Hepatocellular carcinoma associated microRNA expression signature: integrated bioinformatics analysis, experimental validation and clinical significance

Promising Novel Biomarkers for Hepatocellular Carcinoma: Diagnostic and Prognostic Insights

The systemic therapy landscape for hepatocellular carcinoma is rapidly evolving, as the recent approvals of checkpoint inhibitor-based regimens such as atezolizumab-bevacizumab and durvalumab-tremelimumab in advanced disease have led to an expanding therapeutic armamentarium. The development of biomarkers, however, has not kept up with the approvals of new agents. Nevertheless, biomarker research for hepatocellular carcinoma has recently been growing at a rapid pace. The most active areas of research are biomarkers for early detection and screening, accurate prognostication, and detection of minimal residual disease following curative intent therapies, and, perhaps most importantly, predictive markers to guide selection and sequencing of the individual agents, including tyrosine kinase inhibitors and immunotherapy. In this review, we briefly summarize the recent developments in systemic therapeutics for hepatocellular carcinoma, introduce the key completed and ongoing prospective and retrospective studies evaluating diagnostic, prognostic, and predictive biomarkers with high clinical relevance, highlight several potentially important areas of future research, and share our insights for each biomarker.

TRAIL and EGFR Pathways Targeting microRNAs are Predominantly Regulated in Human Diabetic Nephropathy

BACKGROUND

Unbiased microRNA profiling of renal tissue and urinary extracellular vesicles (uEVs) from diabetic nephropathy (DN) subjects may unravel novel targets with diagnostic and therapeutic potential. Here we used the miRNA profile of uEVs and renal biopsies from DN subjects available on the GEO database.

METHODS

The miR expression profiles of kidney tissue (GSE51674) and urinary exosomes (GSE48318) from DN and control subjects were obtained by GEO2R tools from Gene Expression Omnibus (GEO) databases. Differentially expressed miRNAs in DN samples, relative to controls, were identified using a bioinformatic pipeline. Targets of miRs commonly regulated in both sample types were predicted by miRWalk, followed by functional gene enrichment analysis. Gene targets were identified by MiRTarBase, TargetScan and MiRDB.

RESULTS

Eight miRs, including let-7c, miR-10a, miR-10b and miR-181c, were significantly regulated in kidney tissue and uEVs in DN subjects versus controls. The top 10 significant pathways targeted by these miRs included TRAIL, EGFR, Proteoglycan syndecan, VEGF and Integrin Pathway. Gene target analysis by miRwalk upon validation using ShinyGO 70 targets with significant miRNA-mRNA interaction.

CONCLUSION

In silico analysis showed that miRs targeting TRAIL and EGFR signaling are predominately regulated in uEVs and renal tissue of DN subjects. After wet-lab validation, the identified miRstarget pairs may be explored for their diagnostic and/or therapeutic potential in diabetic nephropathy.

Non-Coding RNAs in Hepatocellular Carcinoma

Liver cancer ranks as the fourth leading cause of cancer-related deaths. Despite extensive research efforts aiming to evaluate the biological mechanisms underlying hepatocellular carcinoma (HCC) development, little has been translated towards new diagnostic and treatment options for HCC patients. Historically, the focus has been centered on coding RNAs and their respective proteins. However, significant advances in sequencing and RNA detection technologies have shifted the research focus towards non-coding RNAs (ncRNA), as well as their impact on HCC development and progression. A number of studies reported complex post-transcriptional interactions between various ncRNA and coding RNA molecules. These interactions offer insights into the role of ncRNAs in both the known pathways leading to oncogenesis, such as dysregulation of p53, and lesser-known mechanisms, such as small nucleolar RNA methylation. Studies investigating these mechanisms have identified prevalent ncRNA changes in microRNAs, snoRNAs, and long non-coding RNAs that can both pre- and post-translationally regulate key factors in HCC progression. In this review, we present relevant publications describing ncRNAs to summarize the impact of different ncRNA species on liver cancer development and progression and to evaluate recent attempts at clinical translation.

A Cross-Comparison of High-Throughput Platforms for Circulating MicroRNA Quantification, Agreement in Risk Classification, and Biomarker Discovery in Non-Small Cell Lung Cancer

Background

Circulating microRNAs (ct-miRs) are promising cancer biomarkers. This study focuses on platform comparison to assess performance variability, agreement in the assignment of a miR signature classifier (MSC), and concordance for the identification of cancer-associated miRs in plasma samples from non‐small cell lung cancer (NSCLC) patients.

Methods

A plasma cohort of 10 NSCLC patients and 10 healthy donors matched for clinical features and MSC risk level was profiled for miR expression using two sequencing-based and three quantitative reverse transcription PCR (qPCR)-based platforms. Intra- and inter-platform variations were examined by correlation and concordance analysis. The MSC risk levels were compared with those estimated using a reference method. Differentially expressed ct-miRs were identified among NSCLC patients and donors, and the diagnostic value of those dysregulated in patients was assessed by receiver operating characteristic curve analysis. The downregulation of miR-150-5p was verified by qPCR. The Cancer Genome Atlas (TCGA) lung carcinoma dataset was used for validation at the tissue level.

Results

The intra-platform reproducibility was consistent, whereas the highest values of inter-platform correlations were among qPCR-based platforms. MSC classification concordance was >80% for four platforms. The dysregulation and discriminatory power of miR-150-5p and miR-210-3p were documented. Both were significantly dysregulated also on TCGA tissue-originated profiles from lung cell carcinoma in comparison with normal samples.

Conclusion

Overall, our studies provide a large performance analysis between five different platforms for miR quantification, indicate the solidity of MSC classifier, and identify two noninvasive biomarkers for NSCLC.

Exploring the underlying molecular mechanism of liver cancer cells under hypoxia based on RNA sequencing

Background

The aim of our study was to use the differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNAs (DEmiRNAs) to illustrate the underlying mechanism of hypoxia in liver cancer.

Methods

In this study, a cell model of hypoxia was established, and autophagy activity was measured with western blotting and transmission electron microscopy. The effect of hypoxia conditions on the invasion of liver cancer cell was evaluated. RNA sequencing was used to identify DEmRNAs and DEmiRNAs to explore the mechanism of hypoxia in liver cancer cells.

Results

We found that autophagy activation was triggered by hypoxia stress and hypoxia might promote liver cancer cell invasion. In addition, a total of 407 shared DEmRNAs and 57 shared DEmiRNAs were identified in both HCCLM3 hypoxia group and SMMC-7721 hypoxia group compared with control group. Furthermore, 278 DEmRNAs and 24 DEmiRNAs were identified as cancer hypoxia-specific DEmRNAs and DEmiRNAs. Finally, we obtained 19 DEmiRNAs with high degree based on the DEmiRNA-DEmRNA interaction network. Among them, hsa-miR-483-5p, hsa-miR-4739, hsa-miR-214-3p and hsa-miR-296-5p may be potential gene signatures related to liver cancer hypoxia.

Conclusions

Our study may help to understand the potential molecular mechanism of hypoxia in liver cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01055-9.

Genetic and Epigenetic Mechanisms Deregulate the CRL2pVHL Complex in Hepatocellular Carcinoma

Dysregulation of ubiquitin-proteasome pathway genes through copy number alteration, promoter hypomethylation, and miRNA deregulation is involved in cancer development and progression. Further characterizing alterations in these genes may uncover novel drug targets across a range of diseases in which druggable alterations are uncommon, including hepatocellular carcinoma (HCC). We analyzed 377 HCC and 59 adjacent non-malignant liver tissue samples, focusing on alterations to component genes of the widely studied CRL2^pVHL E3 ubiquitin ligase complex. mRNA upregulation of the component genes was common, and was correlated with DNA hypomethylation and copy number increase, but many tumours displayed overexpression that was not explained by either mechanism. Interestingly, we found 66 miRNAs, including 39 previously unannotated miRNAs, that were downregulated in HCC and predicted to target one or more CRL2^pVHL components. Several miRNAs, including hsa-miR-101-3p and hsa-miR-139-5p, were negatively correlated with multiple component genes, suggesting that miRNA deregulation may contribute to CRL2^pVHL overexpression. Combining miRNA and mRNA expression, DNA copy number, and methylation status into one multidimensional survival analysis, we found a significant association between greater numbers of alterations and poorer overall survival for multiple component genes. While the intricacies of CRL2^pVHL complex gene regulation require additional research, it is evident that multiple causes for the deregulation of these genes must be considered in HCC, including non-traditional mechanisms.

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.

Identifying the biomarkers and pathways associated with hepatocellular carcinoma based on an integrated analysis approach

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related death worldwide. The molecular mechanism underlying HCC is still unclear. In this study, we conducted a comprehensive analysis to explore the genes, pathways and their interactions involved in HCC.

METHODS

We analysed the gene expression datasets corresponding to 488 samples from 10 studies on HCC and identified the genes differentially expressed in HCC samples. Then, the genes were compared against Phenolyzer and GeneCards to screen those potentially associated with HCC. The features of the selected genes were explored by mapping them onto the human protein-protein interaction network, and a subnetwork related to HCC was constructed. Hub genes in this HCC specific subnetwork were identified, and their relevance with HCC was investigated by survival analysis.

RESULTS

We identified 444 differentially expressed genes (177 upregulated and 267 downregulated) related to HCC. Functional enrichment analysis revealed that pathways like p53 signalling and chemical carcinogenesis were eriched in HCC genes. In the subnetwork related to HCC, five disease modules were detected. Further analysis identified six hub genes from the HCC specific subnetwork. Survival analysis showed that the expression levels of these genes were negatively correlated with survival rate of HCC patients.

CONCLUSIONS

Based on a systems biology framework, we identified the genes, pathways, as well as the disease specific network related to HCC. We also found novel biomarkers whose expression patterns were correlated with progression of HCC, and they could be candidates for further investigation.

Non-Coding RNA-Based Biosensors for Early Detection of Liver Cancer

Primary liver cancer is an aggressive, lethal malignancy that ranks as the fourth leading cause of cancer-related death worldwide. Its 5-year mortality rate is estimated to be more than 95%. This significant low survival rate is due to poor diagnosis, which can be referred to as the lack of sufficient and early-stage detection methods. Many liver cancer-associated non-coding RNAs (ncRNAs) have been extensively examined to serve as promising biomarkers for precise diagnostics, prognostics, and the evaluation of the therapeutic progress. For the simple, rapid, and selective ncRNA detection, various nanomaterial-enhanced biosensors have been developed based on electrochemical, optical, and electromechanical detection methods. This review presents ncRNAs as the potential biomarkers for the early-stage diagnosis of liver cancer. Moreover, a comprehensive overview of recent developments in nanobiosensors for liver cancer-related ncRNA detection is provided.

Construction of Novel lncRNA-miRNA-mRNA Network Associated With Recurrence and Identification of Immune-Related Potential Regulatory Axis in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant diseases globally. Despite continuous improvement of treatment methods, high postoperative recurrence rate remains an urgent problem. In order to determine the mechanism underlying recurrence of liver cancer and identify prognostic genes, data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were integrated and analyzed. Differentially expressed genes (DEGs) between HCC tissue and normal liver tissue were identified, and a protein–protein interaction network was constructed to find hub genes. Clinical correlation analysis and disease-free survival (DFS) analysis were performed using the R language and GEPIA to identify relapse-related genes. Correlation analysis was used to identify a potential regulatory axis. Dual-luciferase reporter gene assay was used to confirm the reliability of the long non-coding RNA (lncRNA)–microRNA (miRNA)–mRNA regulatory axis. Immune infiltration analysis was performed using the TIMER database. Correlations between immune gene markers and ASF1B were verified using quantitative real-time polymerase chain reaction (RT-qPCR). In this work, we found that nine lncRNAs and five mRNAs were significantly overexpressed in HCC tissues from patients with recurrence. SNHG3, LINC00205, ASF1B, AURKB, CCNB1, CDKN3, and DTL were also closely related to HCC grade and stage. Survival analysis showed that these seven DEGs were significantly correlated with poor DFS. Correlation analysis identified SNHG3–miR-214-3p–ASF1B as a potential regulatory axis. Dual-luciferase reporter gene assay showed that SNHG3 and ASF1B directly bound to miR-214-3p. ASF1B was negatively regulated by miRNA-214-3p, and overexpression of SNHG3 could inhibit the expression of miRNA-214-3p. In addition, ASF1B was positively correlated with immune infiltration. A reduction in ASF1B could markedly inhibit the expression of CD86, CD8, STAT1, STAT4, CD68, and PD1 in HCC cells. Flow cytometry showed that SNHG3 promoted the PD-1 expression by regulating ASF1B. Meanwhile, elevated ASF1B predicted poor prognosis of HCC patients in subgroups with decreased B cells, CD8+ T cells, or neutrophils, and those with enriched CD4+ T cells. In conclusion, we found that a novel lncRNA SNHG3/miR-214-3p/ASF1B axis could promote the recurrence of HCC by regulating immune infiltration.

Prognostic gene biomarker identification in liver cancer by data mining

BACKGROUND

Liver cancer is a common cancer that enormously threatens the health of people worldwide. With the continuous advances of high-throughput gene sequencing technology and computer data mining technology, researchers can understand liver cancer based on the current accumulation of gene expression data and clinical information.

METHODS

We downloaded the TCGA data of liver cancer on the cancer-related website (https://genome-cancer.ucsc.edu/proj/site/hgHeatmap/), comprising 438 patients and 20,530 genes. After removing some patients with missing survival data, we collected 397 patients' samples. Our data were collected from a public database without real patient participation. While matching the patient samples in the gene expression spectrum, we attained 330 samples with primary tumors and 50 samples with normal solid tissue.

RESULTS

After the 330 tumor tissue samples were randomized into two equal-numbered groups (one is a training set, and the other is a test set), we selected 26 gene biomarkers from the training set and validated them in the test set. Based on the selected 26 gene biomarkers, RBM14, ALG11, MAG, SETD3, HOXD10 and other 26 genes were considered independent risk factors for the prognosis of liver cancer, and genes such as GHR significantly affect human growth hormone for liver cancer. The findings discovered that low-risk patients survived remarkably better than the high-risk patients (P<0.001), and the area under the curve (AUC) of receiver operating characteristic curve (ROC) was greater than 0.5.

CONCLUSION

Our numerical results showed that these 26 gene biomarkers can be used to guide the effective prognostic therapy of patients with liver cancer.

Atractylenolide III predisposes miR-195-5p/FGFR1 signaling axis to exert tumor-suppressive functions in liver cancer

BACKGROUND

Antineoplastic activity of atractylenolide III (ATL) has been reported in several malignant tumors. However, its activity has not been completely clarified in hepatocellular carcinoma (HCC). Herein, anticancer effects and underlying molecular mechanisms of ATL were investigated in HCC cells in vitro.

METHODS

Cell viability was evaluated by CCK-8 assay. Cell migration and invasion were evaluated using the transwell assay. TUNEL staining was performed to evaluate cell apoptosis. Protein expression was measured by western blotting analysis. Online database TargetScan and luciferase reporter gene analysis were performed to validate FGFR1 as a target of miR-195-5p.

RESULTS

HepG2 and SMMC7721 cell growth, migration, and invasion were inhibited by ATL treatment in a dose-dependent pattern. ATL treatment-induced apoptosis of HepG2 and SMMC7721 cells. Intriguingly, ATL treatment unexpectedly inhibited FGFR1 protein expression in HepG2 and SMMC7721 cells. Knockdown of FGFR1 inhibited proliferation, migration, and invasion, and evoked apoptosis of HepG2 and SMMC7721 cells. We also found that ATL treatment could increase the expression of miR-195-5p, which as a posttranscriptional targeted FGFR1. In HCC tissues, miR-195-5p expression is negatively correlated with FGFR1. Furthermore, the antiproliferative and proapoptotic roles of miR-195-5p were neutralized by overexpressed FGFR1 in HCC cells.

CONCLUSION

ATL effectively repressed growth and induced apoptosis of human HCC cells through the upregulation of miR-195-5p to downregulate FGFR1 expression.

PRACTICAL APPLICATIONS

Atractylenolide III as a bioactive anticancer adjuvant medication will provide chemosensitization strategy for reversing the drug resistance of HCC.

miRNA-mRNA Regulatory Network and Factors Associated with Prediction of Prognosis in Hepatocellular Carcinoma

The aim of this study was to identify novel gene and miRNA biomarkers of risk and prognostic factors for hepatocarcinogenesis using methods in systems biology. Differentially expressed genes (DEGs), microRNAs (miRNAs), and long non-coding RNA (lncRNAs) were compared between hepatocellular carcinoma (HCC) tumour tissue and normal liver tissues in the Cancer Genome Atlas (TCGA) database. Subsequently, the prognosis-associated gene co-expression network, mRNA-miRNA, and mRNA-miRNA-lncRNA regulatory networks were constructed to identify biomarkers of risk for HCC through Cox survival analysis. Seven prognosis-associated gene co-expression modules were obtained by analyzing these DEGs. An expression module including 120 genes significantly correlated with HCC patient survival. Combined with patient survival data, several mRNAs and miRNAs, including CHST4, SLC22A8, STC2, hsa-miR-326, and hsa-miR-21 were identified from the network to predict HCC patient prognosis. Clinical significance was investigated using tissue microarray analysis of samples from 258 patients with HCC. Functional annotation of hsa-miR-326 and hsa-miR-21-5p indicated specific associations with several cancer-related pathways. The present study provides a bioinformatics method for biomarker screening, which led to the identification of an integrated mRNA-miRNA-lncRNA regulatory network and their co-expression in relation to predicting HCC patient survival.

Bioinformatic analysis and in vitro validation of a five-microRNA signature as a prognostic biomarker of hepatocellular carcinoma

Background

Existing research has identified correlations between numerous microRNAs (miRNAs) and the prognosis of hepatocellular carcinoma (HCC). However, the role of a combination of miRNAs in predicting HCC survival requires further elucidation.

Methods

miRNA expression profiles and clinical data from HCC patients were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed (DE) miRNAs in tumor versus normal samples were identified. All HCC patients were randomly assigned to a training cohort or a validation cohort at a ratio of 1 to 1. A least absolute shrinkage and selection operator (LASSO) Cox regression model was subsequently employed to establish the miRNA signature. The constructed miRNA signature was then developed and validated.

Results

In total, 127 DE miRNAs were detected between HCC and paracancerous tissue using HCC RNA sequencing (RNA-Seq) data extracted from TCGA database. LASSO Cox regression generated a five-miRNA signature consisting of has-mir-105-2, has-mir-9-3, has-mir-137, has-mir-548f-1, and has-mir-561 in the training cohort. This risk model was significantly related to survival (P=5.682e-6). Log-rank tests and multivariate Cox regression analyses revealed the five-miRNA signature as an independent prognostic indicator [HR =3.285, 95% confidence interval (CI): 1.737–6.213], with the area under curve (AUC) of the miRNA signature being 0.728. The effects of the miRNA signature were further confirmed in the validation cohort and in the OncomiR Cancer Database and Gene Expression Omnibus (GEO) dataset. Functional enrichment analysis revealed the potential effects of the five-miRNA signature in tumor-related biological pathways and processes. Cell Counting Kit-8, Transwell, and wound healing assays, were used to evaluate the role of has-mir-137 in HCC cell proliferation and migration in vitro.

Conclusions

We established a novel five-miRNA signature which reliably predicted prognosis in HCC patients and which could be used to assist in both strategic counseling and personalized management in HCC.

Circulating exosomal microRNAs as potential biomarkers of hepatic injury and inflammation in a murine model of glycogen storage disease type 1a

Most patients affected by glycogen storage disease type 1a (GSD1a), an inherited metabolic disorder caused by mutations in the enzyme glucose-6-phosphatase-α (G6Pase-α), develop renal and liver complications, including the development of hepatocellular adenoma/carcinoma. The purpose of this study was to identify potential biomarkers of the pathophysiology of the GSD1a-affected liver. To this end, we used the plasma exosomes of a murine model of GSD1a, the LS-G6pc ^{-/ -} mouse, to uncover the modulation in microRNA expression associated with the disease. The microRNAs differentially expressed between LS-G6pc ^-/- and wild-type mice, LS-G6pc ^-/- mice with hepatocellular adenoma and LS-G6pc ^-/- mice without adenoma, and LS-G6pc ^-/- mice with amyloidosis and LS-G6pc ^-/- mice without amyloidosis were identified. Pathway analysis demonstrated that the target genes of the differentially expressed microRNA were significantly enriched for the insulin signaling pathway, glucose and lipid metabolism, Wnt/β-catenin, telomere maintenance and hepatocellular carcinoma, and chemokine and immune regulation signaling pathways. Although some microRNAs were common to the different pathologic conditions, others were unique to the cancerous or inflammatory status of the animals. Therefore, the altered expression of several microRNAs is correlated with various pathologic liver states and might help to distinguish them during the progression of the disease and the development of late GSD1a-associated complications.

Small RNAs, Big Diseases

The past two decades have seen extensive research done to pinpoint the role of microRNAs (miRNAs) that have led to discovering thousands of miRNAs in humans. It is not, therefore, surprising to see many of them implicated in a number of common as well as rare human diseases. In this review article, we summarize the progress in our understanding of miRNA-related research in conjunction with different types of cancers and neurodegenerative diseases, as well as their potential in generating more reliable diagnostic and therapeutic approaches.

Dysregulated microRNAs in Hepatitis B Virus-Related Hepatocellular Carcinoma: Potential as Biomarkers and Therapeutic Targets

MicroRNAs (miRNAs) are non-coding small RNAs that can function as gene regulators and are involved in tumorigenesis. We review the commonly dysregulated miRNAs in liver tumor tissues and plasma/serum of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients. The frequently reported up-regulated miRNAs in liver tumor tissues include miR-18a, miR-21, miR-221, miR-222, and miR-224, whereas down-regulated miRNAs include miR-26a, miR-101, miR-122, miR-125b, miR-145, miR-199a, miR-199b, miR-200a, and miR-223. For a subset of these miRNAs (up-regulated miR-222 and miR-224, down-regulated miR-26a and miR-125b), the pattern of dysregulated circulating miRNAs in plasma/serum is mirrored in tumor tissue based on multiple independent studies. Dysregulated miRNAs target oncogenes or tumor suppressor genes involved in hepatocarcinogenesis. Normalization of dysregulated miRNAs by up- or down-regulation has been shown to inhibit HCC cell proliferation or sensitize liver cancer cells to chemotherapeutic treatment. miRNAs hold as yet unrealized potential as biomarkers for early detection of HCC and as precision therapeutic targets, but further studies in diverse populations and across all stages of HCC are needed.

Serum microRNA expression profiling identifies serum biomarkers for HCV-related hepatocellular carcinoma

BACKGROUND

The identification of high-sensitivity biomarkers for detection of hepatocellular carcinoma (HCC) from high-risk individuals is essential.

OBJECTIVE

The present study was undertaken to identify and validate serum microRNAs (miRNAs) as potential biomarkers for hepatitis C virus (HCV)-related HCC.

METHODS

Illumina sequencing was employed to screen the expression profiles of miRNAs in serum samples of HCV-related HCC patients and liver cirrhosis (LC) patients. RT-qPCR was used to confirm the altered miRNAs between the two groups. Moreover, candidate miRNAs were examined in serum samples of 40 HCC patients, 54 LC patients, 55 patients with chronic HCV hepatitis and 45 healthy controls. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the miRNAs for the detection of HCC.

RESULTS

Four miRNAs (miR-122-5p, miR-331-3p, miR-494-3p, miR-224-5p) were significantly increased and two miRNAs (miR-185-5p, miR-23b-3p) were significantly decreased in HCC patients compared to LC patients. ROC curve analysis demonstrated that the six miRNAs could be used as potential biomarkers for HCC detection. Combination of the six miRNAs could efficiently detect HCC in LC patients with the area under the ROC curve (AUC) of 0.995 and combination of the six miRNAs also provided high diagnostic accuracy (AUC = 0.961) for detection of HCC in non-HCC subjects.

CONCLUSIONS

The six serum miRNAs can be utilized as a surrogate and non-invasive biomarker for HCV-related HCC diagnosis.

TransmiR v2.0: an updated transcription factor-microRNA regulation database

MicroRNAs (miRNAs) are important post-transcriptional regulators of gene expression and play vital roles in various biological processes. It has been reported that aberrant regulation of miRNAs was associated with the development and progression of various diseases, but the underlying mechanisms are not fully deciphered. Here, we described our updated TransmiR v2.0 database for more comprehensive information about transcription factor (TF)-miRNA regulations. 3730 TF–miRNA regulations among 19 species from 1349 reports were manually curated by surveying >8000 publications, and more than 1.7 million tissue-specific TF–miRNA regulations were further incorporated based on ChIP-seq data. Besides, we constructed a ‘Predict’ module to query the predicted TF–miRNA regulations in human based on binding motifs of TFs. To facilitate the community, we provided a ‘Network’ module to visualize TF–miRNA regulations for each TF and miRNA, or for a specific disease. An ‘Enrichment analysis’ module was also included to predict TFs that are likely to regulate a miRNA list of interest. In conclusion, with improved data coverage and webserver functionalities, TransmiR v2.0 would be a useful resource for investigating the regulation of miRNAs. TransmiR v2.0 is freely accessible at http://www.cuilab.cn/transmir.

Biomarkers for the Early Detection of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, and the cancer with the fastest increase in mortality in the United States, with more than 39,000 cases and 29,000 deaths in 2018. As with many cancers, survival is significantly improved by early detection. The median survival of patients with early HCC is >60 months but <15 months when detected at an advanced stage. Surveillance of at-risk patients improves outcome, but fewer than 20% of those at risk for HCC receive surveillance, and current surveillance strategies have limited sensitivity and specificity. Ideally, blood-based biomarkers with adequate sensitivity or specificity would be available for early detection of HCC; however, the most commonly used biomarker for HCC, alpha-fetoprotein, has inadequate performance characteristics. There are several candidate serum proteomic, glycomic, and genetic markers that have gone through early stages of biomarker validation and have shown promise for the early detection of HCC, but these markers require validation in well-curated cohorts. Ongoing prospective cohort studies will permit retrospective longitudinal (phase III biomarker study) validation of biomarkers. In this review, we highlight promising candidate biomarkers and biomarker panels that have completed phase II evaluation but require further validation prior to clinical use.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Uncovering the potential differentially expressed miRNAs as diagnostic biomarkers for hepatocellular carcinoma based on machine learning in The Cancer Genome Atlas database

The present study aimed to identify novel diagnostic differentially expressed microRNAs (miRNAs/miRs) in order to understand the molecular mechanisms underlying hepatocellular carcinoma. The expression data of miRNA and mRNA were downloaded for differential expression analysis. Optimal diagnostic differentially expressed miRNA biomarkers were identified via a random forest algorithm. Classification models were established to distinguish patients with hepatocellular carcinoma and normal individuals. A regulatory network between optimal diagnostic differentially expressed miRNA and differentially expressed mRNAs was then constructed. The GSE63046 dataset and in vitro experiments were used to validate the expression of the optimal diagnostic differentially expressed miRNAs identified. In addition, diagnostic and prognostic analyses of optimal diagnostic differentially expressed miRNAs were performed. In total, 14 differentially expressed miRNAs (all upregulated) and 2,982 differentially expressed mRNAs (1,989 upregulated and 993 downregulated) were identified. hsa-miR-10b-5p, hsa-miR-10b-3p, hsa-miR-224-5p, hsa-miR-183-5p and hsa-miR-182-5p were considered as the optimal diagnostic biomarkers for hepatocellular carcinoma. The mRNAs targeted by these five miRNAs included secreted frizzled related protein 1 (SFRP1), endothelin receptor type B (EDNRB), nuclear receptor subfamily 4 group A member 3 (NR4A3), four and a half LIM domains 2 (FHL2), NK3 homeobox 1 (NKX3-1), interleukin 6 signal transducer (IL6ST) and forkhead box O1 (FOXO1). ‘Bile acid biosynthesis and cholesterol’ was the most enriched signaling pathways of these target mRNAs. The expression validation of the five miRNAs was consistent with the present bioinformatics analysis. Notably, hsa-miR-10b-5p and hsa-miR-10b-3p had a significant prognosis value for patients with hepatocellular carcinoma. In conclusion, the five differentially expressed miRNAs may be considered as diagnostic biomarkers for patients with hepatocellular carcinoma. In addition, the differential expression levels of the targets of these five mRNAs, including SFRP1, EDNRB, NR4A3, FHL2, NKX3−1, IL6ST and FOXO1, may be involved in hepatocellular carcinoma tumorigenesis.

Identification of candidate RNA signatures in triple-negative breast cancer by the construction of a competing endogenous RNA network with integrative analyses of Gene Expression Omnibus and The Cancer Genome Atlas data

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that is characterized by aggressive and metastatic clinical characteristics and generally leads to earlier distant recurrence and poorer prognosis than other molecular subtypes. Accumulating evidence has demonstrated that long non-coding RNAs (lncRNAs) serve a crucial role in a wide variety of biological processes by interacting with microRNAs (miRNAs) as competing endogenous RNAs (ceRNAs) and, thus, affect the expression of target genes in multiple types of cancer. Seven datasets from the Gene Expression Omnibus (GEO) database, including 444 tumor and 88 healthy tissue samples, were utilized to investigate the underlying mechanisms of TNBC and identify prognostic biomarkers. Differentially expressed genes (DEGs) were further validated in The Cancer Genome Atlas database and the associations between their expression levels and clinical information were analyzed to identify prognostic values. A potential lncRNA-miRNA-mRNA ceRNA network was also constructed. Finally, 69 mRNAs from the integrated Gene Expression Omnibus datasets were identified as DEGs using the robust rank aggregation method with |log2FC|>1 and adjusted P<0.01 set as the significance cut-off levels. In addition, 29 lncRNAs, 21 miRNAs and 27 mRNAs were included in the construction of the ceRNA network. The present study elucidated the mechanisms underlying the progression of TNBC and identified novel prognostic biomarkers for TNBC.

Identification of circular RNA-microRNA-messenger RNA regulatory network in hepatocellular carcinoma by integrated analysis

BACKGROUND AND AIM

Hepatocellular carcinoma (HCC) is the most common types of hepatic malignancies. This study aimed to better understand the pathogenesis of HCC and may help facilitate the improvement of the diagnostic of HCC.

METHODS

The mRNA and miRNA expression profiles of HCC, which was retrieved from The Cancer Genome Atlas database, and the circRNA expression profiles of HCC, which was retrieved from Gene Expression Omnibus database, were included in this study to perform an integrated analysis. The differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed circRNAs (DEcircRNAs) were identified, and competing endogenous RNA (ceRNA) (DEcircRNA-DEmiRNA-DEmRNA) regulatory network was conducted. Functional annotation of host gene of DEcircRNAs and DEmRNAs in ceRNA regulatory network was performed. Quantitative real-time polymerase chain reaction validation of the expression of the selected DEmRNAs, DEmiRNAs, and DEcircRNAs was performed.

RESULTS

A total of 2982 DEmRNAs, 144 DEmiRNAs, and 264 DEcircRNAs were obtained. The ceRNA network contained 61 circRNA-miRNA pairs and 1149 miRNA-mRNA pairs, including 48 circRNAs, 30 miRNAs, and 1149 mRNAs. Functional annotation of DEmRNAs in ceRNA regulatory network revealed that these DEmRNAs were significantly enriched in tryptophan metabolism, fatty acid metabolism, and pathways in cancer. Except for ARNT2 and hsa-miR-214-3p, expression of the others in the quantitative real-time polymerase chain reaction results was consistent with that in our integrated analysis, generally.

CONCLUSION

We speculate that hsa_circRNA_104268/hsa-miR-214-3p/E2F2, hsa_circRNA_104168/hsa-miR-139-5p/HRAS, and hsa_circRNA_104769/hsa-miR-93-5p/JUN interaction pairs may play a vital role in HCC. This study expected to provide a novel insight into the pathogenesis and therapy of HCC from the circRNA-miRNA-mRNA network view.

Identification of key genes as potential biomarkers for triple‑negative breast cancer using integrating genomics analysis

Triple-negative breast cancer (TNBC) accounts for the worst prognosis of all types of breast cancers due to a high risk of recurrence and a lack of targeted therapeutic options. Extensive effort is required to identify novel targets for TNBC. In the present study, a robust rank aggregation (RRA) analysis based on genome-wide gene expression datasets involving TNBC patients from the Gene Expression Omnibus (GEO) database was performed to identify key genes associated with TNBC. A total of 194 highly ranked differentially expressed genes (DEGs) were identified in TNBC vs. non-TNBC. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was utilized to explore the biological functions of the identified genes. These DEGs were mainly involved in the biological processes termed positive regulation of transcription from RNA polymerase II promoter, negative regulation of apoptotic process, response to drug, response to estradiol and negative regulation of cell growth. Genes were mainly involved in the KEGG pathway termed estrogen signaling pathway. The aberrant expression of several randomly selected DEGs were further validated in cell lines, clinical tissues and The Cancer Genome Atlas (TCGA) cohort. Furthermore, all the top-ranked DEGs underwent survival analysis using TCGA database, of which overexpression of 4 genes (FABP7, ART3, CT83, and TTYH1) were positively correlated to the life expectancy (P<0.05) of TNBC patients. In addition, a model consisting of two genes (FABP7 and CT83) was identified to be significantly associated with the overall survival (OS) of TNBC patients by means of Cox regression, Kaplan-Meier, and receiver operating characteristic (ROC) analyses. In conclusion, the present study identified a number of key genes as potential biomarkers involved in TNBC, which provide novel insights into the tumorigenesis of TNBC at the gene level and may serve as independent prognostic factors for TNBC prognosis.

MicroRNAs in Animal Models of HCC

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality. Molecular heterogeneity and absence of biomarkers for patient allocation to the best therapeutic option contribute to poor prognosis of advanced stages. Aberrant microRNA (miRNA) expression is associated with HCC development and progression and influences drug resistance. Therefore, miRNAs have been assayed as putative biomarkers and therapeutic targets. miRNA-based therapeutic approaches demonstrated safety profiles and antitumor efficacy in HCC animal models; nevertheless, caution should be used when transferring preclinical findings to the clinics, due to possible molecular inconsistency between animal models and the heterogeneous pattern of the human disease. In this context, models with defined genetic and molecular backgrounds might help to identify novel therapeutic options for specific HCC subgroups. In this review, we describe rodent models of HCC, emphasizing their representativeness with the human pathology and their usefulness as preclinical tools for assessing miRNA-based therapeutic strategies.

Bioinformatics analysis to screen key genes in papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common type of thyroid carcinoma, and its incidence has been on the increase in recent years. However, the molecular mechanism of PTC is unclear and misdiagnosis remains a major issue. Therefore, the present study aimed to investigate this mechanism, and to identify key prognostic biomarkers. Integrated analysis was used to explore differentially expressed genes (DEGs) between PTC and healthy thyroid tissue. To investigate the functions and pathways associated with DEGs, Gene Ontology, pathway and protein-protein interaction (PPI) network analyses were performed. The predictive accuracy of DEGs was evaluated using the receiver operating characteristic (ROC) curve. Based on the four microarray datasets obtained from the Gene Expression Omnibus database, namely GSE33630, GSE27155, GSE3467 and GSE3678, a total of 153 DEGs were identified, including 66 upregulated and 87 downregulated DEGs in PTC compared with controls. These DEGs were significantly enriched in cancer-related pathways and the phosphoinositide 3-kinase-AKT signaling pathway. PPI network analysis screened out key genes, including acetyl-CoA carboxylase beta, cyclin D1, BCL2, and serpin peptidase inhibitor clade A member 1, which may serve important roles in PTC pathogenesis. ROC analysis revealed that these DEGs had excellent predictive performance, thus verifying their potential for clinical diagnosis. Taken together, the findings of the present study suggest that these genes and related pathways are involved in key events of PTC progression and facilitate the identification of prognostic biomarkers.

Silencing Of hsa_circ_0008450 Represses Hepatocellular Carcinoma Progression Through Regulation Of microRNA-214-3p/EZH2 Axis

Purpose

Circular RNA (circRNA) hsa_circ_0008450 has been shown to be up-regulated in hepatocellular carcinoma (HCC). However, the functional role of hsa_circ_0008450 and its molecular mechanism are still unknown.

Patients and methods

We used qRT-PCR and Western blot to examine the expression levels of hsa_circ_0008450, microRNA-214-3p (miR-214-3p), and enhancer of zeste homolog 2 (EZH2) protein. CCK8 assay and wound healing assay were used to detect cell viability and cell migration capability. Cell apoptosis was assessed by flow cytometry. Luciferase reporter assay was used to explore the interaction among hsa_circ_0008450, miR-214-3p, and EZH2.

Results

hsa_circ_0008450 was significantly increased in HCC tissues and cells. Furthermore, knockdown of hsa_circ_0008450 in HCC cells inhibited cell proliferation, invasion, and migration. Mechanically, hsa_circ_0008450 promoted the expression of EZH2 protein through sponging miR-214-3p. Knockdown of circ_0008450 suppressed tumorigenesis of HCC cells in vivo.

Conclusion

Knockdown of hsa_circ_0008450 inhibits HCC progression by regulating miR-214-3p/EZH2 axis. This study suggests that hsa_circ_0008450 may serve as a novel target for the treatment of HCC.

DNA Methylation and Micro-RNAs: The Most Recent and Relevant Biomarkers in the Early Diagnosis of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a frequently encountered cancer type, and its alarming incidence is explained by genetic and epigenetic alterations. Epigenetic changes may represent diagnostic and prognostic biomarkers of HCC. In this review we discussed deoxyribonucleic acid (DNA) hypomethylation, DNA hypermethylation, and aberrant expression of small non-coding ribonucleic acid (RNA), which could be useful new biomarkers in the early diagnosis of HCC. We selected the articles on human subjects published in English over the past two years involving diagnostic markers detected in body fluids, cancer diagnosis made on histopathological exam, and a control group of those with benign liver disease or without liver disease. These biomarkers need further investigation in clinical trials to develop clinical applications for early diagnosis and management of HCC.

Identification of differentially expressed genes and biological characteristics of colorectal cancer by integrated bioinformatics analysis

Colorectal cancer (CRC) ranks as one of the most common malignant tumors worldwide. Its mortality rate has remained high in recent years. Therefore, the aim of this study was to identify significant differentially expressed genes (DEGs) involved in its pathogenesis, which may be used as novel biomarkers or potential therapeutic targets for CRC. The gene expression profiles of GSE21510, GSE32323, GSE89076, and GSE113513 were downloaded from the Gene Expression Omnibus (GEO) database. After screening DEGs in each GEO data set, we further used the robust rank aggregation method to identify 494 significant DEGs including 212 upregulated and 282 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by DAVID and the KOBAS online database, respectively. These DEGs were shown to be significantly enriched in different cancer-related functions and pathways. Then, the STRING database was used to construct the protein-protein interaction network. The module analysis was performed by the MCODE plug-in of Cytoscape based on the whole network. We finally filtered out seven hub genes by the cytoHubba plug-in, including PPBP, CCL28, CXCL12, INSL5, CXCL3, CXCL10, and CXCL11. The expression validation and survival analysis of these hub genes were analyzed based on The Cancer Genome Atlas database. In conclusion, the robust DEGs associated with the carcinogenesis of CRC were screened through the GEO database, and integrated bioinformatics analysis was conducted. Our study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for CRC.

Cluster miRNAs and cancer: Diagnostic, prognostic and therapeutic opportunities

MiRNAs are class of noncoding RNA important for gene expression regulation in many plants, animals and viruses. MiRNA clusters contain a set of two or more miRNA encoding genes, transcribed together as polycistronic miRNAs. Currently, there are approximately 159 miRNA clusters reported in the human genome consisting of miRNAs ranging from two or more miRNA genes. A large proportion of clustered miRNAs resides in and around the fragile sites or cancer associated genomic hotspots and plays an important role in carcinogenesis. Altered expression of miRNA cluster can be pro-tumorigenic or anti-tumorigenic and can be targeted for clinical management of cancer. Over the past few years, manipulation of miRNA clusters expression is attempted for experimental purpose as well as for diagnostic, prognostic and therapeutic applications in cancer. Re-expression of miRNAs by epigenetic therapy, genome editing such as clustered regulatory interspaced short palindromic repeats (CRISPR) and miRNA mowers showed promising results in cancer therapy. In this review, we focused on the potential of miRNA clusters as a biomarker for diagnosis, prognosis, targeted therapy as well as strategies for modulating their expression in a therapeutic context. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Processing > Processing of Small RNAs RNA in Disease and Development > RNA in Disease Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs.

Recent advances in liver transplantation for cancer: The future of transplant oncology

Liver transplantation is widely indicated as a curative treatment for selected patients with hepatocellular carcinoma. However, with recent therapeutic advances, as well as efforts to increase the donor pool, liver transplantation has been carefully expanded to patients with other primary or secondary malignancies in the liver. Cholangiocarcinoma, colorectal and neuroendocrine liver metastases, and hepatic epithelioid haemangioendothelioma are amongst the most relevant new indications. In this review we discuss the fundamental concepts of this ambitious undertaking, as well as the newest indications for liver transplantation, with a special focus on future perspectives within the recently established concept of transplant oncology.

Activation of the oncogenic miR-21-5p promotes HCV replication and steatosis induced by the viral core 3a protein

BACKGROUND & AIMS

miR-21-5p is a potent oncogenic microRNA targeting many key tumour suppressors including phosphatase and tensin homolog (PTEN). We recently identified PTEN as a key factor modulated by hepatitis C virus (HCV) to promote virion egress. In hepatocytes, expression of HCV-3a core protein was sufficient to downregulate PTEN and to trigger lipid droplet accumulation. Here, we investigated whether HCV controls PTEN expression through miR-21-5p-dependent mechanisms to trigger steatosis in hepatocytes and to promote HCV life cycle.

METHODS

MiR-21-5p expression in HCV-infected patients was evaluated by transcriptome meta-analysis. HCV replication and viral particle production were investigated in Jc1-infected Huh-7 cells after miR-21-5p inhibition. PTEN expression and steatosis were assessed in HCV-3a core protein-expressing Huh-7 cells and in mouse primary hepatocytes having miR-21-5p inhibited or genetically deleted respectively. HCV-3a core-induced steatosis was assessed in vivo in Mir21a knockout mice.

RESULTS

MiR-21-5p expression was significantly increased in hepatic tissues from HCV-infected patients. Infection by HCV-Jc1, or transduction with HCV-3a core, upregulated miR-21-5p expression and/or activity in Huh-7 cells. miR-21-5p inhibition decreased HCV replication and release of infectious virions by Huh-7 cells. HCV-3a core-induced PTEN downregulation and steatosis were further prevented in Huh-7 cells following miR-21-5p inhibition or in Mir21a knockout mouse primary hepatocytes. Finally, steatosis induction by AAV8-mediated HCV-3a core expression was reduced in vivo in Mir21a knockout mice.

CONCLUSION

MiR-21-5p activation by HCV is a key molecular step, promoting both HCV life cycle and HCV-3a core-induced steatosis and may be among the molecular changes induced by HCV-3a to promote carcinogenesis.

Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients

BACKGROUND

Due to the phenotypic and molecular diversity of hepatocellular carcinomas (HCC), it is still a challenge to determine patients' prognosis. We aim to identify new prognostic markers for resected HCC patients.

METHODS

274 patients were retrospectively identified and samples collected from Zhongshan hospital, Fudan University. We analyzed the gene expression patterns of tumors and compared expression patterns with patient survival times. We identified a "9-gene signature" associated with survival by using the coefficient and regression formula of multivariate Cox model. This molecular signature was then validated in three patients cohorts from internal cohort (n = 69), TCGA (n = 369) and GEO dataset (n = 80).

RESULTS

We identified 9-gene signature consisting of ZC2HC1A, MARCKSL1, PTGS1, CDKN2B, CLEC10A, PRDX3, PRKCH, MPEG1 and LMO2. The 9-gene signature was used, combined with clinical parameters, to fit a multivariable Cox model to the training cohort (concordance index, ci = 0.85), which was successfully validated (ci = 0.86 for internal cohort; ci = 0.78 for in silico cohort). The signature showed improved performance compared with clinical parameters alone (ci = 0.70). Furthermore, the signature predicted patient prognosis than previous gene signatures more accurately. It was also used to stratify early-stage, HBV or HCV-infected patients into low and high-risk groups, leading to significant differences in survival in training and validation (P < 0.001).

CONCLUSIONS

The 9-gene signature, in which four were upregulated (ZC2HC1A, MARCKSL1, PTGS1, CDKN2B) and five (CLEC10A, PRDX3, PRKCH, MPEG1, LMO2) were downregulated in HCC with poor prognosis, stratified HCC patients into low and high risk group significantly in different clinical settings, including receiving adjuvant transarterial chemoembolization and especially in early stage disease. This new signature should be validated in prospective studies to stratify patients in clinical decisions.

Identification of key genes and pathways of thyroid cancer by integrated bioinformatics analysis

Thyroid cancer is a common endocrine malignancy with a rapidly increasing incidence worldwide. Although its mortality is steady or declining because of earlier diagnoses, its survival rate varies because of different tumour types. Thus, the aim of this study was to identify key biomarkers and novel therapeutic targets in thyroid cancer. The expression profiles of GSE3467, GSE5364, GSE29265 and GSE53157 were downloaded from the Gene Expression Omnibus database, which included a total of 97 thyroid cancer and 48 normal samples. After screening significant differentially expressed genes (DEGs) in each data set, we used the robust rank aggregation method to identify 358 robust DEGs, including 135 upregulated and 224 downregulated genes, in four datasets. Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analyses of DEGs were performed by DAVID and the KOBAS online database, respectively. The results showed that these DEGs were significantly enriched in various cancer-related functions and pathways. Then, the STRING database was used to construct the protein-protein interaction network, and modules analysis was performed. Finally, we filtered out five hub genes, including LPAR5, NMU, FN1, NPY1R, and CXCL12, from the whole network. Expression validation and survival analysis of these hub genes based on the The Cancer Genome Atlas database suggested the robustness of the above results. In conclusion, these results provided novel and reliable biomarkers for thyroid cancer, which will be useful for further clinical applications in thyroid cancer diagnosis, prognosis and targeted therapy.

miR-101-3p sensitizes hepatocellular carcinoma cells to oxaliplatin by inhibiting Beclin-1-mediated autophagy

BACKGROUND

Increasing evidence has shown that autophagy can contribute to drug resistance. Whether microRNA-101-3p (miR-101-3p) participates in oxaliplatin (OXA) resistance via modulating Beclin-1-mediated autophagy in hepatocellular carcinoma (HCC) has not been reported.

METHODS

OXA-resistant Huh7 cells (Huh7/OXA) or HepG2 cells (HepG2/OXA) and OXA-sensitive Huh7 or HepG2 cells were treated with OXA in various concentrations. The expressions of miR-101-3p and Beclin-1 were monitored using qRT-PCR. Western blot was used to evaluate cell autophagy. Cell viability and the IC50 of OXA were determined using an MTT assay. Cell apoptosis was evaluated by flow cytometry. A luciferase reporter assay was introduced to confirm the relationship between miR-101-3p and Beclin-1.

RESULTS

miR-101-3p was decreased in HCC resistant tissues and cells. Moreover, an increased expression of miR-101-3p reduced cell viability and the IC50 of OXA, and it promoted cell apoptosis in Huh7/OXA and HepG2/OXA cells. miR-101-3p negatively modulated the expression of Beclin-1. Interestingly, the overexpression of Beclin-1 receded the effect of the ectopic expression of miR-101-3p in OXA-resistant HCC cells. In OXA-sensitive Huh7 and HepG2 cells, OXA significantly increased the expressions of LC3 and Beclin-1, and it decreased the abundance of p62. Furthermore, OXA markedly blocked cell viability, which was exacerbated by the introduction of the autophagy inhibitor CQ. Additionally, the elevated expression of miR-101-3p suppressed cell autophagy by inhibiting the expression of LC3 and Beclin-1 and facilitating the expression of p62.

CONCLUSION

miR-101-3p is responsible for the sensitivity of HCC cells to OXA by inhibiting Beclin-1-mediated autophagy.

Prognostic alternative mRNA splicing signature in hepatocellular carcinoma: a study based on large-scale sequencing data

Most genes are alternatively spliced and increasing number of evidences show that alternative splicing (AS) is modified and related to tumor progression. Systematic profiles of AS signature in hepatocellular carcinoma (HCC) is absent and urgently needed. Here, differentially spliced AS transcripts between HCC and non-HCC tissues were compared, prognosis-associated AS events by using univariate Cox regression analysis were selected. Our gene functional enrichment analysis demonstrated the potential pathways enriched by survival-associated AS. Prognostic AS signatures were then constructed for HCC prognosis prediction by Lasso regression model. We also analyzed splicing factors (SFs) regulating underlying mechanisms by Pearson correlation and then built corresponding regulatory networks. In addition, we explored the performance of AS signature in the mutated HCC samples. Genome-wide AS events in 377 HCC patients from TCGA were profiled. Among 34 163 AS events in 8985 genes, 3950 AS events in 2403 genes associated with overall survival (OS) significantly for HCC were detected. In addition, computational algorithm results showed that metabolic and ribosome pathways may be the potential molecular mechanisms regulating the poor prognosis. More importantly, survival-associated AS signatures revealed high performance in predicting HCC prognosis. The area under curve for AS signature was 0.806 in all HCC and 0.944 in TP53 mutated HCC samples at 2000 days of OS. We submitted prognostic SFs to build the AS regulatory network, from which we found prognostic AS events were significantly enriched in metabolism-related pathways. A robust AS signature for HCC patients and revealed the regulatory splicing networks contributing to the potential significantly enriched metabolism-related pathways.

miR-224-5p inhibits proliferation, migration, and invasion by targeting PIK3R3/AKT3 in uveal melanoma

Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Accumulating investigations have identified the aberrant expression of miRNAs (microRNAs) in UM, such as miR-181, miR-20a, miR-144, miR-146a. The purpose of this study is to investigate the biological function of miR-224-5p in UM. The expression of miR-224-5p, PIK3R3, and AKT3 in 30 tumor tissues and paired adjacent noncancerous tissues were analyzed using Western blot analysis and quantitative real-time polymerase chain reaction (qRT-PCR) assays. Cell proliferation assay, transwell assay, and wound healing assay were used to measure the effects of miR-224-5p on the motility of UM in vitro. Western blot analysis and luciferase assays were used to detect the expression of PIK3R3 and AKT3 as miR-224-5p downstream targets. The results of Western blot analysis and qRT-PCR assays indicated that the expression of miR-224-5p was lower in UM tissues compared to normal tissue, while the expression of PIK3R3 and AKT3 were simultaneously increased. Upregulation of miR-224-5p significantly inhibited capacities of proliferation, invasion, and migration of OCM-1A cells and decreased expression of PIK3R3 and AKT3. Luciferase assay demonstrated PIK3R3 and AKT3 as downstream targets of miR-224-5p. Moreover, upregulating PIK3R3 and AKT3 restrained miR-224-5p-induced inhibition of the motility of OCM-1A cells. Thus, our study proved that miR-224-5p was involved in proliferation, invasion, and migration of UM cells via regulation the expression of PIK3R3 and AKT3. And the results also established a miR-224-5p/PIK3R3/PI3K/AKT axis in the regulation of UM progression, providing an experimental basis for further exploring the miR-224-5p as a therapeutic and diagnosis target for patients with UM.

Development and validation of serum exosomal microRNAs as diagnostic and prognostic biomarkers for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide. China accounts for over half of the new cases and deaths. Diagnostic imprecision and a lack of complimentary molecular biomarkers are partially responsible for this lack of progress. Herein, serum-derived exosomal microRNA (miRNA) profiling was performed on 80 patients which histologically confirmed HCC and 30 normal controls. A classification of 8 exosomal miRNAs had biologically and statistically significant differences between HCC and normal serum samples, including miR-122, miR-125b, miR-145, miR-192, miR-194, miR-29a, miR-17-5p, and miR-106a. Online algorithm showed strong independent classification accuracy (area under the curve) reached 0.535 to 0.850, separately. The significant correlation between serum exosomal miRNAs and tumor size was observed. In addition, the survival difference of HCC patients with high or low exosomal miR-106a was statistically significant using Kaplan-Meier analysis. Besides, we also measured the proliferation and invasion ability of HCC cells following exosomal miR-106a mimics or inhibitor treatment. After prediction with algorithms, mitogen-activated protein kinase and c-Jun N-terminal kinase pathways were identified associated with miR-106a's function. In summary, differentially expressed serum exosomal miRNAs can be helpful for diagnostic and prognostic of HCC.

Prospects of Noncoding RNAs in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a global health problem and one of the most common malignant tumors. Recent studies have shown that noncoding RNAs (ncRNAs) contribute to the pathogenesis of hepatocellular carcinoma (HCC). These RNAs may be involved in a variety of pathological processes such as cell proliferation, apoptosis, angiogenesis, invasion, and metastasis. In addition, abnormal expression of ncRNAs in HCC may provide potential prognostic or diagnostic biomarkers. This review provides an overview of the role and potential applications of ncRNAs, miRNAs, lncRNAs, circRNAs, and snoRNAs in liver cancer.

Long non-coding RNA PVT1 promotes malignancy in human endometrial carcinoma cells through negative regulation of miR-195-5p

The plasmacytoma variant translocation 1 (PVT1)1 gene is a long non-coding RNA (lncRNA)2 that has been shown to be an oncogene in many cancers. Herein, the function and potential molecular mechanisms connecting PVT1 and miR-195-5p were elucidated in endometrial cancer cell lines. Quantitative real-time PCR and fluorescence in situ hybridization (FISH)3 demonstrated that PVT1 is up-regulated concomitant with miR-195-5p down-regulation in human endometrial carcinoma tissues. PVT1 knockdown inhibited cell proliferation, migration, and invasion while facilitating apoptosis of endometrial cancer cells. Moreover, restoration of miR-195-5p due to PVT1 knockdown exerted tumor-suppressive functions. We observed that PVT1 promotes malignant cell behavior by decreasing miR-195-5p expression. Binding of PVT1 and miR-195-5p was confirmed using luciferase assays. Furthermore, expression of miR-195-5p negatively correlates with PVT1 expression. At the molecular level, either PVT1 knockdown or miR-195-5p overexpression resulted in a decrease of acidic fibroblast growth factor receptor (FGFR1)4 and basic fibroblast growth factor (FGF2).5 FGFR1 and FGF2 are targets of miR-195-5p that play a critical role in endometrial carcinoma by activating PI3K/AKT and MAPK/Erk pathways. Remarkably, PVT1 knockdown combined with miR-195-5p overexpression led to tumor regression in vivo. Overall, these results depict a novel pathway mediated by PVT1 in endometrial carcinoma, which may have potential application for endometrial carcinoma therapy.

Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis

Background and Objective: Despite striking advances in multimodality management, gastric cancer (GC) remains the third cause of cancer mortality globally and identifying novel diagnostic and prognostic biomarkers is urgently demanded. The study aimed to identify potential key genes associated with the pathogenesis and prognosis of GC.

Methods: Differentially expressed genes between GC and normal gastric tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Key genes related to the pathogenesis and prognosis of GC were identified by employing protein–protein interaction network and Cox proportional hazards model analyses.

Results: We identified nine hub genes (TOP2A, COL1A1, COL1A2, NDC80, COL3A1, CDKN3, CEP55, TPX2, and TIMP1) which might be tightly correlated with the pathogenesis of GC. A prognostic gene signature consisted of CST2, AADAC, SERPINE1, COL8A1, SMPD3, ASPN, ITGBL1, MAP7D2, and PLEKHS1 was constructed with a good performance in predicting overall survivals.

Conclusion: The findings of this study would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of GC.

Identification of four plasma microRNAs as potential biomarkers in the diagnosis of male lung squamous cell carcinoma patients in China

Dysregulated microRNAs (miRNAs) in the plasma of patients with lung squamous cell carcinoma (LSCC) might serve as biomarkers for LSCC diagnosis. The expression of miRNAs was performed using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) on the basis of Exiqon panels in the initial screening phase including three male LSCC pool samples and one normal control (NC) pool sample (per 10 samples were pooled as one pool sample). After the training (32 LSCC vs. 31 NCs), the testing (55 LSCC vs. 55 NCs), and the external validation (15 LSCC vs. 15 NCs) stages via qRT-PCR, a four-miRNA signature (miR-181a-5p, miR-21-5p, miR-106a-5p, and miR-93-5p) was identified for LSCC detection. Areas under the receiver operating characteristic (ROC) curve (AUC) of the four-miRNA panel for the training, the testing, and the external validation phases were 0.795, 0.827, and 0.914, respectively. Then, the four miRNAs were explored in LSCC tissue samples (23 LSCC vs. 23 NCs), and their expression was significantly up-regulated. However, none of the four miRNAs found significantly up-regulated in plasma exosomes expect miR-93-5p with borderline significance (16 LSCC vs. 16 NCs). In summary, our study established a four-miRNA peripheral plasma signature, which contributed to diagnosing male LSCC patients in China to a certain degree.

Non-coding RNAs, the Trojan horse in two-way communication between tumor and stroma in colorectal and hepatocellular carcinoma

In a continuous and mutual exchange of information, cancer cells are invariably exposed to microenvironment transformation. This continuous alteration of the genetic, molecular and cellular peritumoral stroma background has become as critical as the management of primary tumor progression events in cancer cells. The communication between stroma and tumor cells within the extracellular matrix is one of the triggers in colon and liver carcinogenesis. All non- codingRNAs including long non-coding RNAs, microRNAs and ultraconserved genes play a critical role in almost all cancers and are responsible for the modulation of the tumor microenvironment in several malignant processes such as initiation, progression and dissemination. This review details the involvement of non codingRNAs in the evolution of human colorectal carcinoma and hepatocellular carcinoma in relationship with the microenvironment. Recent research has shown that a considerable number of dysregulated non- codingRNAs could be valuable diagnostic and prognostic biomarkers in cancer. Therefore, more in-depth knowledge of the role non- codingRNAs play in stroma-tumor communication and of the complex regulatory mechanisms between ultraconserved genes and microRNAs supports the validation of future effective therapeutic targets in patients suffering from hepatocellular and colorectal carcinoma, two distinctive entities which share quite a lot common non-coding RNAs.

The down-regulation of the CYP2C19 gene is associated with aggressive tumor potential and the poorer recurrence-free survival of hepatocellular carcinoma

Project HOPE (High-tech Omics-based Patient Evaluation) began in 2014 using integrated gene expression profiling (GEP) of cancer tissues as well as diathesis of each patient who underwent an operation at our institution. The aim of this study was to clarify the association between the expression of cytochrome P450s (CYP) genes and recurrence of hepatocellular carcinoma (HCC). The present study included 92 patients. Genes with aberrant expression were selected based on a ≥10-fold difference in the expression between tumor and non-tumor tissues. The GEP analysis showed that the down-regulated genes in tumor tissue were CYP3A4 in 56 patients (61%), CYP2C8 in 44 patients (48%), CYP2C19 in 30 patients (33%), CYP2D6 in 11 patients (12%), CYP3A5 in 7 patients (8%) and CYP1B1 in 2 patients (2%). There was no patients with down-regulation of the CYP17A1 gene. A multivariate analysis revealed that the presence of microscopic portal invasion (hazard ratio [HR] 2.57, 95% confidence interval [CI] 1.30–5.05 P = 0.006), the presence of intrahepatic-metastasis (HR 3.09 95% CI 1.52–6.29 P = 0.002) and down-regulation of the CYP2C19 gene (HR 3.69 95% CI 1.83–7.46 P < 0.001) were independent predictors for the recurrence-free survival (RFS). The down-regulation of the CYP2C19 gene were correlated with the RFS in HCC.

Identification of molecular target genes and key pathways in hepatocellular carcinoma by bioinformatics analysis

Background and aim

Hepatocellular carcinoma (HCC) is a major cause of cancer mortality and is increasing incidence worldwide. The aim of this study was to identify the key genes and microRNAs in HCC and explore their potential mechanisms.

Methods

The gene expression profiles of GSE76427, GSE64041, GSE57957, and the microRNA dataset GSE67882 were downloaded from the Gene Expression Omnibus database. The online tool GEO2R was used to obtain differentially expressed genes (DEGs) and miRNAs (DEMs). The gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed for DEGs using the Database for Annotation, Visualization, and Integrated Discovery. A protein–protein interaction (PPI) network of the DEGs was constructed by Search Tool for the Retrieval of Interacting Genes and visualized by Cytoscape. Moreover, miRecords was used to predict the target genes of DEMs.

Results

In total, 106 DEGs were screened out in HCC, consisting of 89 upregulated genes and 17 downregulated genes, which were mainly enriched in biological processes associated with oxidation–reduction process. Besides, the Kyoto Encyclopedia of Genes and Genomes pathways including chemical carcinogenesis, drug metabolism-cytochrome P450, tryptophan metabolism, and retinol metabolism were involved. A PPI network was constructed consisting of 105 nodes and 66 edges. A significant module including nine hub genes, ASPM, AURKA, CCNB2, CDKN3, MELK, NCAPG, NUSAP1, PRC1, and TOP2A, was detected from the PPI network by Molecular Complex Detection. The enriched functions were mainly associated with the mitotic cell cycle process, cell division, and mitotic cell cycle. In addition, a total of 21 DEMs were identified, including 9 upregulated and 12 downregulated miRNAs. Interestingly, ZBTB41 was the potential target of seven miRNAs. Finally, the nine hub genes and three miRNA-target genes expression levels were validated by reverse transcription-polymerase chain reaction. The relative expression levels of nine genes (ASPM, AURKA, CDKN3, MELK, NCAPG, PRC1, TOP2A, ZBTB41, and ZNF148) were significantly upregulated in cancer tissues.

Conclusion

This study identified the key genes and potential molecular mechanisms underlying the development of HCC, which could provide new insight for HCC interventional strategies.