Comprehensive analysis of transcriptome and metabolome analysis in Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma

Unveil Intrahepatic Cholangiocarcinoma Heterogeneity through the Lens of Omics and Multi-Omics Approaches

Intrahepatic cholangiocarcinoma (iCCA) is recognized worldwide as the second leading cause of morbidity and mortality among primary liver cancers, showing a continuously increasing incidence rate in recent years. iCCA aggressiveness is revealed through its rapid and silent intrahepatic expansion and spread through the lymphatic system leading to late diagnosis and poor prognoses. Multi-omics studies have aggregated information derived from single-omics data, providing a more comprehensive understanding of the phenomena being studied. These approaches are gradually becoming powerful tools for investigating the intricate pathobiology of iCCA, facilitating the correlation between molecular signature and phenotypic manifestation. Consequently, preliminary stratifications of iCCA patients have been proposed according to their "omics" features opening the possibility of identifying potential biomarkers for early diagnosis and developing new therapies based on personalized medicine (PM). The focus of this review is to provide new and advanced insight into the molecular pathobiology of the iCCA, starting from single- to the latest multi-omics approaches, paving the way for translating new basic research into therapeutic practices.

Multi-Omics Classification of Intrahepatic Cholangiocarcinoma: A Systematic Review and Meta-Analysis

Intrahepatic cholangiocarcinoma (ICC) is a heterogeneous disease characterized by a dismal prognosis. Various attempts have been made to classify ICC subtypes with varying prognoses, but a consensus has yet to be reached. This systematic review aims to gather relevant data on the multi-omics-based ICC classification. The PubMed, Embase, and Cochrane databases were searched for terms related to ICC and multi-omics analysis. Studies that identified multi-omics-derived ICC subtypes and investigated clinicopathological predictors of long-term outcomes were included. Nine studies, which included 910 patients, were considered eligible. Mean 3- and 5-year overall survival were 25.7% and 19.6%, respectively, for the multi-omics subtypes related to poor prognosis, while they were 70.2% and 63.3%, respectively, for the subtypes linked to a better prognosis. Several negative prognostic factors were identified, such as genes' expression profile promoting inflammation, mutations in the KRAS gene, advanced tumor stage, and elevated levels of oncological markers. The subtype with worse clinicopathological characteristics was associated with worse survival (Ref.: good prognosis subtype; pooled hazard ratio 2.06, 95%CI 1.67-2.53). Several attempts have been made to classify molecular ICC subtypes, but they have yielded heterogeneous results and need a clear clinical definition. More efforts are required to build a comprehensive classification system that includes both molecular and clinical characteristics before implementation in clinical practice to facilitate decision-making and select patients who may benefit the most from comprehensive molecular profiling in the disease's earlier stages.

Establishment and validation of a nomogram containing cytokeratin fragment antigen 21-1 for the differential diagnosis of intrahepatic cholangiocarcinoma and hepatocellular carcinoma

Background

Our study aimed to develop a nomogram incorporating cytokeratin fragment antigen 21-1 (CYFRA21-1) to assist in differentiating between patients with intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC).

Methods

A total of 487 patients who were diagnosed with ICC and HCC at Qilu Hospital of Shandong University were included in this study. The patients were divided into a training cohort and a validation cohort based on whether the data collection was retrospective or prospective. Univariate and multivariate analyses were employed to select variables for the nomogram. The discrimination and calibration of the nomogram were evaluated using the area under the receiver operating characteristic curve (AUC) and calibration plots. Decision curve analysis (DCA) was used to assess the nomogram's net benefits at various threshold probabilities.

Results

Six variables, including CYFRA21-1, were incorporated to establish the nomogram. Its satisfactory discriminative ability was indicated by the AUC (0.972 for the training cohort, 0.994 for the validation cohort), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) values. The Hosmer-Lemeshow test and the calibration plots demonstrated favorable consistency between the nomogram predictions and the actual observations. Moreover, DCA revealed the clinical utility and superior discriminative ability of the nomogram compared to the model without CYFRA21-1 and the model consisting of the logarithm of alpha-fetoprotein (Log AFP) and the logarithm of carbohydrate antigen 19-9 (Log CA19-9). Additionally, the AUC values suggested that the discriminative ability of Log CYFRA21-1 was greater than that of the other variables used as diagnostic biomarkers.

Conclusions

This study developed and validated a nomogram including CYFRA21-1, which can aid clinicians in the differential diagnosis of ICC and HCC patients.

Characterization of circulating miRNAs in the treatment of primary liver tumors

BACKGROUND AND AIM

Circulating micro RNAs (miRNAs) indicate clinical pathologies such as inflammation and carcinogenesis. In this study, we aimed to investigate whether miRNA expression level patterns in could be used to diagnose hepatocellular carcinoma (HCC) and biliary tract cancer (BTC), and the relationship miRNA expression patterns and cancer etiology.

METHODS

Patients with HCC and BTC with indications for surgery were selected for the study. Total RNA was extracted from the extracellular vesicle (EV)-rich fraction of the serum and analyzed using Toray miRNA microarray. Samples were divided into two cohorts in order of collection, the first 85 HCC were analyzed using a microarray based on miRBase ver.2.0 (hereafter v20 cohort), and the second 177 HCC and 43 BTC were analyzed using a microarray based on miRBase ver.21 (hereafter v21 cohort).

RESULTS

Using miRNA expression patterns, we found that HCC and BTC could be identified with an area under curve (AUC) 0.754 (v21 cohort). Patients with anti-hepatitis C virus (HCV) treatment (SVR-HCC) and without antiviral treatment (HCV-HCC) could be distinguished by an AUC 0.811 (v20 cohort) and AUC 0.798 (v21 cohort), respectively.

CONCLUSIONS

In this study, we could diagnose primary hepatic malignant tumor using miRNA expression patterns. Moreover, the difference of miRNA expression in SVR-HCC and HCV-HCC can be important information for enclosing cases that are prone to carcinogenesis after being cured with antiviral agents, but also for uncovering the mechanism for some carcinogenic potential remains even after persistent virus infection has disappeared.

Metabolic reprogramming in the tumor microenvironment of liver cancer

The liver is essential for metabolic homeostasis. The onset of liver cancer is often accompanied by dysregulated liver function, leading to metabolic rearrangements. Overwhelming evidence has illustrated that dysregulated cellular metabolism can, in turn, promote anabolic growth and tumor propagation in a hostile microenvironment. In addition to supporting continuous tumor growth and survival, disrupted metabolic process also creates obstacles for the anticancer immune response and restrains durable clinical remission following immunotherapy. In this review, we elucidate the metabolic communication between liver cancer cells and their surrounding immune cells and discuss how metabolic reprogramming of liver cancer impacts the immune microenvironment and the efficacy of anticancer immunotherapy. We also describe the crucial role of the gut-liver axis in remodeling the metabolic crosstalk of immune surveillance and escape, highlighting novel therapeutic opportunities.

Metabolic reprogramming and its clinical implication for liver cancer

Cancer cells often encounter hypoxic and hypo-nutrient conditions, which force them to make adaptive changes to meet their high demands for energy and various biomaterials for biomass synthesis. As a result, enhanced catabolism (breakdown of macromolecules for energy production) and anabolism (macromolecule synthesis from bio-precursors) are induced in cancer. This phenomenon is called "metabolic reprogramming," a cancer hallmark contributing to cancer development, metastasis, and drug resistance. HCC and cholangiocarcinoma (CCA) are 2 different liver cancers with high intertumoral heterogeneity in terms of etiologies, mutational landscapes, transcriptomes, and histological representations. In agreement, metabolism in HCC or CCA is remarkably heterogeneous, although changes in the glycolytic pathways and an increase in the generation of lactate (the Warburg effect) have been frequently detected in those tumors. For example, HCC tumors with activated β-catenin are addicted to fatty acid catabolism, whereas HCC tumors derived from fatty liver avoid using fatty acids. In this review, we describe common metabolic alterations in HCC and CCA as well as metabolic features unique for their subsets. We discuss metabolism of NAFLD as well, because NAFLD will likely become a leading etiology of liver cancer in the coming years due to the obesity epidemic in the Western world. Furthermore, we outline the clinical implication of liver cancer metabolism and highlight the computation and systems biology approaches, such as genome-wide metabolic models, as a valuable tool allowing us to identify therapeutic targets and develop personalized treatments for liver cancer patients.

Interplay between the Human Microbiome and Biliary Tract Cancer: Implications for Pathogenesis and Therapy

Biliary tract cancer, encompassing intrahepatic and extrahepatic cholangiocarcinoma as well as gallbladder carcinoma, stands as a prevalent malignancy characterized by escalating incidence rates and unfavorable prognoses. The onset of cholangiocarcinoma involves a multitude of risk factors and could potentially be influenced by microbial exposure. The human microbiome, encompassing the entirety of human microbial genetic information, assumes a pivotal role in regulating key aspects such as host digestion, absorption, immune responses, and metabolism. The widespread application of next-generation sequencing technology has notably propelled investigations into the intricate relationship between the microbiome and diseases. An accumulating body of evidence strongly suggests a profound interconnection between biliary tract cancer and the human microbiome. This article critically appraises the existing evidence pertaining to the microbiome milieu within patients afflicted by biliary tract cancer. Furthermore, it delves into potential mechanisms through which dysregulation of the human microbiome could contribute to the advancement of biliary tract cancer. Additionally, the article expounds on its role in the context of chemotherapy and immunotherapy for biliary tract cancer.

An integrated mRNA-lncRNA signature for overall survival prediction in cholangiocarcinoma

The combination of mRNA and lncRNA profiles for establishing an integrated mRNA-lncRNA prognostic signature has remained unexplored in cholangiocarcinoma (CCA) patients. We utilized a training dataset of 36 samples from The Cancer Genome Atlas dataset and a validation cohort (GSE107943) of 30 samples from Gene Expression Omnibus. Two mRNAs (CFHR3 and PIWIL4) and 2 lncRNAs (AC007285.1 and AC134682.1) were identified to construct the integrated signature through a univariate Cox regression (P-value = 1.35E-02) and a multivariable Cox analysis (P-value = 3.07E-02). Kaplan-Meier curve showed that patients with low risk scores had notably prolonged overall survival than those with high risk scores (P-value = 4.61E-03). Subsequently, the signature was validated in GSE107943 cohort with an area under the curve of 0.750 at 1-year and 0.729 at 3-year. The signature was not only independent from diverse clinical features (P-value = 3.07E-02), but also surpassed other clinical characteristics as prognostic biomarkers with area under the curve of 0.781 at 3-year. Moreover, the weighted gene co-expression network analysis and gene enrichment analyses found that the integrated signature were associated with metabolic-related biological process and lipid metabolism pathway, which has been implicated in the pathogenesis of CCA. Taken together, we developed an integrated mRNA-lncRNA signature that had an independent prognostic value in the risk stratification of patients with CCA.

Integration analysis of miRNA-mRNA expression exploring their potential roles in intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is the second common primary hepatic malignancy tumor. In this study, an integrative analysis of differentially expressed genes (DEGs) and miRNAs from the ICC onset and adjacent normal tissues were performed to explore the regulatory roles of miRNA-mRNA interaction. A total of 1018 DEGs and 39 miRNAs were likely involved in ICC pathogenesis, suggesting the changes in cell metabolism in ICC development. The built network indicated that 30 DEGs were regulated by 16 differentially expressed miRNA. The screened DEGs and miRNA together were probably considered the biomarkers of ICC, and their important roles in ICC pathogenesis remain to be elucidated. This study could provide a good basis to uncover the regulatory mechanism of miRNA and mRNAs in ICC pathogenesis.

Comprehensive transcriptomic analysis to identify biological and clinical differences in cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma (CC) is a rare and aggressive disease with limited therapeutic options and a poor prognosis. All available public records of cohorts reporting transcriptomic data on intrahepatic cholangiocarcinoma (ICC) and extrahepatic cholangiocarcinoma (ECC) were collected with the aim to provide a comprehensive gene expression-based classification with clinical relevance.

METHODS

A total of 543 patients with primary tumor tissues profiled by RNAseq and microarray platforms from seven public datasets were used as a discovery set to identify distinct biological subgroups. Group predictors developed on the discovery sets were applied to a single cohort of 131 patients profiled with RNAseq for validation and assessment of clinical relevance leveraging machine learning techniques.

RESULTS

By unsupervised clustering analysis of gene expression data we identified both in the ICC and ECC discovery datasets four subgroups characterized by a distinct type of immune infiltrate and signaling pathways. We next developed class predictors using short gene list signatures and identified in an independent dataset subgroups of ICC tumors at different prognosis.

CONCLUSIONS

The developed class-predictor allows identification of CC subgroups with specific biological features and clinical behavior at single-sample level. Such results represent the starting point for a complete molecular characterization of CC, including integration of genomics data to develop in clinical practice.

Prognostic value of des-γ-carboxyprothrombin in patients with AFP-negative HCC treated with TACE

In patients with AFP-negative hepatocellular carcinoma (HCC), des-γ-carboxyprothrombin (DCP) is an important prognostic indicator for the preoperative assessment of transarterial chemoembolization (TACE). However, the association between the serum DCP levels and the degree of progression and prognosis of patients with AFP-negative HCC treated with TACE has not been thoroughly investigated to date, and the molecular mechanism is also unclear. The present study retrospectively analyzed the clinical data of 107 patients with AFP-negative HCC treated with TACE and divided them into two groups based on the median serum DCP levels. The association between DCP and the clinical characteristics of the patients was analyzed, and the survival data were analyzed using Kaplan-Meier curves and Cox regression models. The results demonstrated that the median follow-up time was 755 days (range, 64-1,556 days), and patients in the low-DCP group (n=11; 20.8%) had a lower mortality rate than those in the high-DCP group (n=20; 37.0%). Cox multivariate regression analysis suggested that preoperative lymph node metastasis [hazard ratio (HR), 3.903; 95% CI, 1.778-8.519; P=0.001] and DCP group (HR, 2.465; 95% CI, 1.038-5.854; P=0.041) were independent risk factors. Furthermore, the Gene Expression Omnibus database was utilized to screen differentially expressed mRNAs. Enrichment analyses were then performed, and a protein-protein interaction (PPI) network was constructed to identify hub genes. A total of 169 differentially expressed genes were screened. Enrichment analyses revealed that cancer-related and ribosomal pathways were significantly enriched. Furthermore, 10 hub genes were identified in the PPI network by counting the number of gene interactions, the majority of which belonged to the ribosomal protein (RPS) family, and the top three significant genes were RPS23, RPS11 and RPS3A. In patients with AFP-negative HCC, higher serum DCP levels were associated with poor prognosis after TACE. This may be associated with genes such as those belonging to the RPS family, which may contribute to future personalized therapy for this disease.

Metabolic reprogramming in cholangiocarcinoma

Metabolic reprogramming is a hallmark of cancer and allows tumour cells to meet the increased energy demands required for rapid proliferation, invasion, and metastasis. Indeed, many tumour cells acquire distinctive metabolic and bioenergetic features that enable them to survive in resource-limited conditions, mainly by harnessing alternative nutrients. Several recent studies have explored the metabolic plasticity of cancer cells with the aim of identifying new druggable targets, while therapeutic strategies to limit the access to nutrients have been successfully applied to the treatment of some tumours. Cholangiocarcinoma (CCA), a highly heterogeneous tumour, is the second most common form of primary liver cancer. It is characterised by resistance to chemotherapy and poor prognosis, with 5-year survival rates of below 20%. Deregulation of metabolic pathways have been described during the onset and progression of CCA. Increased aerobic glycolysis and glutamine anaplerosis provide CCA cells with the ability to generate biosynthetic intermediates. Other metabolic alterations involving carbohydrates, amino acids and lipids have been shown to sustain cancer cell growth and dissemination. In this review, we discuss the complex metabolic rewiring that occurs during CCA development and leads to unique nutrient addiction. The possible role of therapeutic interventions based on metabolic changes is also thoroughly discussed.

Linoleic acid pathway disturbance contributing to potential cancerization of intrahepatic bile duct stones into intrahepatic cholangiocarcinoma

Background

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary hepatic malignancy with poor prognosis. Intrahepatic bile duct stone (IBDS) is one of the key causes to ICC occurrence and can increase morbidity rate of ICC about forty times. However, the specific carcinogenesis of IBDS is still far from clarified. Insight into the metabolic phenotype difference between IBDS and ICC can provide potential mechanisms and therapeutic targets, which is expected to inhibit the carcinogenesis of IBDS and improve the prognosis of ICC.

Methods

A total of 34 participants including 25 ICC patients and 9 IBDS patients were recruited. Baseline information inclusive of liver function indicators, tumor biomarkers, surgery condition and constitution parameters etc. from patients were recorded. ICC and IBDS pathological tissues, as well as ICC para-carcinoma tissues, were collected for GC–MS based metabolomics experiments. Multivariate analysis was performed to find differentially expressed metabolites and differentially enriched metabolic pathways. Spearman correlation analysis was then used to construct correlation network between key metabolite and baseline information of patients.

Results

The IBDS tissue and para-carcinoma tissue have blurred metabolic phenotypic differences, but both of them essentially distinguished from carcinoma tissue of ICC. Metabolic differences between IBDS and ICC were enriched in linoleic acid metabolism pathway, and the level of 9,12-octadecadienoic acid in IBDS tissues was almost two times higher than in ICC pathological tissues. The correlation between 9,12-octadecadienoic acid level and baseline information of patients demonstrated that 9,12-octadecadienoic acid level in pathological tissue was negative correlation with gamma-glutamyl transpeptidase (GGT) and alkaline phosphatase (ALP) level in peripheral blood. These two indicators were all cancerization marker for hepatic carcinoma and disease characteristic of IBDS.

Conclusion

Long-term monitoring of metabolites from linoleic acid metabolism pathway and protein indicators of liver function in IBDS patients has important guiding significance for the monitoring of IBDS carcinogenesis. Meanwhile, further insight into the causal relationship between linoleic acid pathway disturbance and changes in liver function can provide important therapeutic targets for both IBDS and ICC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02354-2.

Serum metabolomic profiling for patients with adenocarcinoma of the esophagogastric junction

INTRODUCTION

The incidence of adenocarcinoma in the esophagogastric junction (AEG) has increased in the recent years. AEG is reported to have a worse prognosis compared with tumor confined to the stomach (non-AEG). Although the metabolic changes of non-AEG have been investigated in extensive studies, little effort focused on the metabolic profiling of AEG serum.

OBJECTIVES

Here we report an untargeted gas chromatography-mass spectrometry (GC-MS) method to explore the abnormal metabolism underlying AEG.

METHODS

GC-MS-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of serum samples from AEG patients (n = 70), non-AEG patients (n = 70) and health controls (n = 71).

RESULTS

A novel serum metabolic profiling of 18 metabolites from patients of AEG and non-AEG was indicated, in comparison with health controls. Moreover, AEG and non-AEG were also well-classified with 9 distinguishing metabolites including hypoxanthine, alanine, proline, pyroglutamate, glycine, lactate, succinic acid, glutamate and kynurenine, which produced a discriminatory model with an area under the Receiver Operating Characteristic (ROC) curve of 0.852, suggesting a distinct metabolic signature of AEG. Importantly, lactate and glutamate disclosed outcome-prediction values by multivariate cox-proportional hazard model and Kaplan-Meier method based on follow-up information for 2-5 years.

CONCLUSION

This is the first metabolomics study to identify serum metabolic signature of AEG. The distinguishing metabolites show a promising application on clinical diagnose and outcome prediction, and allow us to unveil several key metabolic variations coexisting in AEG, which may aid to understand the underlying metabolic mechanisms.

RTK25: A Comprehensive Molecular Profiling Strategy in Cholangiocarcinoma Using an Integrated Bioinformatics Approach

Cholangiocarcinoma (CCA) is a heterogeneous group of malignancies that primarily originate from the bile duct. Tumor heterogeneity is a prime characteristic of CCA and considering the scarcity of approved targeted therapy drugs, this makes precision oncology impractical in CCA. Stratifying patients based on their molecular signature and biomarker-guided therapy may offer a conducive solution. Receptors tyrosine kinases (RTK) are potential targets for novel therapeutic strategies in CCA as RTK signaling is dysregulated in CCA. This study aims to identify targetable RTK profile in CCA using a bioinformatic approach. We discovered that CCA samples could be grouped into molecular subtypes based on the gene expression profile of selected RTKs (RTK25). Using the RTK25 gene list, we discovered five distinct molecular subtypes of CCA in this cohort. Tyrosine kinase inhibitors that target each RTK profile and their subsequent molecular signatures were also discovered. These results suggest that certain RTKs correlate with each other, indicating that tailored dual inhibition of RTKs may be more favorable than monotherapy. The results from this study can direct future investigative attention towards validating this concept in in vivo and in vitro systems. Ultimately, this will facilitate biomarker-guided clinical trials for the successful approval of novel therapeutic options in CCA.

PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients

Coronavirus disease 2019 (COVID-19) is raging worldwide. This potentially fatal infectious disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the complete mechanism of COVID-19 is not well understood. Therefore, we analyzed gene expression profiles of COVID-19 patients to identify disease-related genes through an innovative machine learning method that enables a data-driven strategy for gene selection from a data set with a small number of samples and many candidates. Principal-component-analysis-based unsupervised feature extraction (PCAUFE) was applied to the RNA expression profiles of 16 COVID-19 patients and 18 healthy control subjects. The results identified 123 genes as critical for COVID-19 progression from 60,683 candidate probes, including immune-related genes. The 123 genes were enriched in binding sites for transcription factors NFKB1 and RELA, which are involved in various biological phenomena such as immune response and cell survival: the primary mediator of canonical nuclear factor-kappa B (NF-κB) activity is the heterodimer RelA-p50. The genes were also enriched in histone modification H3K36me3, and they largely overlapped the target genes of NFKB1 and RELA. We found that the overlapping genes were downregulated in COVID-19 patients. These results suggest that canonical NF-κB activity was suppressed by H3K36me3 in COVID-19 patient blood.

A Contemporary Approach to Diagnosis and Treatment of Combined Hepatocellular-Cholangiocarcinoma

Purpose of review

To provide updates on terminology, epidemiology, diagnosis, and treatment of combined hepatocellular-cholangiocarcinoma (cHCC-CCA).

Recent findings

cHCC-CCAs are tumors that in the same nodule contain a variable degree of HCC and CCA components with a transition zone. cHCC-CCAs develop in cirrhotic and non-cirrhotic livers like and is associated with poor outcomes. Mutations in TP53, TERT promoter, and ARID1A are the most common genetic aberrations in cHCC-CCA. Fusion gene PTMS-AP1G1 is unique for cHCC-CCA. A biopsy is required for diagnosis. Surgical resection remains treatment of choice, while liver transplantation for early cHCC-CCA is associated with favorable outcomes. Gemcitabine-based therapy shows benefits for advanced cHCC-CCA.

Summary

cHCC-CCAs are a heterogeneous group of primary liver cancers with unique biological behavior. Multicenter studies are required for a molecular analysis to inform novel therapeutic approaches, and understand epidemiology and benefits of liver transplantation, liver-directed and targeted therapies for this rare aggressive cancer.

Identification of Prognostic Markers in Cholangiocarcinoma Using Altered DNA Methylation and Gene Expression Profiles

Background

Cholangiocarcinoma (CCA) is a rare disease, but it is amongst the most lethal cancers with a median survival under 1 year. Variations in DNA methylation and gene expression have been extensively studied in other cancers for their role in pathogenesis and disease prognosis, but these studies are very limited in CCA. This study focusses on the identification of DNA methylation and gene expression prognostic biomarkers using multi-omics data of CCA tumors from The Cancer Genome Atlas (TCGA).

Method

We have conducted a genome-wide analysis of differential DNA methylation and gene/miRNA expression using data from 36 CCA tumor and 9 normal samples from TCGA. The impact of DNA methylation in promoters and long-range distal enhancers on the regulation and expression of CCA-associated genes was examined using linear regression. Next, we conducted network analyses on genes which are regulated by DNA methylation as well as by miRNA. Finally, we performed Kaplan–Meier and Cox proportional hazards regression analyses in order to identify the role of selected methylation sites and specific genes and miRNAs in patient survival. We also performed real-time quantitative PCR (qPCR) to confirm the change in gene expression in CCA patients’ tumor and adjacent normal samples.

Results

Altered DNA methylation was observed on 12,259 CpGs across all chromosomes, of which 78% were hypermethylated. We observed a strong negative relationship between promoter hypermethylation and corresponding gene expression in 92% of the CpGs. Differential expression analyses revealed altered expression patterns in 3,305 genes and 101 miRNAs. Finally, we identified 17 differentially methylated promoter CpGs, 72 differentially expressed genes, and two miRNAs that are likely associated with patient survival. Pathway analysis suggested that cell division, bile secretion, amino acid metabolism, PPAR signaling, hippo signaling were highly affected by gene expression and DNA methylation alterations. The qPCR analysis further confirmed that MDK, HNF1B, PACS1, and GLUD1 are differentially expressed in CCA.

Conclusion

Based on the survival analysis, we conclude that DEPDC1, FUT4, MDK, PACS1, PIWIL4 genes, miR-22, miR-551b microRNAs, and cg27362525 and cg26597242 CpGs can strongly support their use as prognostic markers of CCA.

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.

Integrated Bioinformatics analysis and clinical validation reveals that high expression of mucin 1 in intrahepatic cholangiocarcinoma predicts recurrence after curative resection

Intrahepatic cholangiocarcinoma (ICC) is a cancer type with high malignancy and a current lack of biomarkers to predict recurrence. In the present study, to identify potential biomarkers, five ICC datasets from the Gene Expression Omnibus database were analyzed to construct initial datasets by using a robust rank aggregation approach. A total of 19 upregulated genes were identified in the initial datasets. The genes identified were then further analysed using data from The Cancer Genome Atlas. Only mucin 1 (MUC1) exhibited significance regarding differential expression and survival prediction. Finally, the expression levels of MUC1 were assessed using reverse transcription-quantitative PCR in 61 pairs of ICC tumor and matched non-cancerous samples. The expression of MUC1 was significantly elevated in ICC tissues compared with that in matched non-cancerous counterparts (P=0.001). Patients with high MUC1 expression levels had significantly shorter overall survival (OS, P=0.009) and recurrence-free survival (RFS, P=0.012). MUC1 was identified as an independent prognostic factor for OS [hazard ratio (HR)=2.364, 95%CI: 1.214-4.485; P=0.023] and RFS (HR=2.552 95%CI: 1.294-5.032; P=0.007) in the multivariate analysis. Using receiver operating characteristic analysis, a co-index including MUC1 had a high accuracy for predicting survival [MUC1 combined with serum levels of CEA and cancer antigen 19-9, and lymph node metastasis, area under curve (AUC)=0.746, 95%CI: 0.620-0.872] and recurrence (MUC1 combined with bile duct invasion and lymph node metastasis, AUC=0.729, 95%CI: 0.605-854). In conclusion, MUC1 is highly expressed in ICC tissue and is a potential prognostic biomarker and therapeutic target for ICC.

Modeling of Nanotherapy Response as a Function of the Tumor Microenvironment: Focus on Liver Metastasis

The tumor microenvironment (TME) presents a challenging barrier for effective nanotherapy-mediated drug delivery to solid tumors. In particular for tumors less vascularized than the surrounding normal tissue, as in liver metastases, the structure of the organ itself conjures with cancer-specific behavior to impair drug transport and uptake by cancer cells. Cells and elements in the TME of hypovascularized tumors play a key role in the process of delivery and retention of anti-cancer therapeutics by nanocarriers. This brief review describes the drug transport challenges and how they are being addressed with advanced in vitro 3D tissue models as well as with in silico mathematical modeling. This modeling complements network-oriented techniques, which seek to interpret intra-cellular relevant pathways and signal transduction within cells and with their surrounding microenvironment. With a concerted effort integrating experimental observations with computational analyses spanning from the molecular- to the tissue-scale, the goal of effective nanotherapy customized to patient tumor-specific conditions may be finally realized.

Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis

MetaboAnalyst (https://www.metaboanalyst.ca) is an easy-to-use web-based tool suite for comprehensive metabolomic data analysis, interpretation, and integration with other omics data. Since its first release in 2009, MetaboAnalyst has evolved significantly to meet the ever-expanding bioinformatics demands from the rapidly growing metabolomics community. In addition to providing a variety of data processing and normalization procedures, MetaboAnalyst supports a wide array of functions for statistical, functional, as well as data visualization tasks. Some of the most widely used approaches include PCA (principal component analysis), PLS-DA (partial least squares discriminant analysis), clustering analysis and visualization, MSEA (metabolite set enrichment analysis), MetPA (metabolic pathway analysis), biomarker selection via ROC (receiver operating characteristic) curve analysis, as well as time series and power analysis. The current version of MetaboAnalyst (4.0) features a complete overhaul of the user interface and significantly expanded underlying knowledge bases (compound database, pathway libraries, and metabolite sets). Three new modules have been added to support pathway activity prediction directly from mass peaks, biomarker meta-analysis, and network-based multi-omics data integration. To enable more transparent and reproducible analysis of metabolomic data, we have released a companion R package (MetaboAnalystR) to complement the web-based application. This article provides an overview of the main functional modules and the general workflow of MetaboAnalyst 4.0, followed by 12 detailed protocols: © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: Data uploading, processing, and normalization Basic Protocol 2: Identification of significant variables Basic Protocol 3: Multivariate exploratory data analysis Basic Protocol 4: Functional interpretation of metabolomic data Basic Protocol 5: Biomarker analysis based on receiver operating characteristic (ROC) curves Basic Protocol 6: Time-series and two-factor data analysis Basic Protocol 7: Sample size estimation and power analysis Basic Protocol 8: Joint pathway analysis Basic Protocol 9: MS peaks to pathway activities Basic Protocol 10: Biomarker meta-analysis Basic Protocol 11: Knowledge-based network exploration of multi-omics data Basic Protocol 12: MetaboAnalystR introduction.

Liquid Biopsies in Hepatocellular Carcinoma: Are We Winning?

Hepatocellular carcinoma (HCC) represents the sixth most common cancer worldwide and the third most common cause of cancer-related death. One of the major problems faced by researchers and clinicians in this area is the lack of reliable disease biomarkers, which would allow for an earlier diagnosis, follow-up or prediction of treatment response, among others. In this regard, the “HCC circulome”, defined as the pool of circulating molecules in the bloodstream derived from the primary tumor, represents an appealing target, the so called liquid biopsy. Such molecules encompass circulating tumor proteins, circulating tumor cells (CTCs), extracellular vesicles (EVs), tumor-educated platelets (TEPs), and circulating tumor nucleic acids, namely circulating tumor DNA (ctDNA) and circulating tumor RNA (ctRNA). In this article, we summarize recent findings highlighting the promising role of liquid biopsies as novel potential biomarkers in HCC, emphasizing on its clinical performance.

TESC Promotes TGF-α/EGFR-FOXM1-Mediated Tumor Progression in Cholangiocarcinoma

Cholangiocarcinoma is a relatively uncommon but highly lethal malignancy. Improving outcomes in patients depends on earlier diagnosis and appropriate treatment; however, no satisfactory diagnostic biomarkers or targeted therapies are currently available. To address this shortcoming, we analyzed the transcriptomic datasets of cholangiocarcinoma from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and found that TESC is highly expressed in cholangiocarcinoma. Elevated cellular levels of TESC are correlated with larger tumor size and predict a poor survival outcome for patients. Knockdown of TESC via RNA interference suppresses tumor growth. RNA-sequencing analysis showed that silencing of TESC decreases the level of FOXM1, leading to cell cycle arrest. Correlation analysis revealed that the cellular level of TESC is correlated with that of FOXM1 in cholangiocarcinoma patients. We further observed that upon TGF-α induction, TESC is upregulated through the EGFR-STAT3 pathway and mediates TGF-α-induced tumor cell proliferation. In vivo experiments revealed that knockdown of TESC significantly attenuates tumor cell growth. Therefore, our data provide novel insight into TESC-mediated oncogenesis and reveal that TESC is a potential biomarker or serves as a therapeutic target for cholangiocarcinoma.

Global metabolomics profiling of colorectal cancer in Malaysian patients

Introduction: The serum metabolomics approach has been used to identify metabolite biomarkers that can diagnose colorectal cancer (CRC) accurately and specifically. However, the biomarkers identified differ between studies suggesting that more studies need to be performed to understand the influence of genetic and environmental factors. Therefore, this study aimed to identify biomarkers and affected metabolic pathways in Malaysian CRC patients. Methods: Serum from 50 healthy controls and 50 CRC patients were collected at UKM Medical Centre. The samples were deproteinized with acetonitrile and untargeted metabolomics profile determined using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOFMS, Agilent USA). The data were analysed using Mass Profiler Professional (Agilent, USA) software. The panel of biomarkers determined were then used to identify CRC from a new set of 20 matched samples. Results: Eleven differential metabolites were identified whose levels were significantly different between CRC patients compared to normal controls. Based on the analysis of the area under the curve, 7 of these metabolites showed high sensitivity and specificity as biomarkers. The use of the 11 metabolites on a new set of samples was able to differentiate CRC from normal samples with 80% accuracy. These metabolites were hypoxanthine, acetylcarnitine, xanthine, uric acid, tyrosine, methionine, lysoPC, lysoPE, citric acid, 5-oxoproline, and pipercolic acid. The data also showed that the most perturbed pathways in CRC were purine, catecholamine, and amino acid metabolisms. Conclusion: Serum metabolomics profiling can be used to identify distinguishing biomarkers for CRC as well as to further our knowledge of its pathophysiological mechanisms.

Multifaceted Aspects of Metabolic Plasticity in Human Cholangiocarcinoma: An Overview of Current Perspectives

Cholangiocarcinoma (CCA) is a deadly tumor without an effective therapy. Unique metabolic and bioenergetics features are important hallmarks of tumor cells. Metabolic plasticity allows cancer cells to survive in poor nutrient environments and maximize cell growth by sustaining survival, proliferation, and metastasis. In recent years, an increasing number of studies have shown that specific signaling networks contribute to malignant tumor onset by reprogramming metabolic traits. Several evidences demonstrate that numerous metabolic mediators represent key-players of CCA progression by regulating many signaling pathways. Besides the well-known Warburg effect, several other different pathways involving carbohydrates, proteins, lipids, and nucleic acids metabolism are altered in CCA. The goal of this review is to highlight the main metabolic processes involved in the cholangio-carcinogeneis that might be considered as potential novel druggable candidates for this disease.

Characterization of Gut Microbiota, Bile Acid Metabolism, and Cytokines in Intrahepatic Cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC), a type of bile duct cancer, has a high mortality rate. Gut microbiota, bile acid (BA) metabolism, and cytokines have not been characterized in patients with ICC, and better noninvasive diagnostic approaches for ICC are essential to be established. Therefore, in this study we aimed to improve our understanding of changes in gut microbiota, BA metabolism, and cytokines in patients with ICC. We found that the α-diversities and β-diversities of ICC were highest and that the abundances of four genera (Lactobacillus, Actinomyces, Peptostreptococcaceae, and Alloscardovia) were increased in patients with ICC compared with those in patients with hepatocellular carcinoma or liver cirrhosis and in healthy individuals. The glycoursodeoxycholic acid and tauroursodeoxycholic acid (TUDCA) plasma-stool ratios were obviously increased in patients with ICC. Furthermore, the genera Lactobacillus and Alloscardovia that were positively correlated with TUDCA plasma-stool ratios were combined to discriminate ICC from the other three diseases. Vascular invasion (VI) frequently led to a poor prognosis in patients with ICC. Compared with patients with ICC without VI, patients with VI had a greater abundance of the family Ruminococcaceae, increased levels of plasma interleukin (IL)-4 and six conjugated BAs, and decreased levels of plasma IL-6 and chenodeoxycholic acid. A positive correlation between plasma taurocholic acid and IL-4 was observed in patients with ICC. Plasma TUDCA was negatively correlated with the abundance of the genus Pseudoramibacter and the survival time of patients with ICC, but had no effect on tumor size, as determined in two murine tumor models. Conclusion: In this study, we identified some biomarkers, including gut microbiota, BAs and inflammatory cytokines, for the diagnosis of ICC and prediction of VI in patients with ICC.

Common transcriptional programs and the role of chemokine (C-C motif) ligand 20 (CCL20) in cell migration of cholangiocarcinoma

The incidence of cholangiocarcinoma (CCA) has risen in many countries, but there is still no appropriate screening and treatment available. The growing number of microarray data published todays can be a powerful resource for the discovery of biomarkers to tackle challenges in the management of CCA. This study analyzed multiple microarray datasets to identify the common transcriptional networks in CCA and select a possible biomarker for functional study in CCA cell lines. A systematic searching identified 4 microarray datasets from Gene Expression Omnibus (GEO) repository and PubMed articles. Differential expression analysis between tumor and normal tissues was performed in each dataset. In order to characterize the common expression pattern, differentially expressed genes (DEGs) from all datasets were combined and visualized by hierarchical clustering and heatmap. Gene enrichment analysis performed in each cluster revealed that over-expressed DEGs were enriched in cell cycle, cell migration and response to cytokines while under-expressed DEGs were enriched in metabolic processes such as oxidation-reduction, lipid, and drug. To explain tumor characteristics, genes enriched in cell migration and response to cytokines were further investigated. Among these genes, CCL20 was selected for functional study because its role has never been studied in CCA. Moreover, its signaling may be regulated by disrupting its only receptor, CCR6. Treatment with recombinant CCL20 induced higher cell migration and increased expression of N-cad. In contrast, knockdown of CCR6 by siRNA reduced cell migration ability and decreased N-cadherin level. Altogether, these results suggested the contribution of CCL20/CCR6 signaling in cell migration through epithelial-mesenchymal transition process. Thus, CCL20/CCR6 signaling might be a target for the management of CCA.

Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data

The high mortality rate of hepatocellular carcinoma (HCC) is primarily due to its late diagnosis. In the past, numerous attempts have been made to design genetic biomarkers for the identification of HCC; unfortunately, most of the studies are based on small datasets obtained from a specific platform or lack reasonable validation performance on the external datasets. In order to identify a universal expression-based diagnostic biomarker panel for HCC that can be applicable across multiple platforms, we have employed large-scale transcriptomic profiling datasets containing a total of 2,316 HCC and 1,665 non-tumorous tissue samples. These samples were obtained from 30 studies generated by mainly four types of profiling techniques (Affymetrix, Illumina, Agilent, and High-throughput sequencing), which are implemented in a wide range of platforms. Firstly, we scrutinized overlapping 26 genes that are differentially expressed in numerous datasets. Subsequently, we identified a panel of three genes (FCN3, CLEC1B, and PRC1) as HCC biomarker using different feature selection techniques. Three-genes-based HCC biomarker identified HCC samples in training/validation datasets with an accuracy between 93 and 98%, Area Under Receiver Operating Characteristic curve (AUROC) in a range of 0.97 to 1.0. A reasonable performance, i.e., AUROC 0.91–0.96 achieved on validation dataset containing peripheral blood mononuclear cells, concurred their non-invasive utility. Furthermore, the prognostic potential of these genes was evaluated on TCGA-LIHC and GSE14520 cohorts using univariate survival analysis. This analysis revealed that these genes are prognostic indicators for various types of the survivals of HCC patients (e.g., Overall Survival, Progression-Free Survival, Disease-Free Survival). These genes significantly stratified high-risk and low-risk HCC patients (p-value <0.05). In conclusion, we identified a universal platform-independent three-genes-based biomarker that can predict HCC patients with high precision and also possess significant prognostic potential. Eventually, we developed a web server HCCpred based on the above study to facilitate scientific community (http://webs.iiitd.edu.in/raghava/hccpred/).

Genetic variant rs3750625 in the 3'UTR of ADRA2A affects the sleep quality of patients in the ICU by promoting miR‑34a binding to ADRA2A

Poor sleep is very common in patients in the ICU and hence, sleep quality is considered an important aspect of intensive care; however, the underlying mechanisms of poor sleep in patients in the ICU remain unknown. In this study, we aimed to explore the role of rs3750625, which is located in the 3'UTR of adrenoceptor alpha 2A (ADRA2A), in sleep quality. For this purpose, luciferase assay was conducted to investigate the association between miR‑34a and ADRA2A, and the effect of rs3750625 on the binding affinity between miR‑34a and ADRA2A was examined. RT‑qPCR and western blot analysis were carried out to examine the regulatory association between miR‑34a and ADRA2A. The differences in sleep time and efficiency were compared between groups carrying the AC and CC genotypes of rs3750625, respectively. According to the results from an online search, miR‑34a could directly bind to the 3'UTR of ADRA2A, and such binding was confirmed by the observation that miR‑34a inhibited the luciferase activity of major or minor ADRA2A 3'UTR in a dose‑dependent manner in HCN‑1A and U251 cells. In addition, the ADRA2A protein and mRNA levels in the HCN‑1A and U251 cells were evidently decreased following transfection with miR‑34a precursors. Notably, patients in the AC group exhibited a similar level of miR‑34a mRNA expression compared with patients in the CC group; however, the ADRA2A mRNA and protein levels in the CC group were significantly increased in comparison with those in the AC group. In addition, the sleep time and sleep efficiency in the CC group were much higher than those in the AC group. Furthermore, the mean arterial pressure (MAP) values in both the AC and CC groups remained stable from 22:00 to 08:00, and the respiratory rates in both groups were quite similar. However, the heart rate of patients in the CC group was much lower than that of patients in the AC group. On the whole, the findings of this study suggest that the genetic variant rs3750625 in the 3'UTR of ADRA2A affects the sleep quality of patients in the ICU by promoting the binding of miR‑34a to ADRA2A, and hence it may serve as a novel biomarker for the prediction of the sleep quality of patients in the ICU.

Using MetaboAnalyst 4.0 for Metabolomics Data Analysis, Interpretation, and Integration with Other Omics Data

MetaboAnalyst ( www.metaboanalyst.ca ) is an easy-to-use, comprehensive web-based tool, freely available for metabolomics data processing, statistical analysis, functional interpretation, as well as integration with other omics data. This chapter first provides an introductory overview to the current MetaboAnalyst (version 4.0) with regards to its underlying design concepts and user interface structure. Subsequent sections describe three common metabolomics data analysis workflows covering targeted metabolomics, untargeted metabolomics, and multi-omics data integration.

Prognostic value and prospective molecular mechanism of miR-100-5p in hepatocellular carcinoma: A comprehensive study based on 1,258 samples

The prognostic value and molecular mechanism of microRNA-100-5p (miR-100-5p) in hepatocellular carcinoma (HCC) are still unclear. To explore the prognostic value and the mechanism of miR-100-5p in HCC, the present study analyzed the results of 18 previous studies and bioinformatic datasets. The clinical significance of miR-100-5p and its targets in HCC were investigated using The Cancer Genome Atlas and the Gene Expression Omnibus, as well as relevant literature. In total, 12 online tools were used to predict the target genes of miR-100-5p. Bioinformatics analysis and Spearman correlation analysis were performed, and genomic alterations of the hub genes were evaluated. A meta-analysis with 1,258 samples revealed that miR-100-5p was significantly downregulated in HCC [standard mean difference (SMD), -0.94; 95% confidence interval (CI), -1.14 to -0.74; I2, 35.2%]. Lower miR-100-5p expression was associated with poorer clinical characteristics and a poorer prognosis for patients with HCC. Additionally, bioinformatics analysis revealed that the 'regulation of transcription', 'chromatin remodeling complex', 'transcription regulator activity', 'pathways in cancer' and 'heparan sulfate biosynthesis' were the most enriched terms. Furthermore, expression of histone deacetylase (HDAC)2, HDAC3, SHC-transforming protein 1 (SHC1), Ras-related protein Rac1 (RAC1) and E3 ubiquitin-protein ligase CBL (CBL) was negatively correlated with miR-100-5p expression. Among these, upregulated HDAC2 [hazard ratio (HR), 1.910; 95% CI, 1.309-2.787; P=0.0007], HDAC3 (HR, 1.474; 95% CI, 1.012-2.146; P=0.0435), SHC1 (HR, 1.52; 95% CI, 1.043-2.215; P=0.0281) and RAC1 (HR, 1.817; 95% CI, 1.248-2.645; P=0.0022) were associated with shorter survival. Alterations in HDAC2, SHC1, RAC1 and IGF1R were linked with a poorer outcome for HCC, and alternative splicing of SHC and RAC1 were significantly decreased and increased in HCC, respectively. In summary, the downregulation of miR-100-5p may be involved in the progression and prognosis of HCC. The upregulation of HDAC2, HDAC3, SHC1 and RAC1 may indicate a poorer survival rate for patients with HCC. Thus, miR-100-5p and these 4 potential target genes may provide novel therapeutic targets and prognostic predictors for patients with HCC.

Metabolic rearrangements in primary liver cancers: cause and consequences

Primary liver cancer (PLC) is the fourth most frequent cause of cancer-related death. The high mortality rates arise from late diagnosis and the limited accuracy of diagnostic and prognostic biomarkers. The liver is a major regulator, orchestrating the clearance of toxins, balancing glucose, lipid and amino acid uptake, managing whole-body metabolism and maintaining metabolic homeostasis. Tumour onset and progression is frequently accompanied by rearrangements of metabolic pathways, leading to dysregulation of metabolism. The limitation of current therapies targeting PLCs, such as hepatocellular carcinoma and cholangiocarcinoma, points towards the importance of deciphering this metabolic complexity. In this Review, we discuss the role of metabolic liver disruptions and the implications of these processes in PLCs, emphasizing their clinical relevance and value in early diagnosis and prognosis and as putative therapeutic targets. We also describe system biology approaches able to reconstruct the metabolic complexity of liver diseases. We also discuss whether metabolic rearrangements are a cause or consequence of PLCs, emphasizing the opportunity to clinically exploit the rewired metabolism. In line with this idea, we discuss circulating metabolites as promising biomarkers for PLCs.

Characterisation of the Urinary Metabolic Profile of Liver Fluke-Associated Cholangiocarcinoma

BACKGROUND

Human infection with Opisthorchis viverrini, a carcinogenic liver fluke inhabiting the biliary tree, is endemic in Southeast Asia. Chronic infection is associated with a fatal complication, cholangiocarcinoma (CCA), a late-presenting and aggressive malignancy. Currently, annual mortality rates from CCA mirror trends in incidence, due in part to limited availability of efficient prognostic and early diagnostic biomarkers. With ability to detect thousands of urinary metabolites using metabonomics, the urine metabolome holds great potential in providing an insight into system-level alterations in carcinogenesis and in identifying metabolic markers altered in response to disturbed homoeostasis.

METHODS

Global molecular profiling using reversed-phase ultraperformance liquid chromatography mass spectrometry was utilised to acquire the urinary spectral profile of 137 Thai subjects (48 at high risk of infection, 41 with O. viverrini infection, 34 periportal fibrosis and 14 CCA) from Khon Kaen, Thailand.

RESULTS

Multivariate statistical analysis identified perturbation in several molecular classes related to purine metabolism and lipid metabolism in the CCA urine metabolome. These markers mainly reflect changes in energy metabolism to support proliferation (increased fatty acid oxidation and purine recycling), DNA methylation and hepatic injury.

CONCLUSIONS

Several metabolites of biological interest were discovered from this proof-of-principle dataset. Augmenting these findings is essential to accelerate the development of urinary metabolic markers in CCA.

Upregulation of miR‑132‑3p in cholangiocarcinoma tissues: A study based on RT‑qPCR, The Cancer Genome Atlas miRNA sequencing, Gene Expression Omnibus microarray data and bioinformatics analyses

MicroRNAs (miRNAs/miRs) have been reported to be closely associated with numerous human diseases, including cholangiocarcinoma (CCA). However, the number of miRNAs known to be involved in CCA is limited, and the association between miR-132-3p and CCA remains unknown. In the present study, the clinical role of miR-132-3p and its potential signaling pathways were investigated by multiple approaches. Reverse transcription-quantitative PCR (RT-qPCR), CCA-associated Gene Expression Omnibus (GEO), ArrayExpress and Sequence Read Archive (SRA) miRNA-microarray or miRNA-sequencing data were screened, and meta-analyses were conducted, in order to calculate the receiver operating characteristic (ROC) curve and standardized mean difference (SMD). The predicted target genes of miR-132-3p were obtained from 12 online databases and were combined with the downregulated differentially expressed genes identified in the RNA-sequencing data of CCA. Gene Ontology annotation and pathway analysis were performed in WebGestalt. Protein-protein interaction analyses were conducted in STRING. The Cancer Genome Atlas (TCGA) mRNA expression profiles were used to validate the expression levels of hub genes at the mRNA level. The Human Protein Atlas was used to identify the protein expression levels of hub genes in CCA tissues and non-tumor biliary epithelium. The meta-analyses comprised 10 groups of RT-qPCR data, eight GEO microarray datasets and one TCGA miRNA-sequencing dataset. The SMD of miR-132-3p in CCA was 0.75 (95% CI: 0.25, 1.24), which indicated that miR-132-3p was overexpressed in CCA tissues. This finding was supported by a summary ROC value of 0.80 (95% CI: 0.76, 0.83). The pooled sensitivity and specificity were 0.81 (95% CI: 0.59, 0.93) and 0.71 (95% CI: 0.58, 0.81), respectively. The relative expression level of miR-132-3p in the early stage of CCA (stages I–II) was 6.8754±0.5279, which was markedly lower than that in the advanced stage (stages III–IVB), 7.3034±0.3267 (P=0.003). Consistently, the miR-132-3p level in low-grade CCA (grades G1-G2) was 6.7581±0.5297, whereas it was 7.1191±0.4651 in patients with high-grade CCA (grades G3-G4) (P=0.037). Furthermore, 555 potential target genes of miR-132-3p in CCA were mainly enriched in the ‘Focal Adhesion-PI3K-Akt-mTOR-signaling pathway’. In conclusion, upregulation of miR-132-3p may serve a pivotal role in the tumorigenesis and progression of CCA by targeting different pathways. Further in vitro and in vivo studies are required to support the current findings.

mTOR/HDAC1 Crosstalk Mediated Suppression of ADH1A and ALDH2 Links Alcohol Metabolism to Hepatocellular Carcinoma Onset and Progression in silico

Hepatocellular carcinoma (HCC) is ranked the third deadliest cancer worldwide whose molecular pathogenesis is not fully understood. Although deregulated metabolic pathways have been implicated in HCC onset and progression, the mechanisms triggering this metabolic imbalance are yet to be explored. Here, we identified a gene signature coding catabolic enzymes (Cat-GS) involved in key metabolic pathways like amino acid, lipid, carbohydrate, drug, and retinol metabolism as suppressed in HCC. A higher expression of deregulated Cat-GS is associated with good survival and less aggressive disease state in HCC patients. On the other hand, we identified mTOR signaling as a key determinant in HCC onset and progression, whose hyperactivation is found associated with poor survival and aggressive disease state in HCC patients. Next, out of Cat-GS, we established two key regulators of alcohol metabolism, alcohol dehydrogenase 1A (ADH1A) and aldehyde dehydrogenase 2 (ALDH2), as being transcriptionally suppressed by histone deacetylase 1 (HDAC1) at the downstream of mTORC1 signaling. Suppressed ADH1A and ALDH2 expression aligns well with HCC-specific molecular profile and can efficiently predict disease onset and progression, whereas higher ADH1A and ALDH2 expression is associated with good survival and less aggressive disease state in HCC patients. Overall, our in silico findings suggest that transcriptional suppression of alcohol metabolism regulators, ADH1A and ALDH2, at the downstream of mTOR signaling is, in part, responsible for triggering oncogenic transformation of hepatocytes resulting in disease onset and progression in HCC.

Tensor Decomposition-Based Unsupervised Feature Extraction Applied to Single-Cell Gene Expression Analysis

Although single-cell RNA sequencing (scRNA-seq) technology is newly invented and a promising one, but because of lack of enough information that labels individual cells, it is hard to interpret the obtained gene expression of each cell. Because of insufficient information available, unsupervised clustering, for example, t-distributed stochastic neighbor embedding and uniform manifold approximation and projection, is usually employed to obtain low-dimensional embedding that can help to understand cell–cell relationship. One possible drawback of this strategy is that the outcome is highly dependent upon genes selected for the usage of clustering. In order to fulfill this requirement, there are many methods that performed unsupervised gene selection. In this study, a tensor decomposition (TD)-based unsupervised feature extraction (FE) was applied to the integration of two scRNA-seq expression profiles that measure human and mouse midbrain development. TD-based unsupervised FE could select not only coincident genes between human and mouse but also biologically reliable genes. Coincidence between two species as well as biological reliability of selected genes is increased compared with that using principal component analysis (PCA)-based FE applied to the same data set in the previous study. Since PCA-based unsupervised FE outperformed the other three popular unsupervised gene selection methods, highly variable genes, bimodal genes, and dpFeature, TD-based unsupervised FE can do so as well. In addition to this, 10 transcription factors (TFs) that might regulate selected genes and might contribute to midbrain development were identified. These 10 TFs, BHLHE40, EGR1, GABPA, IRF3, PPARG, REST, RFX5, STAT3, TCF7L2, and ZBTB33, were previously reported to be related to brain functions and diseases. TD-based unsupervised FE is a promising method to integrate two scRNA-seq profiles effectively.

Diagnostic and prognostic biomarkers in cholangiocarcinoma

The high mortality rate of cholangiocarcinoma (CCA) is due, in part, to the lack of non-invasive approaches able to accurately detect this silent tumour at early stages, when therapeutic options can be potentially curative or may at least increase the overall survival of patients. The fact that the majority of CCA tumours are not linked to any known aetiological factor highly compromises the monitoring of patients at risk for tumour development and also their early diagnosis. Combination of clinical/biochemical features, imaging techniques and analysis of non-specific tumour biomarkers in serum are commonly used to help in the diagnosis of CCA, but tumour biopsy is usually required to confirm the diagnosis. Moreover, no prognostic biomarkers are currently used in the clinical setting, deserving more innovative research, and international validation and consensus. Important efforts have been made in the last few years to identify accurate non-invasive biomarkers, by using innovative techniques and high-throughput omics technologies. This review summarizes and discusses the advances in the investigation of novel diagnostic and prognostic biomarkers in CCA and envisions the future directions in this field of research.

Intrahepatic Cholangiocarcinoma: Continuing Challenges and Translational Advances

Intrahepatic cholangiocarcinoma (iCCA) has over the last 10-20 years become the focus of increasing concern, largely due to its rising incidence and high mortality rates worldwide. The significant increase in mortality rates from this primary hepatobiliary cancer, particularly over the past decade, has coincided with a rapidly growing interest among clinicians, investigators, and patient advocates to seek greater mechanistic insights and more effective biomarker-driven targeted approaches for managing and/or preventing this challenging liver cancer. In addition to discussing challenges posed by this aggressive cancer, this review will emphasize recent epidemiological, basic, and translational research findings for iCCA. In particular, we will highlight emerging demographic changes and evolving risk factors, the critical role of the tumor microenvironment, extracellular vesicle biomarkers and therapeutics, intertumoral and intratumoral heterogeneity, and current and emerging targeted therapies regarding iCCA. Specifically, recent evidence linking non-bile duct medical conditions, such as nonalcoholic fatty liver disease and nonspecific cirrhosis, to intrahepatic cholangiocarcinogenesis together with geographic and ethnic variation will be assessed. Recent developments concerning the roles played by transforming growth factor-β and platelet-derived growth factor D in driving the recruitment and expansion of cancer-associated myofibroblasts within cholangiocarcinoma (CCA) stroma as well as their therapeutic implications will also be discussed. In addition, the potential significance of extracellular vesicles as bile and serum biomarkers and therapeutic delivery systems for iCCA will be described. An integrated systems approach to classifying heterogeneous iCCA subtypes will be further highlighted, and recent clinical trials and emerging targeted therapies will be reviewed, along with recommendations for future translational research opportunities. Established international CCA networks are now facilitating collaborations aimed at advancing iCCA translational and clinical research.

Drug candidate identification based on gene expression of treated cells using tensor decomposition-based unsupervised feature extraction for large-scale data

Background

Although in silico drug discovery is necessary for drug development, two major strategies, a structure-based and ligand-based approach, have not been completely successful. Currently, the third approach, inference of drug candidates from gene expression profiles obtained from the cells treated with the compounds under study requires the use of a training dataset. Here, the purpose was to develop a new approach that does not require any pre-existing knowledge about the drug–protein interactions, but these interactions can be inferred by means of an integrated approach using gene expression profiles obtained from the cells treated with the analysed compounds and the existing data describing gene–gene interactions.

Results

In the present study, using tensor decomposition-based unsupervised feature extraction, which represents an extension of the recently proposed principal-component analysis-based feature extraction, gene sets and compounds with a significant dose-dependent activity were screened without any training datasets. Next, after these results were combined with the data showing perturbations in single-gene expression profiles, genes targeted by the analysed compounds were inferred. The set of target genes thus identified was shown to significantly overlap with known target genes of the compounds under study.

Conclusions

The method is specifically designed for large-scale datasets (including hundreds of treatments with compounds), not for conventional small-scale datasets. The obtained results indicate that two compounds that have not been extensively studied, WZ-3105 and CGP-60474, represent promising drug candidates targeting multiple cancers, including melanoma, adenocarcinoma, liver carcinoma, and breast, colon, and prostate cancers, which were analysed in this in silico study.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2395-8) contains supplementary material, which is available to authorized users.

MicroRNA-197-3p acts as a prognostic marker and inhibits cell invasion in hepatocellular carcinoma

MicroRNAs (miRNAs) serve an important regulatory role in carcinogenesis and cancer progression. Aberrant expression of miR-197-3p has been reported in various human malignancies. However, the role of miR-197-3p in the progression and prognosis of hepatocellular carcinoma (HCC) remains unknown. The present study demonstrated that miR-197-3p was downregulated in HCC tissues and that the low level of miR-197-3p expression in HCC tumours correlated with aggressive clinicopathological characteristics; thus, miR-197-3p may serve as a predictor for poor prognosis in patients with HCC. Additionally, miR-197-3p markedly inhibited the metastasis of HCC cells in vitro and in vivo. Bioinformatics analysis further identified zinc finger protein interacted with K protein 1 (ZIK1) as a novel target of miR-197-3p in HCC cells. These findings suggest that miR-197-3p may regulate the survival of HCC cells, partially through the downregulation of ZIK1. Therefore, the miR-197-3p/ZIK1 axis may serve as a novel therapeutic target in patients with HCC.

Oncogenic value of microRNA-15b-5p in hepatocellular carcinoma and a bioinformatics investigation

miR-15b-5p has frequently been reported to function as a biomarker in some malignancies; however, the function of miR-15b-5p in hepatocellular carcinoma (HCC) and its molecular mechanism are still not well understood. The present study was designed to confirm the clinical value of miR-15b-5p and further explore its underlying molecular mechanism. A comprehensive investigation of the clinical value of miR-15b-5p in HCC was investigated by data mining The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets as well as literature. In addition, intersected target genes of miR-15b-5p were predicted using the miRWalk database and differentially expressed genes of HCC from TCGA. Furthermore, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were carried out. Then, a protein-protein interaction network (PPI) was constructed to reveal the interactions between some hub target genes of miR-15b-5p. The miR-15b-5p expression level in HCC was predominantly overexpressed compared with non-HCC tissues samples (SMD=0.618, 95% CI: 0.207, 1.029; P<0.0001) based on 991 HCC and 456 adjacent non-HCC tissue samples. The pooled summary receiver operator characteristic (SROC) of miR-15b-5p was 0.81 (Q*=0.74), and the pooled sensitivity and specificity of miR-15b-5p in HCC were 72% (95% CI: 69–75%) and 68% (95% CI: 65–72%), respectively. Bioinformatically, 225 overlapping genes were selected as prospective target genes of miR-15b-5p in HCC, and profoundly enriched GO terms and KEGG pathway investigation in silico demonstrated that the target genes were associated with prostate cancer, proximal tubule bicarbonate reclamation, heart trabecula formation, extracellular space, and interleukin-1 receptor activity. Five genes (ACACB, RIPK4, MAP2K1, TLR4 and IGF1) were defined as hub genes from the PPI network. The high expression of miR-15b-5p could play an essential part in hepatocarcinogenesis through diverse regulation approaches.

Investigation of the clinical significance and molecular mechanism of miR-21-5p in hepatocellular carcinoma: A systematic review based on 24 studies and bioinformatics investigation

To investigate the prospective roles and the clinicopathological application of microRNA-21-5p (miR-21-5p) in hepatocellular carcinoma (HCC), the present review is based on 24 studies and bioinformatics investigation. Firstly, HCC-associated miR-21-5p data were aggregated from literature databases and two public genomic data repositories, including the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Potential target genes of miR-21-5p in HCC were identified using TCGA and GEO, Natural Language Processing and 14 online software packages. The oncogenic roles of these target genes was probed for understanding using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis. Hub genes were further investigated by protein-protein interaction network (PPI) analysis. Comprehensive meta-analysis, including 10 microarrays from GEO datasets, 13 literature studies and TCGA-based RNA sequencing data, indicated a reliable diagnostic capacity of miR-21-5p [area under the curve (AUC), 0.887; sensitivity, 0.78% and specificity, 0.79%]. The healthy control group (AUC, 0.926; sensitivity, 0.87% and specificity, 0.82%) demonstrated high diagnostic capacity of miR-21-5p compared with the chronic hepatitis B infection group (AUC, 0.904; sensitivity, 0.75% and specificity, 0.84%). A total of 10 significant enrichment pathways were indicated by KEGG analysis, with cytokine-cytokine receptor interaction exhibiting the highest score. A total of 5 genes, hepatocyte growth factor, forkhead box O1 (FOXO1), thrombospondin 1, estrogen receptor 1 (ESR1) and C-X-C motif chemokine ligand 12 were selected from 39 overlapping genes, according to the PPI network. Target genes were assembled in GO terms associated with ‘response to chemical stimulus’, ‘cell surface’ and ‘growth factor binding’. In particular, low expression of FOXO1 and ESR1 was associated with miR-21-5p expression. In conclusion, upregulated expression of miR-21-5p may be a functional regulator of the metabolism or apoptosis in HCC and a novel tumor marker for the early diagnosis of HCC.

Potential clinical value and putative biological function of miR-122-5p in hepatocellular carcinoma: A comprehensive study using microarray and RNA sequencing data

In order to determine the diagnostic efficacy of microRNA (miR)-122-5p and to identify the potential molecular signaling pathways underlying the function of miR-122-5p in hepatocellular carcinoma (HCC), the expression profiles of data collected from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and literature databases were analyzed, along with any associations between clinicopathological characteristics and the diagnostic value of miR-122-5p in HCC. The intersection of 12 online prediction databases and differentially expressed genes from TCGA and GEO were utilized in order to select the prospective target genes of miR-122-5p in HCC. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction network (PPI) analyses were subsequently performed based on the selected target genes. The average expression level of miR-122-5p was decreased in HCC patients compared with controls from TCGA database (P<0.001), and the downregulation of miR-122-5p was significantly associated with HCC tissues (P<0.001), tumor vascular invasion (P<0.001), metastasis (P=0.001), sex (P=0.006), virus infection status (P=0.001) and tissue (compared with serum; P<0.001) in cases from the GEO database. The pooled sensitivity and specificity for miR-122-5p to diagnose HCC were 0.60 [95% confidence interval (CI), 0.48–0.71] and 0.81 (95% CI, 0.70–0.89), respectively. The area under the curve (AUC) value was 0.76 (95% CI, 0.72–0.80), while in Meta-DiSc 1.4, the AUC was 0.76 (Q*=0.70). The pooled sensitivity and specificity were 0.60 (95% CI, 0.57–0.62) and 0.79 (95% CI, 0.76–0.81), respectively. A total of 198 overlapping genes were selected as the potential target genes of miR-122-5p, and 7 genes were defined as the hub genes from the PPI network. Cell division cycle 6 (CDC6), minichromosome maintenance complex component 4 (MCM4) and MCM8, which serve pivotal functions in the occurrence and development of HCC, were the most significant hub genes. The regulation of cell proliferation for cellular adhesion and the biosynthesis of amino acids was highlighted in the GO and KEGG pathway analyses. The downregulation of miR-122-5p in HCC demonstrated diagnostic value, worthy of further attention. Therefore, miR-122-5p may function as a tumor suppressor by modulating genome replication.

Novel tumor suppressor SPRYD4 inhibits tumor progression in hepatocellular carcinoma by inducing apoptotic cell death

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-associated deaths worldwide. Although recent studies have proposed different biomarkers for HCC progression and therapy resistance, a better understanding of the molecular mechanisms underlying HCC progression and recurrence, as well as the identification of molecular markers with a higher diagnostic accuracy, are necessary for the development of more effective clinical management strategies. Here, we aimed to identify novel players in HCC progression.

METHODS

SPRYD4 mRNA and protein expression analyses were carried out on a normal liver-derived cell line (HL-7702) and four HCC-derived cell lines (HepG2, SMMC7721, Huh-7, BEL-7402) using qRT-PCR and Western blotting, respectively. Cell proliferation Cell Counting Kit-8 (CCK-8) assays, protein expression analyses for apoptosis markers using Western blotting, and Caspase-Glo 3/7 apoptosis assays were carried out on the four HCC-derived cell lines. Expression comparison, functional annotation, gene set enrichment, correlation and survival analyses were carried out on patient data retrieved from the NCBI Gene module, the NCBI GEO database and the TCGA database.

RESULTS

Through a meta-analysis we found that the expression of SPRYD4 was downregulated in primary HCC tissues compared to non-tumor tissues. We also found that the expression of SPRYD4 was downregulated in HCC-derived cells compared to normal liver-derived cells. Subsequently, we found that the expression of SPRYD4 was inversely correlated with a gene signature associated with HCC cell proliferation. Exogenous SPRYD4 expression was found to inhibit HCC cell proliferation by inducing apoptotic cell death. We also found that SPRYD4 expression was associated with a good prognosis and that its expression became downregulated when HCCs progressed towards more aggressive stages and higher grades. Finally, we found that SPRYD4 expression may serve as a biomarker for a good overall and relapse-free survival in HCC patients.

CONCLUSIONS

Our data indicate that a decreased SPRYD4 expression may serve as an independent predictor for a poor prognosis in patients with HCC and that increased SPRYD4 expression may reduce HCC growth and progression through the induction of apoptotic cell death, thereby providing a potential therapeutic target.

Tensor Decomposition-Based Unsupervised Feature Extraction Can Identify the Universal Nature of Sequence-Nonspecific Off-Target Regulation of mRNA Mediated by MicroRNA Transfection

MicroRNA (miRNA) transfection is known to degrade target mRNAs and to decrease mRNA expression. In contrast to the notion that most of the gene expression alterations caused by miRNA transfection involve downregulation, they often involve both up- and downregulation; this phenomenon is thought to be, at least partially, mediated by sequence-nonspecific off-target effects. In this study, I used tensor decomposition-based unsupervised feature extraction to identify genes whose expression is likely to be altered by miRNA transfection. These gene sets turned out to largely overlap with one another regardless of the type of miRNA or cell lines used in the experiments. These gene sets also overlap with the gene set associated with altered expression induced by a Dicer knockout. This result suggests that the off-target effect is at least as important as the canonical function of miRNAs that suppress translation. The off-target effect is also suggested to consist of competition for the protein machinery between transfected miRNAs and miRNAs in the cell. Because the identified genes are enriched in various biological terms, these genes are likely to play critical roles in diverse biological processes.