasmic transport pathways, respectively. We further examined FDA-approved drugs for the treatment of liver cancer and performed high-throughput drug screening of the gene-mutant organoids. Different drug responses and promising drug therapies, including chemotherapy and targeted drugs, have been discovered for ICC.

Cartilage oligomeric matrix protein overexpression is an independent poor prognostic indicator in patients with intrahepatic cholangiocarcinoma

Cartilage oligomeric matrix protein (COMP) interacts with various extracellular matrix proteins in tissues. Elevated COMP levels recently linked to worse overall survival in multiple cancer types. COMP's significance in intrahepatic cholangiocarcinoma (iCCA) remains uncertain. Here we report a retrospective study to explore COMP's impact on iCCA outcomes. We collected 182 patients' iCCA tumor tissues. COMP overexpression was associated with adverse factors like R1 resection (p = 0.008), advanced T stage (p < 0.001), large duct type (p = 0.004), and poorly differentiated histology (p = 0.002). COMP overexpression correlates with poorer DFS (HR, 3.651; p = 0.001), OS (HR, 1.827; p = 0.023), LRFS (HR, 4.077; p < 0.001), and MFS (HR, 3.718; p < 0.001). High COMP expression ties to worse overall survival (p = 0.0001), DSS (p < 0.0001), LRFS (p < 0.0001), and MFS (p < 0.0001). In conclusion, COMP overexpression links to poor prognosis and pathological features in iCCA, indicating its potential as a biomarker.

Single-cell transcriptome analysis identifies novel biomarkers involved in major liver cancer subtypes

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the two aggressive subtypes of liver cancer (LC). Immense cellular heterogeneity and cross-talk between cancer and healthy cells make it challenging to treat these cancer subtypes. To address these challenges, the study aims to systematically characterize the tumor heterogeneity of LC subtypes using single-cell RNA sequencing (scRNA-seq) datasets. The study combined 51,927 single cells from HCC, ICC, and healthy scRNA-seq datasets. After integrating the datasets, cell groups with similar gene expression patterns are clustered and cluster annotation has been performed based on gene markers. Cell-cell communication analysis (CCA) was implemented to understand the cross-talk between various cell types. Further, differential gene expression analysis and enrichment analysis were carried out to identify unique molecular drivers associated with HCC and ICC. Our analysis identified T cells, hepatocytes, epithelial cells, and monocyte as the major cell types present in the tumor microenvironment. Among them, abundance of natural killer (NK) cells in HCC, epithelial cells, and hepatocytes in ICC was detected. CCA revealed key interaction between T cells to NK cells in HCC and smooth muscle cells to epithelial cells in the ICC. Additionally, SOX4 and DTHD1 are the top differentially expressed genes (DEGs) in HCC, while keratin and CCL4 are in ICC. Enrichment analysis of DEGs reveals major upregulated genes in HCC affect protein folding mechanism and in ICC alter pathways involved in cell adhesion. The findings suggest potential targets for the development of novel therapeutic strategies for the treatment of these two aggressive subtypes of LC.

An Efficient Nomogram for Discriminating Intrahepatic Cholangiocarcinoma From Hepatocellular Carcinoma: A Retrospective Study

Objective

This study aims to establish a nomogram and provide an effective method to distinguish between intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC).

Methods

A total of 1,591 patients with HCC or ICC hospitalized at Shandong Provincial Hospital between January 2016 and August 2021 were included and randomly divided into development and validation groups in a ratio of 3:1. Univariate and multivariate analyses were performed to determine the independent differential factors between HCC and ICC patients in the development cohort. By combining these independent differential factors, the nomogram was established for discriminating ICC from HCC. The accuracy of the nomogram was estimated by using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Furthermore, the predictive nomogram was assessed in the internal testing set.

Results

Through multivariate analysis, independent differential factors between HCC and ICC involved hepatitis B virus (HBV), logarithm of alpha-fetoprotein (Log AFP), logarithm of protein induced by vitamin K absence or antagonist-II (Log PIVKA-II), logarithm of carbohydrate antigen 199 (Log CA199), and logarithm of carbohydrate antigen 125 (Log CA125). A nomogram was finally established by incorporating these five independent differential factors. Comparing a model of conventional tumor biomarkers including AFP and CA199, the nomogram showed a better distinction between ICC and HCC. The area under the ROC curve (AUC) of ICC diagnosis was 0.951 (95% CI, 0.938–0.964) for the nomogram. The results were consistent in the validation cohort with an AUC of 0.958 (95% CI, 0.938–0.978). After integrating patient preferences into the analysis, the DCA showed that using this nomogram to distinguish ICC and HCC increased more benefit compared with the conventional model.

Conclusion

An efficient nomogram has been established for the differential diagnosis between ICC and HCC, which may facilitate the detection and diagnosis of ICC. Further use of the nomogram in multicenter investigations will confirm the practicality of the tool for future clinical application.

Signaling Pathways Involved in 5-FU Drug Resistance in Cancer

Anti-metabolite drugs prevent the synthesis of essential cell growth compounds. 5-fluorouracil is used as an anti-metabolic drug in various cancers in the first stage of treatment. Unfortunately, in some cancers, 5-fluorouracil has low effectiveness because of its drug resistance. Studies have shown that drug resistance to 5-fluorouracil is due to the activation of specific signaling pathways and increased expressions of enzymes involved in drug metabolites. However, when 5-fluorouracil is used in combination with other drugs, the sensitivity of cancer cells to 5-fluorouracil increases, and the effect of drug resistance is reversed. This study discusses how the function of 5-fluorouracil in JAK/STAT, Wnt, Notch, NF-κB, and hedgehogs in some cancers.

Prognostic Values and Clinical Significance of S100 Family Member's Individualized mRNA Expression in Pancreatic Adenocarcinoma

Objective: Pancreatic adenocarcinoma (PAAD) is a common malignant tumor worldwide. S100 family (S100s) is wildly involved in regulating the occurrence, development, invasion, metastasis, apoptosis, and drug resistance of many malignant tumors. However, the expression pattern, prognostic value, and oncological role of individual S100s members in PAAD need to be elucidated.

Methods: The transcriptional expression levels of S100s were analyzed through the Oncomine and GEPIA, respectively. The protein levels of S100s members in PAAD were studied by Human Protein Atlas. The correlation between S100 mRNA expression and overall survival and tumor stage in PAAD patients was studied by GEPIA. The transcriptional expression correlation and gene mutation rate of S100s members in PAAD patients were explored by cBioPortal. The co-expression networks of S100s are identified using STRING and Gene MANIA to predict their potential functions. The correlation of S100s expression and tumor-infiltrating immune cells was tested by TIMER. Pathway activity and drug target analyzed by GSCALite.

Results: 13 S100s members were upregulated in PAAD tissues. 15 S100s members were associated with TP53 mutation. Expression levels of S100A3/A5/A6/A10/A11/A14/A16/B/P/Z were significantly correlated with the pathological stage. Prognosis analysis demonstrated that PAAD patients with low mRNA levels of S100A1/B/Z or high levels of S100A2/A3/A5/A10/A11/A14/A16 had a poor prognosis. Immuno-infiltration analysis showed that the mRNA levels of S100A10/A11/A14/A16 were correlated with the infiltration degree of macrophages in PAAD. Drug sensitivity analysis showed that PAAD expressing high levels of S100A2/A6/A10/A11/A13/A14/A16 maybe resistant to small molecule drugs.

Conclusion: This study identifies the clinical significance and biological functions of the S100s in PAAD, which may provide novel insights for the selection of prognostic biomarkers.

Clinical Value of Machine Learning-Based Ultrasomics in Preoperative Differentiation Between Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma: A Multicenter Study

OBJECTIVE

This study aims to explore the clinical value of machine learning-based ultrasomics in the preoperative noninvasive differentiation between hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC).

METHODS

The clinical data and ultrasonic images of 226 patients from three hospitals were retrospectively collected and divided into training set (n = 149), test set (n = 38), and independent validation set (n = 39). Manual segmentation of tumor lesion was performed with ITK-SNAP, the ultrasomics features were extracted by the pyradiomics, and ultrasomics signatures were generated using variance filtering and lasso regression. The prediction models for preoperative differentiation between HCC and ICC were established by using support vector machine (SVM). The performance of the three models was evaluated by the area under curve (AUC), sensitivity, specificity, and accuracy.

RESULTS

The ultrasomics signatures extracted from the grayscale ultrasound images could successfully differentiate between HCC and ICC (p < 0.05). The combined model had a better performance than either the clinical model or the ultrasomics model. In addition to stability, the combined model also had a stronger generalization ability (p < 0.05). The AUC (along with 95% CI), sensitivity, specificity, and accuracy of the combined model on the test set and the independent validation set were 0.936 (0.806-0.989), 0.900, 0.857, 0.868, and 0.874 (0.733-0.961), 0.889, 0.867, and 0.872, respectively.

CONCLUSION

The ultrasomics signatures could facilitate the preoperative noninvasive differentiation between HCC and ICC. The combined model integrating ultrasomics signatures and clinical features had a higher clinical value and a stronger generalization ability.

Comprehensive Analysis of the Prognosis and Correlations With Immune Infiltration of S100 Protein Family Members in Hepatocellular Carcinoma

S100 protein family members (S100s) are commonly dysregulated in various tumors including hepatocellular carcinoma (HCC). However, the diverse expression, mutation, prognosis and associations with immune infiltration of S100s in HCC have yet to be analyzed. Herein we investigated the roles of S100s in HCC from the Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas, Kaplan-Meier Plotter, cBioPortal and TIMER databases. Compared with para-cancer tissues, the expression levels of S100A4/S100A6/S100A10/S100A11/S100A13/S100A14/S100P were higher in HCC tissues, while the expression levels of S100A8/S100A9/S100A12 were decreased in tumor tissues. The mRNA levels of S100A2/S100A7/S100A7A/S100A8/S100A9/S100A11 were correlated with advanced tumor stage. Besides, higher mRNA expressions of S100A6/S100A10/S100A11/S100A13/S100A14/S100P were shown to have shorter overall survival (OS), while higher expression of S100A12 was associated with favorable OS. Further, the mutation rate of S100s was investigated, and the high mutation rate (53%) was associated with shorter OS. Additionally, the expressions of S100s were found to be significantly associated with various immune infiltrating cells. Hence, our results showed that S100A6/S100A10/S100A11/S10012/S100A13/S100A14/S100P may be regarded as new prognostic or therapeutic markers and S100s inhibitors may be helpful in the combination of immunotherapies.

Developing models of cholangiocarcinoma to close the translational gap in cancer research

Introduction: Cholangiocarcinoma (CCA) is an aggressive primary liver malignancy with abysmal prognosis and increasing global incidence. Individuals afflicted with CCA often remain asymptomatic until late stages of disease, resulting in very limited possibilities for therapeutic intervention. The emergence of numerous preclinical models in vitro and in vivo has expanded the tool kit for CCA researchers; nonetheless, how these tools can be best applied to understand CCA biology and accelerate drug development requires further scrutiny.Areas covered: The paper reviews the literature on animal and organoid models of CCA (available through PubMed between September 2020 and January 2021) and examines their investigational role in CCA therapeutics. Finally, the potential of these systems for screening therapeutics to improve CCA patient outcomes is illuminated.Expert Opinion: The expansion of CCA models has yielded a diverse and interesting tool kit for preclinical research. However, investigators should consider which tools are best suited to answer key preclinical questions for real progress. A combination of advanced in vitro cell systems and in vivo testing will be necessary to accelerate translational medicine in cholangiocarcinoma.

Identification of a Transcriptomic Prognostic Signature by Machine Learning Using a Combination of Small Cohorts of Prostate Cancer

Determining which treatment to provide to men with prostate cancer (PCa) is a major challenge for clinicians. Currently, the clinical risk-stratification for PCa is based on clinico-pathological variables such as Gleason grade, stage and prostate specific antigen (PSA) levels. But transcriptomic data have the potential to enable the development of more precise approaches to predict evolution of the disease. However, high quality RNA sequencing (RNA-seq) datasets along with clinical data with long follow-up allowing discovery of biochemical recurrence (BCR) biomarkers are small and rare. In this study, we propose a machine learning approach that is robust to batch effect and enables the discovery of highly predictive signatures despite using small datasets. Gene expression data were extracted from three RNA-Seq datasets cumulating a total of 171 PCa patients. Data were re-analyzed using a unique pipeline to ensure uniformity. Using a machine learning approach, a total of 14 classifiers were tested with various parameters to identify the best model and gene signature to predict BCR. Using a random forest model, we have identified a signature composed of only three genes (JUN, HES4, PPDPF) predicting BCR with better accuracy [74.2%, balanced error rate (BER) = 27%] than the clinico-pathological variables (69.2%, BER = 32%) currently in use to predict PCa evolution. This score is in the range of the studies that predicted BCR in single-cohort with a higher number of patients. We showed that it is possible to merge and analyze different small and heterogeneous datasets altogether to obtain a better signature than if they were analyzed individually, thus reducing the need for very large cohorts. This study demonstrates the feasibility to regroup different small datasets in one larger to identify a predictive genomic signature that would benefit PCa patients.

Notch signalling pathway in development of cholangiocarcinoma

Cholangiocarcinoma (CCA) comprises of extra-hepatic cholangiocarcinoma and intrahepatic cholangiocarcinoma cancers as a result of inflammation of epithelium cell lining of the bile duct. The incidence rate is increasing dramatically worldwide with highest rates in Eastern and South Asian regions. Major risk factors involve chronic damage and inflammation of bile duct epithelium from primary sclerosing cholangitis, chronic hepatitis virus infection, gallstones and liver fluke infection. Various genetic variants have also been identified and as CCA develops on the background of biliary inflammation, diverse range of molecular mechanisms are involved in its progression. Among these, the Notch signalling pathway acts as a major driver of cholangiocarcinogenesis and its components (receptors, ligands and downstream signalling molecules) represent a promising therapeutic targets. Gamma-Secretase Inhibitors have been recognized in inhibiting the Notch pathway efficiently. A comprehensive knowledge of the molecular pathways activated by the Notch signalling cascade as well as its functional crosstalk with other signalling pathways provide better approach in developing innovative therapies against CCA.

Cholangiocarcinoma 2020: the next horizon in mechanisms and management

Cholangiocarcinoma (CCA) includes a cluster of highly heterogeneous biliary malignant tumours that can arise at any point of the biliary tree. Their incidence is increasing globally, currently accounting for ~15% of all primary liver cancers and ~3% of gastrointestinal malignancies. The silent presentation of these tumours combined with their highly aggressive nature and refractoriness to chemotherapy contribute to their alarming mortality, representing ~2% of all cancer-related deaths worldwide yearly. The current diagnosis of CCA by non-invasive approaches is not accurate enough, and histological confirmation is necessary. Furthermore, the high heterogeneity of CCAs at the genomic, epigenetic and molecular levels severely compromises the efficacy of the available therapies. In the past decade, increasing efforts have been made to understand the complexity of these tumours and to develop new diagnostic tools and therapies that might help to improve patient outcomes. In this expert Consensus Statement, which is endorsed by the European Network for the Study of Cholangiocarcinoma, we aim to summarize and critically discuss the latest advances in CCA, mostly focusing on classification, cells of origin, genetic and epigenetic abnormalities, molecular alterations, biomarker discovery and treatments. Furthermore, the horizon of CCA for the next decade from 2020 onwards is highlighted.

Can contrast enhanced ultrasound differentiate intrahepatic cholangiocarcinoma from hepatocellular carcinoma?

BACKGROUND

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) differ in treatment and prognosis, warranting an effective differential diagnosis between them. The LR-M category in the contrast-enhanced ultrasound (CEUS) liver imaging reporting and data system (LI-RADS) was set up for lesions that are malignant but not specific to HCC. However, a substantial number of HCC cases in this category elevated the diagnostic challenge.

AIM

To investigate the possibility and efficacy of differentiating ICC from HCC classified in the LR-M category according to the CEUS LI-RADS.

METHODS

Patients with complete CEUS records together with pathologically confirmed ICC and LR-M HCC (HCC classified in the CEUS LI-RADS LR-M category) between January 2015 and October 2018 were included in this retrospective study. Each ICC was assigned a category as per the CEUS LI-RADS. The enhancement pattern, washout timing, and washout degree between the ICC and LR-M HCC were compared using the χ 2 test. Logistic regression analysis was used for prediction of ICC. Receiver operating characteristic (ROC) curve analysis was used to investigate the possibility of LR-M criteria and serum tumor markers in differentiating ICC from LR-M HCC.

RESULTS

A total of 228 nodules (99 ICCs and 129 LR-M HCCs) in 228 patients were included. The mean sizes of ICC and LR-M HCC were 6.3 ± 2.8 cm and 5.5 ± 3.5 cm, respectively (P = 0.03). Peripheral rim-like arterial phase hyperenhancement (APHE) was detected in 50.5% (50/99) of ICCs vs 16.3% (21/129) of LR-M HCCs (P < 0.001). Early washout was found in 93.4% (93/99) of ICCs vs 96.1% (124/129) of LR-M HCCs (P > 0.05). Marked washout was observed in 23.2% (23/99) of ICCs and 7.8% (10/129) of LR-M HCCs (P = 0.002), while this feature did not show up alone either in ICC or LR-M HCC. Homogeneous hyperenhancement was detected in 15.2% (15/99) of ICCs and 37.2% (48/129) of LR-M HCCs (P < 0.001). The logistic regression showed that rim APHE, carbohydrate antigen 19-9 (CA 19-9), and alpha fetoprotein (AFP) had significant correlations with ICC (r = 1.251, 3.074, and -2.767, respectively; P < 0.01). Rim APHE presented the best enhancement pattern for diagnosing ICC, with an area under the ROC curve (AUC) of 0.70, sensitivity of 70.4%, and specificity of 68.8%. When rim hyperenhancement was coupled with elevated CA 19-9 and normal AFP, the AUC and sensitivity improved to 0.82 and 100%, respectively, with specificity decreasing to 63.9%.

CONCLUSION

Rim APHE is a key predictor for differentiating ICC from LR-M HCC. Rim APHE plus elevated CA 19-9 and normal AFP is a strong predictor of ICC rather than LR-M HCC. Early washout and marked washout have limited value for the differentiation between the two entities.

Analysis of Liver Resection Versus Liver Transplantation on Outcome of Small Intrahepatic Cholangiocarcinoma and Combined Hepatocellular-Cholangiocarcinoma in the Setting of Cirrhosis

This multicenter study compares the outcomes of patients with cirrhosis undergoing liver transplantation (LT) or liver resection (LR) between January 2002 and July 2015 who had intrahepatic cholangiocarcinoma (iCCA) or combined hepatocellular-cholangiocarcinoma (cHCC-CCA) found incidentally in the native liver. A total of 49 (65%) LT and 26 (35%) LR patients with cirrhosis and histologically confirmed iCCA/cHCC-CCA ≤5 cm were retrospectively analyzed. LT patients had significantly lower tumor recurrence (18% versus 46%; P = 0.01), for which the median diameter of the largest nodule (hazard ratio [HR], 1.07; 95% confidence interval [CI], 1.02-1.12]; P = 0.006) and tumor differentiation (HR, 3.74; 95% CI 1.71-8.17; P = 0.001) were independently predictive. The LT group had significantly higher 5-year recurrence-free survival (RFS; 75% versus 36%; P = 0.004). In patients with tumors >2 cm but ≤5 cm, LT patients had a lower recurrence rate (21% versus 48%; P = 0.06) and a higher 5-year RFS (74% versus 40%; P = 0.06). Independent risk factors for recurrence were LT (protective; HR, 0.23; 95% CI, 0.07-0.82; P = 0.02), the median diameter of the largest nodule (HR, 1.10; 95% CI, 1.02-1.73; P = 0.007), and tumor differentiation (HR, 4.16; 95% CI, 1.37-12.66; P = 0.01). In the LT group, 5-year survival reached 69% and 65% (P = 0.40) in patients with tumors ≤2 cm and >2-5 cm, respectively, and survival was also comparable between iCCA and cHCC-CCA patients (P = 0.29). LT may offer a benefit for highly selected patients with cirrhosis and unresectable iCCA/cHCC-CCA having tumors ≤5 cm. Efforts should be made to evaluate tumor differentiation, and these results need to be confirmed prospectively in a larger population.

Tumor-infiltrating immune cells in hepatocellular carcinoma: Tregs is correlated with poor overall survival

Systematic interrogation of tumor-infiltrating immune cells (TIICs) is key to the prediction of clinical outcome and development of immunotherapies. However, little is known about the TIICs of hepatocellular carcinoma (HCC) and its impact on the prognosis of patients and potential for immunotherapy. We applied CIBERSORT of 1090 tumors to infer the infiltration of 22 subsets of TIICs using gene expression data. Unsupervised clustering analysis by 22 TIICs revealed 4 clusters of tumors, mainly defined by macrophages and T cells, with distinct prognosis and associations with immune checkpoint molecules, including PD-1, CD274, CTLA-4, LAG-3 and IFNG. We found tumors with decreased number of M1 macrophages or increased regulatory T cells were associated with poor prognosis. Based on the multivariate Cox analysis, a nomogram was also established for clinical application. In conclusion, composition of the TIICs in HCC was quite different, which is an important determinant of prognosis with great potential to identify candidates for immunotherapy.

Combined hepatocellular cholangiocarcinoma (cHCC-CC): an update of genetics, molecular biology, and therapeutic interventions

Combined hepatocellular cholangiocarcinoma (CC) is a rare and aggressive primary hepatic malignancy with significant histological and biological heterogeneity. It presents with more aggressive behavior and worse survival outcomes than either hepatocellular carcinoma or CC and remains a diagnostic challenge. An accurate diagnosis is crucial for its optimal management. Major hepatectomy with hilar node resection remains the mainstay of treatment in operable cases. Advances in the genetic and molecular characterization of this tumor will contribute to the better understanding of its pathogenesis and shape its future management.

Higher notch expression implies poor survival in pancreatic ductal adenocarcinoma: A systematic review and meta-analysis

BACKGROUND

At present, pancreatic ductal adenocarcinoma (PDAC) is a fetal disease lack of effective prognostic and therapeutic methods resulting in high mortality. The Notch signaling has been demonstrated being up- or down-regulated in many cancers, but the effects in pancreatic ductal adenocarcinoma are still controversial. Moreover, the available cases in an individual study are of small samples. Therefore, it is essential to define the effect of Notch signaling in pancreatic ductal adenocarcinoma with larger samples.

METHODS

Conducted from 6 eligible studies and 463 pancreatic ductal adenocarcinoma patients, this was the first meta-analysis to analyze the correlation between the Notch signal pathway and pancreatic ductal adenocarcinoma. All data were sourced from The National Center for Biotechnology Information, Web of Science and Cochrane. The articles which matched the inclusion criteria were included. All included data were analyzed and performed by Review Manager 5.3.

RESULTS

The results indicated that high expression of Notch signaling proteins was associated with poor overall survival of pancreatic ductal adenocarcinoma patients (pooled hazard ratio>2.00; P < 0.001). Moreover, poor survival was related to high expression of Notch3 (pooled hazard ratio: 2.05; confidence interval: 1.49-2.82; P < 0.001) and DLL4 (pooled hazard ratio: 2.13; confidence interval: 1.37-3.32; P < 0.001).

CONCLUSIONS

This meta-analysis supports that Notch signaling proteins may be available as prognostic factors for pancreatic ductal adenocarcinoma progression and patient survival. Higher expression of Notch signaling proteins indicated poor survival of pancreatic ductal adenocarcinoma patients. Targeting Notch signaling components, especially Notch3 protein, would be beneficial for therapies.

Subclassification and Detection of New Markers for the Discrimination of Primary Liver Tumors by Gene Expression Analysis Using Oligonucleotide Arrays

Background/Aims

The failure to correctly differentiate between intrahepatic cholangiocarcinoma (CC) and hepatocellular carcinoma (HCC) is a significant clinical problem, particularly in terms of the different treatment goals for both cancers. In this study a specific gene expression profile to discriminate these two subgroups of liver cancer was established and potential diagnostic markers for clinical use were analyzed.

Methods

To evaluate the gene expression profiles of HCC and intrahepatic CC, Oligonucleotide arrays (AffymetrixU133A) were used. Overexpressed genes were checked for their potential use as new markers for discrimination and their expression values were validated by reverse transcription polymerase chain reaction and immunohistochemistry analyses.

Results

695 genes/expressed sequence tags (ESTs) in HCC (245 up-/450 down-regulated) and 552 genes/ESTs in CC (221 up-/331 down-regulated) were significantly dysregulated (p＜0.05, fold change >2, ≥70%). Using a supervised learning method, and one-way analysis of variance a specific 270-gene expression profile that enabled rapid, reproducible differentiation between both tumors and nonmalignant liver tissues was established. A panel of 12 genes (e.g., HSP90β, ERG1, GPC3, TKT, ACLY, and NME1 for HCC; SPT2, T4S3, CNX43, TTD1, HBD01 for CC) were detected and partly described for the first time as potential discrimination markers.

Conclusions

A specific gene expression profile for discrimination of primary liver cancer was identified and potential marker genes with feasible clinical impact were described.

S100A11 promotes cell proliferation via P38/MAPK signaling pathway in intrahepatic cholangiocarcinoma

S100A11 is reported to associate with progression and poor prognosis in several tumors. We previously reported that S100A11 was highly expressed in intrahepatic cholangiocarcinoma (ICC) cells and promoted TGF-β1-induced EMT through SMAD2/3 signaling pathway. Here, we explored the prognostic role of S100A11 on ICC patients and preliminary molecular mechanisms how S100A11 regulated ICC cell proliferation. Our results showed that S100A11 was obviously increased in ICC tumor tissues. High expression of S100A11 was closely correlated with lymph node metastasis (LNM) and TNM stage and was an independent risk factor for patients' overall survival (OS) and recurrence-free survival (RFS). The nomograms comprising LNM and S100A11 achieved better predictive accuracy compared with TNM staging system for OS and RFS prediction. Silencing S100A11 significantly suppressed RBE cells and HCCC9810 cells proliferation, colony formation, and activation of P38/mitogen-activated protein kinase (MAPK) signaling pathway in vitro and inhibited tumor growth in vivo. In contrast, the overexpression of S100A11 in RBE cells and HCCC9810 cells achieved the opposite results. S100A11-induced proliferation was abolished after treatment with P38 inhibitor. Our findings suggest S100A11/P38/MAPK signaling pathway may be a potential therapeutic target for ICC patients.

S100A11 promotes TGF-β1-induced epithelial-mesenchymal transition through SMAD2/3 signaling pathway in intrahepatic cholangiocarcinoma

AIM

Our previous study found S100A11 was significantly raised in intrahepatic cholangiocarcinoma cells, but the relationship between S100A11 and intrahepatic cholangiocarcinoma remains unclear.

METHODS

We investigated the effect of silencing S100A11 on TGF-β1-induced epithelial-mesenchymal transition (EMT), cell migration and invasion.

RESULTS

Our results demonstrated silencing S100A11 inhibited TGF-β1-induced cell migration, invasion and EMT, expression of EMT markers E-cadherin, N-cadherin, β-catenin, vimentin, Slug and Snail was reversed. Furthermore, TGF-β1-induced p-SMAD2 and 3 were also inhibited due to low S100A11 expression.

CONCLUSION

Our present study indicated that S100A11 promotes EMT through accumulation of TGF-β1 expression, and TGF-β1-induced upregulation of p-SMAD2 and 3.

A nomogram incorporating six easily obtained parameters to discriminate intrahepatic cholangiocarcinoma and hepatocellular carcinoma

Intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are the most prevalent histologic types of primary liver cancer (PLC). Although ICC and HCC share similar risk factors and clinical manifestations, ICC usually bears poorer prognosis than HCC. Confidently discriminating ICC and HCC before surgery is beneficial to both treatment and prognosis. Given the lack of effective differential diagnosis biomarkers and methods, construction of models based on available clinicopathological characteristics is in need. Nomograms present a simple and efficient way to make a discrimination. A total of 2894 patients who underwent surgery for PLC were collected. Of these, 1614 patients formed the training cohort for nomogram construction, and thereafter, 1280 patients formed the validation cohort to confirm the model's performance. Histopathologically confirmed ICC was diagnosed in 401 (24.8%) and 296 (23.1%) patients in these two cohorts, respectively. A nomogram integrating six easily obtained variables (Gender, Hepatitis B surface antigen, Aspartate aminotransferase, Alpha-fetoprotein, Carcinoembryonic antigen, Carbohydrate antigen 19-9) is proposed in accordance with Akaike's Information Criterion (AIC). A score of 15 was determined as the cut-off value, and the corresponding discrimination efficacy was sufficient. Additionally, patients who scored higher than 15 suffered poorer prognosis than those with lower scores, regardless of the subtype of PLC. A nomogram for clinical discrimination of ICC and HCC has been established, where a higher score indicates ICC and poor prognosis. Further application of this nomogram in multicenter investigations may confirm the practicality of this tool for future clinical use.

S100A6 promotes proliferation of intrahepatic cholangiocarcinoma cells via the activation of the p38/MAPK pathway

Aim: We explored the expression of S100A6 and its role in intrahepatic cholangiocarcinoma (ICC). Methods: The expression of S100A6 in ICC samples was detected by immunohistochemistry. In vitro experiments, we silenced and overexpressed S100A6 to investigate its role in cell functions. Results: The expression of S100A6 was markedly increased in ICC tissues and cell lines. S100A6 overexpression was an independent risk factor for patients’ survival. Silencing S100A6 resulted in a suppression of proliferation and p38/MAPK activity, while overexpressing S100A6 caused a promotion of proliferation and p38/MAPK. Discussion: S100A6 participated in the proliferation of ICC cells and correlated with a more aggressive behavior of ICC. Conclusion: S100A6 may serve as a novel prognostic marker and a potential therapeutic target for ICC patients.

Role of the Notch signaling in cholangiocarcinoma

INTRODUCTION

Cholangiocarcinoma (CCA) is an emerging cancer entity of the liver, associated with poor outcome and characterized by resistance to conventional chemotherapeutic treatments. In the last decade, many signaling pathways associated with CCA development and progression have been identified and are currently under intense investigation. Cumulating evidence indicates that the Notch cascade, a highly-conserved pathway in most multicellular organisms, is a critical player both in liver malignant transformation and tumor aggressiveness, thus representing a potential therapeutic target in this pernicious disease. Areas covered: In the present review article, we comprehensively summarize and critically discuss the current knowledge on the Notch pathway, its specific and key roles in cholangiocarcinogenesis, the treatment strategies aimed at suppressing this signaling cascade in cancer, and the encouraging results coming from preclinical trials. Expert opinion: The Notch pathway represents a major driver of carcinogenesis and a promising therapeutic target in human CCA. A better understanding of the molecular mechanisms triggered by the Notch pathway as well as its functional crosstalk with other signaling cascade will be highly helpful for the design of innovative therapies against human CCA.

Transforming Growth Factors α and β Are Essential for Modeling Cholangiocarcinoma Desmoplasia and Progression in a Three-Dimensional Organotypic Culture Model

To gain insight into the cellular and molecular interactions mediating the desmoplastic reaction and aggressive malignancy of mass-forming intrahepatic cholangiocarcinoma (ICC), we modeled ICC desmoplasia and progression in vitro. A unique three-dimensional (3D) organotypic culture model was established; within a dilute collagen-type I hydrogel, a novel clonal strain of rat cancer-associated myofibroblasts (TDF_SM) was co-cultured with a pure rat cholangiocarcinoma cell strain (TDE_CC) derived from the same ICC type as TDF_SM. This 3D organotypic culture model reproduced key features of desmoplastic reaction that closely mimicked those of the in situ tumor, as well as promoted cholangiocarcinoma cell growth and progression. Our results supported a resident liver mesenchymal cell origin of the TDF_SM cells, which were not neoplastically transformed. Notably, 3D co-culturing of TDE_CC cells with TDF_SM cells provoked the formation of a dense fibrocollagenous stroma in vitro that was associated with significant increases in both proliferative TDF_SM myofibroblastic cells and TDE_CC cholangiocarcinoma cells accumulating within the gel matrix. This dramatic desmoplastic ICC-like phenotype, which was not observed in the TDE_CC or TDF_SM controls, was highly dependent on transforming growth factor (TGF)-β, but not promoted by TGF-α. However, TGF-α was determined to be a key factor for promoting cholangiocarcinoma cell anaplasia, hyperproliferation, and higher malignant grading in this 3D culture model of desmoplastic ICC.

Clinical features, histology, and histogenesis of combined hepatocellular-cholangiocarcinoma

Combined hepatocellular-cholangiocarcinoma (CHC) is a rare tumor with poor prognosis, with incidence ranging from 1.0%-4.7% of all primary hepatic tumors. This entity will be soon renamed as hepato-cholangiocarcinoma. The known risk factors for hepatocellular carcinoma (HCC) have been implicated for CHC including viral hepatitis and cirrhosis. It is difficult to diagnose this tumor pre-operatively. The predominant histologic component within the tumor largely determines the predominant radiographic features making it a difficult distinction. Heterogeneous and overlapping imaging features of HCC and cholangiocarcinoma should raise the suspicion for CHC and multiple core biopsies (from different areas of tumor) are recommended before administering treatment. Serum tumor markers CA19-9 and alpha-fetoprotein can aid in the diagnosis, but it remains a challenging diagnosis prior to resection. There is sufficient data to support bipotent hepatic progenitor cells as the cell of origin for CHC. The current World Health Organization classification categorizes two main types of CHC based on histo-morphological features: Classical type and CHC with stem cell features. Liver transplant is one of the available treatment modalities with other management options including transarterial chemoembolization, radiofrequency ablation, and percutaneous ethanol injection. We present a review paper on CHC highlighting the risk factors, origin, histological classification and therapeutic modalities.

Meta-analysis of gene expression profiles identifies differential biomarkers for hepatocellular carcinoma and cholangiocarcinoma

Hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) are the members of hepatobiliary diseases. Both types of cancer often exert high levels of similarity in terms of phenotypic characteristics, thus leading to difficulties in HCC and CCA differential diagnoses. In this study, a transcriptome meta-analysis was performed on HCC and CCA microarray data to identify differential transcriptome networks and potential biomarkers for HCC and CCA. Raw data from nine gene expression profiling datasets, consisting of 1,185 samples in total, were methodologically compiled and analyzed. To evaluate differentially expressed (DE) genes in HCC and CCA, the levels of gene expression were compared between cancer and its normal counterparts (i.e., HCC versus normal liver and CCA versus normal bile duct) using t test (P < 0.05) and k-fold validation. A total of 226 DE genes were specific to HCC, 249 DE genes specific to CCA, and 41 DE genes in both HCC and CCA. Gene ontology and pathway enrichment analyses revealed different patterns between functional transcriptome networks of HCC and CCA. Cell cycle and glycolysis/gluconeogenesis pathways were exclusively dysregulated in HCC whereas complement and coagulation cascades as well as glycine, serine, and threonine metabolism were prodominantly differentially expressed in CCA. Our meta-analysis revealed distinct dysregulation in transcriptome networks between HCC and CCA. Certain genes in these networks were discussed in the context of HCC and CCA transition, unique characteristics of HCC and CCA, and their potentials as HCC and CCA differential biomarkers.