A novel microRNA signature predicts vascular invasion in hepatocellular carcinoma

Identification of a vascular invasion-related signature based on lncRNA pairs for predicting prognosis in hepatocellular carcinoma

OBJECTIVES

Most signatures are constructed on the basis of RNA or protein expression levels. The value of vascular invasion-related signatures based on lncRNA pairs, regardless of their specific expression level in hepatocellular carcinoma (HCC), is not yet clear.

METHODS

Vascular invasion-related differentially expressed lncRNA (DElncRNA) pairs were identified with a two-lncRNA combination strategy by using a novel modeling algorithm. Based on the optimal cutoff value of the ROC curve, patients with HCC were classified into high- and low-risk subgroups. We used KM survival analysis to evaluate the overall survival rate of patients in the high- and low-risk subgroups. The independent indicators of survival were identified using univariate and multivariate Cox analyses.

RESULTS

Five pairs of vascular invasion-related DElncRNAs were selected to develop a predictive model for HCC. High-risk subgroups were closely associated with aggressive clinicopathological characteristics and genes, chemotherapeutic sensitivity, and highly expressed immune checkpoint inhibitors.

CONCLUSIONS

We identified a signature composed of 5 pairs of vascular invasion-related lncRNAs that does not require absolute expression levels of lncRNAs and shows promising clinical predictive value for HCC prognosis. This predictive model provides deep insight into the value of vascular invasion-related lncRNAs in prognosis.

miR-210 promotes hepatocellular carcinoma progression by modulating macrophage autophagy through PI3K/AKT/mTOR signaling

BACKGROUND

Tumor-associated macrophages (TAMs) play an important role in tumor development. Increasing research suggests that miR-210 may promote the progression of tumor virulence, but whether its pro-carcinogenic effect in primary hepatocellular carcinoma (HCC) is via an action on M2 macrophages has not been examined.

METHODS

Differentiation of THP-1 monocytes into M2-polarized macrophages was induced with phorbol myristate acetate (PMA) and IL-4, IL-13. M2 macrophages were transfected with miR-210 mimics or miR-210 inhibitors. Flow cytometry was used to identify macrophage-related markers and apoptosis levels. The autophagy level of M2 macrophages, expression of PI3K/AKT/mTOR signaling pathway-related mRNAs and protein were detected by qRT-PCR and Western blot. HepG2 and MHCC-97H HCC cell lines were cultured with M2 macrophages conditioned medium to explore the effects of M2 macrophage-derived miR-210 on the proliferation, migration, invasion and apoptosis of HCC cells.

RESULTS

qRT-PCR showed increased expression of miR-210 in M2 macrophages. Autophagy-related gene and protein expression was enhanced in M2 macrophages transfected with miR-210 mimics, while apoptosis-related proteins were decreased. MDC staining and transmission electron microscopy observed the accumulation of MDC-labeled vesicles and autophagosomes in M2 macrophages in the miR-210 mimic group. The expression of PI3K/AKT/mTOR signaling pathway in M2 macrophages was reduced in miR-210 mimic group. HCC cells co-cultured with M2 macrophages transfected with miR-210 mimics exhibited enhanced proliferation and invasive ability as compared to the control group, while apoptosis levels were reduced. Moreover, promoting or inhibiting autophagy could enhance or abolish the above observed biological effects, respectively.

CONCLUSIONS

miR-210 can promote autophagy of M2 macrophages via PI3K/AKT/mTOR signaling pathway. M2 macrophage-derived miR-210 promotes the malignant progression of HCC via autophagy, suggesting that macrophage autophagy may serve as a new therapeutic target for HCC, and targeting miR-210 may reset the effect of M2 macrophages on HCC.

GBA1-dependent membrane glucosylceramide reprogramming promotes liver cancer metastasis via activation of the Wnt/β-catenin signalling pathway

The effect of glucosylceramide (GlcCer) reprogramming on liver cancer metastasis remains poorly understood. In this study, we demonstrated that the protein expression of GBA1, which catalyses the conversion of GlcCer to ceramide, was downregulated in liver cancer tissue. A clinical relevance analysis revealed that low expression of GBA1 was associated with the metastatic potential of liver cancer cells. Furthermore, loss- and gain-of-function studies confirmed that low expression of GBA1 promoted metastasis of liver cancer both in vitro and in vivo. Mechanistic studies indicated that low expression of GBA1 enhanced the metastatic ability of liver cancer by promoting the epithelial-mesenchymal transition (EMT), in which Wnt signalling pathway is involved. In the plasma membrane (PM), GBA1-dependent GlcCer reprogramming increased LRP6 location in the PM leading to an interaction between GlcCer and LRP6, subsequently promoting LRP6 phosphorylation at Ser1490, and finally activating the Wnt/β-catenin signalling pathway. To our knowledge, this is the first time to be found that GlcCer interacted with a protein. In addition, the results of mass spectrometry indicated that GlcCer d18:1/18:0 was the most notably increased studied species in the PM when GBA1 was downregulated, suggesting that GlcCer d18:1/18:0 may be the major functional lipid that promotes GBA1-dependent liver cancer metastasis. Thus, GBA1-mediated GlcCer reprogramming in the PM promotes metastasis of liver cancer via activation of the Wnt/β-catenin signalling pathway, upregulation of GBA1 may be a potential therapeutic strategy to combat liver cancer metastasis.

A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion

BACKGROUND

Hepatocellular carcinoma (HCC) is prevalent worldwide with a high mortality rate. Prognosis prediction is crucial for improving HCC patient outcomes, but effective tools are still lacking. Characteristics related to vascular invasion (VI), an important process involved in HCC recurrence and metastasis, may provide ideas on prognosis prediction.

METHODS

Tools, including R 4.0.3, Funrich version 3, Cytoscape 3.8.2, STRING 11.5, Venny 2.1.0, and GEPIA 2, were used to perform bioinformatic analyses. The VI-related microRNAs (miRNAs) were identified using Gene Expression Omnibus HCC miRNA dataset GSE67140, containing 81 samples of HCC with VI and 91 samples of HCC without VI. After further evaluated the identified miRNAs based on The Cancer Genome Atlas database, a prognostic model was constructed via Cox regression analysis. The miRNAs in this model were also verified in HCC patients. Moreover, a nomogram was developed by integrating risk score from the prognostic model with clinicopathological parameters. Finally, a potential miRNA-mRNA network related to VI was established through weighted gene co-expression network analysis of HCC mRNA dataset GSE20017, containing 40 samples of HCC with VI and 95 samples of HCC without VI.

RESULTS

A prognostic model of 5 VI-related miRNAs (hsa-miR-126-3p, hsa-miR-148a-3p, hsa-miR-15a-5p, hsa-miR-30a-5p, hsa-miR-199a-5p) was constructed. The area under receiver operating characteristic curve was 0.709 in predicting 5-year survival rate, with a sensitivity of 0.74 and a specificity of 0.63. The nomogram containing risk score could also predict prognosis. Moreover, a VI-related miRNA-mRNA network covering 4 miRNAs and 15 mRNAs was established.

CONCLUSION

The prognostic model and nomogram might be potential tools in HCC management, and the VI-related miRNA-mRNA network gave insights into how VI was developed.

m5C RNA methyltransferase-related gene NSUN4 stimulates malignant progression of hepatocellular carcinoma and can be a prognostic marker

Hepatocellular carcinoma (HCC) is a cancer with relatively high mortality, yet little attention has been devoted for related prognostic biomarkers. This study analyzed differential expression of m5C RNA methyltransferase-related genes in normal samples and tumors samples in TCGA-LIHC using Wilcoxon test. K-means consensus clustering analysis was implemented to subdivide samples. Independent prognostic factors were screened by univariate and multivariate Cox regression analyses. KEGG pathway enrichment analysis was performed on the screened independent prognostic factor using GSEA tools. qPCR was conducted to test mRNA expression of key m5C RNA methyltransferase-related genes in tissues and cells. There were 7 m5C RNA methyltransferase-related genes (NOP2, NSUN4, etc.) differentially expressed in HCC tumor tissues. HCC samples were classified into 3 subgroups through clustering analysis according to the expression mode of m5C RNA methyltransferase-related genes. It was also discovered that patients in different subgroups presented significant differences in survival rate and distribution of grade. Additionally, NOP2, NSUN4 and NSUN5 expression notable varied in different grades. Through regression analyses combined with various clinical pathological factors, it was displayed that NSUN4 could work as an independent prognostic factor. KEGG analysis showed that NSUN4 mainly enriched in signaling pathways involved in ADHERENS JUNCTION, RNA DEGRADATION, MTOR SIGNALING PATHWAY, COMPLEMENT and COAGULATION CASCADES. As examined by qPCR, NSUN4 was conspicuously upregulated in HCC patient's tissues and cells. Altogether, our study preliminarily developed a novel biomarker that could be independently used in prognosis of HCC, which may provide a new direction for the study of related molecular mechanism or treatment regimen.

Molecular classification of hepatocellular carcinoma: prognostic importance and clinical applications

Hepatocellular carcinoma (HCC) is a lethal human malignancy with a very low overall and long-term survival rate. Poor prognostic outcomes are predominantly associated with HCC due to a huge landscape of heterogeneity found in the deadliest disease. However, molecular subtyping of HCC has significantly improved the knowledge of the underlying mechanisms that contribute towards the heterogeneity and progression of the disease. In this review, we have extensively summarized the current information available about molecular classification of HCC. This review can be of great significance for providing the insight information needed for development of novel, efficient and personalized therapeutic options for the treatment of HCC patients globally.

Risk Factors and Prevention of Viral Hepatitis-Related Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common cancer in the world, and its incidence is increasing yearly. Hepatitis B virus (HBV) infection and hepatitis C virus (HCV) infection are important causes of HCC. Liver cirrhosis, age, sex, smoking and drinking, and metabolic risk factors will increase the risk of cancer in HBV/HCV patients. And viral load, APRI, FIB-4, and liver stiffness can all predict the risk of HCC in patients with viral infection. In addition, effective prevention strategies are essential in reducing the risk of HCC. The prevention of HCC involves mainly tertiary prevention strategies, while the primary prevention is based on standardized vaccine injections to prevent the occurrence of HBV/HCV. Eliminating the route of transmission and vaccination will lead to a decrease in the incidence of HCC. Secondary prevention involves effective antiviral treatment of HBV/HCV to prevent the disease from progressing to HCC, and tertiary prevention is actively treating HCC to prevent its recurrence.

HCG18 Participates in Vascular Invasion of Hepatocellular Carcinoma by Regulating Macrophages and Tumor Stem Cells

Objectives

To identify key genes involved in vascular invasion in hepatocellular carcinoma (HCC), to describe their regulatory mechanisms, and to explore the immune microenvironment of HCC.

Methodology

In this study, the genome, transcriptome, and immune microenvironment of HCC were assessed by using multi-platform data from The Cancer Genome Atlas (n = 373) and GEO data (GSE149614). The key regulatory networks, transcription factors and core genes related to vascular invasion and prognosis were explored based on the CE mechanism. Survival analysis and gene set enrichment were used to explore pathways related to vascular invasion. Combined with single-cell transcriptome data, the distribution of core gene expression in various cells was observed. Cellular communication analysis was used to identify key cells associated with vascular invasion. Pseudo-temporal locus analysis was used to explore the regulation of core genes in key cell phenotypes. The influence of core genes on current immune checkpoint therapy was evaluated and correlations with tumor stem cell scores were explored.

Results

We obtained a network containing 1,249 pairs of CE regulatory relationships, including 579 differential proteins, 28 non-coding RNAs, and 37 miRNAs. Three key transcription factors, ILF2, YBX1, and HMGA1, were identified, all regulated by HCG18 lncRNA. ScRNAseq showed that HCG18 co-localized with macrophages and stem cells. CIBERSORTx assessed 22 types of immune cells in HCC and found that HCG18 was positively correlated with M0 macrophages, while being negatively correlated with M1 and M2 macrophages, monocytes, and dendritic cells. Cluster analysis based on patient prognosis suggested that regulating phenotypic transformation of macrophages could be an effective intervention for treating HCC. At the same time, higher expression of HCG18, HMGA1, ILF2, and YBX1 was associated with a higher stem cell score and less tumor differentiation. Pan cancer analysis indicated that high expression of HCG18 implies high sensitivity to immune checkpoint therapy.

Conclusion

HCG18 participates in vascular invasion of HCC by regulating macrophages and tumor stem cells through three key transcription factors, YBX1, ILF2, and HMGA1.

Construction of a ceRNA Network and a Prognostic lncRNA Signature associated with Vascular Invasion in Hepatocellular Carcinoma based on Weighted Gene Co-Expression Network Analysis

Background: Understanding risk factors for vascular invasion (VI) is crucial for assessing the risk of recurrence and overall prognosis of hepatocellular carcinoma (HCC). This study aimed to construct a prognostic long non-coding RNA (lncRNA) signature and a ceRNA Network associated with vascular invasion in HCC. Methods: Differentially expressed genes (DEGs) of HCC patients associated with VI were identified by analyzing data from TCGA. Weighted gene co-expression network analysis (WGCNA) was used to identify associations between gene expression modules and clinical features. A VI-related prognostic lncRNA signature was then established using univariate, LASSO and multivariate Cox proportional hazards regression analyses. Based on the hub modules identified by the WGCNA, we constructed a VI-related lncRNA-miRNA-mRNA ceRNA network and screened hub lncRNAs for further research. Finally, we conducted in vitro and in vivo experiments to determine the biological roles of the identified hub gene BBOX1-AS1. Results: The key module related to VI and OS was identified using WGCNA, after which a prognostic model consisting of eight lncRNAs was established, and verified using time-dependent receiver operating characteristic (ROC) curve analysis. BBOX1-AS1 was confirmed to be highly expressed in HCC tissues, and its expression was significantly correlated with a poor prognosis. Silencing BBOX1-AS1 in vitro significantly suppressed the proliferation, migration and invasion of HCC cells. In vivo experiments demonstrated that knocking down of BBOX1-AS1 could result in significant decrease of tumor volume and tumor weight. Conclusions: The VI-related lncRNA signature established in this study can be used to predict the clinical outcomes of HCC patients. In addition, we constructed a VI-related lncRNA-miRNA-mRNA ceRNA network and demonstrated that BBOX1-AS1 might be a novel biomarker associated with VI in HCC.

Construction of liver hepatocellular carcinoma-specific lncRNA-miRNA-mRNA network based on bioinformatics analysis

Liver hepatocellular carcinoma (LIHC) is one of the major causes of cancer-related death worldwide with increasing incidences, however there are very few studies about the underlying mechanisms and pathways in the development of LIHC. We obtained LIHC samples from The Cancer Genome Atlas (TCGA) to screen differentially expressed mRNAs, lncRNAs, miRNAs and driver mutations. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses and protein–protein interaction (PPI) network were performed. Moreover, we constructed a competing endogenous lncRNAs-miRNAs-mRNAs network. Finally, cox proportional hazards regression analysis was used to identify important prognostic differentially expressed genes. Total of 1284 mRNAs, 123 lncRNAs, 47 miRNAs were identified within different tissues of LIHC patients. GO analysis indicated that upregulated and downregulated differentially expressed mRNAs (DEmRNAs) were mainly associated with cell division, DNA replication, mitotic sister chromatid segregation and complement activation respectively. Meanwhile, KEGG terms revealed that upregulated and downregulated DEmRNAs were primarily involved in DNA replication, Metabolic pathways, cell cycle and Metabolic pathways, chemical carcinogenesis, retinol metabolism pathway respectively. Among the DERNAs, 542 lncRNAs-miRNAs-mRNAs pairs were predicted to construct a ceRNA regulatory network including 35 DElncRNAs, 26 DEmiRNAs and 112 DEmRNAs. In the Kaplan‐Meier analysis, total of 43 mRNAs, 14 lncRNAs and 3 miRNAs were screened out to be significantly correlated with overall survival of LIHC. The mutation signatures were analyzed and its correlation with immune infiltrates were evaluated using the TIMER in LIHC. Among the mutation genes, TTN mutation is often associated with poor immune infiltration and a worse prognosis in LIHC. This work conducted a novel lncRNAs-miRNAs-mRNAs network and mutation signatures for finding potential molecular mechanisms underlying the development of LIHC. The biomarkers also can be used for predicting prognosis of LIHC.

Prognostic Cancer Gene Expression Signatures: Current Status and Challenges

Current staging systems of cancer are mainly based on the anatomical extent of disease. They need refinement by biological parameters to improve stratification of patients for tumor therapy or surveillance strategies. Thanks to developments in genomic, transcriptomic, and big-data technologies, we are now able to explore molecular characteristics of tumors in detail and determine their clinical relevance. This has led to numerous prognostic and predictive gene expression signatures that have the potential to establish a classification of tumor subgroups by biological determinants. However, only a few gene signatures have reached the stage of clinical implementation so far. In this review article, we summarize the current status, and present and future challenges of prognostic gene signatures in three relevant cancer entities: breast cancer, colorectal cancer, and hepatocellular carcinoma.

Notch Signaling Regulation in HCC: From Hepatitis Virus to Non-Coding RNAs

The Notch family includes evolutionary conserved genes that encode for single-pass transmembrane receptors involved in stem cell maintenance, development and cell fate determination of many cell lineages. Upon activation by different ligands, and depending on the cell type, Notch signaling plays pleomorphic roles in hepatocellular carcinoma (HCC) affecting neoplastic growth, invasion capability and stem like properties. A specific knowledge of the deregulated expression of each Notch receptor and ligand, coupled with resultant phenotypic changes, is still lacking in HCC. Therefore, while interfering with Notch signaling might represent a promising therapeutic approach, the complexity of Notch/ligands interactions and the variable consequences of their modulations raises concerns when performed in undefined molecular background. The gamma-secretase inhibitors (GSIs), representing the most utilized approach for Notch inhibition in clinical trials, are characterized by important adverse effects due to the non-specific nature of GSIs themselves and to the lack of molecular criteria guiding patient selection. In this review, we briefly summarize the mechanisms involved in Notch pathway activation in HCC supporting the development of alternatives to the γ-secretase pan-inhibitor for HCC therapy.

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.

Hypoxia-Induced Placenta-Specific microRNA (miR-512-3p) Promotes Hepatocellular Carcinoma Progression by Targeting Large Tumor Suppressor Kinase 2

Background

Sustained proliferation and active metastasis are hallmarks of cancer, and they pose major challenges to the development of treatments and a cure for hepatocellular carcinoma (HCC). Thus, the mechanisms of proliferation, migration, and invasion of cancer cells need to be investigated. Many studies indicate that dysregulation of microRNA plays important roles in the progression of HCC, but the role of placenta-specific microRNA (miR-512-3p) in HCC has not been systematically investigated.

Purpose

In the current study, the expression, biological function, and mechanisms of miR-512-3p involvement in HCC were investigated.

Methods

Real-time quantitative polymerase chain reaction assays were conducted to determine miR-512-3p levels in HCC tissues and cell lines. The StarBase V3.0 online platform was used to compare miR-512-3p levels in HCC tissues with TCGA data and to identify potential miR-512-3p target genes. Associations between miR-512-3p and clinicopathological characteristics were analyzed statistically. MTT, ethynyl deoxyuridine, and transwell assays were performed to assess cell viability, proliferation, migration, and invasion. The luciferase reporter gene assay was used to verify target genes. Recuse assays were performed to confirm whether large tumor suppressor kinase 2 (LATS2) participated in the regulatory effects of miR-512-3p on HCC cell proliferation and motility, and whether miR-512-3p mediated the tumor-promoting effects of hypoxia.

Results

miR-512-3p was upregulated in HCC and it was associated with worse survival and unfavorable clinicopathological characteristics. Functional assays indicated that miR-512-3p contributed to HCC cell proliferation, migration, and invasion. Mechanistically, LATS2—a downstream target of miR-512-3p—mediated the tumor-promoting effects of miR-512-3p in HCC. Hypoxia could elevate miR-512-3p levels in HCC cells, and miR-512-3p partially mediated the tumor-promoting effects of hypoxia.

Conclusion

Hypoxia-induced miR-512-3p contributes to HCC cell proliferation, migration, and invasion by targeting LATS2 and inhibiting the Hippo/yes-associated protein 1 pathways.

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

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

CircRNA-104718 acts as competing endogenous RNA and promotes hepatocellular carcinoma progression through microRNA-218-5p/TXNDC5 signaling pathway

Accumulating evidences indicate that circular RNAs (circRNAs) play a vital role in diverse cancer biology. However, the contributions of circRNAs to hepatocellular carcinoma (HCC) and their underlying mechanism remain largely unknown. The present study aims at investigating the role of circRNA-104718 in HCC progression, which has been observed to be significantly up-regulated in HCC tissues. We found that, higher expression of circRNA-104718 also leds to a poor prognosis in HCC patients. Using luciferase binding assays and RNA immunoprecipitation studies, we identified circRNA-104718 is physically associated and co-expressed with microRNA (miR)-218-5p in HCC. Mechanistically, we demonstrated that circRNA-104718 functions as a competing endogenous RNAs (ceRNAs) and competes with thioredoxin domain-containing protein 5 (TXNDC5) mRNA and directly binds to miR-218-5p. Functionally, we found that ectopically expressed circRNA-104718 accelerated cell proliferation, migration, invasion, and inhibited apoptosis. In vivo studies on a nude mice model showed that circRNA-104718 overexpression could increase the tumor size and the rate of metastasis. Silencing of circRNA-104718 could decrease both the tumor size and metastasis significantly. Conversely, we also observed overexpression of miR-218-5p could in turn decrease the proliferation, migration, invasion, and increase apoptosis. Furthermore, circRNA-104718 could relieve the suppression of miR-218-5p target TXNDC5 and thereby cause an inhibition of miR’s functions. In summary, our results indicate that circRNA-104718 acts as a ceRNA and promotes HCC progression through the targeting of miR-218-5p/TXNDC5 signaling pathway. Thus, we propose that circRNA-104718 would be a promising target for HCC diagnosis and therapy.