Gene Expression In Hepatocellular Carcinoma Research Articles

Identification of CFHR4 as a Potential Prognosis Biomarker Associated With lmmune Infiltrates in Hepatocellular Carcinoma.

BackgroundComplement factor H-related 4 (CFHR4) is a protein-coding gene that plays an essential role in multiple diseases. However, the prognostic value of CFHR4 in hepatocellular carcinoma (HCC) is unknown.MethodsUsing multiple databases, we investigated CFHR4 expression levels in HCC and multiple cancers. The relationship between CFHR4 expression levels and clinicopathological variables was further analyzed. Various potential biological functions and regulatory pathways of CFHR4 in HCC were identified by performing a Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA). Single-sample gene set enrichment analysis (ssGSEA) was performed to confirm the correlation between CFHR4 expression and immune cell infiltration. The correlations between CFHR4 expression levels in HCC and N6-methyladenosine (m6A) modifications and the competing endogenous RNA (ceRNA) regulatory networks were confirmed in TCGA cohort.ResultsCFHR4 expression levels were significantly decreased in HCC tissues. Low CFHR4 expression in HCC tissues was significantly correlated with the patients’ sex, race, age, TNM stage, pathological stage, tumor status, residual tumor, histologic grade and alpha fetal protein (AFP) level. GO and KEGG analyses revealed that differentially expressed genes related to CFHR4 may be involved in the synaptic membrane, transmembrane transporter complex, gated channel activity, chemical carcinogenesis, retinol metabolism, calcium signaling pathway, PPAR signaling pathway, insulin and gastric acid secretion. GSEA revealed that the FCGR-activated reaction, PLK1 pathway, ATR pathway, MCM pathway, cascade reactions of PI3K and FGFR1, reactant-mediated MAPK activation and FOXM1 pathway were significantly enriched in HCC with low CFHR4 expression. Moreover, CFHR4 expression was inversely correlated the levels of infiltrating Th2 cells, NK CD56bright cells and Tfh cells. In contrast, we observed positive correlations with the levels of infiltrating DCs, neutrophils, Th17 cells and mast cells. CFHR4 expression showed a strong correlation with various immunomarker groups in HCC. In addition, high CFHR4 expression significantly prolonged the overall survival (OS), disease-specific survival (DSS) and progression-free interval (PFI). We observed a substantial correlation between the expression of CFHR4 and multiple N6-methyladenosine genes in HCC and constructed potential CFHR4-related ceRNA regulatory networks.ConclusionsCFHR4 might be a potential therapeutic target for improving the HCC prognosis and is closely related to immune cell infiltration.

Data mining of key genes expression in hepatocellular carcinoma: novel potential biomarkers of diagnosis prognosis or progression

Hepatocellular carcinoma (HCC) is one of the main cancer-related causes of death worldwide. The study aimed to perform a data mining analysis of the expression and regulatory role of key genes in HCC to reveal novel potential biomarkers of diagnosis prognosis, or progression since their availability is still almost lacking. Starting from data of our cohort of patients (HCV-positive HCC pts undergoing liver transplantation (LR, n = 10) and donors (LD, n = 14), deeply analyzed previously, in which apelin, osteopontin, osteoprotegerin, NOTCH-1, CASP-3, Bcl-2, BAX, PTX3, and NPTX2 were analyzed, we applied statistical analysis and in-silico tools (Gene Expression Profiling Interactive Analysis, HCCDB database and GeneMania, UALCAN) to screen and identify the key genes. Firstly, we performed a stepwise regression analysis using our mRNA-datasets which revealed that higher expression levels of apelin and osteopontin were positively associated with the HCC and identified that the most consistently differentially expressed gene across multiple HCC expression datasets was only OPN. This comprehensive strategy of data mining evidenced that OPN might have a potential function as an important tumor marker-driven oncogenesis being associated with poor prognosis of HCC patients.

MicroRNA-378a-3p regulates the progression of hepatocellular carcinoma by regulating PD-L1 and STAT3

ABSTRACT Programmed death ligand 1 (PD-L1) plays an essential role in the development or progression of hepatocellular carcinoma (HCC). MicroRNAs (miRNAs) are small RNA molecules that regulate gene expression during normal and pathophysiological events. Here, we explored the functions and detailed mechanisms of miR-378a-3p and PD-L1 in HCC progression. First, miR-378a-3p was selected by analyzing miRNA levels in two HCC Gene Expression Omnibus datasets. We found that miR-378a-3p levels exhibited a downward trend in HCC and were negatively correlated with PD-L1 levels. Additionally, a dual luciferase assay predicted that miR-378a-3p directly targets PD-L1. Moreover, the transfection of miR-378a-3p mimics into Li-7 and HuH-7 cells effectively decreased the PD-L1 mRNA and protein expression levels, and inhibited Treg differentiation in co-culture models by modulating the expression levels of certain cytokines. Furthermore, the overexpression of miR-378a-3p hindered cell proliferation and migration but facilitated apoptosis by repressing STAT3 signaling in HCC cells. In conclusion, miR-378a-3p appears to inhibit HCC tumorigenesis by regulating PD-L1 and STAT3 levels. Thus, miR-378a-3p may be a potential target for HCC therapy.

Identification of circadian clock genes as regulators of immune infiltration in Hepatocellular Carcinoma.

Background: Multiple studies have reported that the immune system is under the control of a circadian clock, especially in cancers, but how circadian clock genes shape tumor immune cell infiltration in hepatocellular carcinoma (HCC) remains unclear.Methods: The rhythmicity of circadian clock genes was investigated using the GETx database. The expression and methylation level of circadian clock genes in HCC and paracancerous was evaluated using the GETx and TCGA databases. The differential expression of circadian clock genes in HCC was analyzed using the “limma” package of the R 4.0.4 software. The prognosis of each circadian clock gene was accessed by Kaplan-Meier survival analysis and Cox proportional hazards regression analysis. Quantitative real-time PCR and immunohistochemistry (IHC) was carried out to confirm the results. The relationship between circadian rhythm and immune infiltration in HCC was evaluated using the TIMER database and the CIBERSORT algorithm.Results: In addition to RORA, RORB, and ARNTL2, there was a rhythmic expression of other circadian clock genes in liver tissue. The correlation between the expression of circadian clock genes differed when comparing HCC and liver tissue. HCC patients who express low levels of PER-1and CRY2 had a poor overall survival (OS). In contrast, patients with higher expression of NPAS2 had a poor prognosis. In HCC, the expression of the PER-1, CRY2, and NPAS2 genes was closely related to immune infiltration.Conclusion: Our study indicated the disruption of the expression of circadian clock-regulated genes in HCC and identified PER-1, CRY2, and NPAS2 as independent predictors of survival. These genes may be applied as candidate molecular targets for diagnosis and therapy of HCC.

The effect of key DNA methylation in different regions on gene expression in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a common cancer with high morbidity and mortality. As we all know, the alteration of DNA methylation has a crucial impact on the occurrence of HCC. However, the mechanism of the effect of DNA methylation in different regions on gene expression is still unclear. Here, by computing and analyzing the distribution of differential methylation in 12 different regions in HCC tissues and adjacent normal tissues, not only the hypermethylation of CpG islands and global hypomethylation were found, but also a stable distribution pattern of differential methylation in HCC was found. Then the correlations between DNA methylations in different regions and gene expressions were calculated, and the diversity of correlations in different regions was determined. The key genes of differential methylation and differential expression related to the survival of HCC patients were obtained by using Cox regression analysis, a four-gene prognostic risk scoring model was constructed, and the prognostic performance was well verified. The regions of the differentially methylated CpG sites corresponding to the four key genes were located and their influences on the expression were analyzed. The results indicate that the promoter, first exon, 5'UTR, sixth exon, N_Shore, and S_Shore hypomethylation promotes the expression of key oncogenes, which together lead to the occurrence of HCC. These results might help to study the role of DNA methylation in HCC and provide potential biomarkers for the diagnosis of HCC.

CDK1, CCNB1 and NDC80 are associated with prognosis and progression of hepatitis B virus-associated hepatocellular carcinoma: a bioinformatic analysis

To identify the key genes involved in the transformation of hepatitis B virus (HBV) into hepatocellular carcinoma (HCC) and explore the underlying molecular mechanisms. We analyzed the mRNA microarray data of 119 HBV-related HCC tissues and 252 HBV-related non-tumor tissues in GSE55092, GSE84044 and GSE121248 from the GEO database, and the "sva" R package was used to remove the batch effects. Integration analysis was performed to identify the differentially expressed genes (DEGs) in HBV-related liver cancer and liver tissues with HBV infection. The significant DEGs were functionally annotated using GO and KEGG analyses, and the most important modules and hub genes were explored with STRING analysis. Kaplan-Meier and Oncomine databases were used to verify the HCC gene expression data in the TCGA database to explore the correlations of the hub genes with the occurrence, progression and prognosis of HCC. We also examined the expressions of the hub genes in 17 pairs of surgical specimens of HCC and adjacent tissues using RT-qPCR. We identified a total of 121 DEGs and 3 genetic markers in HCC (P < 0.01). These DEGs included cyclin1 (CDK1), cyclin B1 (CCNB1), and nuclear division cycle 80 (NDC80), which participated in cell cycle, pyrimidine metabolism and DNA replication and were highly correlated (P < 0.05). Analysis of the UALCAN database confirmed high expressions of these 3 genes in HCC tissues, which were correlated with a low survival rate of the patients, as shown by Kaplan-Meier analysis of the prognostic data from the UALCAN database. CDK1, CCNB1 and NDC80 were all correlated with the clinical grading of HCC (P < 0.05). The results of RT-qPCR on the surgical specimens verified significantly higher expressions of CDK1, CCNB1 and NDC80 mRNA in HCC tissues than in the adjacent tissues. CDK1, CCNB1 and NDC80 genes can be used as prognostic markers of HBV-related HCC and may serve as potential targets in preclinical studies and clinical treatment of HCC.

Integrated Transcriptomic Analysis Revealed Hub Genes and Pathways Involved in Sorafenib Resistance in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC), a high mortality malignancy, has become a worldwide public health concern. Acquired resistance to the multikinase inhibitor sorafenib challenges its clinical efficacy and the survival benefits it provides to patients with advanced HCC. This study aimed to identify critical genes and pathways associated with sorafenib resistance in HCC using integrated bioinformatics analysis. Differentially expressed genes (DEGs) were identified using four HCC gene expression profiles (including 34 sorafenib-resistant and 29 sorafenib-sensitive samples) based on the robust rank aggregation method and R software. Gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING), and small molecules reversing sorafenib resistance were searched for using the connectivity map (CMAP) database. Pearson correlation and survival analyses of hub genes were performed using cBioPortal and Gene Expression Profiling and Interactive Analysis (GEPIA). Finally, the expression levels of hub genes in sorafenib-resistant HCC cells were verified using quantitative polymerase chain reaction (q-PCR). A total of 165 integrated DEGs (66 upregulated and 99 downregulated in sorafenib resistant samples compared sorafenib sensitive ones) primarily enriched in negative regulation of endopeptidase activity, extracellular exosome, and protease binding were identified. Some pathways were commonly shared between the integrated DEGs. Seven promising therapeutic agents and 13 hub genes were identified. These findings provide a strategy and theoretical basis for overcoming sorafenib resistance in HCC patients.

Correlation of N-Ras Gene Expression in Hepatocellular Carcinoma with Color Doppler Ultrasound Findings

Objective: This study aims to study the N-ras gene expression in hepatocellular carcinoma (HCC) and its correlation with color Doppler imaging manifestations. Methods: The tumors of 145 HCC patients were evaluated via color Doppler ultrasonography before operation and N-ras level in tissue specimens obtained after operation were detected via RT-PCR, Western blotting and immunohistochemistry along with correlation analysis. Results: N-ras mRNA in para-carcinoma tissues was significantly reduced compared with carcinoma tissues (P &lt; 0.05). Western blotting and immunohistochemistry showed a significant difference of N-ras protein level between para-carcinoma tissues and carcinoma tissues (P &lt; 0.05). Moreover, N-ras gene expression was siginificantly correlated with the number of tumor nodules, the integrity of tumor capsule, vascular invasion, blood flow classification, RI (P &lt; 0.05). Conclusion: Our data demonstrate the elevation of N-ras in the carcinoma tissues of HCC patients and its correlation with color Doppler imaging manifestations, which lays foundation for the development of the diagnosis of hepatocellular carcinoma.

Isotretinoin and Thalidomide Down-Regulate c-MYC Gene Expression and Modify Proteins Associated with Cancer in Hepatic Cells.

Hepatocellular carcinoma (HCC) is the most common form of liver cancer. The number of cases is increasing and the trend for the next few years is not encouraging. HCC is usually detected in the advanced stages of the disease, and pharmacological therapies are not entirely effective. For this reason, it is necessary to search for new therapeutic options. The objective of this work was to evaluate the effect of the drugs isotretinoin and thalidomide on c-MYC expression and cancer-related proteins in an HCC cellular model. The expression of c-MYC was measured using RT-qPCR and western blot assays. In addition, luciferase activity assays were performed for the c-MYC promoters P1 and P2 using recombinant plasmids. Dose-response-time analyses were performed for isotretinoin or thalidomide in cells transfected with the c-MYC promoters. Finally, a proteome profile analysis of cells exposed to these two drugs was performed and the results were validated by western blot. We demonstrated that in HepG2 cells, isotretinoin and thalidomide reduced c-MYC mRNA expression levels, but this decrease in expression was linked to the regulation of P1 and P1-P2 c-MYC promoter activity in isotretinoin only. Thalidomide did not exert any effect on c-MYC promoters. Also, isotretinoin and thalidomide were capable of inducing and repressing proteins associated with cancer. In conclusion, isotretinoin and thalidomide down-regulate c-MYC mRNA expression and this is partially due to P1 or P2 promoter activity, suggesting that these drugs could be promising options for modulating the expression of oncogenes and tumor suppressor genes in HCC.

Does timing matter in radiotherapy of hepatocellular carcinoma? An experimental study in mice.

This study investigates whether a chronotherapeutic treatment of hepatocellular carcinoma (HCC) may improve treatment efficacy and mitigate side effects on non‐tumoral liver (NTL). HCC was induced in Per2::luc mice which were irradiated at four time points of the day. Proliferation and DNA‐double strand breaks were analyzed in irradiated and nonirradiated animals by detection of Ki67 and γ‐H2AX. Prior to whole animal experiments, organotypic slice cultures were investigated to determine the dosage to be used in whole animal experiments. Irradiation was most effective at the proliferation peaks in HCC at ZT02 (early inactivity phase) and ZT20 (late activity phase). Irradiation effects on NTL were minimal at ZT20. As compared with NTL, nonirradiated HCC revealed disruption in daily variation and downregulation of all investigated clock genes except Per1. Irradiation affected rhythmic clock gene expression in NTL and HCC at all ZTs except at ZT20 (late activity phase). Irradiation at ZT20 had no effect on total leukocyte numbers. Our results indicate ZT20 as the optimal time point for irradiation of HCC in mice at which the ratio between efficacy of tumor treatment and toxic side effects was maximal. Translational studies are now needed to evaluate whether the late activity phase is the optimal time point for irradiation of HCC in man.

Identification of LOXL3-associating immune infiltration landscape and prognostic value in hepatocellular carcinoma.

In recent years, breakthroughs in the field of tumor immunotherapy with immune checkpoint inhibitors (ICIs) have made a therapeutic revolution, which has been shown to improve the prognosis of patients with hepatocellular carcinoma (HCC). Immune infiltrates represent a major component of tumor microenvironment (TME), and play an essential role in both tumor progression and therapeutic response. The major unmet challenge in tumor immunotherapy is exploring the intrinsic and extrinsic mechanisms of TME promoting the management of HCC. Lysyl oxidase like 3 (LOXL3) participates in the remodeling of extracellular matrix (ECM) and the cross-linking of collagen and elastic fibers. It has been reported that LOXL3 is associated with the development and tumorigenesis of multiple types of cancer. RNA sequencing data and corresponding clinical information were extracted from The Cancer Genome Atlas (TCGA) databases, then subjected to gene expression, tumor microenvironment, survival, enrichment analyses utilizing R packages. In this study, we first found that LOXL3 gene was upregulated in tumor tissues compared with the normal tissues. Furthermore, LOXL3 expression is positively correlated with the infiltration of multiple immune cells and the expression of immune checkpoint genes in HCC. Meanwhile, high LOXL3 expression predicted poor outcomes of the patients with HCC. Functional enrichment analysis suggested that LOXL3 was mainly linked to extracellular structure and matrix organization, cell-cell adhesion, and T cell activation. This is the first comprehensive study to indicate that LOXL3 is correlated with immune infiltrates and may serve as a novel biomarker predicting prognosis and immunotherapy in HCC.

Identification of Multiple Hub Genes and Pathways in Hepatocellular Carcinoma: A Bioinformatics Analysis.

Hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive system, and its early asymptomatic characteristic increases the difficulty of diagnosis and treatment. This study is aimed at obtaining some novel biomarkers with diagnostic and prognostic meaning and may find out potential therapeutic targets for HCC. We screen differentially expressed genes (DEGs) from the HCC gene expression profile GSE14520 using GEO2R. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted by using the clusterProfiler software while a protein-protein interaction (PPI) network was performed based on the STRING database. Then, prognosis analysis of hub genes was conducted using The Cancer Genome Atlas (TCGA) database. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to further verify the expression of hub genes and explore the correlation between gene expression and clinicopathological parameters. A total of 1053 DEGs were captured, containing 497 upregulated genes and 556 downregulated genes. GO and KEGG analysis indicated that the downregulated DEGs were mainly enriched in the fatty acid catabolic process while upregulated DEGs were primarily enriched in the cell cycle. Simultaneously, ten hub genes (CYP3A4, UGT1A6, AOX1, UGT1A4, UGT2B15, CDK1, CCNB1, MAD2L1, CCNB2, and CDC20) were identified by the PPI network. Five prognosis-related hub genes (CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20) were uncovered by the survival analysis based on TCGA database. The ten hub genes were further validated by qRT-PCR using samples obtained from our hospital. The prognosis-related hub genes such as CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20 could be considered potential diagnosis biomarkers and prognosis targets for HCC. We also use Oncomine for further verification, and we found CCNB1, CCNB2, CDK1, and CYP3A4 which were highly expressed in HCC. Meanwhile, CCNB1, CCNB2, and CDK1 are highly expressed in almost all cancer types, which may play an important role in cancer. Still, further functional study should be conducted to explore the underlying mechanism and biological effect in the near future.

Key factors and potential drug combinations of nonalcoholic steatohepatitis: Bioinformatic analysis and experimental validation-based study

BackgroundNonalcoholic fatty liver disease and its advanced stage, nonalcoholic steatohepatitis (NASH), are the major cause of hepatocellular carcinoma (HCC) and other end-stage liver disease. However, the potential mechanism and therapeutic strategies have not been clarified. This study aimed to identify potential roles of miRNA/mRNA axis in the pathogenesis and drug combinations in the treatment of NASH. MethodsMicroarray GSE59045 and GSE48452 were downloaded from the Gene Expression Omnibus and analyzed using R. Then we obtained differentially expressed genes (DE-genes). DAVID database was used for Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis. Protein-protein interaction (PPI) networks were used for the identification of hub genes. We found upstream regulators of hub genes using miRTarBase. The expression and correlation of key miRNA and its targets were detected by qPCR. Drug Pair Seeker was employed to predict drug combinations against NASH. The expression of miRNA and hub genes in HCC was identified in the Cancer Genome Atlas database and Human Protein Atlas database. ResultsNinety-four DE-genes were accessed. GO and KEGG analysis showed that these predicted genes were linked to lipid metabolism. Eleven genes were identified as hub genes in PPI networks, and they were highly expressed in cells with vigorous lipid metabolism. hsa-miR-335-5p was the upstream regulator of 9 genes in the 11 hub genes, and it was identified as a key miRNA. The hub genes were highly expressed in NASH models, while hsa-miR-335-5p was lowly expressed. The correlation of miRNA-mRNA was established by qPCR. Functional verification indicated that hsa-miR-335-5p had inhibitory effect on the development of NASH. Finally, drug combinations were predicted and the expression of miRNA and hub genes in HCC was identified. ConclusionsIn the study, potential miRNA-mRNA pathways related to NASH were identified. Targeting these pathways may be novel strategies against NASH.

Integrated analysis of the rhesus monkey liver transcriptome during development and human primary HCC AFP-related gene expression

Embryonic development and tumorigenesis have a certain degree of similarity. Alpha-fetoprotein (AFP), a protein related to embryonic development, is a well-known biomarker for the diagnosis and prognosis of hepatocellular carcinoma (HCC). In this study, we analyzed the differences in gene expression profiles and molecular mechanisms in human HCC tissues from patients in AFPhigh (serum AFP level ≥ 25 ng/mL) and AFPlow (serum AFP level < 25 ng/mL) groups. The results indicated that AFPhigh HCC has more malignant biological characteristics. Single-sample gene set enrichment analysis (ssGSEA) showed significantly higher levels of genes expressed in dendritic cells, neutrophils, and natural killer cells in the AFPlow group than in the AFPhigh group. Then, we defined a rhesus monkey fetal liver developmental landscape and compared it to the HCC gene expression profile. The gene signatures of AFPhigh HCC tissues were similar to those of early embryonic liver tissues. In this study, we comprehensively analyzed the rhesus monkey liver transcriptome during development and human primary HCC AFP-related gene expression profiles and clarified the function of AFP in the occurrence and development of HCC from the perspective of developmental biology, which might provide a new perspective on the pathogenesis of HCC.

High S100A9+ cell density predicts a poor prognosis in hepatocellular carcinoma patients after curative resection.

S100A9 is differentially expressed in various cell types and is associated with the development, progression and metastasis of various cancers. However, the expression, distribution, and clinical significance of S100A9 in hepatocellular carcinoma (HCC) remain unclear. In the present study, The Cancer Genome Atlas (TCGA) database was used to examine S100A9 gene expression in HCC; we found that S100A9 expression was associated with HCC prognosis. In addition, S100A9 protein expression was assessed by immunohistochemistry analysis of tissues from 382 HCC patients. We found that the infiltration of S100A9+ cells in both tumor and nontumor tissues could predict poor overall survival (P = 0.0329, tumor; P = 0.0003, nontumor) and a high recurrence risk (P = 0.0387, tumor; P = 0.0015, nontumor) in our tissue microarray analysis. Furthermore, immunofluorescence double staining revealed that the primary S100A9-expressing cells in adjacent nontumoral tissue were CD15+ neutrophils, and both CD68+ macrophages and CD15+ neutrophils expressed S100A9 in HCC tumor tissues. Taken together, the results suggest that high S100A9+ cell density predicts a poor prognosis in HCC patients, and S100A9 expression could potentially serve as an independent prognostic marker 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.

Correlation analysis of tumor mutation burden of hepatocellular carcinoma based on data mining.

The aim of this study was to determine the relationship between tumor mutation burden (TMB) and prognosis of patients with hepatocellular carcinoma (HCC), and to explore the differential expression of genes in HCC by TMB and the relationship between immune cells, TMB, and HCC. Somatic variation data, gene transcriptional expression data and clinical information of patients with HCC were obtained from cancer genome map (TCGA) database. Analyze the characteristics of the gene mutation data of the sample, divide the high and low TMB groups and draw the survival curve at the same time, carry on the difference analysis to the gene of TMB, further carry on the univariate Cox regression analysis and Lasso regression analysis and construct the clinical model. Download the dataset GSE14520, from the Gene Expression Omnibus (GEO) database to verify the genes of the prognostic model. The differential genes were analyzed by gene ontology (GO) enrichment analysis and Kyoto encyclopedia of genes and genomes by (KEGG) enrichment analysis. Then the relative abundance of 22 immune cell types in HCC and normal control samples was calculated. Finally, the correlation between the scores of immune cells and Risk model was analyzed. Tumor protein p53 (TP53), catenin1 (CTNNB1), titin (TTN), mucin 16 (MUC16), and albumin (ALB) are the most common top 5 mutations in HCC. The prognosis of high level TMB group is worse than that of low TMB group. A total of 122 differentially expressed genes were screened by differential analysis of TMB genes. SQSTM1, ME1, BAMBI and PTTG1 are independent risk factors for poor prognosis of HCC. GO and KEGG analysis showed that the differential genes were mainly in extracellular matrix and immune response. There were significant differences in the distribution of Macrophages M0 and T cells CD4 native cells between HCC and normal tissues, which were correlated with the differential genes of TMB and correlated with prognosis. There is a negative correlation between TMB and the prognosis of patients with HCC. TMB has an effect on the differential expression of genes in HCC cells and the distribution of immune cells in tumor tissues.

Identification of Potential Biomarkers From Hepatocellular Carcinoma With MT1 Deletion.

Background: Hepatocellular carcinoma (HCC) is one of the deadliest cancers worldwide. Metallothioneins (MTs) are metal-binding proteins involved in multiple biological processes such as metal homeostasis and detoxification, as well as in oncogenesis. Copy number variation (CNV) plays a vital role in pathogenesis and carcinogenesis. Nevertheless, there is no study on the role of MT1 CNV in HCC. Methods: Array-based Comparative Genomic Hybridization (aCGH) analysis was performed to obtain the CNV data of 79 Guangxi HCC patients. The prognostic effect of MT1-deletion was analyzed by univariate and multivariate Cox regression analysis. The differentially expressed genes (DEGs) were screened based on The Gene Expression Omnibus database (GEO) and the Liver Hepatocellular Carcinoma of The Cancer Genome Atlas (TCGA-LIHC). Then function and pathway enrichment analysis, protein-protein interaction (PPI) and hub gene selection were applied on the DEGs. Lastly, the hub genes were validated by immunohistochemistry, tissue expression and prognostic analysis. Results: The MT1-deletion was demonstrated to affect the prognosis of HCC and can act as an independent prognostic factor. 147 common DEGs were screened. The most significant cluster of DEGs identified by Molecular Complex Detection (MCODE) indicated that the expression of four MT1s were down-regulated. MT1X and other five hub genes (TTK, BUB1, CYP3A4, NR1I2, CYP8B1) were associated with the prognosis of HCC. TTK, could affect the prognosis of HCC with MT1-deletion and non-deletion. NR1I2, CYP8B1, and BUB1 were associated with the prognosis of HCC with MT1-deletion. Conclusions: In the current study, we demonstrated that MT1-deletion can be an independent prognostic factor in HCC. We identified TTK, BUB1, NR1I2, CYP8B1 by processing microarray data, for the first time revealed the underlying function of MT1 deletion in HCC, MT1-deletion may influence the gene expression in HCC, which may be the potential biomarkers for HCC with MT1 deletion.

Prediction of Overall Survival Rate in Patients With Hepatocellular Carcinoma Using an Integrated Model Based on Autophagy Gene Marker.

The autophagy cell, which can inhibit the formation of tumor in the early stage and can promote the development of tumor in the late stage, plays an important role in the development of tumor. Therefore, it has potential significance to explore the influence of autophagy-related genes (AAGs) on the prognosis of hepatocellular carcinoma (HCC). The differentially expressed AAGs are selected from HCC gene expression profile data and clinical data downloaded from the TCGA database, and human autophagy database (HADB). The role of AAGs in HCC is elucidated by GO functional annotation and KEGG pathway enrichment analysis. Combining with clinical data, we selected age, gender, grade, stage, T state, M state, and N state as Cox model indexes to construct the multivariate Cox model and survival curve of Kaplan Meier (KM) was drawn to estimate patients’ survival between high- and low-risk groups. Through an ROC curve drawn by univariate and multivariate Cox regression analysis, we found that seven genes with high expression levels, including HSP90AB1, SQSTM1, RHEB, HDAC1, ATIC, HSPB8, and BIRC5 were associated with poor prognosis of HCC patients. Then the ICGC database is used to verify the reliability and robustness of the model. Therefore, the prognosis model of HCC constructed by autophagy genes might effectively predict the overall survival rate and help to find the best personalized targeted therapy of patients with HCC, which can provide better prognosis for patients.

Icaritin promotes apoptosis and inhibits proliferation by down-regulating AFP gene expression in hepatocellular carcinoma

BackgroundIcaritin, an active ingredient of the Chinese herb Epimedium, plays an anti-tumor role in liver cancer by inhibiting the proliferation of hepatocellular cells and promoting their apoptosis. In China, phase II and a large phase III clinical trial of icaritin reagent for the treatment of hepatocellular cancer is under-going, but the specific mechanism of icaritin action was unclear. Alpha-fetoprotein (AFP), an oncofetal protein, produced in the healthy fetal liver and yolk sac. Intracellular AFP promoted cellular proliferation and inhibited cellular apoptosis in hepatocellular carcinoma (HCC). The study was aimed to investigate the effect of icaritin on HCC through p53/AFP pathway.MethodsReal-time RT PCR and western blot were used to detect p53 and AFP expression levels in HCC cells treated with icaritin. The mechanism of icaritin affecting p53 expression was verified by ubiquitination experiment, and the binding activity of icaritin on p53 in AFP promoter region was verified by luciferase experiment. EdU, MTT and flow cytometry were used to determine whether icaritin affected HCC cellular proliferation and apoptosis through p53/ AFP pathway. Expression levels of p53 and AFP in xenograft mouse model were determined by western blotting.ResultsOur results showed icaritin inhibited AFP expression at mRNA and protein level. AFP was also identified as the target gene of the p53 transcription factor. Icaritin abrogated murine double minute (Mdm) 2-mediated p53 ubiquitination degradation to improve the stability of p53. Up-regulated p53 protein levels then transcriptionally inhibited the AFP promoter. Icaritin-mediated decrease of AFP through Mdm2/p53 pathways inhibited HCC cellular proliferation and promoted HCC cellular apoptosis.ConclusionOur findings revealed the mechanism of icaritin in promoting apoptosis and inhibiting proliferation in liver cancer cells. The regulatory mechanism of icaritin in AFP protein down-regulation provides a theoretical and experimental basis for further research into new drugs for the treatment of liver cancer.