Comprehensive analysis of liver and blood miRNA in precancerous conditions

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.

DAEMDA: A Method with Dual-Channel Attention Encoding for miRNA-Disease Association Prediction

A growing number of studies have shown that aberrant microRNA (miRNA) expression is closely associated with the evolution and development of various complex human diseases. These key biomarkers' identification and observation are significant for gaining a deeper understanding of disease pathogenesis and therapeutic mechanisms. Consequently, pinpointing potential miRNA-disease associations (MDA) has become a prominent bioinformatics subject, encouraging several new computational methods given the advances in graph neural networks (GNN). Nevertheless, these existing methods commonly fail to exploit the network nodes' global feature information, leaving the generation of high-quality embedding representations using graph properties as a critical unsolved issue. Addressing these challenges, we introduce the DAEMDA, a computational method designed to optimize the current models' efficacy. First, we construct similarity and heterogeneous networks involving miRNAs and diseases, relying on experimentally corroborated miRNA-disease association data and analogous information. Then, a newly-fashioned parallel dual-channel feature encoder, designed to better comprehend the global information within the heterogeneous network and generate varying embedding representations, follows this. Ultimately, employing a neural network classifier, we merge the dual-channel embedding representations and undertake association predictions between miRNA and disease nodes. The experimental results of five-fold cross-validation and case studies of major diseases based on the HMDD v3.2 database show that this method can generate high-quality embedded representations and effectively improve the accuracy of MDA prediction.

Female-to-male differential transcription patterns of miRNA-mRNA networks in the livers of dioxin-exposed mice

Non-coding microRNAs (miRNAs) have important roles in regulating the expression of liver mRNAs in response to xenobiotic-exposure, but their roles concerning dioxins such as TCDD (2,3,7,8-Tetrachlorodibenzo-p-dioxin) are less clear. This report concerns the potential implication of liver (class I) and circulating (class II) miRNAs in hepatotoxicity of female and male mice after acute exposure to TCDD. The data show that, of a total of 38 types of miRNAs, the expression of eight miRNAs were upregulated in both female and male mice exposed to TCDD. Inversely, the expression of nine miRNAs were significantly downregulated in both animal genders. Moreover, certain miRNAs were preferentially induced in either females or males. The potential downstream regulatory effects of miRNAs on their target genes was evaluated by determining the expression of three group of genes that are potentially involved in cancer biogenesis, other diseases and in hepatotoxicity. It was found that certain cancer-related genes were more highly expressed females rather than males after exposure to TCDD. Furthermore, a paradoxical female-to-male transcriptional pattern was found for several disease-related and hepatotoxicity-related genes. These results suggest the possibility of developing of new miRNA-specific interfering molecules to address their dysfunctions as caused by TCDD.

Photothermal Responsive Digital Polymerase Chain Reaction Resolving Exosomal microRNAs Expression in Liver Cancer

Exosomal microRNAs have been studied as a good source of noninvasive biomarkers due to their functions in genetic exchange between cells and have been already well documented in many biological activities; however, inaccuracy remains a key challenge for liver cancer surveillance. Herein, a versatile duplex photothermal digital polymerase chain reaction (PCR) strategy combined with a lipid nanoparticle-based exosome capture approach is proposed to profile microRNAs expression through a 3-h easy-to-operate process. The microfluidically-generated molybdenum disulfide-nanocomposite-doped gelatin microcarriers display attractive properties as a 2-4 °C s^-1 ramping-up rate triggered by near-infrared and reversible sol-gel transforming in step with PCR activation. To achieve PCR thermocycling, the corresponding irradiation coordinating with fan cooling are automatically performed via a homemade control module with programs. Thus, taking the multiplexing capability of dual-color labeling, 19-31 folds higher in exosomal microRNA-200b-3p and microRNA-21-5p, and tenfold lower in microRNA-22-3p expressions relative to the control microRNA-26a-5p are quantified in two liver cancer cells (Huh7 and HepG2) than in those from the healthy cells. It is believed that this exosomal microRNA genotyping method would be highly applicable for liver cancer diagnostics.

Identification of potential microRNA groups for the diagnosis of hepatocellular carcinoma (HCC) using microarray datasets and bioinformatics tools

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and the third cause of cancer-related death worldwide. Potential microRNAs have been reported as biomarkers for early detection of HCC as well as novel molecular targets for HCC treatment. Various tissue expression profiles of miRNAs using three microarray datasets from groups in Asia (2), Europe, America (GSE147892, GSE21362, GSE74618, GSE40744) and multiple bioinformatics tools were integrated to determine the most significant miRNA groups to assist in the diagnosis of HCC. Statistical analyses identified at least 30 miRNAs with 17 up-regulated and 13 down-regulated in HCC-related tumor tissues. All the miRNAs also showed relevance to the hallmarks of cancer such as cell proliferation, invasion, metastasis, angiogenesis, metabolism, epithelial-mesenchymal transition and apoptosis. Expression levels of miRNAs observed in the European group showed up-regulation at 5–37% compared to both Asian and American groups. Interestingly, four miRNAs divided into two groups as miR-182-5p/miR-1269a and miR-199a/miR-422a were the most promising for diagnosis of HCC patients from healthy controls, with AUC values of 0.902 and 0.892, respectively. Results provided evidence of the correlation between potential miRNAs and HCC that could be useful for disease diagnosis based on in-depth analyses of large case numbers and cohort studies.

Exosomal MicroRNAs as Potential Biomarkers of Hepatic Injury and Kidney Disease in Glycogen Storage Disease Type Ia Patients

Glycogen storage disease type Ia (GSDIa) is an inherited metabolic disorder caused by mutations in the enzyme glucose-6-phosphatase-α (G6Pase-α). Affected individuals develop renal and liver complications, including the development of hepatocellular adenoma/carcinoma and kidney failure. The purpose of this study was to identify potential biomarkers of the evolution of the disease in GSDIa patients. To this end, we analyzed the expression of exosomal microRNAs (Exo-miRs) in the plasma exosomes of 45 patients aged 6 to 63 years. Plasma from age-matched normal individuals were used as controls. We found that the altered expression of several Exo-miRs correlates with the pathologic state of the patients and might help to monitor the progression of the disease and the development of late GSDIa-associated complications.

Identification of Key Regulators of Hepatitis C Virus-Induced Hepatocellular Carcinoma by Integrating Whole-Genome and Transcriptome Sequencing Data

Background: Hepatitis C virus (HCV) infection is a major cause of cirrhosis and hepatocellular carcinoma (HCC). Despite recent advances in the understanding of the biological basis of HCC development, the molecular mechanisms underlying HCV-induced HCC (HCC-HCV) remain unclear. The carcinogenic potential of HCV varies according to the genotype and mutation in its viral sequence. Moreover, regulatory pathways play important roles in many pathogenic processes. Therefore, identifying the pathways by which HCV induces HCC may enable improved HCC diagnosis and treatment.

Methods: We employed a systematic approach to identify an important regulatory module in the process of HCV-HCC development to find the important regulators. First, an HCV-related HCC subnetwork was constructed based on the gene expression in HCC-HCV patients and HCC patients. A priority algorithm was then used to extract the module from the subnetworks, and all the regulatory relationships of the core genes of the network were extracted. Integrating the significantly highly mutated genes involved in the HCC-HCV patients, core regulatory modules and key regulators related to disease prognosis and progression were identified.

Result: The key regulatory genes including EXO1, VCAN, KIT, and hsa-miR-200c-5p were found to play vital roles in HCV-HCC development. Based on the statistics analysis, EXO1, VCAN, and KIT mutations are potential biomarkers for HCV–HCC prognosis at the genomic level, whereas has-miR-200c-5P is a potential biomarker for HCV–HCC prognosis at the expression level.

Conclusion: We identified three significantly mutated genes and one differentially expressed miRNA, all related to HCC prognosis. As potential pathogenic factors of HCC, these genes and the miRNA could be new biomarkers for HCV-HCC diagnosis.

Dipeptidyl peptidase-4 (DPP4) inhibitor sitagliptin alleviates liver inflammation of diabetic mice by acting as a ROS scavenger and inhibiting the NFκB pathway

As a common chronic metabolic disease, the development of diabetes mellitus (DM) may also be accompanied by liver damage and inflammatory disorders. Sitagliptin is an inhibitor of dipeptidyl peptidase-4 (DPP4, also known as CD26), which is clinically used for DM treatment. However, the mechanism of sitagliptin’s efficiency in liver diseases is largely unknown. In this study, mice suffering from streptozotocin (STZ) exhibit elevated liver DPP4 expression and activity, as well as inflammatory and chronic liver injury phenotype, whereas specifically inhibiting the activity of DPP4 in mouse liver tissues and hepatocytes by sitagliptin contributes to decreased cytokines, oxidative stress, cell apoptosis, and inflammation in STZ-induced diabetic mice. Moreover, sitagliptin reduced TNFα or LPS-induced cellular reactive oxygen species (ROS) level, cell apoptosis, and protein expression in the NFκB signaling pathway in HepG2 cells or primary mouse hepatocytes. Altogether, our study confirms that sitagliptin may protect liver tissue by alleviating ROS production and NFκB signaling activation, providing a putative mechanism for preventing the development of diabetic liver disease.