Tissue- and Serum-Associated Biomarkers of Hepatocellular Carcinoma

Unleashing the potential of gene signatures as prognostic and predictive tools: A step closer to personalized medicine in hepatocellular carcinoma (HCC)

Hepatocellular carcinoma (HCC) is one of the growing malignancies globally, affecting a myriad of people and causing numerous cancer-related deaths. Despite therapeutic improvements in treatment strategies over the past decades, HCC still remains one of the leading causes of person-years of life lost. Numerous studies have been conducted to assess the characteristics of HCC with the aim of predicting its prognosis and responsiveness to treatment. However, the identified biomarkers have shown limited sensitivity, and the translation of these findings into clinical practice has faced challenges. The development of sequencing techniques has facilitated the exploration of a wide range of genes, leading to the emergence of gene signatures. Although several studies assessed differentially expressed genes in normal and HCC tissues to find the unique gene signature with prognostic value, to date, no study has reviewed the task, and to the best of our knowledge, this review represents the first comprehensive analysis of relevant studies in HCC. Most gene signatures focused on immune-related genes, while others investigated genes related to metabolism, autophagy, and apoptosis. Even though no identical gene signatures were found, NDRG1, SPP1, BIRC5, and NR0B1 were the most extensively studied genes with prognostic value. Finally, despite challenges such as the lack of consistent patterns in gene signatures, we believe that comprehensive analysis of pertinent gene signatures will bring us a step closer to personalized medicine in HCC, where treatment strategies can be tailored to individual patients based on their unique molecular profiles.

Integrated analysis of multiple transcriptomic data identifies ST8SIA6‑AS1 and LINC01093 as potential biomarkers in HBV‑associated liver cancer

The mechanisms of long-non-coding RNAs (lncRNAs) in hepatitis B virus (HBV) infection-associated liver cancer remain largely unclear. Therefore, the aim of the present study was to investigate the regulatory mechanisms of lncRNAs in this disease. HBV-liver cancer related transcriptome expression profile data (GSE121248 and GSE55092) from the Gene Expression Omnibus database and survival prognosis information from The Cancer Genome Atlas (TCGA) database were obtained for analysis. The limma package was used to identify the overlapped differentially expressed RNAs (DERs), including DElncRNAs and DEmRNAs, in the GSE121248 and GSE55092 datasets. The screened optimized lncRNA signatures were used to develop a nomogram model based on the GSE121248 dataset, which was validated using the GSE55092 and TCGA datasets. A competitive endogenous RNA (ceRNA) network was constructed based on the screened prognosis-associated lncRNA signatures from TCGA dataset. In addition, the levels of specific lncRNAs were evaluated in HBV-infected human liver cancer tissues and cells, and Cell Counting Kit-8, ELISA and Transwell assays were performed to evaluate the effects of the lncRNAs in HBV-expressing liver cancer cells. A total of 535 overlapped DERs, including 30 DElncRNAs and 505 DEmRNAs, were identified in the GSE121248 and GSE55092 datasets. An optimized DElncRNA signature comprising 10 lncRNAs was used to establish a nomogram. ST8SIA6-AS1 and LINC01093 were identified as lncRNAs associated with HBV-liver cancer prognosis in TCGA dataset, and were applied to construct a ceRNA network. Reverse transcription-quantitative PCR analysis showed that ST8SIA6-AS1 was upregulated and LINC01093 was downregulated in HBV-infected human liver cancer tissues and HBV-expressing liver cancer cells compared with non-HBV-infected controls. ST8SIA6-AS1 knockdown and LINC01093 overexpression independently reduced the number of copies of HBV DNA, the levels of hepatitis B surface antigen and hepatitis B e antigen, as well as cell proliferation, migration and invasion. In summary, the present study identified ST8SIA6-AS1 and LINC01093 as two potential biomarkers that may be effective therapeutic targets for HBV-associated liver cancer.

Circulating Metabolic Markers Related to the Diagnosis of Hepatocellular Carcinoma

Primary liver carcinoma is the sixth most common cancer worldwide, while hepatocellular carcinoma (HCC) is the most dominant cancer type. Chronic hepatitis B and C virus infections and aflatoxin exposure are the main risk factors, while nonalcoholic fatty liver disease caused by obesity, diabetes, and metabolic syndrome are the more common risk factors for HCC. Metabolic disorders caused by these high-risk factors are closely related to the tumor microenvironment of HCC, revealing a possible cause-and-effect relationship between the two. These metabolic disorders involve many complex metabolic pathways, such as carbohydrate, lipid, lipid derivative, amino acid, and amino acid derivative metabolic processes. The resulting metabolites with significant abnormal changes in the concentration level in circulating blood may be used as biomarkers to guide the diagnosis, treatment, or prognosis of HCC. At present, there are high-throughput technologies that can quickly detect small molecular metabolites in many samples. Compared to tissue biopsy, blood samples are easier to obtain, and patients’ willingness to participate is higher, which makes it possible to study blood HCC biomarkers. Over the past few years, a substantial body of research has been performed worldwide, and other potential biomarkers have been identified. Unfortunately, due to the limitations of each study, only a few markers have been widely verified and are suitable for clinical use. This review briefly summarizes the potential blood metabolic markers related to the diagnosis of HCC, mainly focusing on amino acids and their derivative metabolism, lipids and their derivative metabolism, and other possible related metabolisms.

Pomegranate juice and punicalagin-mediated chemoprevention of hepatocellular carcinogenesis via regulating miR-21 and NF-κB-p65 in a rat model

Background

Hepatocellular carcinoma (HCC) is the most common neoplasm among primary liver malignancies, accounting for 70%–85% of total liver cancer cases worldwide. It is also the second-leading cause of cancer-related death worldwide. Recent research has investigated naturally occurring products high in polyphenolic compounds in the regression and prevention of HCC. This study investigated the chemoprevention effects of pomegranate juice (PJ) and punicalagin (PCG) against diethylnitrosamine (DENA)-induced hepatocarcinogenesis in male albino rats.

Methods

Animals were randomized into six groups and treated for 11 weeks as follows: group 1 was a negative control group, group 2 was treated orally with 10 mL PJ per kilogram body weight (kg bw), group 3 was treated orally with 18.5 mg PCG/kg bw, and groups 4–6 were injected with an intraperitoneal dose of DENA (50 mg/kg bw) weekly beginning in the third week. Group 4 was a HCC control (DENA-treated group), group 5 was HCC + PJ, and group 6 was HCC + PCG.

Results

PJ antagonized DENA-induced elevations of ALAT, TNF-α, NF-κB-p65, GST, MDA, and NO and restored total protein, IL-10, SOD, and CAT levels. Moreover, PJ resulted in downregulation of miR-21, Bcl-2, and Bcl-XL and an upregulation of caspase-3 and Bax mRNA expressions. These chemoprevention effects of PJ also alleviated the hepatic preneoplastic lesions induced by DENA. Although PCG treatment induced some modulation in DENA-treated rats, it did not show potent chemoprevention activity and induced some side effects.

Conclusion

Both of PJ and PCG downregulated miR-21 expression and triggered apoptosis. However, PJ was more effective than pure PCG in alleviating the hepatic antioxidant defense state and the inflammatory status. So, PJ was superior in prevention of DENA-induced hepatocellular carcinogenesis in rats than pure PCG.

Graphical Abstract

During HCV DAA Therapy Plasma Mip1B, IP10, and miRNA Profile Are Distinctly Associated with Subsequent Diagnosis of Hepatocellular Carcinoma: A Pilot Study

Background: Hepatitis C virus (HCV) therapy lowers risk of hepatocellular carcinoma (HCC). Little is known about factors driving/preceding HCC in treated persons. MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) regulate host response and pathogenesis of disease. We investigated plasma levels of these RNAs and select serum markers before, during, and after HCV therapy, preceding HCC. Methods: Of 187 DAA treated HCV patients where therapy oriented longitudinal sampling was performed at a time without HCC diagnosis, 9 were subsequently diagnosed with HCC within 2 years of therapy. They were matched with 7 patients not diagnosed with HCC over the same time period. RNASeq was performed on plasma, and serum was assessed for biomarkers of inflammation by ELISA. Results: HCC diagnosis was 19 months (6-28) after therapy start in the HCC group. 73 and 63 miRs were differentially expressed at baseline (before DAA therapy) and 12 weeks after DAA therapy comparing HCC and non-HCC groups. Several lncRNA- showed differential expression as well. Several miRNA suppressors of cancer-related pathways, lncRNA- and mRNA-derived stabilized short RNAs were consistently absent in the plasma of patients who developed HCC. Serum IP10, and MCP-1 level was higher in the HCC group 12 weeks after therapy, and distinct miRNAs correlated with IP10 and MCP-1. Finally, in a focused analysis of 8 miRNAs best associated with HCC we observed expression of mi576 and mi-5189 correlation with expression of a select group of PBMC mRNA. Conclusions: These results are consistent with complex interplay between RNA-mediated host immune regulation and cancer suppression, strikingly skewed 12 weeks following therapy, prior to HCC diagnosis.

A Bayesian two-step integrative procedure incorporating prior knowledge for the identification of miRNA-mRNAs involved in hepatocellular carcinoma

Recent studies have confirmed the role of miRNA regulation of gene expression in oncogenesis for various cancers. In parallel, prior knowledge about relationships between miRNA and mRNA have been accumulated from biological experiments or statistical analyses. Improved identification of disease-associated miRNA-mRNA pairs may be achieved by incorporating prior knowledge into integrative genomic analyses. In this study we focus on 39 patients with hepatocellular carcinoma (HCC) and 25 patients with liver cirrhosis and use a flexible Bayesian two-step integrative method. We found 66 significant miRNA-mRNA pairs, several of which contain molecules that have previously been identified as potential biomarkers. These results demonstrate the utility of the proposed approach in providing a better understanding of relationships between different biological levels, thereby giving insights into the biological mechanisms underlying the diseases, while providing a better selection of biomarkers that may serve as diagnostic, prognostic, or therapeutic biomarker candidates.

Bi-specific T1 positive-contrast-enhanced magnetic resonance imaging molecular probe for hepatocellular carcinoma in an orthotopic mouse model

BACKGROUND

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality. HCC-targeted magnetic resonance imaging (MRI) is an effective noninvasive diagnostic method that involves targeting clinically-related HCC biomarkers, such as alpha-fetoprotein (AFP) or glypican-3 (GPC3), with iron oxide nanoparticles. However, in vivo studies of HCC-targeted MRI utilize single-target iron oxide nanoprobes as negative (T2) contrast agents, which might weaken their future clinical applications due to tumor heterogeneity and negative MRI contrast. Ultra-small superparamagnetic iron oxide (USPIO) nanoparticles (approximately 5 nm) are potential optimal positive (T1) contrast agents. We previously verified the efficiency of AFP/GPC3-double-antibody-labeled iron oxide MR molecular probe in vitro.

AIM

To validate the effectiveness of a bi-specific probe in vivo for enhancing T1-weighted positive contrast to diagnose the early-stage HCC.

METHODS

The single- and double-antibody-conjugated 5-nm USPIO probes, including anti-AFP-USPIO (UA), anti-GPC3-USPIO (UG), and anti-AFP-USPIO-anti-GPC3 (UAG), were synthesized. T1- and T2-weighted MRI were performed on day 10 after establishment of the orthotopic HCC mouse model. Following intravenous injection of U, UA, UG, and UAG probes, T1- and T2-weighted images were obtained at 12, 12, and 32 h post-injection. At the end of scanning, mice were euthanized, and a histologic analysis was performed on tumor samples.

RESULTS

T1- and T2-weighted MRI showed that absolute tumor-to-background ratios in UAG-treated HCC mice peaked at 24 h post-injection, with the T1- and T2-weighted signals increasing by 46.7% and decreasing by 11.1%, respectively, relative to pre-injection levels. Additionally, T1-weighted contrast in the UAG-treated group at 24 h post-injection was enhanced 1.52-, 2.64-, and 4.38-fold compared to those observed for single-targeted anti-GPC3-USPIO, anti-AFP-USPIO, and non-targeted USPIO probes, respectively. Comparison of U-, UA-, UG-, and UAG-treated tumor sections revealed that UAG-treated mice exhibited increased stained regions compared to those observed in UG- or UA-treated mice.

CONCLUSION

The bi-specific T1-positive contrast-enhanced MRI probe (UAG) for HCC demonstrated increased specificity and sensitivity to diagnose early-stage HCC irrespective of tumor size and/or heterogeneity.

Identification of Immune-Related Prognostic mRNA and lncRNA in Patients with Hepatocellular Carcinoma

Background

As the most common hepatic malignancy, hepatocellular carcinoma (HCC) has a high incidence; therefore, in this paper, the immune-related genes were sought as biomarkers in liver cancer.

Methods

In this study, a differential expression analysis of lncRNA and mRNA in The Cancer Genome Atlas (TCGA) dataset between the HCC group and the normal control group was performed. Enrichment analysis was used to screen immune-related differentially expressed genes. Cox regression analysis and survival analysis were used to determine prognostic genes of HCC, whose expression was detected by molecular experiments. Finally, important immune cells were identified by immune cell infiltration and detected by flow cytometry.

Results

Compared with the normal group, 1613 differentially expressed mRNAs (DEmRs) and 1237 differentially expressed lncRNAs (DElncRs) were found in HCC. Among them, 143 immune-related DEmRs and 39 immune-related DElncRs were screened out. These genes were mainly related to MAPK cascade, PI3K-AKT signaling pathway, and TGF-beta. Through Cox regression analysis and survival analysis, MMP9, SPP1, HAGLR, LINC02202, and RP11-598F7.3 were finally determined as the potential diagnostic biomarkers for HCC. The gene expression was verified by RT-qPCR and western blot. In addition, CD4 + memory resting T cells and CD8 + T cells were identified as protective factors for overall survival of HCC, and they were found highly expressed in HCC through flow cytometry.

Conclusion

The study explored the dysregulation mechanism and potential biomarkers of immune-related genes and further identified the influence of immune cells on the prognosis of HCC, providing a theoretical basis for the prognosis prediction and immunotherapy in HCC patients.

Monitoring one-carbon metabolism by mass spectrometry to assess liver function and disease

Precision medicine promises to overcome the constraints of the traditional “one-for-all” healthcare approach through a clear understanding of the molecular features of a disease, allowing for innovative and tailored treatments. State-of-the-art proteomics has the potential to accurately explore the human proteome to identify, quantify, and characterize proteins associated with disease progression. There is a pressing need for informative biomarkers to diagnose liver disease early in its course to prevent severe disease for which no efficient treatment is yet available. Here, we propose the concept of a cellular pathway as a functional biomarker, whose monitorization may inform normal and pathological status. We have developed a standardized targeted selected-reaction monitoring assay to detect and quantify 13 enzymes of one-carbon metabolism (1CM). The assay is compliant with Clinical Proteomics Tumor Analysis Consortium (CPTAC) guidelines and has been included in the protein quantification assays that can be accessed through the assay portal at the CPTAC web page. To test the feasibility of the assay, we conducted a retrospective, proof-of-concept study on a collection of liver samples from healthy controls and from patients with cirrhosis or hepatocellular carcinoma (HCC). Our results indicate a significant reconfiguration of 1CM upon HCC development resulting from a process that can already be identified in cirrhosis. Our findings indicate that the systematic and integrated quantification of 1CM enzymes is a promising cell function-based biomarker for patient stratification, although further experiments with larger cohorts are needed to confirm these findings.

Potential lncRNA Biomarkers for HBV-Related Hepatocellular Carcinoma Diagnosis Revealed by Analysis on Coexpression Network

Background

Increasing evidence demonstrated that long noncoding RNA (lncRNA) could affect inflammatory tumor immune microenvironment by modulating gene expression and could be used as a biomarker for HBC-related hepatocellular carcinoma (HCC) but still needs further research. The aim of the present study was to determine an lncRNA signature for the diagnosis of HBV-related HCC.

Methods

HBV-related HCC expression profiles (GSE55092, GSE19665, and GSE84402) were abstracted from the GEO (Gene Expression Omnibus) data resource, and R package limma and RobustRankAggreg were employed to identify common differentially expressed genes (DEGs). Using machine learning, optimal diagnostic lncRNA molecular markers for HBV-related HCC were identified. The expression of candidate lncRNAs was cross-validated in GSE121248, and an ROC (receiver operating characteristic) curve of lncRNA biomarkers was carried out. Additionally, a coexpression network and functional annotation was built, after which a PPI (protein-protein interaction) network along with module analysis were conducted with the Cytoscape open source software.

Result

A total of 38 DElncRNAs and 543 DEmRNAs were identified with a fold change larger than 2.0 and a P value < 0.05. By machine learning, AL356056.2, AL445524.1, TRIM52-AS1, AC093642.1, EHMT2-AS1, AC003991.1, AC008040.1, LINC00844, and LINC01018 were screened out as optional diagnostic lncRNA biosignatures for HBV-related HCC. The AUC (areas under the curve) of the SVM (support vector machine) model and random forest model were 0.957 and 0.904, respectively, and the specificity and sensitivity were 95.7 and 100% and 94.3 and 86.5%, respectively. The results of functional enrichment analysis showed that the integrated coexpressed DEmRNAs shared common cascades in the p53 signaling pathway, retinol metabolism, PI3K-Akt signaling cascade, and chemical carcinogenesis. The integrated DEmRNA PPI network complex was found to be comprised of 87 nodes, and two vital modules with a high degree were selected with the MCODE app.

Conclusion

The present study identified nine potential diagnostic biomarkers for HBV-related HCC, all of which could potentially modulated gene expression related to inflammatory conditions in the tumor immune microenvironment. The functional annotation of the target DEmRNAs yielded novel evidence in evaluating the precise functions of lncRNA in HBV-related HCC.

Identifying novel transcript biomarkers for hepatocellular carcinoma (HCC) using RNA-Seq datasets and machine learning

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death in the world owing to limitations in its prognosis. The current prognosis approaches include radiological examination and detection of serum biomarkers, however, both have limited efficiency and are ineffective in early prognosis. Due to such limitations, we propose to use RNA-Seq data for evaluating putative higher accuracy biomarkers at the transcript level that could help in early prognosis.

METHODS

To identify such potential transcript biomarkers, RNA-Seq data for healthy liver and various HCC cell models were subjected to five different machine learning algorithms: random forest, K-nearest neighbor, Naïve Bayes, support vector machine, and neural networks. Various metrics, namely sensitivity, specificity, MCC, informedness, and AUC-ROC (except for support vector machine) were evaluated. The algorithms that produced the highest values for all metrics were chosen to extract the top features that were subjected to recursive feature elimination. Through recursive feature elimination, the least number of features were obtained to differentiate between the healthy and HCC cell models.

RESULTS

From the metrics used, it is demonstrated that the efficiency of the known protein biomarkers for HCC is comparatively lower than complete transcriptomics data. Among the different machine learning algorithms, random forest and support vector machine demonstrated the best performance. Using recursive feature elimination on top features of random forest and support vector machine three transcripts were selected that had an accuracy of 0.97 and kappa of 0.93. Of the three transcripts, two were protein coding (PARP2-202 and SPON2-203) and one was a non-coding transcript (CYREN-211). Lastly, we demonstrated that these three selected transcripts outperformed randomly taken three transcripts (15,000 combinations), hence were not chance findings, and could then be an interesting candidate for new HCC biomarker development.

CONCLUSION

Using RNA-Seq data combined with machine learning approaches can aid in finding novel transcript biomarkers. The three biomarkers identified: PARP2-202, SPON2-203, and CYREN-211, presented the highest accuracy among all other transcripts in differentiating the healthy and HCC cell models. The machine learning pipeline developed in this study can be used for any RNA-Seq dataset to find novel transcript biomarkers. Code: www.github.com/rajinder4489/ML_biomarkers.

Hepatic mRNA Expression Levels of the Oncogenes Alpha-Fetoprotein and Osteopontin as Diagnostics for Liver Cancer in a Murine Model of Diet-Induced Non-Alcoholic Steatohepatitis

Non-alcoholic steatohepatitis (NASH) is associated with an increased risk of hepatocellular carcinoma (HCC). Expression levels of hepatic oncogenes, alpha-fetoprotein (afp) and osteopontin (opn)/secreted phosphoprotein 1 (spp1), were investigated using a model of diet-induced NASH. Mice were randomized to a standard diet or a fast-food diet (FFD) for 17 months. Livers from the FFD cohort exhibited hallmark characteristics of NASH with liver fibrosis, with a subset of animals exhibiting HCC. Expression levels of hepatic afp and opn/spp1 were elevated ~2.5 and ~5-fold, respectively, in the FFD cohort. Hepatic opn/spp1 exhibited a direct (r = 0.65) and significant (p < 0.01) correlation with liver hydroxyproline content. Receiver operating characteristic (ROC) curve analysis for hepatic afp, as a diagnostic for HCC, returned an area under (AU) ROC 0.84, a sensitivity of 87.5%, a specificity of 77% and a threshold of >1.05-fold change in mRNA level. The use of hepatic opn/ssp1 as a diagnostic for HCC returned an AUROC 0.88, a sensitivity of 83.3%, a specificity of 86.7% and a threshold of >2.4-fold change in mRNA level. These data point to a transformation of NASH to an oncotype with hepatic oncogene levels as a diagnostic for NASH.

Longitudinal Circulating Levels of miR-23b-3p, miR-126-3p and lncRNA GAS5 in HCC Patients Treated with Sorafenib

Human hepatocellular carcinoma (HCC) is the most frequent primary tumor of the liver and the third cause of cancer-related deaths. The multikinase inhibitor sorafenib is a systemic drug for unresectable HCC. The identification of molecular biomarkers for the early diagnosis of HCC and responsiveness to treatment are needed. In this work, we performed an exploratory study to investigate the longitudinal levels of cell-free long ncRNA GAS5 and microRNAs miR-126-3p and -23b-3p in a cohort of 7 patients during the period of treatment with sorafenib. We used qPCR to measure the amounts of GAS5 and miR-126-3p and droplet digital PCR (ddPCR) to measure the levels of miR-23b-3p. Patients treated with sorafenib displayed variable levels of GAS5, miR-126-3p and miR-23b-3p at different time-points of follow-up. miR-23b-3p was further measured by ddPCR in 37 healthy individuals and 25 untreated HCC patients. The amount of miR-23b-3p in the plasma of untreated HCC patients was significantly downregulated if compared to healthy individuals. The ROC curve analysis underlined its diagnostic relevance. In conclusion, our results highlight a potential clinical significance of circulating miR-23b-3p and an exploratory observation on the longitudinal plasmatic levels of GAS5, miR-126-3p and miR-23b-3p during sorafenib treatment.

Tumor metabolism and associated serum metabolites define prognostic subtypes of Asian hepatocellular carcinoma

Treatment effectiveness in hepatocellular carcinoma (HCC) depends on early detection and precision-medicine-based patient stratification for targeted therapies. However, the lack of robust biomarkers, particularly a non-invasive diagnostic tool, precludes significant improvement of clinical outcomes for HCC patients. Serum metabolites are one of the best non-invasive means for determining patient prognosis, as they are stable end-products of biochemical processes in human body. In this study, we aimed to identify prognostic serum metabolites in HCC. To determine serum metabolites that were relevant and representative of the tissue status, we performed a two-step correlation analysis to first determine associations between metabolic genes and tissue metabolites, and second, between tissue metabolites and serum metabolites among 49 HCC patients, which were then validated in 408 additional Asian HCC patients with mixed etiologies. We found that certain metabolic genes, tissue metabolites and serum metabolites can independently stratify HCC patients into prognostic subgroups, which are consistent across these different data types and our previous findings. The metabolic subtypes are associated with β-oxidation process in fatty acid metabolism, where patients with worse survival outcome have dysregulated fatty acid metabolism. These serum metabolites may be used as non-invasive biomarkers to define prognostic tumor molecular subtypes for HCC.

Diagnosis and Resection Treatment of Triplet Hepatocellular Carcinomas with a non-B non-C Background in a Middle Aged Man over a Period of 6-years

We report a 71-year-old man with non-B non-C chronic liver damage who had been regularly visiting our hospital since he was 38 years of age. He underwent three partial hepatectomies for hepatocellular carcinoma (HCC) diagnosed at 65, 67, and 71 years of age, respectively. A histopathological examination showed moderately-differentiated HCC, and chronic hepatitis with mild fibrosis stage in non-tumor areas. alpha-fetoprotein (AFP) and PIVKAII were not useful for the early prediction of HCC, but TERT promotor mutation (C228T) in serum cell-free DNA was useful. This is the first report on the importance of long-term follow-up in non-B non-C chronic liver damage, regardless of the fibrosis stage.

Integrative Analysis to Identify Race-Associated Metabolite Biomarkers for Hepatocellular Carcinoma

Compared to European-Americans (EAs), the incidence of hepatocellular carcinoma (HCC) is higher in African-Americans (AAs) and is associated with more advanced tumor stage at diagnosis and lower survival rates. The increasing burden makes discovery of novel diagnostic, prognostic, and therapeutic biomarkers distinguishing HCC from underlying cirrhosis a significant focus. In this study, we analyzed tissue and serum samples from 40 HCC cases and 25 patients with liver cirrhosis to identify candidate biomarkers that distinguish HCC from cirrhotic patients in a race specific manner. Through integrative analysis of transcriptomic and metabolomic data, we investigated candidate metabolite biomarkers that are specific to AAs and EAs. The results from this demonstrate the utility of integrating transcriptomic and metabolomic data to prioritize clinically and biologically relevant metabolite biomarkers that can increase understanding of molecular mechanisms driving HCC in different racial groups.

Liver Biopsy Hydroxyproline Content Is a Diagnostic for Hepatocellular Carcinoma in Murine Models of Nonalcoholic Steatohepatitis

There is increasing evidence that nonalcoholic steatohepatitis (NASH) is a risk factor for hepatocellular carcinoma (HCC) in the absence of cirrhosis, a phenomenon termed noncirrhotic HCC. Early diagnosis of HCC is critical to a favorable prognosis. We tested the hypothesis that hydroxyproline content of liver biopsy samples is diagnostic for HCC in murine models of NASH induced by diet or by diet and chemicals. The training set comprised mice fed a standard diet or a fast-food diet with or without administration of thioacetamide. At harvest, livers from the modified diet cohort exhibited NASH with a subset of NASH livers exhibiting HCC. Hydroxyproline content was measured in liver biopsy samples with tissue in the NASH+HCC cohort sampled from the remote, nontumor parenchyma. Plotting the receiver operating characteristics (ROC) with hydroxyproline as the continuous variable against the absence or presence of HCC yielded an area under ROC of 0.87, a threshold of >0.18 μg hydroxyproline/mg liver and sensitivity of 91% with a specificity of 83.3%. The use of liver hydroxyproline content as a diagnostic for HCC in a test set comprising healthy, NASH and NASH+HCC livers proved 87% accurate.

A Circulating Long Noncoding RNA Panel Serves as a Diagnostic Marker for Hepatocellular Carcinoma

Background

Circulating long noncoding RNAs (lncRNAs) have been demonstrated to serve as diagnostic biomarkers for various cancers. We aimed to elucidate the diagnostic efficacy of eight serum lncRNAs HULC, MALAT1, Linc00152, PTENP1, PTTG3P, SPRY4-IT1, UBE2CP3, and UCA1 and their combinations for the diagnosis of hepatocellular carcinoma (HCC).

Methods

A total of 129 patients with HCC, 49 patients with liver cirrhosis, 27 patients with chronic hepatitis B, and 93 healthy controls were enrolled in this study. The levels of serum lncRNAs were assessed by quantitative real-time polymerase chain reaction. The correlations between serum lncRNAs and clinicopathological characteristics were further analyzed. The receiver operating characteristic (ROC) curve and area under curve (AUC) were utilized to estimate the diagnostic capacity of serum lncRNAs and their combination with AFP for HCC. A logistic regression model was performed to establish a multiple-lncRNA panel.

Results

The levels of serum HULC, MALAT1, Linc00152, PTTG3P, SPRY4-IT1, UBE2CP3, and UCA1 were significantly higher in HCC patients than in patients with benign liver diseases and healthy controls, whereas serum PTENP1 was significantly decreased in HCC patients compared with healthy participants. Positive correlations between serum Linc00152 and GGT, serum PTTG3P and GGT, and serum SPRY4-IT1 and ALT were noted in HCC patients. ROC analysis revealed that all these lncRNAs had a significantly predictive value for HCC except for PTENP1. The best performance of single lncRNA was obtained by Linc00152 with an AUC of 0.877. When combined with AFP, the combination of Linc00152 and AFP gained the highest accuracy, yielding an AUC of 0.906. Through logistic regression analysis, the panel consisting of serum linc00152, UCA1, and AFP provided the greatest predictive ability, obtaining an AUC of 0.912 with 82.9% sensitivity and 88.2% specificity.

Conclusion

The panel of serum Linc00152, UCA1, and AFP demonstrates a novel and noninvasive biomarker with relatively high sensitivity and specificity for HCC diagnosis.

The Prediction of Survival in Hepatocellular Carcinoma Based on A Four Long Non-coding RNAs Expression Signature

Prognostic stratification in hepatocellular carcinoma (HCC) patients is still challenging. Long non-coding RNAs (lncRNAs) have been proven to play a crucial role in tumorigenesis and progression of cancers. The aim of this study is to develop a useful prognostic index based on lncRNA signature to identify patients at high risk of disease progression. We obtained lncRNA expression profiles from three publicly available datasets from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). By the risk scoring method, we built an individualized four-lncRNA signature (HCCLnc-4) to predict survival of HCC patients in the discovery set (ROC curve, AUC: 0.83, 95% CI: 0.65-1.00, P < 0.05, Kaplan-Meier analysis and log-rank test, P < 0.01). Similar prognostic value of HCCLnc-4 has been further verified in two other independent sets. Stratified analysis and multivariate Cox regression analysis suggested the independence of HCCLnc-4 for prediction of HCC patient survival from traditional clinicopathological factors. Area under curve (AUC) analysis suggested that HCCLnc-4 could compete sufficiently with, or might be even better than classical pathological staging systems to predict HCC patient prognosis in the same data sets. Functional analysis and network analysis suggested the potential implication of lncRNA biomarkers. Our study developed and validated the lncRNA prognostic index of HCC patients, warranting further clinical evaluation and preventive interventions.

Identification of Candidate Biomarkers for HCV Leading to Hepatocellular Carcinoma Differential Stages From Serum Samples

Background:

Hepatocellular carcinoma (HCC) is one of the most deadly liver malignancy found and Hepatitis C virus (HCV) is a prominent risk factor for this disease. Prognosis of HCC is poor; initiate the need of markers to discover therapeutic targets in HCC.

Introduction:

Clinical staging systems of HCC composed of tumor characteristics along with liver function test are important in prognosis but they are not precise. Molecular profiling can lead to a better understanding of the physiopathology of HCC and can help in the development of novel therapeutic approaches.

Methods:

64 HCC serum samples (shifted from HCV) were graded into stage I- IV; along with +ive (3 Hepatitis C) and -ive control (2 healthy persons). Proteins were separated by sodium dodecyl sulfatepolyacrylamide gel electrophoresis (SDS-PAGE) and differential mRNA expression from serum samples of different HCC stages was confirmed by Real Time Polymerase Chain Reaction (qPCR).

Results:

HCC serum proteins displayed differential expression of glutathione s-transferase (GST), glypican-3 (GPC3), vitronectin (VTN), and clusterin (CLU) by SDS-PAGE. GST was expressed in -ive control, while GPC3 was found in both -ive and +ive control. The qPCR analysis, display more than 0.07 fold decrease in GST in I-IV HCC stages. The highest increase in HCC stages was observed by GPC3; about 4 fold increase in I-IV stages. VTN show 1.7-3.4 fold; while CLU show 2-3.5 fold increase in four stages of HCC.

Conclusion:

GPC3, VTN and CLU in combination can be good potential markers for differentiating stages (I-IV) of HCC.

Origin and role of hepatic myofibroblasts in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and is the second leading cause of cancer-related death worldwide. Fibrosis and cirrhosis are important risk factors for the development of HCC. Hepatic myofibroblasts are the cells responsible for extracellular matrix deposition, which is the hallmark of liver fibrosis. It is believed that myofibroblasts are predominantly derived from hepatic stellate cells (HSCs), also known as Ito cells. Nevertheless, depending on the nature of insult to the liver, it is thought that myofibroblasts may also originate from a variety of other cell types such as the portal fibroblasts (PFs), fibrocytes, hepatocytes, hepatic progenitor cells (HPCs), and mesothelial cells. Liver myofibroblasts are believed to transform into cancer-associated fibroblasts (CAFs) while HCC is developing. There is substantial evidence suggesting that activated HSCs (aHSCs)/cancer-associated fibroblasts (CAFs) may play an important role in HCC initiation and progression. In this paper, we aim to review current literature on cellular origins of myofibroblasts with a focus on hepatitis B virus (HBV)- and hepatitis C virus (HCV)-induced hepatic fibrosis. We also address the role of aHSCs/CAFs in HCC progression through the regulation of immune cells as well as mechanisms of evolvement of drug resistance.

Origin and role of hepatic myofibroblasts in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and is the second leading cause of cancer-related death worldwide. Fibrosis and cirrhosis are important risk factors for the development of HCC. Hepatic myofibroblasts are the cells responsible for extracellular matrix deposition, which is the hallmark of liver fibrosis. It is believed that myofibroblasts are predominantly derived from hepatic stellate cells (HSCs), also known as Ito cells. Nevertheless, depending on the nature of insult to the liver, it is thought that myofibroblasts may also originate from a variety of other cell types such as the portal fibroblasts (PFs), fibrocytes, hepatocytes, hepatic progenitor cells (HPCs), and mesothelial cells. Liver myofibroblasts are believed to transform into cancer-associated fibroblasts (CAFs) while HCC is developing. There is substantial evidence suggesting that activated HSCs (aHSCs)/cancer-associated fibroblasts (CAFs) may play an important role in HCC initiation and progression. In this paper, we aim to review current literature on cellular origins of myofibroblasts with a focus on hepatitis B virus (HBV)- and hepatitis C virus (HCV)-induced hepatic fibrosis. We also address the role of aHSCs/CAFs in HCC progression through the regulation of immune cells as well as mechanisms of evolvement of drug resistance.

Identification of miRNA-mRNA associations in hepatocellular carcinoma using hierarchical integrative model

Background

The established role miRNA-mRNA regulation of gene expression has in oncogenesis highlights the importance of integrating miRNA with downstream mRNA targets. These findings call for investigations aimed at identifying disease-associated miRNA-mRNA pairs. Hierarchical integrative models (HIM) offer the opportunity to uncover the relationships between disease and the levels of different molecules measured in multiple omic studies.

Methods

The HIM model we formulated for analysis of mRNA-seq and miRNA-seq data can be specified with two levels: (1) a mechanistic submodel relating mRNAs to miRNAs, and (2) a clinical submodel relating disease status to mRNA and miRNA, while accounting for the mechanistic relationships in the first level.

Results

mRNA-seq and miRNA-seq data were acquired by analysis of tumor and normal liver tissues from 30 patients with hepatocellular carcinoma (HCC). We analyzed the data using HIM and identified 157 significant miRNA-mRNA pairs in HCC. The majority of these molecules have already been independently identified as being either diagnostic, prognostic, or therapeutic biomarker candidates for HCC. These pairs appear to be involved in processes contributing to the pathogenesis of HCC involving inflammation, regulation of cell cycle, apoptosis, and metabolism. For further evaluation of our method, we analyzed miRNA-seq and mRNA-seq data from TCGA network. While some of the miRNA-mRNA pairs we identified by analyzing both our and TCGA data are previously reported in the literature and overlap in regulation and function, new pairs have been identified that may contribute to the discovery of novel targets.

Conclusion

The results strongly support the hypothesis that miRNAs are important regulators of mRNAs in HCC. Furthermore, these results emphasize the biological relevance of studying miRNA-mRNA pairs.

Patients with Cholangiocarcinoma Present Specific RNA Profiles in Serum and Urine Extracellular Vesicles Mirroring the Tumor Expression: Novel Liquid Biopsy Biomarkers for Disease Diagnosis

Cholangiocarcinoma (CCA) comprises a group of heterogeneous biliary cancers with dismal prognosis. The etiologies of most CCAs are unknown, but primary sclerosing cholangitis (PSC) is a risk factor. Non-invasive diagnosis of CCA is challenging and accurate biomarkers are lacking. We aimed to characterize the transcriptomic profile of serum and urine extracellular vesicles (EVs) from patients with CCA, PSC, ulcerative colitis (UC), and healthy individuals. Serum and urine EVs were isolated by serial ultracentrifugations and characterized by nanoparticle tracking analysis, transmission electron microscopy, and immunoblotting. EVs transcriptome was determined by Illumina gene expression array [messenger RNAs (mRNA) and non-coding RNAs (ncRNAs)]. Differential RNA profiles were found in serum and urine EVs from patients with CCA compared to control groups (disease and healthy), showing high diagnostic capacity. The comparison of the mRNA profiles of serum or urine EVs from patients with CCA with the transcriptome of tumor tissues from two cohorts of patients, CCA cells in vitro, and CCA cells-derived EVs, identified 105 and 39 commonly-altered transcripts, respectively. Gene ontology analysis indicated that most commonly-altered mRNAs participate in carcinogenic steps. Overall, patients with CCA present specific RNA profiles in EVs mirroring the tumor, and constituting novel promising liquid biopsy biomarkers.

Multi-omic Pathway and Network Analysis to Identify Biomarkers for Hepatocellular Carcinoma

The threat of Hepatocellular Carcinoma (HCC) is a growing problem, with incidence rates anticipated to near double over the next two decades. The increasing burden makes discovery of novel diagnostic, prognostic, and therapeutic biomarkers distinguishing HCC from underlying cirrhosis a significant focus. In this study, we analyzed tissue and serum samples from 40 HCC cases and 25 patients with liver cirrhosis (CIRR) to better understand the mechanistic differences between HCC and CIRR. Through pathway and network analysis, we are able to take a systems biology approach to conduct multi-omic analysis of transcriptomic, glycoproteomic, and metabolomic data acquired through various platforms. As a result, we are able to identify the FXR/RXR Activation pathway as being represented by molecules spanning multiple molecular compartments in these samples. Specifically, serum metabolites deoxycholate and chenodeoxycholic acid and serum glycoproteins C4A/C4B, KNG1, and HPX are biomarker candidates identified from this analysis that are of interest for future targeted studies. These results demonstrate the integrative power of multi-omic analysis to prioritize clinically and biologically relevant biomarker candidates that can increase understanding of molecular mechanisms driving HCC and make an impact in patient care.

Proteomic Analysis of Human Serum from Patients with Chronic Kidney Disease

Chronic kidney disease (CKD) is an important public health problem in the world. The aim of our research was to identify novel potential serum biomarkers of renal injury. ELISA assay showed that cytokines and chemokines IL-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12 (p70), IL-13, IL-15, IL-17, Eotaxin, FGFb, G-CSF, GM-CSF, IP-10, MCP-1, MIP-1α, MIP-1β, PDGF-1bb, RANTES, TNF-α and VEGF were significantly higher (R > 0.6, p value < 0.05) in the serum of patients with CKD compared to healthy subjects, and they were positively correlated with well-established markers (urea and creatinine). The multiple reaction monitoring (MRM) quantification method revealed that levels of HSP90B2, AAT, IGSF22, CUL5, PKCE, APOA4, APOE, APOA1, CCDC171, CCDC43, VIL1, Antigen KI-67, NKRF, APPBP2, CAPRI and most complement system proteins were increased in serum of CKD patients compared to the healthy group. Among complement system proteins, the C8G subunit was significantly decreased three-fold in patients with CKD. However, only AAT and HSP90B2 were positively correlated with well-established markers and, therefore, could be proposed as potential biomarkers for CKD.

Aptamer-Functionalized Drug Nanocarrier Improves Hepatocellular Carcinoma toward Normal by Targeting Neoplastic Hepatocytes

Site-specific delivery of chemotherapeutics specifically to neoplastic hepatocytes without affecting normal hepatocytes should be a focus for potential therapeutic management of hepatocellular carcinoma (HCC). The aptamer TLS 9a with phosphorothioate backbone modifications (L5) has not been explored so far for preferential delivery of therapeutics in neoplastic hepatocytes to induce apoptosis. Thus, the objective of the present investigation was to compare the therapeutic potential of L5-functionalized drug nanocarrier (PTX-NPL5) with those of the other experimental drug nanocarriers functionalized by previously reported HCC cell-targeting aptamers and non-aptamer ligands, such as galactosamine and apotransferrin. A myriad of well-defined investigations such as cell cycle analysis, TUNEL (terminal deoxynucleotidyltransferase-mediated deoxyuridine triphosphate nick end labeling) assay, and studies related to apoptosis, histopathology, and immunoblotting substantiated that PTX-NPL5 had the highest potency among the different ligand-attached experimental formulations in inducing selective apoptosis in neoplastic hepatocytes via a mitochondrial-dependent apoptotic pathway. PTX-NPL5 did not produce any notable toxic effects in healthy hepatocytes, thus unveiling a new and a safer option in targeted therapy for HCC. Molecular modeling study identified two cell-surface biomarker proteins (tumor-associated glycoprotein 72 [TAG-72] and heat shock protein 70 [HSP70]) responsible for ligand-receptor interaction of L5 and preferential internalization of PTX-NPL5 via clathrin-mediated endocytosis in neoplastic hepatocytes. The potential of PTX-NPL5 has provided enough impetus for its rapid translation from the pre-clinical to clinical domain to establish itself as a targeted therapeutic to significantly prolong survival in HCC.

The Emerging Role of Long Non-Coding RNAs in the Metastasis of Hepatocellular Carcinoma

Long non-coding RNAs (lncRNAs) play multifaceted roles in modulating gene expression under both physiological and pathological processes. The dysregulation of lncRNAs has been increasingly linked with many human diseases, including a plethora of cancers. Mounting evidence indicates that lncRNAs are aberrantly expressed in hepatocellular carcinoma (HCC) and can regulate HCC progression, as well as metastasis. In this review, we summarize the recent findings on the expanding roles of lncRNAs in modulating various functions of HCC, and elaborate on how can lncRNAs impact HCC metastasis and progression via interacting with chromatin, RNA, and proteins at the epigenetic, transcriptional, and post-transcriptional levels. This mini-review also highlights the current advances regarding the signaling pathways of lncRNAs in HCC metastasis and sheds light on the possible application of lncRNAs for the prevention and treatment of HCC.

Acylcarnitine: Useful biomarker for early diagnosis of hepatocellular carcinoma in non-steatohepatitis patients

BACKGROUND

Early diagnosis of hepatocellular carcinoma (HCC) is necessary to improve the prognosis of patients. However, the currently available tumor biomarkers are insufficient for the early detection of HCC. Acylcarnitine is essential in fatty acid metabolic pathways. A recent study reported that a high level of acylcarnitine may serve as a useful biomarker for the early diagnosis of HCC in steatohepatitis (SH) patients. In contrast, another study reported that the level of acetylcarnitine (AC2) - one of the acylcarnitine species - in non-SH patients with HCC was decreased vs that reported in those without HCC.

AIM

To investigate the usefulness of acylcarnitine as a biomarker for the early diagnosis of HCC in non-SH patients.

METHODS

Thirty-three non-SH patients (14 with HCC and 19 without HCC) were enrolled in this study. Blood samples were obtained from patients at the time of admission. The levels of acylcarnitine and AC2 in the serum were determined through tandem mass spectrometry. The levels of vascular endothelial growth factor (VEGF) and VEGF receptor 2 (VEGFR-2) were determined by enzyme-linked immunosorbent assay. Univariate and multivariate analyses were used to determine early diagnostic factors of HCC.

RESULTS

The level of acylcarnitine was significantly lower in non-SH patients with HCC vs those without HCC (P < 0.05). In contrast, the level of lens culinaris agglutinin-reactive fraction of α-fetoprotein (AFP) - AFP-L3% - was significantly higher in non-SH patients with HCC vs those without HCC (P < 0.05). However, the levels of total carnitine, free carnitine, AFP, des-γ-carboxy prothrombin, VEGF, and VEGFR-2 were not different between patients with and without HCC. The multivariate analysis showed that a low level of acylcarnitine was the only independent factor for the early diagnosis of HCC. The patients with a low level of AC2 had a significantly higher level of VEGF vs those with a high level of AC2 (P < 0.05).

CONCLUSION

The metabolic pathways of fatty acids may differ between SH HCC and non-SH HCC. Further studies are warranted to investigate these differences.

Comprehensive investigation of key biomarkers and pathways in hepatitis B virus-related hepatocellular carcinoma

Objective: Our study is aim to explore potential key biomarkers and pathways in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) using genome-wide expression profile dataset and methods.

Methods: Dataset from the GSE14520 is used as the training cohort and The Cancer Genome Atlas dataset as the validation cohort. Differentially expressed genes (DEGs) screening were performed by the limma package. Gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), gene ontology, the Kyoto Encyclopedia of Genes and Genomes, and risk score model were used for pathway and genes identification.

Results: GSEA revealed that several pathways and biological processes are associated with hepatocarcinogenesis, such as the cell cycle, DNA repair, and p53 pathway. A total of 160 DEGs were identified. The enriched functions and pathways of the DEGs included toxic substance decomposition and metabolism processes, and the P450 and p53 pathways. Eleven of the DEGs were identified as hub DEGs in the WGCNA. In survival analysis of hub DEGs, high expression of PRC1 and TOP2A were significantly associated with poor clinical outcome of HBV-related HCC, and shown a good performance in HBV-related HCC diagnosis. The prognostic signature consisting of PRC1 and TOP2A also doing well in the prediction of HBV-related HCC prognosis. The diagnostic and prognostic values of PRC1 and TOP2A was confirmed in TCGA HCC patients.

Conclusions: Key biomarkers and pathways identified in the present study may enhance the comprehend of the molecular mechanisms underlying hepatocarcinogenesis. Additionally, mRNA expression of PRC1 and TOP2A may serve as potential diagnostic and prognostic biomarkers for HBV-related HCC.

Development and in vitro study of a bi-specific magnetic resonance imaging molecular probe for hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) ranks second in terms of cancer mortality worldwide. Molecular magnetic resonance imaging (MRI) targeting HCC biomarkers such as alpha-fetoprotein (AFP) or glypican-3 (GPC3) offers new strategies to enhance specificity and help early diagnosis of HCC. However, the existing iron oxide nanoparticle-based MR molecular probes singly target AFP or GPC3, which may hinder their efficiency to detect heterogeneous micro malignant HCC tumors < 1 cm (MHCC). We hypothesized that the strategy of double antibody-conjugated iron oxide nanoparticles which simultaneously target AFP and GPC3 antigens may potentially be used to overcome the tumor heterogeneity and enhance the detection rate for MRI-based MHCC diagnosis.

AIM

To synthesize an AFP/GPC3 double antibody-labeled iron oxide MRI molecular probe and to assess its impact on MRI specificity and sensitivity at the cellular level.

METHODS

A double antigen-targeted MRI probe for MHCC anti-AFP–USPIO–anti-GPC3 (UAG) was developed by simultaneously conjugating AFP andGPC3 antibodies to a 5 nm ultra-small superparamagnetic iron oxide nanoparticle (USPIO). At the same time, the singly labeled probes of anti-AFP–USPIO (UA) and anti-GPC3–USPIO (UG) and non-targeted USPIO (U) were also prepared for comparison. The physical characterization including morphology (transmission electron microscopy), hydrodynamic size, and zeta potential (dynamic light scattering) was conducted for each of the probes. The antigen targeting and MRI ability for these four kinds of USPIO probes were studied in the GPC3-expressing murine hepatoma cell line Hepa1-6/GPC3. First, AFP and GPC3 antigen expression in Hepa1-6/GPC3 cells was confirmed by flow cytometry and immunocytochemistry. Then, the cellular uptake of USPIO probes was investigated by Prussian blue staining assay and in vitro MRI (T2-weighted and T2-map) with a 3.0 Tesla clinical MR scanner.

RESULTS

Our data showed that the double antibody-conjugated probe UAG had the best specificity in targeting Hepa1-6/GPC3 cells expressing AFP and GPC3 antigens compared with single antibody-conjugated and unconjugated USPIO probes. The iron Prussian blue staining and quantitative T2-map MRI analysis showed that, compared with UA, UG, and U, the uptake of double antigen-targeted UAG probe demonstrated a 23.3% (vs UA), 15.4% (vs UG), and 57.3% (vs U) increased Prussian stained cell percentage and a 14.93% (vs UA), 9.38% (vs UG), and 15.3% (vs U) reduction of T2 relaxation time, respectively. Such bi-specific probe might have the potential to overcome tumor heterogeneity. Meanwhile, the coupling of two antibodies did not influence the magnetic performance of USPIO, and the relatively small hydrodynamic size (59.60 ± 1.87 nm) of double antibody-conjugated USPIO probe makes it a viable candidate for use in MHCC MRI in vivo, as they are slowly phagocytosed by macrophages.

CONCLUSION

The bi-specific probe presents enhanced targeting efficiency and MRI sensitivity to HCC cells than singly- or non-targeted USPIO, paving the way for in vivo translation to further evaluate its clinical potential.

[Identification of differentially expressed genes in peripheral blood mononuclear cells of patients with hepatocellular carcinoma and its regulatory network analysis]

OBJECTIVE

To identify the differentially expressed genes (DEGs) in peripheral blood mononuclear cells (PBMC) of patients with hepatocellular carcinoma (HCC) and to analyze their regulatory network.

METHODS

The DEGs in PBMCs of HCC patients were screened based on GEO database. The functional enrichment analysis and interaction analysis were carried out for DEGs. MCODE algorithm was used to screen core genes of DEGs, and the mirDIP and starBase online tools were used to predict upstream miRNAs and lncRNAs of the core genes.

RESULTS

A total of 265 DEGs with a high credibility were identified, which were mainly enriched in the biological activity, such as regulation of cell proliferation, metabolic regulation, cell communication and signaling, and inflammatory diseases according to Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and the two analyses were correlated. Four diagnostic candidate genes were identified, including FUS RNA binding protein, C-X-C motif chemokine ligand 8, cullin 1 and RNA polymerase Ⅱ subunit H. Subsequently, 10 miRNAs, 1 lncRNAs and 38 circRNAs were predicted, and finally a lncRNA/circRNA-miRNA-mRNA-pathway regulatory networks was constructed.

CONCLUSIONS

The diagnostic candidate genes and its regulatory network in HCC PBMC have been identified based on data mining, which could provide potential tumor biomarkers for early diagnosis and treatment of HCC.

Systems Challenges of Hepatic Carcinomas: A Review

Hepatocellular Carcinoma (HCC) is ubiquitous in its prevalence in most of the developing countries. In the era of systems biology, multi-omics has evinced an extensive approach to define the underlying mechanism of disease progression. HCC is a multifactorial disease and the investigation of progression of liver cirrhosis becomes much extensive with cultivating omics approaches. We have performed a comprehensive review about such challenges in multi-omics approaches that are concerned to identify the immunological, genetics and epidemiological factors associated with HCC.

INT-HA induces M2-like macrophage differentiation of human monocytes via TLR4-miR-935 pathway

As a major component of the microenvironment of solid tumors, tumor-associated macrophages (TAMs) facilitate tumor progression. Intermediate-sized hyaluronan (INT-HA) fragments have an immunological function in cell differentiation; however, their role in promoting the polarization of non-activated macrophages to an M2-like TAM phenotype has not been characterized, and the underlying mechanisms remain unclear. Here, we used a miRNA microarray to find that some miRNAs (especially miR-935) were differentially regulated in INT-HA-induced M2-like macrophages. According to RT-qPCR and Western blot, there was an association between miR-935 and C/EBPβ, that control the polarization of macrophages. Moreover, we found that INT-HA induced an M2-like phenotype via the TLR4 receptor. In our study, there was a negative correlation between plasma HA and miR-935 in monocytes from the peripheral blood of patients with solid tumors. There was also a negative correlation between miR-935 and M2-like macrophage markers in monocytes. These findings suggest that HA fragments interact with TLR4 and educate macrophage polarization to an M2-like phenotype via miR-935. Therefore, this study provides new insight into the role of miR-935 in INT-HA-induced M2-like polarization, and suggests a potential therapeutic target for antitumor treatment.

Optimizing the Diagnostic Role of Alpha-Fetoprotein and Abdominal Ultrasound by Adding Overexpressed Blood mRNA Matrix Metalloproteinase-12 for Diagnosis of HCV-Related Hepatocellular Carcinoma

Background and Aims

Matrix metalloproteinase-12 (MMP-12) is involved in tumor invasiveness and metastasis and significantly overexpressed in hepatocellular carcinoma (HCC) tissues. We aimed to investigate the diagnostic and prognostic value of blood mRNA MMP-12 overexpression in patients with HCC.

Patients and Methods

From January 2017 to June 2017, 100 patients with HCC (HCV-related cirrhosis) and 100 patients with HCV-related cirrhosis (without HCC) were included in this study. All patients were subjected to triphasic CT abdomen when indicated, liver profile, alpha-fetoprotein (AFP), and molecular characterization of metalloproteinase-12 expression.

Results

There were no statistically significant differences between both groups regarding CBC parameters and liver profile (p value > 0.05). There was a statistically significant difference between patients with and without HCC regarding blood mRNA MMP-12 overexpression (p value < 0.01), blood mRNA MMP-12, and/or AFP (sensitivity 84.0%, specificity 60.0%, PPV 51.2%, and NPP 88.2%). The accuracy of mRNA MMP-12 and/or AFP in detection of HCC was 68.0%.

Conclusion

Blood mRNA MMP-12 has a good sensitivity and a bad specificity but is accurate in HCC diagnosis. Adding blood mRNA MMP-12 to AFP optimizes the current screening program to improve early diagnosis of HCC and hence better prognosis.

Lnc-PCDH9-13:1 Is a Hypersensitive and Specific Biomarker for Early Hepatocellular Carcinoma

Background

Long non-coding RNAs (lncRNAs) show great potential as diagnostic tools in many diseases. We aimed to develop sensitive and noninvasive biomarkers in saliva for detecting early hepatocellular carcinoma (HCC).

Methods

Candidate lncRNA biomarkers identified by Agilent microarray were subjected to validation using qPCR for the quantification of their expression levels in independent tissue, plasma and saliva sample sets, including healthy controls, HBsAg carriers, patients with chronic Hepatitis B, liver cirrhosis, early HCC, and advanced HCC. Levels of candidate biomarkers were also measured in totally 108 saliva samples from patients with any one of other nine leading causes of cancer death in men and women.

Findings

Lnc-PCDH9-13:1 was significantly elevated in HCC tissues, plasma and saliva of HCC patients compared with healthy controls and groups of several benign liver diseases and other leading cancers. Its level was significantly reduced after curative hepatectomy but significantly elevated again if HCC recurrence occurred. Salivary lnc-PCDH9-13:1 showed reasonable specificities and sensitivities for detecting HCC compared with several control groups. Furthermore, the overexpression of lnc-PCDH9-13:1 promotes cell proliferation and migration in vitro.

Interpretation

Salivary lnc-PCDH9-13:1 is a desirable biomarker for early HCC. It may help warrant prospective validation with larger sample sizes in multi-centers.

•

This study highlight the potential of salivary lncRNAs for detecting early HCC and HCC recurrence, which might provide patients with chances of curative operation and longer survival.

Long non-coding RNAs (lncRNAs) show great potential as diagnostic tools in many diseases. Lnc-PCDH9-13:1 was significantly elevated in cancer tissues, plasma and saliva of patients with liver cancer compared with healthy controls and groups of several benign liver diseases and other leading cancers. Its level was significantly reduced after the curative operation but significantly elevated again if liver cancer recurrence occurred. Salivary lnc-PCDH9-13:1 showed reasonable specificities and sensitivities for detecting liver cancer. Conclusively, salivary lnc-PCDH9-13:1 is indicative of the early diagnosis and recurrence of liver after the operation with reasonable sensitivities and specificities.

Prognostic value of plasma fibrinogen in hepatocellular carcinoma: a meta-analysis

Background

Elevated plasma fibrinogen levels have been associated with tumor progression in several malignancies. Our study aims to characterize the clinical significance of elevated plasma fibrinogen levels in patients with hepatocellular carcinoma (HCC).

Materials and methods

Relevant published articles were systematically searched in electronic databases including PubMed, Embase, and Web of Science. The pooled differences in plasma fibrinogen levels among HCC, cirrhotic, and control groups were expressed as weighted mean differences (WMDs) and their corresponding 95% CIs. The associations between elevated fibrinogen and overall survival (OS) and disease-free survival (DFS)/recurrence-free survival (RFS) were expressed as HRs and their 95% CIs, whereas the associations between elevated fibrinogen and various types of clinical characteristic of patients with HCC were expressed as ORs and their corresponding 95% CIs.

Results

Results showed that the plasma fibrinogen levels in patients with HCC were not significantly different than that in healthy controls (WMD = 0.50, 95% CI = [−0.82, 1.82], P = 0.457) or patients with cirrhosis (WMD = −0.62, 95% CI = [−1.56, 0.33], P = 0.200). However, our results showed that compared to those with normal levels, patients with HCC and elevated plasma fibrinogen levels showed poorer OS (HR = 2.08, 95% CI = [1.67, 2.59], P < 0.0001) and DFS/RFS (HR = 1.90, 95% CI = [1.52, 2.37], P < 0.0001). Results of trial sequential analysis of the OS indicated that currently available studies were sufficient to validate the negative prognostic value of elevated plasma fibrinogen in patients with HCC. Clinicopathological analyses showed that high plasma fibrinogen levels were associated with tumor progression as indicated by advanced tumor stage, larger tumor size, increased tumor number, and the presence of vascular invasion.

Conclusion

Elevated plasma fibrinogen levels are associated with poor prognosis and advanced tumor progression. Plasma fibrinogen may serve as a negative prognostic biomarker in patients with HCC.

Potential Effect of Exosomes Derived from Cancer Stem Cells and MSCs on Progression of DEN-Induced HCC in Rats

Cross talk, mediated by exosomes, between normal stem cells and cancer stem cells (CSCs) in the tumor microenvironment has been given less attention so far. In addition, no publications are available in the literature that address the in vivo impact of exosomes derived from CSCs and mesenchymal stem cells (MSCs) on progression of long-term hepatocellular carcinoma (HCC). Herein, we hypothesized that transfer of exosomes among the cells in the HCC microenvironment could either induce or inhibit tumor growth and metastasis depending on their source. To check this hypothesis, we investigated the effect of exosomes coming from two different stem cell populations, hepatic CSCs and bone marrow (BM) MSCs, on progression of long-term DEN-induced HCC in rats and the involved underlying mechanisms. CSCs-exosomes induced a significant increase in liver relative weight and serum levels of cancer markers (AFP and GGT) and liver enzymes (ALT, AST, and ALP), intensive immunostaining for the HCC marker GST-P, and an increased number and area of tumor nodules as compared to HCC rats injected by PBS. CSCs-exosomes also decreased apoptosis (marked by downregulation of Bax and p53 and upregulation of Bcl2, and increased immunostaining of PCNA), increased angiogenetic activity (revealed by upregulation of VEGF), enhanced metastasis and invasiveness (indicated by upregulation of P13K and ERK proteins and their downstream target MMP9 and downregulation of TIMP1), and induced epithelial mesenchymal transition (marked by increased serum and hepatic level of TGFβ1 mRNA and protein). Notably, CSCs-exosomes also elevated HCC exosomal microRNA (miR) 21, exosomal long noncoding (lnc) RNA Tuc339, lncHEIH, and the HCC lncHOTAIR and decreased liver miR122 and HCC miRs (miR148a, miR16, and miR125b). All these cellular, functional, and molecular changes were reversed following injection of BM-MSCs-exosomes. However, both CSCs- and MSCs-exosomes failed to change the elevated oxidative stress or the inhibited antioxidant activities induced by HCC. Collectively, our results revealed a tumor stimulatory effect (induction of tumor growth, progression, and metastasis) for exosomes derived from CSCs and an inhibitory effect for exosomes derived from MSCs. These results provide valuable insight on the effect of CSCs- and MSCs-exosomes on HCC growth and progression in vivo, which may be helpful to understand the mechanism of HCC development.

Therapeutic Effect of Camel Milk and Its Exosomes on MCF7 Cells In Vitro and In Vivo

Background/Objectives: In the Middle East, people consume camel milk regularly as it is believed to improve immunity against diseases and decrease the risk for cancer. Recently, it was noted that most of the beneficial effects of milk come from their nanoparticles, especially exosomes. Herein, we evaluated the anticancer potential of camel milk and its exosomes on MCF7 breast cancer cells (in vitro and in vivo) and investigated the possible underlying molecular mechanism of action. Methods/Results: Administration of camel milk (orally) and its exosomes (orally and by local injection) decreased breast tumor progression as evident by (a) higher apoptosis (indicated by higher DNA fragmentation, caspase-3 activity, Bax gene expression, and lower Bcl2 gene expression), (b) remarkable inhibition of oxidative stress (decrease in MDA levels and iNOS gene expression); (c) induction of antioxidant status (increased activities of SOD, CAT, and GPX), (d) notable reduction in expression of inflammation-(IL1b, NFκB), angiogenesis-(VEGF) and metastasis-(MMP9, ICAM1) related genes; and (e) higher immune response (high number of CD⁺4, CD⁺8, NK1.1 T cells in spleen). Conclusions: Overall, administration of camel milk–derived exosomes showed better anticancer effect, but less immune response, than treatment by camel milk. Moreover, local injection of exosomes led to better improvement than oral administration. These findings suggest that camel milk and its exosomes have anticancer effect possibly through induction of apoptosis and inhibition of oxidative stress, inflammation, angiogenesis and metastasis in the tumor microenvironment. Thus, camel milk and its exosomes could be used as an anticancer agent for cancer treatment.

Supervised learning reveals circulating biomarker levels diagnostic of hepatocellular carcinoma in a clinically relevant model of non-alcoholic steatohepatitis; An OAD to NASH

Although cirrhosis is a key risk factor for the development of hepatocellular carcinoma (HCC), mounting evidence indicates that in a subset of patients presenting with non-alcoholic steatohepatitis (NASH) HCC manifests in the absence of cirrhosis. Given the sheer size of the ongoing non-alcoholic fatty liver disease (NAFLD) epidemic and the dismal prognosis associated with late-stage primary liver cancer there is an urgent need for HCC surveillance in the NASH population. Using serum levels of HCC biomarkers as vectors and biopsy-proven HCC or no HCC as outputs / binary classifier, a supervised learning campaign was undertaken to develop a minimally invasive technique for making a diagnosis of HCC in a clinically relevant model of NASH. Adult mice randomized to control diet or a fast food diet (FFD) were followed for up to 14 mo and serum level of a panel of HCC-relevant biomarkers was compared with liver biopsies at 3 and 14 mo. Both NAFLD Activity Score (NAS) and hepatic hydroxyproline content were elevated at 3 and 14 mo on FFD. Picrosirius red staining of liver sections revealed a filigree pattern of fibrillar collagen deposition with no cirrhosis at 14 mo on FFD. Nevertheless, 46% of animals bore one or more tumors on their livers confirmed as HCC in hematoxylin-eosin-stained liver sections. In this training set, receiver operating characteristic (ROC) curves analysis for serum levels of the HCC biomarkers osteopontin (OPN), alpha-fetoprotein (AFP) and Dickkopf-1 (DKK1) returned concordance-statistic/area under ROC curve of ≥ 0.89. Serum levels of OPN (threshold, 218 ng/mL; sensitivity, 82%; specificity, 86%), AFP (136 ng/mL; 91%; 97%) and DKK1 (2.4 ng/mL; 82%; 81%) diagnostic for HCC were confirmed in a test set comprising mice on control diet or FFD and mice subjected to hepatic ischemia-reperfusion injury. These data suggest that levels of circulating OPN, AFP and DKK1 can be used to make a diagnosis of HCC in a clinically relevant model of NASH.

Differentially expressed genes of HepG2 cells treated with gecko polypeptide mixture

Gecko (Gekko japonicus) extracts have been used in traditional Chinese medicine for many years. It has been proven that the gecko polypeptide mixture (GPM) extracted from gecko can inhibit the growth of multiple types of tumor cells. In order to investigate the possible anti-tumor molecular mechanisms of GPM, we used RNA-seq technology to identify the differentially expressed genes (DEGs) of human hepatocellular carcinoma (HCC) HepG2 cells treated with or without GPM. MTT assay was used to detect the viability of HepG2 cells. DAPI fluorescence staining was performed to observe morphological changes in the nuclei of HepG2 cells. Western blot analysis was applied to observe the expressions of apoptosis-related and endoplasmic reticulum stress (ERS)-related proteins in HepG2 cells. Flow cytometry assay was performed to detect the apoptosis and reactive oxygen species (ROS) in HepG2 cells. Our results showed that GPM inhibited HepG2 cells proliferation and induced the apoptosis of HepG2 cells. RNA-seq analysis suggested that the ER-nucleus signaling pathway involved in the anti-cancer molecular mechanism of GPM. Therefore, GPM may induce apoptosis in HepG2 cells via the ERs pathway.

Microarray analysis of long non-coding RNA expression profiles in monocytic myeloid-derived suppressor cells in Echinococcus granulosus-infected mice

Background

Cystic echinococcosis is a worldwide chronic zoonotic disease caused by infection with the larval stage of Echinococcus granulosus. Previously, we found significant accumulation of myeloid-derived suppressor cells (MDSCs) in E. granulosus infection mouse models and that they play a key role in immunosuppressing T lymphocytes. Here, we compared the long non-coding RNA (lncRNA) and mRNA expression patterns between the splenic monocytic MDSCs (M-MDSCs) of E. granulosus protoscoleces-infected mice and normal mice using microarray analysis.

Methods

LncRNA functions were predicted using Gene Ontology enrichment and the Kyoto Encyclopedia of Genes and Genomes pathway analysis. Cis- and trans-regulation analyses revealed potential relationships between the lncRNAs and their target genes or related transcription factors.

Results

We found that 649 lncRNAs were differentially expressed (fold change ≥ 2, P < 0.05): 582 lncRNAs were upregulated and 67 lncRNAs were downregulated; respectively, 28 upregulated mRNAs and 1043 downregulated mRNAs were differentially expressed. The microarray data was validated by quantitative reverse transcription-PCR. The results indicated that mRNAs co-expressed with the lncRNAs are mainly involved in regulating the actin cytoskeleton, Salmonella infection, leishmaniasis, and the vascular endothelial growth factor (VEGF) signaling pathway. The lncRNA NONMMUT021591 was predicted to cis-regulate the retinoblastoma gene (Rb1), whose expression is associated with abnormal M-MDSCs differentiation. We found that 372 lncRNAs were predicted to interact with 60 transcription factors; among these, C/EBPβ (CCAAT/enhancer binding protein beta) was previously demonstrated to be a transcription factor of MDSCs.

Conclusions

Our study identified dysregulated lncRNAs in the M-MDSCs of E. granulosus infection mouse models; they might be involved in M-MDSC-derived immunosuppression in related diseases.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-2905-6) contains supplementary material, which is available to authorized users.

Serum long noncoding RNA LRB1 as a potential biomarker for predicting the diagnosis and prognosis of human hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a type of malignant tumor with a high mortality rate. Long non-coding RNAs (lncRNAs) serve important roles in cellular processes and gene regulation. Identifying novel prognostic biomarkers is important for the monitoring and treatment of HCC. However, only a limited number of biomarkers with high sensitivity and specificity have been determined and are used in clinical practice. The aim of the present study was to investigate the use of serum lncRNA uc007biz.1 (LRB1) expression levels as a novel non-invasive biomarker for the monitoring and diagnosis of HCC. The expression levels of LRB1 were detected in 326 patients with HCC and 73 healthy volunteers by using lncRNA expression microarrays and reverse transcription quantitative polymerase chain reaction analysis, and the associations between LRB1 expression and clinical parameters were analyzed. The results indicated that the serum LRB1 levels in patients with HCC were significantly increased compared with healthy volunteers. The serum LRB1 levels were positively associated with α-fetoprotein (AFP) expression, large tumor sizes, tumor stage (tumor-node metastasis or Barcelona Clinic Liver Cancer stage) and venous invasion, and were negatively associated with overall survival. Additionally, the use of a combination of LRB1, AFP and des-γ-carboxy prothrombin (DCP) markers for the diagnosis of HCC, the diagnostic accuracy was increased compared with using LRB1 alone. LRB1 may act as an important regulator in the progression of HCC, and LRB1 may be considered as a novel biomarker for diagnosis and prediction of prognosis of HCC, additionally complementing the accuracy of AFP and DCP.

von Willebrand factor is a useful biomarker for liver fibrosis and prediction of hepatocellular carcinoma development in patients with hepatitis B and C

Background

Several noninvasive biomarkers are available for diagnosing liver fibrosis stage and predicting hepatocellular carcinoma (HCC) development in patients with chronic hepatitis and liver cirrhosis. However, these biomarkers are not sufficiently accurate. Recently, von Willebrand factor (VWF) has been related to angiogenesis and apoptosis. Furthermore, VWF is associated with hepatic spare ability and HCC.

Objective

We aimed to determine whether VWF is a potential biomarker for liver fibrosis and HCC development.

Methods

Two hundred and twelve patients with chronic hepatitis B and C were recruited. VWF antigen (VWF: Ag) levels in each patient were determined via enzyme-linked immunosorbent assay. Univariable and multivariable analyses were used to determine the risk factor of HCC.

Results

The VWF: Ag levels were higher in patients with severe liver fibrosis stage and/or HCC development than in those without. The area under the curve of VWF: Ag for diagnosis of severe liver fibrosis stage was 0.721. Multivariable analysis showed that only VWF: Ag was a predictive biomarker for HCC development.

Conclusions

VWF: Ag is related to liver fibrosis and may be useful for predicting HCC development. VWF is a potentially useful biomarker to diagnose severe liver fibrosis and predict HCC development.

Microenvironment and tumor cells: two targets for new molecular therapies of hepatocellular carcinoma

Hepatocellular carcinoma (HCC), is one of the most frequent human cancer and is characterized by a high mortality rate. The aggressiveness appears strictly related to the liver pathological background on which cancer develops. Inflammation and the consequent fibro/cirrhosis, derived from chronic injuries of several origins (viral, toxic and metabolic) and observable in almost all oncological patients, represents the most powerful risk factor for HCC and, at the same time, an important obstacle to the efficacy of systemic therapy. Multiple microenvironmental cues, indeed, play a pivotal role in the pathogenesis, evolution and recurrence of HCC as well as in the resistance to standard therapies observed in most of patients. The identification of altered pathways in cancer cells and of microenvironmental changes, strictly connected in pathogenic feedback loop, may permit to plan new therapeutic approaches targeting tumor cells and their permissive microenvironment, simultaneously.

Sustained activation of detoxification pathways promotes liver carcinogenesis in response to chronic bile acid-mediated damage

Chronic inflammation promotes oncogenic transformation and tumor progression. Many inflammatory agents also generate a toxic microenvironment, implying that adaptive mechanisms must be deployed for cells to survive and undergo transformation in such unfavorable contexts. A paradigmatic case is represented by cancers occurring in pediatric patients with genetic defects of hepatocyte phosphatidylcholine transporters and in the corresponding mouse model (Mdr2-/- mice), in which impaired bile salt emulsification leads to chronic hepatocyte damage and inflammation, eventually resulting in oncogenic transformation. By combining genomics and metabolomics, we found that the transition from inflammation to cancer in Mdr2-/- mice was linked to the sustained transcriptional activation of metabolic detoxification systems and transporters by the Constitutive Androstane Receptor (CAR), a hepatocyte-specific nuclear receptor. Activation of CAR-dependent gene expression programs coincided with reduced content of toxic bile acids in cancer nodules relative to inflamed livers. Treatment of Mdr2-/- mice with a CAR inhibitor blocked cancer progression and caused a partial regression of existing tumors. These results indicate that the acquisition of resistance to endo- or xeno-biotic toxicity is critical for cancers that develop in toxic microenvironments.

In silico identification of microRNAs predicted to regulate N-myristoyltransferase and Methionine Aminopeptidase 2 functions in cancer and infectious diseases

Protein myristoylation is a key protein modification carried out by N-Myristoyltransferase (NMT) after Methionine aminopeptidase 2 (MetAP2) removes methionine from the amino-terminus of the target protein. Protein myristoylation by NMT augments several signaling pathways involved in a myriad of cellular processes, including developmental pathways and pathways that when dysregulated lead to cancer or immune dysfunction. The emerging evidence pointing to NMT-mediated myristoylation as a major cellular regulator underscores the importance of understanding the framework of this type of signaling event. Various studies have investigated the role that myristoylation plays in signaling dysfunction by examining differential gene or protein expression between normal and diseased states, such as cancers or following HIV-1 infection, however no study exists that addresses the role of microRNAs (miRNAs) in the regulation of myristoylation. By performing a large scale bioinformatics and functional analysis of the miRNAs that target key genes involved in myristoylation (NMT1, NMT2, MetAP2), we have narrowed down a list of promising candidates for further analysis. Our condensed panel of miRNAs identifies 35 miRNAs linked to cancer, 21 miRNAs linked to developmental and immune signaling pathways, and 14 miRNAs linked to infectious disease (primarily HIV). The miRNAs panel that was analyzed revealed several NMT-targeting mRNAs (messenger RNA) that are implicated in diseases associated with NMT signaling alteration, providing a link between the realms of miRNA and myristoylation signaling. These findings verify miRNA as an additional facet of myristoylation signaling that must be considered to gain a full perspective. This study provides the groundwork for future studies concerning NMT-transcript-binding miRNAs, and will potentially lead to the development of new diagnostic/prognostic biomarkers and therapeutic targets for several important diseases.

Evaluation of circulating placenta-related long noncoding RNAs as potential biomarkers for preeclampsia

Increasing evidence has indicated that circulating placental RNAs may reflect the pathophysiology of the placenta. In the current study, circulating placenta-related long noncoding RNAs (lncRNAs) were evaluated as potential biomarkers for preeclampsia (PE). Two parts of the case-control study were simultaneously executed, including the following sets: 52 patients with late-onset PE (LOPE) (diagnosed after 34 weeks) and 52 gestational age (GA)-matched controls; 58 patients with early-onset PE (EOPE) (diagnosed before 34 weeks) and 58 GA-matched controls. LncRNA expression was detected in the placenta analysis part, and the participants were delivered by caesarean sections. The levels of circulating placenta-associated lncRNAs were measured in the plasma analysis part and all pregnant women were included. Using microarray analysis, 163 differentially expressed lncRNAs were identified in placental samples from patients with LOPE, some of which were also detected in plasma samples from pregnant women. There were significant positive correlations between plasma, and placental expression levels of NONHSAT116812 and NONHSAT145880, which in plasma provided high diagnostic efficiencies for LOPE and EOPE. The present study demonstrated that circulating placenta-associated lncRNAs, paticularly NONHSAT116812 and NONHSAT145880 have potential as biomarkers for PE.

Mutations in hepatitis B virus polymerase are associated with the postoperative survival of hepatocellular carcinoma patients

Proofreading deficiencies of hepatitis B virus polymerase result in frequent DNA mutations in the hepatitis B virus genome. Here, we performed sequencing analysis of the hepatitis B virus polymerase gene to assess its association with the postoperative survival in 92 patients with HBV-related hepatocellular carcinoma by using the Kaplan–Meier method. The 2525, 2733, 2738, 2768, 2946, 3063, 3066, 3109, 31, 529, 735, 939, 1078, 1137, 1383, 1461, 1485, 1544, and 1613 mutation sites were identified as being associated with HCC outcomes by the log-rank test. After adjusting for clinical characteristics by using the Cox hazard model, site 31 (relative risk, 8.929; 95% confidence interval, 3.433–23.22; P = 0.000) in the spacer domain and sites 529 (relative risk, 5.656; 95% confidence interval, 1.599–19.999; P = 0.007) and 1078 (relative risk, 3.442; 95% confidence interval, 1.070–11.068; P = 0.038) in the reverse transcriptase domain of hepatitis B virus polymerase were identified as independent predictors of postoperative survival in hepatitis B virus related hepatocellular carcinoma. The mutations at the 31 (Ser314Pro), 529 (Asp480Asn), and 1078 (Ser663Ala) sites all resulted in amino acid changes in hepatitis B virus polymerase and were associated with shortened life-span. The 31 and 529 sites were located in the overlapping region for the PreS and S genes but did not induce amino acid substitution in these two regions. Our finding of the correlation between hepatitis B virus DNA polymerase mutations and hepatocellular carcinoma survival will help identify the patients subgroup with poor prognosis, and help the clinicians to refine the therapeutic decision individualized.