Identification of long noncoding RNAs biomarkers in patients with hepatitis B virus-associated hepatocellular carcinoma

The role of long non-coding RNA in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a prevalent liver malignancy with complex etiology and generally poor prognosis. Recently, long non-coding RNAs (lncRNAs), non-protein-coding RNA molecules exceeding 200 nucleotides, have emerged as pivotal players in HCC, influencing its initiation, progression, invasion, and metastasis. These lncRNAs modulate gene expression at epigenetic, transcriptional, and post-transcriptional levels, actively participating in the pathological and physiological processes of HCC. Understanding the intricate relationship between lncRNAs and HCC is important for improving prognosis and reducing mortality. This review summarizes advancements in elucidating the role of lncRNAs in HCC pathogenesis.

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.

LINC02875 Upregulation Contributed to Poor Prognosis for the Hepatocellular Carcinoma and Progression for the Cancerous Cells

The prognostic implications and physiological effect of LINC02875 are unknown in hepatocellular carcinoma (HCC). We sought to examine the prognostic value of LINC02875 in HCC and assessed its role in HCC cellular function. LINC02875 expression was evaluated by RT-qPCR in HCC specimens and cell lines. LINC02875 expression was subjected to assess the correlation with clinical parameters by Chi-squared test and overall survival by Kaplan - Meier curve and Cox regression analysis. The effects of LINC02875 on the biological characteristics of HCC cells were studied by MTS and Transwell assay. LINC02875 was high-expressed in HCC, and this was associated with unfavorable clinical features and poor prognosis of HCC, especially HBV-related HCC. Knockdown of LINC02875 inhibited the proliferation, migration, and invasion of HCC cells. miR-485-5p was a downstream microRNA of LINC02875. LINC02875 affects the prognosis of HCC patients, especially HBV-related ones. LINC02875 represents a suitable therapeutic target for HCC.

Immune-Related lncRNAs with WGCNA Identified the Function of SNHG10 in HBV-Related Hepatocellular Carcinoma

Objective. The hepatitis B virus (HBV) infection led to hepatitis, which was one of common reasons for hepatocellular carcinoma (HCC). The immune microenvironment alteration played a crucial role in this process. The study aimed to identify immune-related long noncoding RNAs (lncRNAs) in HBV-related HCC and explore potential mechanisms. Methods. In total, 1,072 immune‐related genes (IRGs) were enriched in different co-expression modules with weighted gene co-expression network analysis (WGCNA) combining the corresponding clinical features in HBV-related HCC. The immune-related lncRNAs were selected from the crucial co-expression model based on the correlation analysis with IRGs. The immune-related lncRNAs were furtherly used to construct prognostic signature by the Cox proportional hazards regression and Lasso regression. Furthermore, the proliferation and migration ability of lncRNA SNHG10 were verified in vitro. Results. A total of nine co-expression modules were identified by WGCNA of which the “red” co-expression module was most correlated with various clinical characteristics. Additionally, the IRGs in this module were significantly enriched in multiple immune-related pathways. The twelve immune-related lncRNAs prognostic signature (HAND2-AS1, LINC00844, SNHG10, MALAT1, LINC00460, LBX2-AS1, MIR31HG, SEMA6A-AS1, LINC1278, LINC00514, CTBP-AS2, and LINC00205) was constructed. The risk score was an independent risk factor in HBV-related HCC and verified by principal components analysis (PCA), nomogram, and PCR between different cell lines. Moreover, the proportion of immune cells were significantly different between high-risk score group and low-risk score group. The malignant behavior of Hep3B was significantly different between si-lncRNA SNHG10 and control group. Conclusions. The immune-related lncRNAs prognostic signature provided some potential biomarkers and molecular mechanisms in HBV-related HCC.

Long non-coding RNA LINC01793 as a potential diagnostic biomarker of hepatitis B virus-related hepatocellular carcinoma

BACKGROUND

There is growing evidence that long non-coding RNAs (lncRNAs) play important roles in the progression of hepatocellular carcinoma (HCC) and may serve as diagnostic markers. This study investigates the diagnostic efficiency of the long intergenic non-protein-coding RNA 1793 (LINC01793) in hepatitis B virus (HBV)-related HCC.

METHODS

Bioinformatics methods were used to screen the aberrantly expressed lncRNAs in HCC tissues based on The Cancer Genome Atlas (TCGA). Quantitative reverse transcription polymerase chain reaction was performed to assess the expression of the candidate lncRNAs in tissues, cells and whole blood samples of patients with HBV-related HCC, liver cirrhosis (LC), chronic hepatitis (CHB), and healthy controls. Then, the correlations between LINC01793 and clinical characteristics were analyzed. Finally，the diagnostic value of LINC01793 was explored based on the receiver operating characteristic curve.

RESULTS

LINC01793 was remarkably upregulated in the HCC tissues and cells. It was highly expressed in the whole blood of the HBV-related HCC patients, unlike in that of the healthy controls and of the CHB and LC patients. Subsequent analysis revealed that high LINC01793 was related to the Barcelona Clinic Liver Cancer (P = 0.007), tumor invasion (P = 0.042), the number of tumors (P = 0.031) and serum level of alanine aminotransferase(p = 0.022). The areas under the curve of LINC01793, for distinguishing HCC from healthy controls, CHB and LC patients, were 0.824, 0.767 and 0.756, respectively. In addition, the combination of LINC01793 with alpha fetoprotein (AFP) had a stronger diagnostic value than LINC01793 or AFP alone in AFP-negative HCC patients.

CONCLUSION

High expression of LINC01793 is correlated with adverse clinical characteristics and can serve as a non-invasive biomarker of HCC.

Identification of a lncRNA prognostic signature-related to stem cell index and its significance in colorectal cancer

Background: The relationship between long noncoding RNAs (lncRNAs) and the mRNA stemness index (mRNAsi) in colorectal cancer (CRC) is still unclear. Materials & methods: The mRNAsi, mRNAsi-related lncRNAs and their clinical significance were analyzed by bioinformatic approaches in The Cancer Genome Atlas (TCGA)-COREAD dataset. Results: mRNAsi was negatively related to pathological features but positively related to overall survival and recurrence-free survival in CRC. A five mRNAsi-related lncRNAs prognostic signature was further developed and showed independent prognostic factors related to overall survival in CRC patients, due to the five mRNAsi-related lncRNAs involved in several pathways of the cancer stem cells and malignant cancer cell phenotypes. Conclusion: The present study highlights the potential roles of mRNAsi-related lncRNAs as alternative prognostic markers.

The biological characteristics of the canine adenovirus type 1 from fox and the transcriptome analysis of the infected MDCK cell

Canine adenovirus type 1 (CAdV-1) is the etiologic agent of fox encephalitis, and a virus strain from fox encephalitis is isolated and related research are conducted. In this experiment, the results showed that the F1301 strain was confirmed to be the CAdV-1. The whole genome of the CAdV-1 F1301 strain isolated from fox was 30,535 bp and had higher homology to the other reported CAdV-1 strains. After 0, 12, and 36 h of CAdV-1 infection, the difference gene of the 592 long noncoding RNA and 11,215 microRNA were involved in cell responses to CAdV-1 infection through the PI3K-AKT, Wnt, Herpes simplex, hepatitis C, and Epstein-Barr virus infection pathway in Madin-Darby canine kidney cell line (MDCK). The results indicate that the biological characterization of the CAdV-1 and the MDCK cell-CAdV-1 interaction are clarified.

Long Non-Coding RNAs: Potential Biomarkers and Targets for Hepatocellular Carcinoma Therapy and Diagnosis

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide. Increasing studies showed that long non-coding RNAs (lncRNAs), a novel class of RNAs that are greater than 200 nucleotides in length but lack the ability to encode proteins, exert crucial roles in the occurrence and progression of HCC. LncRNAs promote the proliferation, migration, invasion, autophagy, and apoptosis of tumor cells by regulating downstream target gene expression and cancer-related signaling pathways. Meanwhile, lncRNA can be used as biomarkers to predict the efficacy of HCC treatment strategies, such as surgery, radiotherapy, chemotherapy, and immunotherapy, and as a potential individualized tool for HCC diagnosis and treatment. In this review, we overview up-to-date findings on lncRNAs as potential biomarkers for HCC surgery, radiotherapy, chemotherapy resistance, target therapy, and immunotherapy, and discuss the potential clinical application of lncRNA as tools for HCC diagnosis and treatment.

A Four-Methylated lncRNAs-Based Prognostic Signature for Hepatocellular Carcinoma

Currently, an increasing number of studies suggest that long non-coding RNAs (lncRNAs) and methylation-regulated lncRNAs play a critical role in the pathogenesis of various cancers including hepatocellular carcinoma (HCC). Therefore, methylated differentially expressed lncRNAs (MDELs) may be critical biomarkers of HCC. In this study, 63 MDELs were identified by screening The Cancer Genome Atlas (TCGA) HCC lncRNAs expression data set and lncRNAs methylation data set. Based on univariate and multivariate survival analysis, four MDELs (AC025016.1, LINC01164, LINC01183 and LINC01269) were selected to construct the survival prognosis prediction model. Through the PI formula, the study indicates that our new prediction model performed well and is superior to the traditional staging method. At the same time, compared with the previous prediction models reported in the literature, the results of time-dependent receiver operating characteristic (ROC) curve analysis show that our 4-MDELs model predicted overall survival (OS) stability and provided better prognosis. In addition, we also applied the prognostic model to Cancer Cell Line Encyclopedia (CCLE) cell lines and classified different hepatoma cell lines through the model to evaluate the sensitivity of different hepatoma cell lines to different drugs. In conclusion, we have established a new risk scoring system to predict the prognosis, which may have a very important guiding significance for the individualized treatment of HCC patients.

Six long noncoding RNAs as potentially biomarkers involved in competitive endogenous RNA of hepatocellular carcinoma

To investigate lncRNAs acting as competing endogenous RNAs (ceRNAs) involved in oncogenesis and progression of HCC. Different expressed lncRNAs, microRNAs, and mRNAs (DElncRNAs, DEmiRNAs, DEmRNAs), downloaded from The Cancer Genome Atlas (TCGA) database, were identified by edgeR package. CeRNA network was constructed based on miRcode, TargetScan, and miRTarBase. Target DEmRNAs were annotated by KEGG pathway and GO analysis. Negatively correlated lncRNA-miRNA pairs were analyzed by Pearson correlation coefficient, simultaneously, overall survival (OS) were evaluated. The expression of these lncRNAs were examined in HCC cell lines and tissues through qRT-PCR. 1070 DElncRNAs, 147 DEmiRNAs and 1993 DEmRNAs were acquired. CeRNA network was successfully established, including 27 lncRNAs, 5 miRNAs, and 30 mRNAs significantly correlated with OS. The DEmRNAs were significantly enriched in "Cell Cycle" and "pathways in cancer". Six lncRNAs and 2 miRNAs were negatively correlated. These lncRNAs were validated by qRT-PCR. These observations will provide a novel perspective to elucidate HCC pathogenesis.

Long Non-coding RNAs: Emerging Roles in the Immunosuppressive Tumor Microenvironment

Tumor immunosuppression may assist the immune escape of cancer cells, which promotes tumor metastasis and resistance to chemo-radiotherapy. The therapeutic strategies against tumor immunosuppression mainly focus on blocking immune checkpoint receptors, enhancing T-cell recognition and neutralizing inhibitory molecules. Although immunotherapies based on these strategies have improved the clinical outcomes, immunological nonresponse and resistance are two barriers to tumor eradication. Therefore, there is an urgent need to identify new biomarkers for patient selection and therapeutic targets for the development of combination regimen with immunotherapy. Recent studies have reported that non-protein-coding modulators exhibit important functions in post-transcriptional gene regulation, which subsequently modulates multiple pathophysiological processes, including neoplastic transformation. Differentiated from microRNAs, long non-coding RNAs (lncRNAs) are reported to be involved in various processes of the immune response in the tumor microenvironment (TME) to promote tumor immunosuppression. Currently, studies on tumor immunity regulated by lncRNAs are mainly confined to certain types of cancer cells or stromal cells. Additionally, the majority of studies are focused on the events involved in T cells and myeloid-derived suppressor cells (MDSCs). Although the reported studies have indicated the significance of lncRNAs in immunotherapy, the lack of comprehensive studies prevents us from exploring useful lncRNAs. In the current review, we have summarized the roles of lncRNAs in tumor immune response, and highlighted major lncRNAs as potential biomarkers or therapeutic targets for clinical application of immunotherapy.

Identification of a nomogram based on long non-coding RNA to improve prognosis prediction of esophageal squamous cell carcinoma

PURPOSE

Esophageal squamous cell carcinoma (ESCC) remains a common aggressive malignancy in the world. Several long non-coding RNAs (lncRNAs) are reported to predict the prognosis of ESCC. Therefore, an in-depth research is urgently needed to further investigate the prognostic value of lncRNAs in ESCC.

RESULTS

From the training set, we identified a eight-lncRNA signature (including AP000487, AC011997, LINC01592, LINC01497, LINC01711, FENDRR, AC087045, AC137770) which separated the patients into two groups with significantly different overall survival (hazard ratio, HR = 3.79, 95% confidence interval, 95% CI [2.56-5.62]; P < 0.001). The signature was applied to the validation set (HR = 2.73, 95%CI [1.65-4.53]; P < 0.001) and showed similar prognostic values. Stratified, univariate and multivariate Cox regression analysis indicated that the signature was an independent prognostic factor for patients with ESCC. A nomogram based on the lncRNAs signature, age, grade and stage was developed and showed good accuracy for predicting 1-, 3- and 5-year survival probability of ESCC patients. We found a strong correlation between the gene significance for the survival time and T stage. Eight modules were constructed, among which the key module most closely associated with clinical information was identified.

CONCLUSIONS

Our eight-lincRNA signature and nomogram could be practical and reliable prognostic tools for esophageal squamous cell carcinoma.

METHODS

We downloaded the lncRNA expression profiles of ESCC patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets and separated to training and validation cohort. The univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to identify a lncRNA-based signature. The predictive value of the signature was assessed using the Kaplan-Meier method, receiver operating characteristic (ROC) curves and area under curve (AUC). Weighted gene co-expression network analysis (WGCNA) was applied to predict the intrinsic relationship between gene expressions. In addition, we further explored the combination of clinical information and module construction.

Integrated bioinformatics analysis reveals role of the LINC01093/miR-96-5p/ZFAND5/NF-κB signaling axis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a significant health burden worldwide and its pathogenesis remains to be fully elucidated. One of the means by which long non-coding (lnc)RNAs regulate gene expression is by interacting with micro (mi)RNAs and acting as competing endogenous (ce)RNAs. lncRNAs have important roles in various diseases. The aim of the present study was to examine the potential roles of lncRNAs in HCC. The RNA expression profiles of 21 paired tissues of HCC and adjacent non-tumor tissues were obtained from the Gene Expression Omnibus database. The differentially expressed RNAs were analyzed using the DESeq package in R. Expression validation and survival analysis of selected RNAs were performed using Gene Expression Profile Interactive Analysis and/or Kaplan-Meier Plotter. The target genes of the miRNAs were predicted using lncBase or TargetScan. Functional analyses were performed using the Database for Annotation, Visualization and Integrated Discovery, and regulatory networks were determined using Cytoscape. Long intergenic non-protein coding RNA 1093 (LINC01093) was identified as one of the most significantly downregulated lncRNAs in HCC tissues. Downregulated expression of LINC01093 was associated with poor prognosis. A ceRNA network involving LINC01093, miR-96-5p and zinc finger AN1-type containing 5 (ZFAND5) was established. According to functional analyses, NF-κB signaling was implicated in the regulatory network for HCC. The present study revealed that a LINC01093/miR-96-5p/ZFAND5/NF-κB signaling axis may have an important role in the pathogenesis of HCC, and further investigation of this axis may provide novel insight into the development and progression of HCC.

Identification of five long noncoding RNAs signature and risk score for prognosis of bladder urothelial carcinoma

Nowadays, an increasing number of studies illustrated that bladder urothelial cancer (BLCA) may act as the most common subtype of urological malignancies with a high rate of recurrence and metastasis. In this study, we attempted to establish a prognostic model and identify the possible pathway crosstalk. Long noncoding RNAs (lncRNAs) and mRNA expression and corresponding clinical information of patients with BLCA were downloaded from The Cancer Genome Atlas (TCGA). The differentially expressed genes analysis, univariate Cox analysis, the least absolute shrinkage, and selection operator Cox (LASSO Cox) regression model were then applied to identify five crucial lncRNAs (AC092725.1, AC104071.1, AL023584.1, AL132642.1, and AL137804.1). The multivariate cox analysis was utilized to calculate the regression coefficients (β_i ). The risk-score model was subsequently constructed as follows: (0.13541AC092725.1) + (0.20968AC104071.1) + (0.1525AL023584.1) - (0.14768AL132642.1) + (0.14387AL137804.1). Nomogram and assessment of overall survival (OS) prediction were verificated by the receiver operating characteristic curve in the testing group. As to 3-, 5-year OS prediction, the area under curve (AUC) for the nomogram of training data set was 0.83 and 0.86. Besides, the AUC (0.883 and 0.879) presented excellent predictive power in the testing group. In addition, the calibration plots validated the predictive performance of the nomogram. Weighted correlation network analysis (WGCNA) coupled with functional enrichment analysis contributed to explore the potential pathways, including PI3K-Akt, HIF-1, and Jak-STAT signaling pathways. Construction of the risk-score model and data analysis were both derived from multiple packages on the basis of the R platform chiefly.

Long Non-coding RNA FENDRR Acts as a miR-423-5p Sponge to Suppress the Treg-Mediated Immune Escape of Hepatocellular Carcinoma Cells

Long non-coding RNAs (lncRNAs) have been known to partake in the development and the immune escape of hepatocellular carcinoma (HCC). The initial microarray analysis of GSE115018 expression profile revealed differentially expressed lncRNA fetal-lethal non-coding developmental regulatory RNA (FENDRR) in HCC. Therefore, this study’s main purpose was to explore the mechanism of tumor suppressor lncRNA FENDRR in regulating the immune escape of HCC cells. Notably, it was further validated through this study that lncRNA FENDRR competitively bound to microRNA-423-5p (miR-423-5p), and miR-423-5p specifically targeted growth arrest and DNA-damage-inducible beta protein (GADD45B). The effects that lncRNA FENDRR and miR-423-5p have on the cell proliferation and apoptosis, the immune capacity of regulatory T cells (Tregs), and the tumorigenicity of HCC cells were examined through overexpressing or the knocking down of lncRNA FENDRR and miR-423-5p both in vitro and in vivo. Subsequently, lncRNA FENDRR and GADD45B were revealed to have poor expressions in HCC. Meanwhile, miR-423-5p was highly expressed in HCC. Importantly, overexpressed lncRNA FENDRR and downregulated miR-423-5p diminished cell proliferation and tumorigenicity, and promoted apoptosis in HCC cells, thus regulating the immune escape of HCC mediated by Tregs. Taken conjointly, lncRNA FENDRR inhibited the Treg-mediated immune escape of HCC cells by upregulating GADD45B by sponging miR-423-5p.

LncRNA FENDRR attenuates colon cancer progression by repression of SOX4 protein

Background and purpose: Homo sapiens FOXF1 adjacent noncoding developmental regulatory RNA (FENDRR) is a novel long noncoding RNA (lncRNA) exerting important effects on transcriptional and post-transcriptional regulation. The purpose of this study was to investigate the potential role of FENDRR in colon cancer. Methods: Multiple cellular and molecular biology experiments were performed in the present study, such as CCK-8, Western blot, immunohistochemistry, confocal immunofluorescent and animal studies. Results: We determined that attenuation of FENDRR was a frequent event in colon cancer tissues and colon cancer cell lines, in contrast to their normal counterparts. Low levels of FENDRR were associated with the clinical stages and poor prognosis. Moreover, ectopic expression of FENDRR repressed colon cancer cell viability, invasion and epithelial-mesenchymal transition. Furthermore, through a series of in vitro and in vivo assays, we reported the discovery of FENDRR modulating the expression of SOX4 protein, and hence in the progression of colon cancer. Conclusion: Based on these data, we demonstrated that FENDRR may function as a tumor-suppressor gene by repressing SOX4 and as a potential therapeutic target for colon cancer.

The discovery of a novel eight-mRNA-lncRNA signature predicting survival of hepatocellular carcinoma patients

Increasing evidence indicates that the expressions of messenger RNAs (mRNAs) and long non-coding RNAs (lncRNAs) undergo a frequent and aberrant change in carcinogenesis and cancer development. But some research was carried out on mRNA-lncRNA signatures for prediction of hepatocellular carcinoma (HCC) prognosis. We aimed to establish an mRNA-lncRNA signature to improve the ability to predict HCC patients' survival. The subjects from the cancer genome atlas (TCGA) data set were randomly divided into two parts: training data set (n = 246) and testing data set (n = 124). Using computational methods, we selected eight gene signatures (five mRNAs and three lncRNAs) to generate the risk score model, which were significantly correlated with overall survival of patients with HCC in both training and testing data set. The signature had the ability to classify the patients in training data set into a high-risk group and low-risk group with significantly different overall survival (hazard ratio = 4.157, 95% confidence interval = 2.648-6.526, P < 0.001). The prognostic value was further validated in testing data set and the entire data set. Further analysis revealed that this signature was independent of tumor stage. In addition, Gene Set Enrichment Analysis suggested that high risk score group was associated with cell proliferation and division related pathways. Finally, we developed a well-performed nomogram integrating the prognostic signature and other clinical information to predict 3- and 5-year overall survival. In conclusion, the prognostic mRNAs and lncRNAs identified in our study indicate their potential role in HCC biogenesis. The risk score model based on the mRNA-lncRNA may be an efficient classification tool to evaluate the prognosis of patients' with HCC.

Integrated analysis of lncRNA-associated ceRNA network reveals potential biomarkers for the prognosis of hepatitis B virus-related hepatocellular carcinoma

Background

There is evidence that abnormal expression of lncRNAs is associated with hepatitis B virus (HBV) infection-induced hepatocellular carcinoma (HCC). However, the mechanisms remain not fully elucidated. The study aimed to identify novel lncRNAs and explore their underlying mechanisms based on the ceRNA hypothesis.

Methods

The RNA and miRNA expression profiling in 20 tumor and matched adjacent tissues from HBV–HCC patients were retrieved from the Gene Expression Omnibus database under accession numbers GSE77509 and GSE76903, respectively. Differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) were identified using the EdgeR package. Protein–protein interaction (PPI) network was constructed for DEGs followed by module analysis. The ceRNA network was constructed based on interaction relationships between miRNAs and mRNAs/lncRNAs. The functions of DEGs were predicted using DAVID and BinGO databases. The prognosis values (overall survival [OS] and recurrence-free survival [RFS]) of ceRNA network genes were determined using The Cancer Genome Atlas (TCGA) data with Cox regression analysis and Kaplan–Meier method.

Results

The present study screened 643 DELs, 83 DEMs, and 1,187 DEGs. PPI network analysis demonstrated that CDK1 and CCNE1 were hub genes and extracted in functionally related modules. E2F2, CDK1, and CCNE1 were significantly enriched into cell cycle pathway. FAM182B-miR-125b-5p-E2F2 and LINC00346-miR-10a-5p-CDK1/CCNE1 ceRNA axes were obtained by constructing the ceRNA network. Patients with high expressions of DELs and DEGs in the above ceRNA axes had poor OS, while patients with the high expression of DEMs possessed excellent OS. CDK1 was also an RFS-related biomarker, with its high expression predicting poor RFS. The upregulation of LINC00346 and CDK1 but the downregulation of miR-10a-5p in HCC was validated in other microarray datasets and TCGA database.

Conclusion

The LINC00346-miR-10a-5p-CDK1 axis may be an important mechanism for HBV-related HCC, and genes in this ceRNA axis may be potential prognostic biomarkers and therapeutic targets.

Long non-coding RNA FENDRR inhibits proliferation and invasion of hepatocellular carcinoma by down-regulating glypican-3 expression

Long non-coding RNA FENDRR is implicated in progression of several cancers, but its exact role and mechanism in hepatocellular carcinoma (HCC) are largely unknown. In this study, we investigated the expression and biological roles of FENDRR in HCC tissues and cell lines. We found that the expression levels of FENDRR were significantly down-regulated in HCC tissues and cells. FENDRR overexpression could inhibit the growth of HCC cells in vitro and in vivo. Moreover, up-regulation of FENDRR suppressed the migration and invasion of HCC cells. Mechanistically, we demonstrated that FENDRR interacted directly with Glypican-3 (GPC3) promoter and methylated GPC3 promoter, which led to down-regulation of GPC3 expression. Ectopic expression of GPC3 ablated the inhibitory effects of FENDRR on HCC cell proliferation, migration and invasion. Taken together, we provided the first evidence for the inhibitory activity of FENDRR in HCC, which is causally linked to targeting GPC3 at the epigenetic level. Restoration of FENDRR may be a potential approach to prevent HCC progression and metastasis.