Characterisation of the Serum Metabolic Signature of Cholangiocarcinoma in a United Kingdom Cohort

Molecular and Metabolic Phenotyping of Hepatocellular Carcinoma for Biomarker Discovery: A Meta-Analysis

Identifying and translating hepatocellular carcinoma (HCC) biomarkers from bench to bedside using mass spectrometry-based metabolomics and lipidomics is hampered by inconsistent findings. Here, we investigated HCC at systemic and metabolism-centric multiomics levels by conducting a meta-analysis of quantitative evidence from 68 cohorts. Blood transcript biomarkers linked to the HCC metabolic phenotype were externally validated and prioritized. In the studies under investigation, about 600 metabolites were reported as putative HCC-associated biomarkers; 39, 20, and 10 metabolites and 52, 12, and 12 lipids were reported in three or more studies in HCC vs. Control, HCC vs. liver cirrhosis (LC), and LC vs. Control groups, respectively. Amino acids, fatty acids (increased 18:1), bile acids, and lysophosphatidylcholine were the most frequently reported biomarkers in HCC. BAX and RAC1 showed a good correlation and were associated with poor prognosis. Our study proposes robust HCC biomarkers across diverse cohorts using a data-driven knowledge-based approach that is versatile and affordable for studying other diseases.

Comparative analysis of bile metabolic profile in patients with biliary obstruction complicated by Clonorchis sinensis infection

Background

Clonorchiasis is an important foodborne parasitic disease. However, eggs of Clonorchis sinensis (C. sinensis) cannot be detected in feces during biliary obstruction. Moreover, many diseases can cause biliary obstruction, such as gallstones, adenocarcinoma, cholangiocarcinoma and Ascaris lumbricoides infection. Therefore, it is of great significance to distinguish between patients of biliary obstruction and biliary obstruction with C. sinensis infection.

Methods

A total of 48 biliary obstruction patients were enrolled, including 23 infected with C. sinensis (C. sinensis) (OB+C.s) and 25 non-infected subjects (OB). The bile samples were collected by endoscopic retrograde cholangiopancreatography and analyzed using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF MS). Additionally, multivariate statistical analysis methods were employed to identify differential metabolites. Next, bile amino acid levels were determined by targeted metabolomics analysis.

Result

A total of 146 and 132 significant metabolites were identified in electrospray ionization (ESI)+ and ESI- modes, respectively. The levels of amino acids (asparagine, glutamate, ornithine) and polyamines (spermidine and spermine) were significantly changed. Targeted analysis showed that the levels of amino acids (such as L-arginine, L-glutamine, L-lysine, L-propionic, and L-tyrosine) were lower in OB+C.s patients compared to those in OB patients. Marked metabolic pathways were involved in "Glutathione metabolism", "Caffeine metabolism", "Alanine, aspartate and glutamate metabolism", "Arginine and proline metabolism", "Purine metabolism", "Beta-Alanine metabolism", and "D-glutamine and D-glutamate metabolism".

Conclusion

These results show that there were significant differences between OB+C.s and OB patients, especially in amino acids. The metabolic signature and perturbations in metabolic pathways may help to better distinguish OB+C.s and OB patients.

Bile metabolites as diagnostic biomarkers for perihilar cholangiocarcinoma

It is difficult to directly obtain pathological diagnosis of perihilar cholangiocarcinoma (pCCA). Analysis of bile in the pCCA microenvironment, based on metabolomics and statistical methods, can help in clinical diagnosis. Clinical information, bile samples, blood liver function, blood CA199, CEA, and other indicators were collected from 33 patients with pCCA and 16 patients with gallstones. Bile samples were analyzed using untargeted metabolomics methods. A combination of multivariate and univariate analyses were used to screen for potential differential metabolites Through Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and differential metabolite remodeling, we explored changes in the pCCA pathway and potential therapeutic targets. There were significant differences in patient blood TBIL, ALT, AST, TBA, CA19-9, and CEA indices (p < 0.05, |log2(fc)| ≥ 1) between two groups. A significant correlation was found between these different indicators by Spearman's analysis. The clinical parameters were correlated with mass-to-charge ratios of 305 (Positive Ion Mode, POS) and 246 (Negative Ion Mode, NEG) in the metabolic group (|r| ≥ 0.7, P ≤ 10^-7). The result of this study indicated that bile untargeted metabolomics combined with statistical analysis techniques may be used for diagnose and treatment of pCCA.

The Role of Purine Metabolism-Related Genes PPAT and IMPDH1 in the Carcinogenesis of Intrahepatic Cholangiocarcinoma Based on Metabonomic and Bioinformatic Analyses

In this study, we investigated the role of tumor microenvironment and serum differential metabolites in intrahepatic cholangiocarcinoma (ICC) carcinogenesis, providing new evidence for ICC treatment. Serum samples from healthy individuals and ICC patients were collected for metabolomic analysis. The purine metabolites such as inosine, guanosine, hypoxanthine, and xanthine were increased in patient serum. TCGA database samples were collected, and the correlation between purine metabolism-related genes and ICC clinical features was analyzed using R language to obtain the differential genes including PPAT, PFAS, ATIC, and IMPDH2. High PPAT expression was associated with poor ICC prognosis. A PPAT silencing model in HCCC-9810 cells was constructed. The cell phenotype was examined by qRT-PCR, CCK-8, transwell, and flow cytometry, showing a decrease in IMPDH1 expression, colony and invasive cells numbers, and an increase in apoptosis. Guanosine reversed IMPDH1 expression in HCCC-9810 cells, promoting the secretion of inflammatory factors IL-6, IL-8, OPN, VEGF, and VCAM-1 and intensifying epithelial-mesenchymal transition (EMT) progression in the cells. In nude mice, the IMPDH1 inhibitory drug MMF inhibited tumor growth and reduced the expression of tumor stem cell characteristic markers CD133 and SOX2. Guanosine accelerated the malignant progression of ICC inhibition of purine metabolism-related genes, PPAT and IMPDH2, suppressed the malignant phenotype in HCCC-9810 cells, and inhibited tumor growth.

1H NMR fecal metabolic phenotyping of periductal fibrosis- and cholangiocarcinoma-specific metabotypes defining perturbation in gut microbial-host co-metabolism

Background

The liver fluke Opisthorchis viverrini (OV), which subsequently inhabits the biliary system and results in periductal fibrosis (PDF), is one of the primarily causes of cholangiocarcinoma (CCA), a bile duct cancer with an exceptionally high incidence in the northeast of Thailand and other Greater Mekong Subregion (GMS) countries. Insights in fecal metabolic changes associated with PDF and CCA are required for further molecular research related to gut health and potential diagnostic biological marker development.

Methods

In this study, nuclear magnetic resonance (NMR) metabolomics was applied for fecal metabolic phenotyping from 55 fecal water samples across different study groups including normal bile duct, PDF and CCA groups.

Results

By using NMR spectroscopy-based metabolomics, fecal metabolic profiles of patients with CCA or PDF and of individuals with normal bile duct have been established with a total of 40 identified metabolites. Further multivariate statistical analysis and hierarchical clustering heat map have demonstrated the PDF- and CCA-specific metabotypes through various altered metabolite groups including amino acids, alcohols, amines, anaerobic glycolytic metabolites, fatty acids, microbial metabolites, sugar, TCA cycle intermediates, tryptophan catabolism substrates, and pyrimidine metabolites. Compared to the normal bile duct group, PDF individuals showed the significantly elevated relative concentrations of fecal ethanol, glycine, tyrosine, and N-acetylglucosamine whereas CCA patients exhibited the remarkable fecal metabolic changes that can be evident through the increased relative concentrations of fecal uracil, succinate, and 5-aminopentanoate. The prominent fecal metabolic alterations between CCA and PDF were displayed by the reduction of relative concentration of methanol observed in CCA. The metabolic alterations associated with PDF and CCA progression have been proposed with the involvement of various metabolic pathways including TCA cycle, ethanol biogenesis, hexamine pathway, methanol biogenesis, pyrimidine metabolism, and lysine metabolism. Among them, ethanol, methanol, and lysine metabolism strongly reflect the association of gut-microbial host metabolic crosstalk in PDF and/or CCA patients.

Conclusion

The PDF- and CCA-associated metabotypes have been investigated displaying their distinct fecal metabolic patterns compared to that of normal bile duct group. Our study also demonstrated that the perturbation in co-metabolism of host and gut bacteria has been involved from the early step since OV infection to CCA tumorigenesis.

Novel approaches in search for biomarkers of cholangiocarcinoma

Cholangiocarcinoma (CCA) arises from the ductular epithelium of the biliary tree, either within the liver (intrahepatic CCA) or more commonly from the extrahepatic bile ducts (extrahepatic CCA). This disease has a poor prognosis and a growing worldwide prevalence. The poor outcomes of CCA are partially explained by the fact that a final diagnosis is challenging, especially the differential diagnosis between hepatocellular carcinoma and intrahepatic CCA, or distal CCA and pancreatic head adenocarcinoma. Most patients present with an advanced disease, unresectable disease, and there is a lack in non-surgical therapeutic modalities. Not least, there is an acute lack of prognostic biomarkers which further complicates disease management. Therefore, there is a dire need to find alternative diagnostic and follow-up pathways that can lead to an accurate result, either singlehandedly or combined with other methods. In the "-omics" era, this goal can be attained by various means, as it has been successfully demonstrated in other primary tumors. Numerous variants can reach a biomarker status ranging from circulating nucleic acids to proteins, metabolites, extracellular vesicles, and ultimately circulating tumor cells. However, given the relatively heterogeneous data, extracting clinical meaning from the inconsequential noise might become a tall task. The current review aims to navigate the nascent waters of the non-invasive approach to CCA and provide an evidence-based input to aid clinical decisions and provide grounds for future research.

Molecular Mechanisms Linking Risk Factors to Cholangiocarcinoma Development

The poor prognosis of cholangiocarcinoma in humans is related to several factors, such as (i) the heterogeneity of the disease, (ii) the late onset of symptoms and (iii) the limited comprehension of the carcinogenic pathways determining neoplastic changes, which all limit the pursuit of appropriate treatment. Several risk factors have been recognized, including different infective, immune-mediated, and dysmorphogenic disorders of the biliary tree. In this review, we report the details of possible mechanisms that lead a specific premalignant pathological condition to become cholangiocarcinoma. For instance, during liver fluke infection, factors secreted from the worms may play a major role in pathogenesis. In primary sclerosing cholangitis, deregulation of histamine and bile-acid signaling may determine important changes in cellular pathways. The study of these molecular events may also shed some light on the pathogenesis of sporadic (unrelated to risk factors) forms of cholangiocarcinoma, which represent the majority (nearly 75%) of cases.

Metabolic Profiling of Praziquantel-mediated Prevention of Opisthorchis viverrini-induced Cholangiocyte Transformation in the Hamster Model of Cholangiocarcinoma

BACKGROUND

Opisthorchis viverrini (Ov) infection-induced cholangiocarcinoma (CCA) is a major public health problem in northeastern Thailand. Praziquantel was shown to prevent CCA development in an Ov-infected hamster model; however, the molecular mechanism remains unknown.

MATERIALS AND METHODS

In this study, we used a hamster model with Ov and N-nitrosodimethylamine-induced CCA to study the mechanisms of praziquantel action. The liver tissues from the hamsters with and without praziquantel treatment were analyzed using ¹H nuclear magnetic resonance spectroscopy.

RESULTS

A total of 14 metabolites were found to be significantly different between the two groups. Furthermore, the combination of acetate, inosine and sarcosine was shown to exert an anti-inflammatory effect through interleukin-6 inhibition in a macrophage cell line, suggesting a mechanism by which praziquantel may prevent inflammation caused by Ov, cholangiocyte transformation and further CCA develpoment.

CONCLUSION

These findings might avail the development of a preventive strategy for CCA in high-risk populations.

Next-Generation Biomarkers for Cholangiocarcinoma

Simple Summary

Early and non-invasive diagnosis of cholangiocarcinoma (CCA) is still challenging, thus largely contributing to the increased mortality rates observed worldwide. Consequently, several efforts have been made in order to report novel biomarkers for CCA, that would aid on diagnosis and also to predict prognosis and therapy response. We herein aim to provide an in-depth and critical revision on the next-generation biomarkers for CCA that have been recently proposed.

Abstract

The increasing mortality rates of cholangiocarcinoma (CCA) registered during the last decades are, at least in part, a result of the lack of accurate non-invasive biomarkers for early disease diagnosis, making the identification of patients who might benefit from potentially curative approaches (i.e., surgery) extremely challenging. The obscure CCA pathogenesis and associated etiological factors, as well as the lack of symptoms in patients with early tumor stages, highly compromises CCA identification and to predict tumor development in at-risk populations. Currently, CCA diagnosis is accomplished by the combination of clinical/biochemical features, radiological imaging and non-specific serum tumor biomarkers, although a tumor biopsy is still needed to confirm disease diagnosis. Furthermore, prognostic and predictive biomarkers are still lacking and urgently needed. During the recent years, high-throughput omics-based approaches have identified novel circulating biomarkers (diagnostic and prognostic) that might be included in large, international validation studies in the near future. In this review, we summarize and discuss the most recent advances in the field of biomarker discovery in CCA, providing new insights and future research directions.

The role of bile acid subtypes in the diagnosis of cholangiocarcinoma

OBJECTIVES

To find the potential biomarkers of cholangiocarcinoma, form a biomarker package, evaluate its efficiency, and validate it.

METHODS

R software was used to analyze the differential expression of mRNAs between cholangiocarcinoma and adjacent nontumorous tissues, obtained from The Cancer Genome Atlas (TCGA), and enrich the KEGG pathway. Metabo-Profile Inc. performed the comprehensive bile acid profiling and quantitation. The training set concluded 20 cholangiocarcinoma and 20 nontumorous volunteers. Receiver operating characteristic (ROC) curve and accompanying area under the curve (AUC) was calculated. The top four bile acids formed a new biomarker package. The validation set included 15 cholangiocarcinoma and 15 nontumorous, and the sensitivity and specificity of the new biomarker package were tested.

RESULTS

Gene expression of 36 cholangiocarcinoma and nine adjacent nontumorous tissues was obtained in January 2020. Totally 9887 differential genes were eligible (logFC ≥ 1 or ≤ -1, P < 0.05, and adjust P < 0.01). GO analysis showed that 20 KEGG pathways were enriched, including primary bile acid biosynthesis and bile secretion. Comprehensive bile acid profiling and quantitation showed 15 differential bile acid types, and the ROC-AUC was between 0.953 and 0.750. HDCA, isoLCA, bCDCA, and DCA were selected to form a biomarker package. The Logit (p = cholangiocarcinoma) = 7.898 - 3.70*(1isoLCA) - 0.444*(bCDCA) + 0.415*(HDCA) + 0.041*DCA. Its ROC-AUC was 0.944. In the validation set, the sensitivity was 0.933 and the specificity was 0.867.

CONCLUSION

Bile acid types package was efficient to distinguish nontumorous population and cholangiocarcinoma. The difference might be associated to the downregulation of primary bile acid biosynthesis and bile secretion pathway of cholangiocarcinoma.

Omics-Based Platforms: Current Status and Potential Use for Cholangiocarcinoma

Cholangiocarcinoma (CCA) has been identified as a highly malignant cancer that can be transformed from epithelial cells of the bile duct, including intrahepatic, perihilar and extrahepatic. High-resolution imaging tools (abdominal ultrasound, computed tomography and percutaneous transhepatic cholangial drainage) are recruited for diagnosis. However, the lack of early diagnostic biomarkers and treatment evaluation can lead to serious outcomes and poor prognosis (i.e., CA19-9, MUC5AC). In recent years, scientists have established a large number of omics profiles to reveal underlying mechanisms and networks (i.e., IL-6/STAT3, NOTCH). With these results, we achieved several genomic alteration events (i.e., TP53_mut, KRAS_mut) and epigenetic modifications (i.e., DNA methylation, histone modification) in CCA cells and clinical patients. Moreover, we reviewed candidate gene (such as NF-kB, YAP1) that drive gene transcription factors and canonical pathways through transcriptomics profiles (including microarrays and next-generation sequencing). In addition, the proteomics database also indicates which molecules and their directly binding status could trigger dysfunction signatures in tumorigenesis (carbohydrate antigen 19-9, mucins). Most importantly, we collected metabolomics datasets and pivotal metabolites. These results reflect the pharmacotherapeutic options and evaluate pharmacokinetic/pharmacodynamics in vitro and in vivo. We reversed the panels and selected many potentially small compounds from the connectivity map and L1000CDS² system. In this paper, we summarize the prognostic value of each candidate gene and correlate this information with clinical events in CCA. This review can serve as a reference for further research to clearly investigate the complex characteristics of CCA, which may lead to better prognosis, drug repurposing and treatment strategies.