Network In Hepatocellular Carcinoma Research Articles

Integrating Single-cell and Spatial Transcriptomics to uncover and elucidate a GP73-mediated Pro-angiogenic Regulatory Networks in Hepatocellular Carcinoma

Integrating Single-cell and Spatial Transcriptomics to uncover and elucidate a GP73-mediated Pro-angiogenic Regulatory Networks in Hepatocellular Carcinoma

Construction of CDKN2A-related competitive endogenous RNA network and identification of GAS5 as a prognostic indicator for hepatocellular carcinoma.

Competitive endogenous RNA (ceRNA) is an innovative way of gene expression modulation, which plays a crucial part in neoplasia. However, the intricacy and behavioral characteristics of the ceRNA network in hepatocellular carcinoma (HCC) remain dismal. To establish a cyclin dependent kinase inhibitor 2A (CDKN2A)-related ceRNA network and recognize potential prognostic indicators for HCC. The mutation landscape of CDKN2A in HCC was first explored using the cBioPortal database. Differential expression analysis was implemented between CDKN2Ahigh and CDKN2Alow expression HCC samples. The targeted microRNAs were predicted by lncBasev3.0, and the targeted mRNAs were predicted by miRDB, and Targetscan database. The univariate and multivariate analysis were utilized to identify independent prognostic indicators. CDKN2A was frequently mutated and deleted in HCC. The single-cell RNA-sequencing analysis revealed that CDKN2A participated in cell cycle pathways. The CDKN2A-related ceRNA network-growth arrest specific 5 (GAS5)/miR-25-3p/SRY-box transcription factor 11 (SOX11) was successfully established. GAS5 was recognized as an independent prognostic biomarker, whose overexpression was correlated with a poor prognosis in HCC patients. The association between GAS5 expression and methylation, immune infiltration was explored. Besides, traditional Chinese medicine effective components targeting GAS5 were obtained. This CDKN2A-related ceRNA network provides innovative insights into the molecular mechanism of HCC formation and progression. Moreover, GAS5 might be a significant prognostic biomarker and therapeutic target in HCC.

Expression of circular RNA has-circ-0009158 and identification of associated miRNA-mRNA network in hepatocellular carcinoma

Expression of circular RNA has-circ-0009158 and identification of associated miRNA-mRNA network in hepatocellular carcinoma

Comprehensive analysis of m6A reader YTHDF2 prognosis, immune infiltration, and related regulatory networks in hepatocellular carcinoma

BackgroundN6-Methyladenosine (m6A) RNA modification is the most prevalent internal modification pattern in eukaryotic mRNAs and plays critical roles in diverse physiological and pathological processes. However, the expression of m6A regulator YTHDF2, its prognostic value, its biological function, its correlation with tumor microenvironment (TME) immune infiltrates, and related regulatory networks in hepatocellular carcinoma (HCC) remain determined. MethodsTCGA, GTEx, and GEO databases were used to investigate the expression profile of YTHDF2 in HCC. We performed differentially expressed genes (DEGs) analysis and constructed a PPI network to explore the biological processes of YTHDF2 in HCC. Kaplan-Meier curves and Cox regression analysis were used to assess the prognostic value of YTHDF2 and then a clinical prognostic nomogram was constructed. Additionally, ssGSEA was performed to assess the correlation between YTHDF2 and immune infiltration levels. The TISIDB database was applied to explore the expression of YTHDF2 in immune and molecular subtypes of HCC. GSEA identifies the YTHDF2-related signaling pathways. Finally, we utilized miRNet and starBase database to construct regulatory networks for HCC based on lncRNA-miRNA and miRNA-YTHDF2 interactions. ResultsYTHDF2 was significantly upregulated in HCC tumor tissues compared with the adjacent normal tissues. HCC patients in the high YTHDF2 expression group had poorer survival. Multivariate Cox analysis suggested that YTHDF2 may be a new independent prognostic indicator for HCC patients, with the prognostic nomogram exhibiting satisfactory results. YTHDF2 expression was significantly correlated with TME immune cell-infiltrating characteristics. Strong correlations were also shown in immune subtypes, molecular subtypes and immune checkpoints. Further analysis revealed that the combination of YTHDF2 expression and immune cell score was considerably associated with survival outcome in HCC patients. GESA analysis demonstrated that high YTHDF2 expression is associated with multiple biological processes and oncogenic pathways. Moreover, 14 possible regulatory networks were constructed, which are associated with HCC progression. ConclusionOur findings revealed that YTHDF2 may serve as a promising prognostic biomarker for HCC and may regulate the tumor immune microenvironment to provide effective therapeutic strategies.

Identification of a novel signature based on macrophage-related marker genes to predict prognosis and immunotherapeutic effects in hepatocellular carcinoma.

Tumor-related macrophages (TAMs) have emerged as an essential part of the immune regulatory network in hepatocellular carcinoma (HCC). Constructing a TAM-related signature is significant for evaluating prognosis and immunotherapeutic response of HCC patients. Informative single-cell RNA sequencing (scRNA-seq) dataset was obtained from the Gene Expression Omnibus (GEO) database, and diverse cell subpopulations were identified by clustering dimension reduction. Moreover, we determined molecular subtypes with the best clustering efficacy by calculating the cumulative distribution function (CDF). The ESTIMATE method, CIBERSORT (cell-type identification by estimating relative subsets of RNA transcripts) algorithm and publicly available tumor immune dysfunction and exclusion (TIDE) tools were used to characterize the immune landscape and tumor immune escape status. A TAM-related gene risk model was constructed through Cox regression and verified in multiple datasets and dimensions. We also performed functional enrichment analysis to detect potential signaling pathways related to TAM marker genes. In total, 10 subpopulations and 165 TAM-related marker genes were obtained from the scRNA-seq dataset (GSE149614). After clustering 3 molecular subtypes based on TAM-related marker genes, we found significantly different prognostic survival and immune signatures among the three subtypes. Subsequently, a 9-gene predictive signature (TPP1, FTL, CXCL8, CD68, ATP6V1F, CSTB, YBX1, LGALS3, and APLP2) was identified as an independent prognostic factor for HCC patients. Those patients with high RiskScore had a lower survival rate and benefited less from immunotherapy than those with low RiskScore. Moreover, more samples of the Cluster C subtype were enriched in the high-risk group, with higher tumor immune escape incidence. We constructed a TAM-related signature with excellent efficacy for predicting prognostic survival and immunotherapeutic responses in HCC patients.

Identification of novel prognostic biomarkers in the TF-enhancer-target regulatory network in hepatocellular carcinoma and immune infiltration analysis.

Background: Hepatocellular carcinoma (HCC) remains notorious for its high malignancy, poor prognosis and high mortality. The exploration of novel therapeutic agents for HCC has remained challenging due to its complex aetiology. Therefore, it is necessary to elucidate the pathogenesis and mechanism of HCC for clinical intervention. Methods: We collected data from several public data portals and systematically analysed the association between transcription factors (TFs), eRNA-associated enhancers and downstream targets. We next filtered the prognostic genes and established a novel prognosis-related nomogram model. Moreover, we explored the potential mechanisms of the identified prognostic genes. The expression level was validated by several ways. Results: We first constructed a significant TF-enhancer-target regulatory network and identified DAPK1 as a coregulatory differentially expressed prognosis-related gene. We combined common clinicopathological factors and built a prognostic nomogram model for HCC. We found that our regulatory network was correlated with the processes of synthesizing various substances. Moreover, we explored the role of DAPK1 in HCC and found that it was associated with immune cell infiltration and DNA methylation. Several immunostimulators and targeting drugs could be promising immune therapy targets. The tumor immune microenvironment was analyzed. Finally, the lower DAPK1 expression in HCC was validated via the GEO database, UALCAN cohort, and qRT-PCR. Conclusion: In conclusion, we established a significant TF-enhancer-target regulatory network and identified downregulated DAPK1 as an important prognostic and diagnostic gene in HCC. Its potential biological functions and mechanisms were annotated using bioinformatics tools.

Comprehensive Analysis of the Sorafenib-Associated Druggable Targets on Differential Gene Expression and ceRNA Network in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the predominant pathological type of liver cancer. Several therapeutic treatments, including sorafenib and regorafenib, have only modestly improved survival in patients with HCC. The aim of this study was to investigate the expression profiles and the regulation of competitive endogenous RNAs (ceRNAs) of the sorafenib-related target genes in HCC. Based on clinical information and expression profiles of HCC clinical samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, shared differentially expressed genes (DEGs) were analyzed and identified. Sorafenib-associated DEGs (SADs) were obtained by intersecting the DEGs with the sorafenib target genes from SuperTarget database. The expression patterns of SADs were verified in the Oncomine database. The biological functions of the SADs were annotated by gene set enrichment analysis (GSEA). In addition, a ceRNA network associated with SADs was constructed. Long non-coding RNAs (lncRNAs) in network that were significantly associated with overall survival were identified as prognosis of patients by Cox regression analysis. Finally, the expression levels of prognostic genes in HCC tissues and cell lines were verified using qRT-PCR. Gene expression differential analysis yielded a total of 146 common DEGs were obtained, including 21 upregulated and 125 downregulated DEGs. Among them, ten SADs were detected to be differentially expressed between tumor and normal tissues, including AXL, CYP2C19, CYP2C8, CYP2C9, CYP3A4, FGFR2, GMNN, PDGFRA, and TTK. GSEA analysis grouped them into three categories by function. The first category (CYP2C19, CYP2C8, CYP2C9 and CYP3A4) and second category (GMNN, TTK and EGER2) had the opposite roles in the enriched terms and pathways, while the third class (AXL and PDGFRA) has enrichment terms and pathways that intersect with those of the first and second categories. A ceRNA network associated with SADs was also constructed including 49 lncRNAs, 14 miRNAs, and 8 mRNAs. Three of these lncRNAs, SNHG7, GAS5 and HCP5, were found upregulated in HCC tissues and to be independent predictors in HCC patients. Significant correlations were found in expression between the prognostic lncRNAs and SADs. Ten SADs were systematically identified using expression data from HCC and normal tissues from TCGA and GEO datasets. GSEA analysis provided us with insight into the function of SADs. In the future, we will continue to explore the mechanisms of coordinated regulation of SADs-related prognostic lncRNAs and SADs at the ceRNA axis level and their potential functions in the development of HCC.

M6A regulator-mediated immune infiltration and methylation modification in hepatocellular carcinoma microenvironment and immunotherapy.

Introduction: Tremendous evidence indicates that N6-methyladenosine (m6A) epigenetic modification and m6A-related enzymes constitute a complex network, which jointly regulates prevailing pathological processes and various signaling pathways in humankind. Currently, the role of the m6A-mediated molecular regulatory network in hepatocellular carcinoma (HCC) remains elusive. Methods: We recruited expression and pathological files of 368 HCC patients from The Cancer Genome Atlas cohort. Four public datasets serve as external authentication sets for nearest template prediction (NTP) validation. The correlation between 35 regulators and their prognostic value was compared. Gene set variation analysis (GSVA) was used to explore the latent mechanism. Four independent algorithms (ssGSEA, xCell, MCP-counter, and TIMER) were used to calculate the ratio of tumor cells and non-tumor cells to evaluate the tumor immune microenvironment. The m6Ascore model was established by principal component analysis (PCA). Prediction of immunotherapy and potential drugs was performed using TIDE and SubMap. Results: A total of 35 m6A regulators were widely associated, most of which were risk factors for HCC patients. The m6A phenotypic-cluster revealed differences in regulator transcriptional level, gene mutation frequency, functional pathways, and immune cell infiltration abundance under distinct m6A patterns. As expected, the m6A gene cluster confirmed the aforementioned results. The m6Ascore model further found that patients in the high-m6Ascore group were associated with lower tumor purity, higher enrichment of immune and stromal cells, upregulation of metabolic pathways, lower expression of m6A regulators, and favorable outcomes. Low-m6Ascore patients were associated with adverse outcomes. Notably, low-m6Ascore patients might be more sensitive to anti-PD-L1 therapy. Conclusion: This study found that a classification model based on the m6A manner could predict HCC prognosis and response to immunotherapy for HCC patients, which might improve prognosis and contribute to clinical individualized decision-making.

Identification of the hsa_circ_0039466/miR-96-5p/FOXO1 regulatory network in hepatocellular carcinoma by whole-transcriptome analysis.

BackgroundCircular RNAs (circRNAs) are important for the process of cancer initiation and progression. However, the role of circRNAs in hepatocellular carcinoma (HCC) remains incompletely understood. Therefore, we further explored the expression network of circRNAs in HCC.MethodsWhole-transcriptome microarrays of HCC and paired normal liver tissues were obtained from the Gene Expression Omnibus (GEO) database. The structures of tumor-associated circRNAs were acquired by the Cancer-Specific CircRNA Database (CSCD). StarBase, circBank, and R packages (miRNAtap and multiMiR) were used to predict miRNA targets of circRNAs and downstream molecules of miRNAs. Expression relationships between RNA-RNA interactions were evaluated by data from The Cancer Genome Atlas (TCGA) and GEO databases. ClusterProfiler and DOSE R packages were used for pathway enrichment to explore the biological functions of potential target genes. Finally, a possible circRNA-miRNA-mRNA regulatory network was established based on the competing endogenous RNA (ceRNA) hypothesis.ResultsThe differentially expressed circRNAs (DECs) were matched with cancer-specific circRNAs in the CSCD database and a screening analysis was performed to obtain 5 cancer-specific circRNAs. A total of 329 possible target miRNAs for 5 cancer-specific circRNAs were predicted by the circBank database, and intersection analysis with differentially expressed miRNAs (DEmiRNAs) revealed that miR-6746-3p and miR-96-5p were the two most suitable miRNAs targets for our selected circRNAs. Further expression verification and prediction of base complementary paired binding sites demonstrated the hsa_circ_0039466/miR-96-5p axis as a crucial pathway in HCC. Next, we found that FOXO1 and LEPR were two potential downstream molecules of the hsa_circ_0039466/miR-96-5p axis through target gene prediction analysis, differential expression analysis, and intersection analysis. The pathway enrichment results suggested that the hsa_circ_0039466/miR-96-5p axis affects the progression and outcome of HCC through the insulin resistance pathway. Finally, through multi-data crossover analysis and data analysis of HCC samples further confirmed the existence of the hsa_circ_0039466/miR-96-5p/FOXO1 ceRNA regulatory network and that the axis was closely related to clinical stage.Conclusionshsa_circ_0039466 facilitates the expression of FOXO1 by sponging miR-96-5p, and ultimately inhibits tumor progression. These results provide a theoretical basis for further understanding of the gene expression network of HCC.

CircCCNB1 silencing acting as a miR-106b-5p sponge inhibited GPM6A expression to promote HCC progression by enhancing DYNC1I1 expression and activating the AKT/ERK signaling pathway.

Background: Circular RNAs (circRNAs), which generally act as microRNA (miRNA) sponges to competitively regulate the downstream target genes of miRNA, play an essential role in cancer biology. However, few studies have been reported on the role of circRNA based competitive endogenous RNA (ceRNA) network in hepatocellular carcinoma (HCC). Herein, we aimed to screen and establish the circRNA/miRNA/mRNA networks related to the prognosis and progression of HCC and further explore the underlying mechanisms of tumorigenesis.Methods: GEO datasets GSE97332, GSE108724, and GSE101728 were utilized to screen the differentially expressed circRNAs (DE-circRNAs), DE-miRNAs, and DEmRNAs between HCC and matched para-carcinoma tissues. After six RNA-RNA predictions and five intersections between DE-RNAs and predicted RNAs, the survival-related RNAs were screened by the ENCORI analysis tool. The ceRNA networks were constructed using Cytoscape software, based on two models of up-regulated circRNA/down-regulated miRNA/up-regulated mRNA and down-regulated circRNA/up-regulated miRNA/down-regulated mRNA. The qRT-PCR assay was utilized for detecting the RNA expression levels in HCC cells and tissues. The apoptosis, Edu, wound healing, and transwell assays were performed to evaluate the effect of miR-106b-5p productions on the proliferation, invasion, and metastasis of HCC cells. In addition, the clone formation, cell cycle, and nude mice xenograft tumor assays were used to investigate the influence of hsa_circ_0001495 (circCCNB1) silencing and overexpression on the proliferation of HCC cells in vitro and in vivo. Furthermore, the mechanism of downstream gene DYNC1I1 and AKT/ERK signaling pathway via the circCCNB1/miR-106b-5p/GPM6A network in regulating the cell cycle was also explored.Results: Twenty DE-circRNAs with a genomic length less than 2000bp, 11 survival-related DE-miRNAs, and 61 survival-related DE-mRNAs were screened out and used to construct five HCC related ceRNA networks. Then, the circCCNB1/miR-106b-5p/GPM6A network was randomly selected for subsequent experimental verification and mechanism exploration at in vitro and in vivo levels. The expression of circCCNB1 and GPM6A were significantly down-regulated in HCC cells and cancer tissues, while miR-106b-5p expression was up-regulated. After transfections, miR-106b-5p mimics notably enhanced the proliferation, invasion, and metastasis of HCC cells, while the opposite was seen with miR-105b-5p inhibitor. In addition, circCCNB1 silencing promoted the clone formation ability, the cell cycle G1-S transition, and the growth of xenograft tumors of HCC cells via GPM6A downregulation. Subsequently, under-expression of GPM6A increased DYNC1I1 expression and activated the phosphorylation of the AKT/ERK pathway to regulate the HCC cell cycle.Conclusions: We demonstrated that circCCNB1 silencing promoted cell proliferation and metastasis of HCC cells by weakening sponging of oncogenic miR-106b-5p to induce GPM6A underexpression. DYNC1I1 gene expression was up-regulated and further led to activation of the AKT/ERK signaling pathway.

The Role of Long Non-Coding RNA and microRNA Networks in Hepatocellular Carcinoma and Its Tumor Microenvironment.

Hepatocellular carcinoma (HCC) is a common liver malignancy with high morbidity and poor prognosis. Long non-coding RNAs (lncRNAs) are involved in crucial biological processes of tumorigenesis and progression, and play four major regulatory roles, namely signal, decoy, guide, and scaffold, to regulate gene expression. Through these processes, lncRNAs can target microRNAs (miRNAs) to form lncRNA and miRNA networks, which regulate cancer cell proliferation, metastasis, drug resistance, and the tumor microenvironment. Here, we summarize the multifaceted functions of lncRNA and miRNA networks in the pathogenesis of HCC, the potential use of diagnostic or prognostic biomarkers, and novel therapeutic targets in HCC. This review also highlights the regulatory effects of lncRNA and miRNA networks in the tumor microenvironment of HCC.

FUT11 is a target gene of HIF1α that promotes the progression of hepatocellular carcinoma.

Hypoxia promotes the progression of hepatocellular carcinoma. However, the hypoxia regulatory network in hepatocellular carcinoma is known to be limited. Thus, this study aimed to identify the crucial hypoxia-associated genes and to explore their effects and molecular mechanisms in hepatocellular carcinoma cells. FUT11 was first identified as a crucial hypoxia-associated gene through bioinformatics analysis. High FUT11 mRNA levels were positively correlated with poor clinical parameters. FUT11 knockdown under normoxia and hypoxia both decreased hepatocellular carcinoma cell proliferation, colony formation, migration, and invasion. HIF1α binds to the promoter of FUT11 and increases its transcription and co-expression with FUT11 in hepatocellular carcinoma tissues. Overexpression of FUT11 in HIF1α knockdown cells reversed the inhibitory effects of HIF1α suppression on hepatocellular carcinoma cell proliferation and mobility under hypoxia. Therefore, our findings indicate that FUT11 is a key target gene of HIF1α, which can promote the proliferation and mobility of hepatocellular carcinoma cells. FUT11 may be a novel and effective target for blocking the hypoxia response of hepatocellular carcinoma cells.

Identification of RNA binding protein interacting with circular RNA and hub candidate network for hepatocellular carcinoma.

The interaction between RNA binding protein (RBP) and circular RNA (circRNA) is important for the regulation of tumor progression. This study aimed to identify the RBP-circRNA network in hepatocellular carcinoma (HCC). 22 differentially expressed (DE) circRNAs in HCC were screened out from Gene Expression Omnibus (GEO) database and their binding RBPs were predicted by Circular RNA Interactome. Among them, 17 DERBPs, which were commonly dysregulated in HCC from The Clinical Proteomic Tumor Analysis Consortium (CPTAC), The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) projects, were utilized to construct the RBP-circRNA network. Through survival analysis, we found TARDBP was the only prognostic RBP for HCC in CPTAC, TCGA and ICGC projects. High expression of TARDBP was correlated with high grade, advanced stage and low macrophage infiltration of HCC. Additionally, gene set enrichment analysis showed that dysregulated TARDBP might be involved in some pathways related to the HCC pathogenesis. Therefore, a hub RBP-circRNA network was generated based on TARDBP. RNA immunoprecipitation and RNA pull-down confirmed that hsa_circ_0004913 binds to TARDBP. These findings indicated certain RBP-circRNA regulatory network potentially involved in the pathogenesis of HCC, which provides novel insights into the mechanism study and biomarker identification for HCC.

Integrated analysis of ceRNA network in hepatocellular carcinoma using bioinformatics analysis.

Background:Long noncoding RNAs (lncRNAs) can work as microRNA (miRNA) sponges through a competitive endogenous RNA (ceRNA) mechanism. LncRNAs and miRNAs are important components of competitive endogenous binding, and their expression imbalance in hepatocellular carcinoma (HCC) is closely related to tumor development, diagnosis, and prognosis. This study explored the potential impact of the ceRNA regulatory network in HCC on the prognosis of HCC patients.Methods:We thoroughly researched the differential expression profiles of lncRNAs, miRNAs, and mRNAs from 2 HCC Gene Expression Omnibus datasets (GSE98269 and GSE60502). Then, a dysregulated ceRNA network was constructed by bioinformatics. In addition, hub genes in the ceRNA network were screened by Cytoscape, these hub genes functional analysis was performed by gene set enrichment analysis, and the expression of these hub genes in tumors and their correlation with patient prognosis were verified with Gene Expression Profiling Interactive Analysis.Results:A ceRNA network was successfully constructed in this study including 4 differentially expressed (DE) lncRNAs, 7 DEmiRNAs, and 166 DEmRNAs. Importantly, 4 core genes (CCNA2, CHEK1, FOXM1, and MCM2) that were significantly associated with HCC prognosis were identified.Conclusions:Our study provides comprehensive and meaningful insights into HCC tumorigenesis and the underlying molecular mechanisms of ceRNA. Furthermore, the specific ceRNAs can be further used as potential therapeutic targets and prognostic biomarkers for HCC.

Comprehensive analysis of the competing endogenous circRNA-lncRNA-miRNA-mRNA network and identification of a novel potential biomarker for hepatocellular carcinoma.

Background: The competing endogenous RNAs (ceRNAs) hypothesis has received increasing attention as a novel explanation for tumorigenesis and cancer progression. However, there is still a lack of comprehensive analysis of the circular RNA (circRNA)-long non-coding RNA (lncRNA)-miRNA-mRNA ceRNA network in hepatocellular carcinoma (HCC).Methods: RNA sequencing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were employed to identify Differentially Expressed mRNAs (DEmRNAs), DElncRNAs, and DEcircRNAs between HCC and normal tissues. Candidates were identified to construct networks through a comprehensive bioinformatics strategy. A prognostic mRNA signature was established based on data from TCGA database and validated using data from the GEO database. Then, the HCC prognostic circRNA-lncRNA-miRNA-mRNA ceRNA network was established. Finally, the expression and function of an unexplored hub gene, deoxythymidylate kinase (DTYMK), was explored through data mining. The results were examined using clinical samples and in vitro experiments.Results: We constructed a prognostic signature with seven target mRNAs by univariate, lasso and multivariate Cox regression analyses, which yielded 1, 3 and 5-year AUC values of 0.797, 0.733 and 0.721, respectively, indicating its sensitivity and specificity in the prognosis of HCC. Moreover, the prognostic signature could be validated in GSE14520. The prognostic ceRNA network of 21 circRNAs, 15 lncRNAs, 5 miRNAs, and 7 mRNAs was established according to the targeting relationship between 7 hub mRNAs and other RNAs. Our experiment results indicated that the depletion of DTYMK inhibited liver cancer cell proliferation and invasion.Conclusions: The network revealed in this study may help comprehensively elucidate the ceRNA mechanisms driving HCC, and provide novel candidate biomarkers for evaluating the prognosis of HCC.

Identification of a Functional ceRNA Network to Explore Potential Biomarkers for Hepatocellular Carcinoma.

PurposeTo establish a novel circRNA–miRNA–mRNA network associated with the poor prognosis of hepatocellular carcinoma (HCC).Materials and MethodsQuantitative real-time PCR was used to verify the differentially expressed circRNA. Moreover, the competing endogenous RNA networks were established using bioinformatics methods. Meanwhile, the prognostic value and potential mechanism of ceRNA network in hepatocellular carcinoma (HCC) were analyzed.ResultsThis work found that circ_0130911 was highly expressed in HCC tissues and early recurring HCC. Further, we effectively constructed a ceRNA network. The ceRNA network regulated by circ_0130911 might influence the prognosis of HCC by regulating cell cycle-related pathways.ConclusionThe ceRNA network proposed here can be used as a novel biomarker for the prognosis of HCC, thereby providing new insights for the targeted therapy of HCC.

Identification and analysis of circRNA-miRNA-mRNA regulatory network in hepatocellular carcinoma.

This study was to identify important circRNA-miRNA-mRNA (ceRNAs) regulatory mechanisms in hepatocellular carcinoma (HCC). The circRNA dataset GSE97332 and miRNA dataset GSE57555 were used for analyses. Functional enrichment analysis for miRNA and target gene was conducted using cluster Profiler. Survival analysis was conducted through R package Survival. The ceRNAs and drug-gene interaction networks were constructed. The ceRNAs network contained five miRNAs including hsa-miR-25-3p, hsa-miR-3692-5p, hsa-miR-4270, hsa-miR-331-3p, and hsa-miR-125a-3p. Among the network, hsa-miR-25-3p targeted the most genes, hsa-miR-3692-5p and hsa-miR-4270 were targeted by more circRNAs than other miRNAs, hsa-circ-0034326 and hsa-circ-0011950 interacted with three miRNAs. Furthermore, target genes, including NRAS, ITGA5, SLC7A1, SEC14L2, SLC12A5, and SMAD2 were obtained in drug-gene interaction network. Survival analysis showed NRAS, ITGA5, SLC7A1, SEC14L2, SLC12A5, and SMAD2 were significantly associated with prognosis of HCC. NRAS, ITGA5, and SMAD2 were significantly enriched in proteoglycans in cancer. Moreover, hsa-circ-0034326 and hsa-circ-0011950 might function as ceRNAs to play key roles in HCC. Furthermore, miR-25-3p, miR-3692-5p, and miR-4270 might be significant for HCC development. NRAS, ITGA5, SEC14L2, SLC12A5, and SMAD2 might be prognostic factors for HCC patients via proteoglycans in cancer pathway. Taken together, the findings will provide novel insight into pathogenesis, selection of therapeutic targets and prognostic factors for HCC.

Investigation of the miRNA and mRNA Coexpression Network and Their Prognostic Value in Hepatocellular Carcinoma.

Purpose To identify pivotal differentially expressed miRNAs and genes and construct their regulatory network in hepatocellular carcinoma. Methods mRNA (GSE101728) and microRNA (GSE108724) microarray datasets were obtained from the NCBI Gene Expression Omnibus (GEO) database. Then, we identified the differentially expressed miRNAs and mRNAs. Sequentially, transcription factor enrichment and gene ontology (GO) enrichment analysis for miRNA were performed. Target genes of these differential miRNAs were obtained using packages in R language (R package multiMiR). After that, downregulated miRNAs were matched with target mRNAs which were upregulated, while upregulated miRNAs were paired with downregulated target mRNA using scripts written in Perl. An miRNA-mRNA network was constructed and visualized in Cytoscape software. For miRNAs in the network, survival analysis was performed. And for genes in the network, we did gene ontology (GO) and KEGG pathway enrichment analysis. Results A total of 35 miRNAs and 295 mRNAs were involved in the network. These differential genes were enriched in positive regulation of cell-cell adhesion, positive regulation of leukocyte cell-cell adhesion, and so on. Eight differentially expressed miRNAs were found to be associated with the OS of patients with HCC. Among which, miR-425 and miR-324 were upregulated while the other six, including miR-99a, miR-100, miR-125b, miR-145, miR-150, and miR-338, were downregulated. Conclusion In conclusion, these results can provide a potential research direction for further studies about the mechanisms of how miRNA affects malignant behavior in hepatocellular carcinoma.

Construction and analysis of macrophage infiltration related circRNA-miRNA-mRNA regulatory networks in hepatocellular carcinoma.

BackgroundMacrophage play a crucial role in regulating tumor progression. This study intended to investigate the circular RNA (circRNA) regulatory network associated with macrophage infiltration in hepatocellular carcinoma (HCC).MethodsThe immune cell fractions of HCC from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium were calculated by Estimation of the Proportion of Immune and Cancer cells algorithm. The differentially expressed mRNAs (DEmRNAs), microRNAs (DEmiRNAs) and circRNAs (DEcircRNAs) were identified from HCC and adjacent non-tumor cases of TCGA or Gene Expression Omnibus database. The DEmRNAs related to macrophage were selected by weighted gene co-expression network analysis and then utilized to generate the circRNA-miRNA-mRNA network. A hub circRNA regulatory network was established based on the co-expressed DEmiRNAs and DEmRNAs owning contrary correlation with the clinical characteristics, survival and macrophage infiltration level. A gene signature based on the DEmRNAs in hub network was also generated for further evaluation. The circRNA binding bite for miRNA was detected by luciferase assay.ResultsHigh macrophage fraction predicted good survival for HCC. A circRNA-miRNA-mRNA network was constructed by 27 macrophage related DEmRNAs, 21 DEmiRNAs, and 15 DEcircRNAs. Among this network, the expression of hsa-miR-139-5p was negatively correlated with CDCA8, KPNA2, PRC1 or TOP2A. Hsa-miR-139-5p low or targeted DEmRNA high expression was associated with low macrophage infiltration, high grade, advanced stage and poor prognosis of HCC. Additionally, the risk score generated by 4-DEmRNA signature could reflect the macrophage infiltration status and function as an independent prognostic factor for HCC. Finally, hsa_circ_0007456 acting on hsa-miR-139-5p related network was viewed as the hub circRNA regulatory network. Taken together, some circRNA regulatory networks may be associated with macrophage infiltration, which provides clues for mechanism study and therapeutic strategies of HCC.

Construction of a potential microRNA, transcription factor and mRNA regulatory network in hepatocellular carcinoma.

BackgroundHepatocellular carcinoma (HCC) is one of the most common malignancies worldwide and the third leading cause of cancer-related death. MicroRNAs and transcription factors (TFs) cooperate to regulate the same target gene, thus affecting the progression of HCC.MethodsDifferentially expressed miRNAs and mRNAs were screened. Functional enrichment analysis of these HCC-related mRNAs was performed, and a protein-protein interaction network was constructed. TFs that regulate these miRNAs and hub genes were also screened.ResultsTen differentially upregulated miRNAs and 5 differentially downregulated miRNAs were screened. Additionally, 183 downregulated mRNAs and 303 upregulated mRNAs that are potentially bound to these differentially expressed miRNAs were identified. The Kyoto Encyclopedia of Genes and Genomes (KEGG) results showed that the differentially expressed mRNAs were significantly enriched in pathways in cancer, the Wnt signaling pathway, and the Rap1 signaling pathway. Then, 220 TFs were identified for 5 candidate genes of the downregulated mRNAs, and 258 TFs were identified for 9 candidate genes of the upregulated mRNAs. Finally, the 9 upregulated hub genes were related to higher overall survival (OS) in the low-expression group, and 4/5 downregulated hub genes were related to higher OS in the high-expression group.ConclusionsThis study constructed a potential regulatory network between candidate molecules and that need to be further verified. These regulatory relationships are expected to clarify the new molecular mechanisms of the occurrence and development of HCC.