The role of CDK1 in apoptin-induced apoptosis in hepatocellular carcinoma cells

4-Furanylvinylquinoline derivative as a new scaffold for the design of oxidative stress initiator and glucose transporter inhibitor drugs

In the present study, a detailed analysis of the effect of a substitution at the C4 position of the quinoline ring by styryl or furanylvinyl substituents on the structure-antitumour activity relationship was conducted. After analysing a library of derivatives from the styrylquinoline and furanylvinylquinoline groups, we selected the most active (IC50 below 100 nM) derivative 13, which contained the strongly electron-withdrawing nitro group in the furan substituent. The mechanism of action of this compound was studied on cell lines that differed in their p53 protein status. For this derivative, both cell cycle arrest (in G2/M phase in both HCT 116 cell lines and S phase for U-251 cell line) and the induction of apoptosis (up to 66% for U-251 cell line) were revealed. These studies were then confirmed by other methods at the gene and protein levels. Interestingly, we observed differences in the mechanism of action depending on the presence and mutation of the p53 protein, thus confirming its key role in cellular processes. Incubation with derivative 13 resulted in the induction of oxidative stress and triggered a cascade of cellular defence proteins that failed in the face of such an active compound. In addition, the results showed an inhibition of the GLUT-1 glucose transporter, which is extremely important in the context of anti-cancer activity.

Investigating the effect of polymerase inhibitors on cellular proliferation: Computational studies, cytotoxicity, CDK1 inhibitory potential, and LC-MS/MS cancer cell entrapment assays

Directly acting antivirals (DAAs) are a breakthrough in the treatment of HCV. There are controversial reports on their tendency to induce hepatocellular carcinoma (HCC) in HCV patients. Numerous reports have concluded that the HCC is attributed to patient-related factors while others are inclined to attribute this as a DAA side-effect. This study aims to investigate the effect of polymerase inhibitor DAAs, especially daclatasivir (DLT) on cellular proliferation as compared to ribavirin (RBV). The interaction of DAAs with variable cell-cycle proteins was studied in silico. The binding affinities to multiple cellular targets were investigated and the molecular dynamics were assessed. The in vitro effect of the selected candidate DLT on cancer cell proliferation was determined and the CDK1 inhibitory potential in was evaluated. Finally, the cellular entrapment of the selected candidates was assessed by an in-house developed and validated LC-MS/MS method. The results indicated that polymerase inhibitor antiviral agents, especially DLT, may exert an anti-proliferative potential against variable cancer cell lines. The results showed that the effect may be achieved via potential interaction with the multiple cellular targets, including the CDK1, resulting in halting of the cellular proliferation. DLT exhibited a remarkable cell permeability in the liver cancer cell line which permits adequate interaction with the cellular targets. In conclusion, the results reveal that the polymerase inhibitor (DLT) may have an anti-proliferative potential against liver cancer cells. These results may pose DLT as a therapeutic choice for patients suffering from HCV and are liable to HCC development.

Based on network pharmacology and experiments to explore the underlying mechanism of Mahonia bealei (Fortune) Carrière for treating alcoholic hepatocellular carcinoma

ETHNOPHARMACOLOGICAL RELEVANCE

Mahonia bealei (Fortune) Carrière (M. bealei) is a traditional medicine widely used by the Hmong community in Guizhou. It possesses diverse biological activities and shows promise in cancer treatment; however, contemporary pharmacological research in this area is lacking.

AIMS OF THE STUDY

This study aimed to investigate the effects and underlying mechanisms of M. bealei on alcoholic hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

We initially employed the LC-MS/MS method to identify the compounds present in M. bealei serum. Subsequently, its potential targets were predicted using public databases. Bioinformatics and network pharmacology approaches, such as univariate Cox regression and random forest (RF) algorithms, were utilized to identify differentially expressed genes (DEGs) associated with the prognosis of alcoholic HCC. Survival curve and receiver operating characteristic (ROC) analyses were conducted using alcoholic HCC-related data from TCGA and GEO to determine the diagnostic value of the identified DEGs. Molecular docking using the CDOCKER approach based on CHARMm was performed to validate the affinity between the predictive compounds and targets. Additionally, we evaluated the impact of M. bealei on cell proliferation, migration, and conducted western blot assays.

RESULTS

The LC-MS/MS approach identified 17 therapeutic components and predicted 483 component-related targets, of which 63 overlapped with alcoholic HCC targets and were considered potential therapeutic targets. GO and KEGG pathway analysis revealed significant associations between the 63 overlapping targets and alcoholic HCC progression. Through various approaches in the Cytoscape 3.9.0 software, we confirmed 9 hub genes (CDK1, CXCR4, DNMT1, ESR1, KIT, PDGFRB, SERPINE1, TOP2A, and TYMS) as core targets. TOP2A and CDK1 genes were identified as advantageous for diagnosing alcoholic HCC using univariate Cox regression, RF, survival curve, and ROC analysis. Molecular docking analysis demonstrated strong binding affinity between key bioactive components cyclamic acid, perfluoroalkyl carboxylic acid, perfluorosulfonic acid, alpha-linolenic acid, adenosine receptor antagonist (CGS 15943), and Prodigiosin and TOP2A and CDK1. In vitro experiments confirmed that M. bealei significantly suppressed cell proliferation and migration of HepG2 cells, while downregulating TOP2A and CDK1 expression.

CONCLUSION

This study highlights the potential of M. bealei as a natural medicine for the treatment of alcoholic HCC. Six compounds (cyclamic acid, perfluoroalkylic carboxylic acids, perfluorosulfonic acid, alpha-linolenic acid, adenosine receptor antagonist (CGS 15943), and Prodigiosin) present in M. bealei serum may exhibit therapeutic effects against alcoholic HCC by downregulating CDK1 and TOP2A expression levels in vitro.

Anti-tumor target screening of sea cucumber saponin Frondoside A: a bioinformatics and molecular docking analysis

Cancer remains the leading cause of death worldwide. In spite of significant advances in targeted and immunotherapeutic approaches, clinical outcomes for cancer remain poor. The aim of the present study was to investigate the potential mechanisms and therapeutic targets of Frondoside A for the treatment of liver, pancreatic, and bladder cancers. The data presented in our study demonstrated that Frondoside A reduced the viability and migration of HepG2, Panc02, and UM-UC-3 cancer cell in vitro. Moreover, we utilized the GEO database to screen and identify for differentially expressed genes (DEGs) in liver, pancreatic, and bladder cancers, which resulted in the identification of 714, 357, and 101 DEGs, respectively. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation were performed using the Metascape database for DEGs that were significantly associated with cancer development. The protein-protein interaction (PPI) networks of the identified DEGs in liver, pancreatic, and bladder cancers were analyzed using Cytoscape 3.9.0 software, and subsequently identified potential key genes that were associated with these networks. Subsequently, their prognostic values were assessed by gene expression level analysis and Kaplan-Meier survival analysis (GEPIA). Furthermore, we utilized TIMER 2.0 to investigate the correlation between the expression of the identified key gene and cancer immune infiltration. Finally, molecular docking simulations were performed to assess the affinity of Frondoside A and key genes. Our results showed a significant correlation between these DEGs and cancer progression. Combined, these analyses revealed that Frondoside A involves in the regulation of multiple pathways, such as drug metabolism, cell cycle in liver cancer by inhibiting the expression of CDK1, TOP2A, CDC20, and KIF20A, and regulates protein digestion and absorption, receptor interaction in pancreatic cancer by down-regulation of ASPM, TOP2A, DLGAP5, TPX2, KIF23, MELK, LAMA3, and ANLN. While in bladder cancer, Frondoside A regulates muscle contraction, complement and coagulation cascade by increase FLNC expression. In conclusion, the present study offers valuable insights into the molecular mechanism underlying the anticancer effects of Frondoside A, and suggests that Frondoside A can be used as a functional food supplement or further developed as a natural anti-cancer drug.

Identifying possible hub genes and biological mechanisms shared between bladder cancer and inflammatory bowel disease using machine learning and integrated bioinformatics

BACKGROUND

Recent studies have shown that inflammatory bowel disease (IBD) is associated with bladder cancer (BC) incidence. But there is still a lack of understanding regarding its pathogenesis. Thus, this study aimed to identify potential hub genes and their important pathways and pathological mechanisms of interactions between IBD and BC using bioinformatics methods.

METHODS

The data from Gene Expression Omnibus (GEO) and the cancer genome atlas (TCGA) were analyzed to screen common differentially expressed genes (DEGs) between IBD and BC. The "clusterProfiler" package was used to analyze GO term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment in DEGs. After that, we conducted a weighted gene co-expression network analysis (WGCNA) on these DEGs to determine the vital modules and genes significantly related to BC. Protein-protein interaction (PPI) networks was used to identify hub genes. Further, the hub genes were used to develop a prognostic signature by Cox analysis. The validity of the ten hub DEGs was tested using three classification algorithms. Finally, we analyzed the microRNAs (miRNA)-mRNA, transcription factors (TFs)-mRNA regulatory network.

RESULTS

Positive regulation of organelle fission, chromosomal region, tubulin binding, and cell cycle signaling pathway were the major enriched pathways for the common DEGs. PPI networks identified three hub proteins (AURKB, CDK1, and CCNA2) with high connectivity. Three machine-learning classification algorithms based on ten hub genes performed well for IBD and BC (accuracy > 0.80). The robust predictive model based on the ten hub genes could accurately classify BC cases with various clinical outcomes. Based on the gene-TFs and gene-miRNAs network construction, 9 TFs and 6 miRNAs were identified as potential critical TFs and miRNAs. There are 13 drugs that interact with the hub gene based on gene-drug interaction analysis.

CONCLUSIONS

This study explored common gene signatures and the potential pathogenesis of IBD and BC. We revealed that an unbalanced immune response, cell cycle pathway, and neutrophil infiltration might be the common pathogenesis of IBD and BC. Molecular mechanisms for the treatment of IBD and CC still require further investigation.

Study on the mechanism of action of Scutellaria barbata on hepatocellular carcinoma based on network pharmacology and bioinformatics

Background: Hepatocellular carcinoma is one of the most common cancers with the characteristics of invasion and high mortality. Current forms of prevention remain severe. Scutellaria barbata is widely used in traditional Chinese medicine treatment of various tumors. This study explored the mechanism of Scutellaria barbata in the treatment of hepatocellular carcinoma by network pharmacology and bioinformatics. Methods: The active ingredients of Scutellaria barbata and potential targets for the treatment of hepatocellular carcinoma were collected by network pharmacology. The protein interaction network was constructed to screen the core targets, and the association between the core targets and diseases was further verified by bioinformatics methods. Finally, the active ingredients corresponding to the targets closely related to the disease were screened for AMDE characteristics analysis. Molecular docking of drug-like ingredients with corresponding targets was performed. We used CCK-8 kit to determine the effect of active ingredients on cell proliferation. Results: 29 candidate active ingredients and 461 related targets of Scutellaria barbata were screened. A total of 8238 potential therapeutic targets for hepatocellular carcinoma were indentified. Finally, 373 potential targets for the treatment of HCC were obtained. The active ingredients: wogonin, Rhamnazin, eriodictyol, quercetin, baicalein, and luteolin, etc. The core targets were CDK1, CDK4, SRC, and E2F1. A total of 3056 GO enrichment entries were obtained, and 180 enrichment results were obtained by KEGG pathway analysis. Genes were mainly enriched in PI3K-Akt signaling pathway, IL-17 signaling pathway, TNF signaling pathway, apoptosis pathway, and hepatocellular carcinoma pathway. Molecular docking results showed that the screened compounds had strong binding ability with the corresponding target proteins. CCK8 assays showed that Rhamnazin and Luteolin suppressed the proliferation of HCC cells significantly compared with controls. Conclusion: This study revealed that the mechanism of Scutellaria barbata in the treatment of hepatocellular carcinoma may be that the active ingredients inhibit the expression of core genes and block the PI3K-AKT signaling pathway to inhibit the proliferation, and migration and induce apoptosis of cancer cells.

Molecular docking and in vitro experiments verified that kaempferol induced apoptosis and inhibited human HepG2 cell proliferation by targeting BAX, CDK1, and JUN

Hepatocellular carcinoma, as a common liver cirrhosis complication, has become the sixth most common cancer worldwide, and its increasing incidence has resulted in considerable medical and economic burdens. As a natural polyphenolic compound, kaempferol has exhibits a wide range of antitumor activities against multiple cancer targets. In this study, the Autodock software was used for molecular docking to simulate the interaction process between kaempferol and HCC targets and the PyMOL software was used for visualization. Proliferation of kaempferol HepG2 cells under the effect of kaempferol was detected using Cell Counting Kit-8 (CCK-8) assay, and the apoptosis rate of HepG2 cells was detected using flow cytometry. The expressions of proteins BAX, CDK1, and JUN protein expressions were detected by Western blot. Molecular docking found that the kaempferol ligand has 3 rotatable bonds, 6 nonpolar hydrogen atoms, and 12 aromatic carbon atoms, and can form complexes with the kaempferol targets P53, BAX, AR, CDK1, and JUN through electrostatic energy. GO (Gene Ontology) enrichment analysis suggests that kaempferol regulates the biological function of hepatocellular carcinoma cells and is related to apoptosis. Cell Counting Kit-8 assay suggested that Kaempferol can significantly inhibited HepG2 cell proliferation, and the inhibition rate increased with the increase in drug concentration and incubation time. Moreover, kaempferol can promoted HepG2 cell apoptosis in a dose-dependent manner. This compound upregulated BAX and JUN expression and downregulated CDK1 expression. Thus, Kaempferol can promote HepG2 cell apoptosis, and the regulatory mechanism may be related to the regulation of the expression levels of the apoptosis-related proteins BAX, CDK1, and JUN.

An advanced network pharmacology study to explore the novel molecular mechanism of Compound Kushen Injection for treating hepatocellular carcinoma by bioinformatics and experimental verification

Background

Compound Kushen Injection (CKI) is a Chinese patent drug that exerts curative effects in the clinical treatment of hepatocellular carcinoma (HCC). This study aimed to explore the targets and potential pharmacological mechanisms of CKI in the treatment of HCC.

Methods

In this study, network pharmacology was used in combination with molecular biology experiments to predict and verify the molecular mechanism of CKI in the treatment of HCC. The constituents of CKI were identified by UHPLC-MS/MS and literature search. The targets corresponding to these compounds and the targets related to HCC were collected based on public databases. To screen out the potential hub targets of CKI in the treatment of HCC, a compound-HCC target network was constructed. The underlying pharmacological mechanism was explored through the subsequent enrichment analysis. Interactive Gene Expression Profiling Analysis and Kaplan-Meier plotter were used to examine the expression and prognostic value of hub genes. Furthermore, the effects of CKI on HCC were verified through molecular docking simulations and cell experiments in vitro.

Results

Network analysis revealed that BCHE, SRD5A2, EPHX2, ADH1C, ADH1A and CDK1 were the key targets of CKI in the treatment of HCC. Among them, only CDK1 was highly expressed in HCC tissues, while the other 5 targets were lowly expressed. Furthermore, the six hub genes were all closely related to the prognosis of HCC patients in survival analysis. Molecular docking revealed that there was an efficient binding potential between the constituents of CKI and BCHE. Experiments in vitro proved that CKI inhibited the proliferation of HepG2 cells and up-regulated SRD5A2 and ADH1A, while down-regulated CDK1 and EPHX2.

Conclusions

This study revealed and verified the targets of CKI on HCC based on network pharmacology and experiments and provided a scientific reference for further mechanism research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03530-3.

Clinical implications and molecular mechanisms of Cyclin-dependent kinases 4 for patients with hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) was frequently considered as a kind of malignant tumor with a poor prognosis. Cyclin-dependent kinases (CDK) 4 was considered to be cell-cycle-related CDK gene. In this study, we explored the clinical significance of CDK4 in HCC patients.

Methods

Data of HCC patients were obtained from The Cancer Genome Atlas database (TCGA) and the Gene Expression Omnibus (GEO) database. Kaplan–Meier analysis and Cox regression model were performed to calculate median survival time (MST) and the hazard ration (HR), respectively. The joint-effect analysis and prognostic risk score model were constructed to demonstrate significance of prognosis-related genes. The differential expression of prognostic genes was further validated using reverse transcription-quantitative PCR (RT-qPCR) of 58 pairs of HCC samples.

Results

CDK1 and CDK4 were considered prognostic genes in TCGA and GSE14520 cohort. The result of joint-effect model indicated patients in CDK1 and CDK4 low expression groups had a better prognosis in TCGA (adjusted HR = 0.491; adjusted P = 0.003) and GSE14520 cohort (adjusted HR = 0.431; adjusted P = 0.002). Regarding Kaplan–Meier analysis, high expression of CDK1 and CDK4 was related to poor prognosis in both the TCGA (P < 0.001 and = 0.001 for CDK1 and CDK4, respectively) and the GSE14520 cohort (P = 0.006 and = 0.033 for CDK1 and CDK4, respectively). However, only CDK4 (P = 0.042) was validated in RT-qPCR experiment, while CDK1 (P = 0.075) was not.

Conclusion

HCC patients with high CDK4 expression have poor prognosis, and CDK4 could be a potential candidate diagnostic biomarker for HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02152-w.

Identification of key genes and carcinogenic pathways in hepatitis B virus-associated hepatocellular carcinoma through bioinformatics analysis

Backgrounds/Aims

Mechanisms for the development of hepatocellular carcinoma (HCC) in hepatitis B virus (HBV)-infected patients remain unclear. The aim of the present study was to identify genes and pathways involved in the development of HBV-associated HCC.

Methods

The GSE121248 gene dataset, which included 70 HCCs and 37 adjacent liver tissues, was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) in HCCs and adjacent liver tissues were identified. Gene ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analyses were then performed.

Results

Of 134 DEGs identified, 34 were up-regulated and 100 were down-regulated in HCCs. The 34 up-regulated DEGs were mainly involved in nuclear division, organelle fission, spindle and midbody formation, histone kinase activity, and p53 signaling pathway, whereas the 100 down-regulated DEGs were involved in steroid and hormone metabolism, collagen-coated extracellular matrix, oxidoreductase activity, and activity on paired donors, including incorporation or reduction of molecular oxygen, monooxygenase activity, and retinol metabolism. Analyses of protein-protein interaction networks with a high degree of connectivity identified significant modules containing 14 hub genes, including ANLN, ASPM, BUB1B, CCNB1, CDK1, CDKN3, ECT2, HMMR, NEK2, PBK, PRC1, RACGAP1, RRM2, and TOP2A, which were mainly associated with nuclear division, organelle fission, spindle formation, protein serine/threonine kinase activity, p53 signaling pathway, and cell cycle.

Conclusions

This study identified key genes and carcinogenic pathways that play essential roles in the development of HBV-associated HCC. This may provide important information for the development of diagnostic and therapeutic targets for HCC.

The circular RNA circSLC7A11 functions as a mir-330-3p sponge to accelerate hepatocellular carcinoma progression by regulating cyclin-dependent kinase 1 expression

Background

Circular RNAs (circRNAs), which are endogenous non-coding RNAs, are associated with various biological processes including development, homeostatic maintenance, and pathological responses. Accumulating evidence has implicated non-coding RNAs in cancer progression, and the role of circRNAs in particular has drawn wide attention. However, circRNA expression patterns and functions in hepatocellular carcinoma (HCC) remain poorly understood.

Methods

CircRNA sequencing was performed to screen differentially expressed circRNAs in HCC. Northern blotting, quantitative real-time polymerase chain reaction, nucleocytoplasmic fractionation, and fluorescence in situ hybridization analyses were conducted to evaluate the expression and localization of circSLC7A11 in HCC tissues and cells. CircSLC7A11 expression levels were modified in cultured HCC cell lines to explore the association between the expression of circSLC7A11 and the malignant behavior of these cells using several cell-based assays. The modified cells were implanted into immunocompetent nude mice to assess tumor growth and metastasis in vivo. We applied bioinformatics methods, RNA pulldown, RNA immunoprecipitation, and luciferase reporter assays to explore the mechanisms of circSLC7A11 in HCC.

Results

CircSLC7A11 (hsa_circ_0070975) was conserved and dramatically overexpressed in HCC tissues and cells. HCC patients showing high circSLC7A11 expression had worse prognoses. Our in vitro and in vivo experiments showed that circSLC7A11 markedly accelerated HCC progression and metastasis through the circSLC7A11/miR-330-3p/CDK1 axis.

Conclusions

The acceleration of HCC progression and metastasis by circSLC7A11 through the circSLC7A11/miR-330-3p/CDK1 axis suggests that circSLC7A11 is a potential novel diagnostic and therapeutic target for HCC treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02351-7.

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

BACKGROUND AND AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Identification of potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma via integrated bioinformatics analysis

Objective

The objective was to identify potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma (HCC).

Methods

Gene expression profile datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HCC and normal samples were identified via an integrated analysis. A protein–protein interaction network was constructed and analyzed using the STRING database and Cytoscape software, and enrichment analyses were carried out through DAVID. Gene Expression Profiling Interactive Analysis and Kaplan–Meier plotter were used to determine expression and prognostic values of hub genes.

Results

We identified 11 hub genes (CDK1, CCNB2, CDC20, CCNB1, TOP2A, CCNA2, MELK, PBK, TPX2, KIF20A, and AURKA) that might be closely related to the pathogenesis and prognosis of HCC. Enrichment analyses indicated that the DEGs were significantly enriched in metabolism-associated pathways, and hub genes and module 1 were highly associated with cell cycle pathway.

Conclusions

In this study, we identified key genes of HCC, which indicated directions for further research into diagnostic and prognostic biomarkers that could facilitate targeted molecular therapy for HCC.

Apoptosis Triggered by ORF3 Proteins of the Circoviridae Family

Apoptosis, a form of the programmed cell death, is an indispensable defense mechanism regulating cellular homeostasis and is triggered by multiple stimuli. Because of the regulation of apoptosis in cellular homeostasis, viral proteins with apoptotic activity are particular foci of on antitumor therapy. One representative viral protein is the open reading frame 3 (ORF3) protein, also named as apoptin in the Circoviridae chicken anemia virus (CAV), and has the ability to induce tumor-specific apoptosis. Proteins encoded by ORF3 in other circovirus species, such as porcine circovirus (PCV) and duck circovirus (DuCV), have also been reported to induce apoptosis, with subtle differences in apoptotic activity based on cell types. This article is aimed at reviewing the latest research advancements in understanding ORF3 protein-mediated apoptosis mechanisms of Circoviridae from three perspectives: subcellular localization, interactions with host proteins, and participation in multiple apoptotic signaling pathways, providing a scientific basis for circovirus pathogenesis and a reference on its potential anticancer function.

Identification of CDK1 as a candidate marker in cutaneous squamous cell carcinoma by integrated bioinformatics analysis

BACKGROUND

Cutaneous squamous cell carcinoma (cSCC) is a relatively common cancer that accounts for nearly 50% of non-melanoma skin cancer cases. However, the genotypes that are linked with poor prognosis and/or high relapse rates and pathogenic mechanisms of cSCC are not fully understood. To address these points, three gene expression datasets were analyzed to identify candidate biomarker genes in cSCC.

METHODS

The GSE117247, GSE32979, and GSE98767 datasets comprising a total of 32 cSCC samples and 31 normal skin tissue samples were obtained from the National Center for Biotechnology Information Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified and underwent pathway enrichment analyses with the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG). A putative DEG protein-protein interaction (PPI) network was also established that included hub genes. The expression of CDK1, MAD2L1, BUB1 ans CDC20 were examined in the study.

RESULTS

A total of 335 genes were identified, encompassing 219 found to be upregulated and 116 genes that were downregulated in cSCC, compared to normal tissue. Enriched functions of these DEGs were associated with Ephrin receptor signaling and cell division; cytosol, membrane, and extracellular exosomes; ATP-, poly(A) RNA-, and identical protein binding. We also established a PPI network comprising 332 nodes and identified KIF2C, CDC42, AURKA, MAD2L1, MYC, CDK1, FEN1, H2AFZ, BUB1, BUB1B, CKS2, CDC20, CCT2, ACTR2, ACTB, MAPK14, and HDAC1 as candidate hub genes. The expression of CDK1 are significantly higher in the cSCC tissues than that in normal skin.

CONCLUSIONS

The DEGs identified in this study are potential therapeutic targets and biomarkers for cSCC. CDK1 is a gene closely related to the occurrence and development of cSCC, which may play an important role. Bioinformatics analysis shows that it is involved in the important pathway of the pathogenesis of cSCC, and may be recognized and applied as a new biomarker in the future diagnosis and treatment of cSCC.

Apoptin as a Tumor-Specific Therapeutic Agent: Current Perspective on Mechanism of Action and Delivery Systems

Cancer remains one of the leading causes of death worldwide in humans and animals. Conventional treatment regimens often fail to produce the desired outcome due to disturbances in cell physiology that arise during the process of transformation. Additionally, development of treatment regimens with no or minimum side-effects is one of the thrust areas of modern cancer research. Oncolytic viral gene therapy employs certain viral genes which on ectopic expression find and selectively destroy malignant cells, thereby achieving tumor cell death without harming the normal cells in the neighborhood. Apoptin, encoded by Chicken Infectious Anemia Virus' VP3 gene, is a proline-rich protein capable of inducing apoptosis in cancer cells in a selective manner. In normal cells, the filamentous Apoptin becomes aggregated toward the cell margins, but is eventually degraded by proteasomes without harming the cells. In malignant cells, after activation by phosphorylation by a cancer cell-specific kinase whose identity is disputed, Apoptin accumulates in the nucleus, undergoes aggregation to form multimers, and prevents the dividing cancer cells from repairing their DNA lesions, thereby forcing them to undergo apoptosis. In this review, we discuss the present knowledge about the structure of Apoptin protein, elaborate on its mechanism of action, and summarize various strategies that have been used to deliver it as an anticancer drug in various cancer models.

Identification of prognostic risk factors for pancreatic cancer using bioinformatics analysis

Background

Pancreatic cancer is one of the most common malignant cancers worldwide. Currently, the pathogenesis of pancreatic cancer remains unclear; thus, it is necessary to explore its precise molecular mechanisms.

Methods

To identify candidate genes involved in the tumorigenesis and proliferation of pancreatic cancer, the microarray datasets GSE32676, GSE15471 and GSE71989 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between Pancreatic ductal adenocarcinoma (PDAC) and nonmalignant samples were screened by GEO2R. The Database for Annotation Visualization and Integrated Discovery (DAVID) online tool was used to obtain a synthetic set of functional annotation information for the DEGs. A PPI network of the DEGs was established using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and a combination of more than 0.4 was considered statistically significant for the PPI. Subsequently, we visualized the PPI network using Cytoscape. Functional module analysis was then performed using Molecular Complex Detection (MCODE). Genes with a degree ≥10 were chosen as hub genes, and pathways of the hub genes were visualized using ClueGO and CluePedia. Additionally, GenCLiP 2.0 was used to explore interactions of hub genes. The Literature Mining Gene Networks module was applied to explore the cocitation of hub genes. The Cytoscape plugin iRegulon was employed to analyze transcription factors regulating the hub genes. Furthermore, the expression levels of the 13 hub genes in pancreatic cancer tissues and normal samples were validated using the Gene Expression Profiling Interactive Analysis (GEPIA) platform. Moreover, overall survival and disease-free survival analyses according to the expression of hub genes were performed using Kaplan-Meier curve analysis in the cBioPortal online platform. The relationship between expression level and tumor grade was analyzed using the online database Oncomine. Lastly, the eight snap-frozen tumorous and adjacent noncancerous adjacent tissues of pancreatic cancer patients used to detect the CDK1 and CEP55 protein levels by western blot.

Conclusions

Altogether, the DEGs and hub genes identified in this work can help uncover the molecular mechanisms underlying the tumorigenesis of pancreatic cancer and provide potential targets for the diagnosis and treatment of this disease.

Identification of Core Genes and Pathways in Medulloblastoma by Integrated Bioinformatics Analysis

Medulloblastoma (MB) is one of the most common intracranial malignancies in children. The present study applied integrated bioinformatics to identify potential core genes associated with the pathogenesis of MB and reveal potential molecular mechanisms. Through the integrated analysis of multiple data sets from the Gene Expression Omnibus (GEO), 414 differentially expressed genes (DEGs) were identified. Combining the protein-protein interaction (PPI) network analysis with gene set enrichment analysis (GSEA), eight core genes, including CCNA2, CCNB1, CCNB2, AURKA, CDK1, MAD2L1, BUB1B, and RRM2, as well as four core pathways, including "cell cycle", "oocyte meiosis", "p53 pathway" and "DNA replication" were selected. In independent data sets, the core genes showed superior diagnostic values and significant prognostic correlations. Moreover, in the pan-caner data of the cancer genome atlas (TCGA), the core genes were also widely abnormally expressed. In conclusion, this study identified core genes and pathways of MB through integrated analysis to deepen the understanding of the molecular mechanisms underlying the MB and provide potential targets and pathways for diagnosis and treatment of MB.

Cell Cycle Genes Are Potential Diagnostic and Prognostic Biomarkers in Hepatocellular Carcinoma

BACKGROUND

The cell cycle pathway genes are comprised of 113 members which are critical to the maintenance of cell cycle and survival of tumor cells. This study was performed to investigate the diagnostic and prognostic values of cell cycle gene expression in hepatocellular carcinoma (HCC) patients.

METHODS

Clinical features and cell cycle pathway gene expression data were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases. Differentially expressed genes (DEGs) were determined by the student t-test between HCC and noncancerous samples. Kaplan-Meier survival, univariate, and multivariate survival analyses and validation analysis were performed to characterize the associations between cell cycle gene expression and patients' overall survival and recurrence-free survival.

RESULTS

47 and 5 genes were significantly upregulated and downregulated genes in HCC samples, respectively. The high expression of BUB3, CDK1, and CHEK1 was associated with increased mortality (adjusted P value = 0.04, odds ratio (OR): 1.89 (95% confidence interval (CI): 1.04-3.46); adjusted P value = 0.02, OR: 2.06 (95% CI:1.15-3.75); and adjusted P value = 0.04, OR: 1.84 (%95 CI: 1.03-3.32), respectively). The expression of PTTG2 and RAD21 was significantly associated with cancer recurrence (adjusted P value = 0.01, OR: 2.17 (95% CI: 1.24-3.86); adjusted P value = 0.03, OR: 1.88[95% CI:1.08-3.28], respectively), while the low expression of MAD1L1 was associated with cancer recurrence (adjusted P value = 0.03, OR: 0.53 (%95 CI: 0.3-0.93)).

CONCLUSIONS

The present study demonstrated that BUB3, CDK1, and CHEK1 may serve as a prognostic biomarker for HCC patients. PTTG2, RAD21, and MAD1L1 expression is a major factor affecting the recurrence of HCC patients.

Identification of key candidate genes and pathways in anaplastic thyroid cancer by bioinformatics analysis

BACKGROUND

Anaplastic thyroid carcinoma (ATC) is a refractory and poor prognosis tumor Present study aimed to investigate the underlying biological functions and pathways involved in the development of ATC and to identify potential hub genes and candidate biomarkers of ATC.

MATERIALS AND METHODS

Bioinformatics analyses were performed to identify the differentially expressed genes (DEGs) between ATC tissue samples and adjacent normal tissue samples. Protein-protein interaction (PPI) networks of the DEGs were constructed using Search Tool for the Retrieval of Interacting Genes online tool and Cytoscape software and divided into sub-networks using the Molecular Complex Detection (MCODE) plug-in. DEGs in each module was analyzed by enrichment analysis of the KEGG Orthology Based Annotation System (KOBAS) web software version 3.0. Eventually, the hub genes from bioinformatics analysis were verified by qRT-PCR assay in different ATC cell lines.

RESULTS

Thirty hub genes were selected and three modules were built by the Cytoscape software from the PPI network. Seven genes (CDK1, CCNB2, BUB1B, CDC20, RRM2, CHEK1 and CDC45) were screened from thirty hub genes. Enrichment analysis showed that these hub genes were primarily accumulated in 'cell cycle', 'p53 signaling pathway', 'viral carcinogenesis', 'pyrimidine metabolism' and 'ubiquitin mediated proteolysis'. The results of qRT-PCR indicated that seven hub genes were unregulated in three ATC cell lines compared with normal thyroid gland cell.

CONCLUSIONS

These findings suggest that CDK1, CCNB2, BUB1B, CDC20, RRM2, CHEK1 and CDC45 may serve as novel diagnosis biomarkers and potential therapeutic target for ATC.

CDK1-PLK1/SGOL2/ANLN pathway mediating abnormal cell division in cell cycle may be a critical process in hepatocellular carcinoma

This study aims to investigate the potential mechanisms and identify core biomarkers of Hepatocellular carcinoma (HCC). The profile GSE113850 was downloaded to analyze the differentially expressed genes. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction network analysis were used to reveal the main signal pathways of the differentially expressed genes (DEGs) and hub genes. The correlation between core gene expression and pathological stages, the disease-free survival analysis, the overall survival analysis were analyzed by Gene Expression Profiling Interactive Analysis. Furthermore, we reidentified the expression level of core genes of carcinoma tissues and para-carcinoma tissues from 14 HCC patients with real-time reverse transcription-polymerase chain reaction analysis (RT-PCR) and western blotting. After SK-Hep1 cell was treated with cyclin-dependent kinase 1 (CDK1) siRNA for 72 h, we detected the expression of the core genes and fluorescence-activated cell sorting analysis. A total of 378 DEGs were found. GO and KEGG analysis revealed that the DEGs were mainly enriched in the cell cycle. There were positive correlations among CDK1, polo-like kinase 1, shugoshin2 and anillin actin-binding protein. Moreover, the expression levels of four core genes were related to the HCC occurrence, pathological stages, and survivorship curve. The clinical HCC specimens verified the higher expression level of core genes by real-time RT-PCR. The transfection of siCDK1 in SK-Hep1 resulted in a disordered cell cycle. Furthermore, CDK1 knockdown suppressed the expression of PLK1, ANLN, and SGOL2. The CDK1-PLK1/SGOL2/ANLN pathway mediating abnormal cell division in the cell cycle might be a critical process in HCC.

The Role of Apoptin in Chicken Anemia Virus Replication

Apoptin is the Vp3 protein of chicken anemia virus (CAV), which infects the thymocytes and erythroblasts in young chickens, causing chicken infectious anemia and immunosuppression. Apoptin is highly studied for its ability to selectively induce apoptosis in human tumor cells and, thus, is a protein of interest in anti-tumor therapy. CAV apoptin is known to localize to different subcellular compartments in transformed and non-transformed cells, depending on the DNA damage response, and the phosphorylation of several identified threonine residues. In addition, apoptin interacts with molecular machinery such as the anaphase promoting complex/cyclosome (APC/C) to inhibit the cell cycle and induce arrest in G2/M phase. While these functions of apoptin contribute to the tumor-selective effect of the protein, they also provide an important fundamental framework to apoptin’s role in viral infection, pathogenesis, and propagation. Here, we reviewed how the regulation, localization, and functions of apoptin contribute to the viral life cycle and postulated its importance in efficient replication of CAV. A model of the molecular biology of infection is critical to informing our understanding of CAV and other related animal viruses that threaten the agricultural industry.

Bioinformatics Analysis based on Multiple Databases Identifies Hub Genes Associated with Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common liver cancer and the mechanisms of hepatocarcinogenesis remain elusive.

Objective

This study aims to mine hub genes associated with HCC using multiple databases.

Methods

Data sets GSE45267, GSE60502, GSE74656 were downloaded from GEO database. Differentially expressed genes (DEGs) between HCC and control in each set were identified by limma software. The GO term and KEGG pathway enrichment of the DEGs aggregated in the datasets (aggregated DEGs) were analyzed using DAVID and KOBAS 3.0 databases. Protein-protein interaction (PPI) network of the aggregated DEGs was constructed using STRING database. GSEA software was used to verify the biological process. Association between hub genes and HCC prognosis was analyzed using patients' information from TCGA database by survminer R package.

Results

From GSE45267, GSE60502 and GSE74656, 7583, 2349, and 553 DEGs were identified respectively. A total of 221 aggregated DEGs, which were mainly enriched in 109 GO terms and 29 KEGG pathways, were identified. Cell cycle phase, mitotic cell cycle, cell division, nuclear division and mitosis were the most significant GO terms. Metabolic pathways, cell cycle, chemical carcinogenesis, retinol metabolism and fatty acid degradation were the main KEGG pathways. Nine hub genes (TOP2A, NDC80, CDK1, CCNB1, KIF11, BUB1, CCNB2, CCNA2 and TTK) were selected by PPI network and all of them were associated with prognosis of HCC patients.

Conclusion

TOP2A, NDC80, CDK1, CCNB1, KIF11, BUB1, CCNB2, CCNA2 and TTK were hub genes in HCC, which may be potential biomarkers of HCC and targets of HCC therapy.

Targeted Inhibitory Effect of Nasopharyngeal Carcinoma Cells by Hre2.Grp78 Chimeric Promoter Regulating Fusion Gene TK/VP3

Objective:

To construct plasmids with Hre₂.Grp78 chimeric promoter regulating fusion gene TK/VP3 and elaborate the effects of overexpressed TK/VP3 on nasopharyngeal carcinoma cells.

Methods:

Four plasmids were constructed, including pcDNA3.1-CMV-TK/VP3, pcDNA3.1-Hre₂.TK/VP3, pcDNA3.1-Grp78.TK/VP3, and pcDNA3.1-Hre₂.Grp78.TK/VP3. The human nasopharyngeal carcinoma cell line HNE1 cells were transfected with the 4 plasmids, respectively. Cell viabilities were evaluated using 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, and apoptosis was conducted using flow cytometry analysis. The expression of TK, VP3, Grp78, and hypoxia-inducible factor 1α and apoptosis-related proteins was determined by real-time quantitative polymerase chain reaction and Western blotting.

Results:

The recombinant plasmids that could steadily overexpress TK and VP3 were successfully constructed. Expression of TK and VP3 in cells transfected with pcDNA3.1-Hre₂.TK/VP3 and pcDNA3.1-Grp78.TK/VP3 was significantly higher than pcDNA3.1-CMV-TK/VP3, and expression in cells transfected with pcDNA3.1-Hre₂.Grp78.TK/VP3 was the highest. Under glucose deprivation or hypoxia condition, Grp78 or hypoxia-inducible factor 1α was overexpressed so that expression of TK and VP3 was significantly upregulated, which could further inhibit cell proliferation and enhance cell apoptosis.

Conclusion:

We successfully constructed 4 plasmids with Hre₂.Grp78 chimeric promoter regulating fusion gene TK/VP3, which could significantly inhibit the proliferation as well as enhance the apoptosis of nasopharyngeal carcinoma cells under glucose deprivation or hypoxia condition.

Identification of Key Genes and Prognostic Value Analysis in Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

Emerging evidence indicates that various functional genes with altered expression are involved in the tumor progression of human cancers. This study is aimed at identifying novel key genes that may be used for hepatocellular carcinoma (HCC) diagnosis, prognosis, and targeted therapy. This study included 3 expression profiles (GSE45267, GSE74656, and GSE84402), which were obtained from the Gene Expression Omnibus (GEO). GEO2R was used to analyze the differentially expressed genes (DEGs) between HCC and normal samples. The functional and pathway enrichment analysis was performed by the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of the identified DEGs was constructed using the Search Tool for the Retrieval of Interacting Gene, and hub genes were identified. ONCOMINE and CCLE databases were used to verify the expression of the hub genes in HCC tissues and cells. Kaplan-Meier plotter was used to assess the effects of the hub genes on the overall survival of HCC patients. A total of 99 DEGs were identified from the 3 expression profiles. These DEGs were enriched with functional processes and pathways related to HCC pathogenesis. From the PPI network, 5 hub genes were identified. The expression of the 5 hub genes was all upregulated in HCC tissues and cells compared with the control tissues and cells. Kaplan-Meier survival curves indicated that high expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), cyclin B2 (CCNB2), MAD2 mitotic arrest deficient-like 1 (MAD2L1), and topoisomerase IIα (TOP2A) predicted poor overall survival in HCC patients (all log-rank P < 0.01). These results revealed that the DEGs may serve as candidate key genes during HCC pathogenesis. The 5 hub genes, including CDK1, CCNB1, CCNB2, MAD2L1, and TOP2A, may serve as promising prognostic biomarkers in HCC.

Role of cyclin-dependent kinases (CDKs) in hepatocellular carcinoma: Therapeutic potential of targeting the CDK signaling pathway

Liver cancer is the fourth leading cause of cancer related mortality in the world, with hepatocellular carcinoma (HCC) representing the most common primary subtype. Two-thirds of HCC patients have advanced disease when diagnosed, and for these patients, treatment strategies remain limited. In addition, there is a high incidence of tumor recurrence after surgical resection with the current treatment regimens. The development of novel and more effective agents is required. Cyclin-dependent kinases (CDKs) constitute a family of 21 different protein kinases involved in regulating cell proliferation, apoptosis, and drug resistance, and are evaluated in preclinical and clinical trials as chemotherapeutics. To summarize and discuss the therapeutic potential of targeting CDKs in HCC, recent published articles identified from PubMed were comprehensively reviewed. The key words included hepatocellular carcinoma, cyclin-dependent kinases, and CDK inhibitors. This review focuses on the emerging evidence from studies describing the genetic and functional aspects of CDKs in HCC. We also present an overview of CDK inhibitors that have shown efficacy in laboratory studies of HCC. Although many of the studies assessing CDK-targeting therapies in HCC are at the preclinical stage, there is significant evidence that CDK inhibitors used alone or in combination with established chemotherapy drugs could have significant applications in HCC.

Bioinformatics analysis to identify the key genes affecting the progression and prognosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer, which has poor outcome. The present study aimed to investigate the key genes implicated in the progression and prognosis of HCC. The RNA-sequencing data of HCC was extracted from The Cancer Genome Atlas (TCGA) database. Using the R package (DESeq), the differentially expressed genes (DEGs) were analyzed. Based on the Cluepedia plug-in in Cytoscape software, enrichment analysis for the protein-coding genes amongst the DEGs was conducted. Subsequently, protein–protein interaction (PPI) network was built by Cytoscape software. Using survival package, the genes that could distinguish the survival differences of the HCC samples were explored. Moreover, quantitative real-time reverse transcription-PCR (qRT-PCR) experiments were used to detect the expression of key genes. There were 2193 DEGs in HCC samples. For the protein-coding genes amongst the DEGs, multiple functional terms and pathways were enriched. In the PPI network, cyclin-dependent kinase 1 (CDK1), polo-like kinase 1 (PLK1), Fos proto-oncogene, AP-1 transcription factor subunit (FOS), serum amyloid A1 (SAA1), and lysophosphatidic acid receptor 3 (LPAR3) were hub nodes. CDK1 interacting with PLK1 and FOS, and LPAR3 interacting with FOS and SAA1 were found in the PPI network. Amongst the 40 network modules, 4 modules were with scores not less than 10. Survival analysis showed that anterior gradient 2 (AGR2) and RLN3 could differentiate the high- and low-risk groups, which were confirmed by qRT-PCR. CDK1, PLK1, FOS, SAA1, and LPAR3 might be key genes affecting the progression of HCC. Besides, AGR2 and RLN3 might be implicated in the prognosis of HCC.

Identification of the Pathogenic Biomarkers for Hepatocellular Carcinoma Based on RNA-seq Analyses

The purpose of this study was to explore potential biomarkers in the diagnosis of hepatocellular carcinoma (HCC) based on RNA-seq. The microarray data GSE98269 were downloaded from the GEO database, including the miRNA, mRNA and lncRNA expression profiles of 3 HCC tissues and 3 normal liver tissues from 3 HCC patients. The limma package was used to identify the differentially expressed miRNAs (DEMs) and the differentially expressed lncRNAs in HCC tissues compared with normal liver tissues. Database of DAVID, KEGG PATHWAY and Reactome were used to perform the functional and pathway enrichment. Putative targets for DEMs, and the miRNA-gene pairs were predicted via the miRWalk V2.0 database. The protein-protein pairs of DEGs were screened via String software. The expression features of the differentially expressed lncRNAs were analyzed. The regulated network of DEGs and DEMs were constructed, and related genes and miRNAs were detected in the HCC tissues and normal liver samples with Q-PCR. A total of 678 DEGs, 32 DEMs and 411 differential expressed lncRNAs were identified. The DEGs were enriched in 196 GO terms and 79 pathways. 38 negative regulation miRNA-gene pairs and 1205 protein-protein interactions were screened out, and the regulated network was constructed based on them. KNG1, CDK1, EHHADH, CYP3A4, hsa-miR-199a-5p and hsa-miR-455-3p might be biomarkers in the occurrence of HCC.

Assessment of in vivo genotoxicity of citrated-coated silver nanoparticles via transcriptomic analysis of rabbit liver tissue

Background

Silver nanoparticles (AgNPs) are widely used in industrial and household applications, arousing concern regarding their safety in humans. The risks posed by stabilizer-coated AgNPs continue to be unclear, and assessing their toxicity is for an understanding of the safety issues involved in their use in various applications.

Purpose

We aimed to investigated the long-term toxicity of citrate-coated silver nanoparticles (cAgNPs) in liver tissue using several toxicity tests and transcriptomic analysis at 7 and 28 days after a single intravenous injection into rabbit ear veins (n=4).

Materials and methods

The cAgNPs used in this study were in the form of a 20% (w/v) aqueous solution, and their size was 7.9±0.95 nm, measured using transmission electron microscopy. The animal experiments were performed based on the principles of good laboratory practice.

Results

Our results showed that the structure and function of liver tissue were disrupted due to a single exposure to cAgNPs. In addition, in vivo comet assay showed unrepaired genotoxicity in liver tissue until 4 weeks after a single injection, suggesting a potential carcinogenic effect of cAgNPs. In our transcriptomic analysis, a total of 244 genes were found to have differential expression at 28 days after a single cAgNP injection. Carefully curated pathway analysis of these genes using Pathway Studio and Ingenuity Pathway Analysis tools revealed major molecular networks responding to cAgNP exposure and indicated a high correlation of the genes with inflammation, hepatotoxicity, and cancer. Molecular validation suggested potential biomarkers for assessing the toxicity of accumulated cAgNPs.

Conclusion

Our investigation highlights the risk associated with a single cAgNP exposure with unrepaired damage persisting for at least a month.

Bioinformatics identification of crucial genes and pathways associated with hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a major cause of cancer-related death worldwide. Up to date, HCC pathogenesis has not been fully understood. The aim of the present study was to identify crucial genes and pathways associated with HCC by bioinformatics methods. The differentially expressed genes (DEGs) between 14 HCC tissues and corresponding non-cancerous tissues were identified using limma package. Gene Ontology (GO) and KEGG pathway enrichment analysis of DEGs were performed by clusterProfiler package. The protein-protein interaction (PPI) network of DEGs was constructed and visualized by STRING database and Cytoscape software, respectively. The crucial genes in PPI network were identified using a Cytoscape plugin, CytoNCA. Furthermore, the effect of the expression level of the crucial genes on HCC patient survival was analyzed by an interactive web-portal, UALCAN. A total of 870 DEGs including 237 up-regulated and 633 down-regulated genes were identified in HCC tissues. KEGG pathway analysis revealed that DEGs were mainly enriched in complement and coagulation cascades pathway, chemical carcinogenesis pathway, retinol metabolism pathway, fatty acid degradation pathway, and valine, leucine and isoleucine degradation pathway. PPI network analysis showed that CDK1, CCNB1, CCNB2, MAD2L1, ACACB, IGF1, TOP2A, and EHHADH were crucial genes. Survival analysis suggested that the high expression of CDK1, CCNB1, CCNB2, MAD2L1, and TOP2A significantly decreased the survival probability of HCC patients. In conclusion, the identification of the above crucial genes and pathways will not only contribute to elucidating the pathogenesis of HCC, but also provide prognostic markers and therapeutic targets for HCC.

LncRNA PVT1 regulates growth, migration, and invasion of bladder cancer by miR-31/ CDK1

PURPOSE

The aim of our study was to validate the sway of long noncoding RNA (lncRNA) plasmacytoma variant translocation 1 (PVT1) on the metabolism and growth of bladder cancer cells by microRNA-31 (miR-31)/cyclin-dependent kinase 1 ( CDK1).

METHODS

The Gene Expression Omnibus database was used for analyzing the differentially expressed lncRNA and messenger RNA (mRNA) in bladder cancer tissues, with the highly expressed lncRNA PVT1 and mRNA CDK1 screened out. The expression level of PVT1 was detected by quantitative reverse-transcription polymerase chain reaction, cell viability by Cell Counting Kit-8 assay, cell proliferation and scratch by 5-bromo-2'-deoxyuridine assay, cell migration and invasion by transwell assays, the expression level of CDK1 by immunohistochemistry and western blot analysis, transcription factor targeting by dual-luciferase assay, and the effect of PVT1 on bladder cancer growth by nude mice tumor formation experiment.

RESULTS

LncRNA PVT1 and mRNA CDK1 had a higher expression in bladder cancer cells than that in neighboring tissues. Activity, proliferation, colony formation, migration, and invasion of bladder cancer cell were noticeably reduced by the PVT1 inhibitor than that of control group. PVT1 and CDK1 have binding sites with miR-31. When miR-31 decreased, CDK1 mRNA and protein levels increased in vivo experiments in nude mice. When PVT1 was downregulated, the tumor size was significantly reduced and tumor proliferation was curbed. Immunohistochemistry showed that the positive rate of CDK1 and Ki-67 decreased and the expression of miR-31 increased after PVT1 was inhibited.

CONCLUSIONS

LncRNA PVT1 was overexpressed in bladder cancer cells, and it was downregulated miR-31 to enhance CDK1 expression and facilitate bladder cancer cells proliferation, migration, and invasion.

Overexpression of CBX3 in Pancreatic Adenocarcinoma Promotes Cell Cycle Transition-Associated Tumor Progression

BACKGROUND

Previous studies showed that Chromobox protein homolog 3 (CBX3) was overexpressed in several types of human cancers, however its pattern and role in pancreatic adenocarcinoma (PAAD) has not yet been understood. The aim of this study was to identify the expression and function of CBX3 in PAAD.

METHODS

Data of transcriptomic and protein expression of CBX3 in PAAD were collected from different databases and analyzed. The in vitro and in vivo role of CBX3 in PAAD was examined.

RESULTS

CBX3 was overexpressed in human PAAD tissues, which was associated with poor prognosis of overall and disease-free survival of the patients. Overexpression of CBX3 induced the in vitro proliferation, anchorage-free growth, migration and invasion of the PAAD cells, and led to in vivo growth of orthotoptic PAAD tumors in mice. GO and KEGG pathway analysis, as well as experimental observation showed that CBX3 may be associated with cell cycle transition of PAAD cells, and cyclin-dependent kinase 1 (CDK1) and proliferating cell nuclear antigen (PCNA) may mediate the tumor-promoting action of CBX3. CDK1 knockdown attenuated the cell cycle transition, proliferation and invasion of CBX3-overexpressing PAAD cells.

CONCLUSION

Our findings suggest the tumor-promoting role of CBX3 in PAAD to be targeted by novel therapeutic strategies.

Expression of the Long Intergenic Non-Protein Coding RNA 665 (LINC00665) Gene and the Cell Cycle in Hepatocellular Carcinoma Using The Cancer Genome Atlas, the Gene Expression Omnibus, and Quantitative Real-Time Polymerase Chain Reaction

Background

Long non-coding RNAs (lncRNAs) have a role in physiological and pathological processes, including cancer. The aim of this study was to investigate the expression of the long intergenic non-protein coding RNA 665 (LINC00665) gene and the cell cycle in hepatocellular carcinoma (HCC) using database analysis including The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and quantitative real-time polymerase chain reaction (qPCR).

Material/Methods

Expression levels of LINC00665 were compared between human tissue samples of HCC and adjacent normal liver, clinicopathological correlations were made using TCGA and the GEO, and qPCR was performed to validate the findings. Other public databases were searched for other genes associated with LINC00665 expression, including The Atlas of Noncoding RNAs in Cancer (TANRIC), the Multi Experiment Matrix (MEM), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) networks.

Results

Overexpression of LINC00665 in patients with HCC was significantly associated with gender, tumor grade, stage, and tumor cell type. Overexpression of LINC00665 in patients with HCC was significantly associated with overall survival (OS) (HR=1.47795%; CI: 1.046–2.086). Bioinformatics analysis identified 469 related genes and further analysis supported a hypothesis that LINC00665 regulates pathways in the cell cycle to facilitate the development and progression of HCC through ten identified core genes: CDK1, BUB1B, BUB1, PLK1, CCNB2, CCNB1, CDC20, ESPL1, MAD2L1, and CCNA2.

Conclusions

Overexpression of the lncRNA, LINC00665 may be involved in the regulation of cell cycle pathways in HCC through ten identified hub genes.

Key signaling pathways, genes and transcription factors associated with hepatocellular carcinoma

The purpose of the present study was to investigate the underlying molecular mechanism of hepatocellular carcinoma (HCC) using bioinformatics approaches. The microarray dataset GSE64041 was downloaded from the Gene Expression Omnibus database, which included 60 tumor liver samples and 60 matched control samples. Differentially expressed genes (DEGs) between HCC and control groups were identified. Then functional enrichment analyses, protein‑protein interaction (PPI) network, sub‑network and integrated transcription factor (TF)‑microRNA (miRNA)‑target network analyses were performed for these DEGs. A total of 378 DEGs were obtained, including 101 upregulated and 277 downregulated DEGs. In addition, functional enrichment analysis for DEGs in the sub‑network revealed 'cell division' and 'cell cycle' as key Gene Ontology (GO) terms and pathways. Topoisomerase (DNA) IIα (TOP2A) and integrin subunit α2 (ITGA2) were hub nodes in the PPI network. TOP2A, cyclin dependent kinase 1 (CDK1) and polo like kinase 1 (PLK1) were revealed to be hub nodes in the sub‑network. Finally, 4 TFs including forkhead box M1 (FOXM1), E2F transcription factor 4 (E2F4), SIN3 transcription regulator family member A (SIN3A) and transcription factor 7 like 1 (TCF7L1) were obtained through integrated network analysis. TOP2A, ITGA2, PLK1 and CDK1 may be key genes involved in HCC development. 'Cell division' and 'cell cycle' were indicated to act as key GO terms and Kyoto Encyclopedia of Genes and Genomes pathways in HCC. In addition, FOXM1, TCF7L1, E2F4 and SIN3A were revealed to be key TFs associated with HCC.

Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the pathogeny, but the molecular mechanisms of HCC are still not well understood. To identify the candidate genes in the carcinogenesis and progression of HCC, microarray datasets GSE19665, GSE33006 and GSE41804 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and function enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using STRING and Cytoscape. A total of 273 DEGs were identified, consisting of 189 downregulated genes and 84 upregulated genes. The enriched functions and pathways of the DEGs include protein activation cascade, complement activation, carbohydrate binding, complement and coagulation cascades, mitotic cell cycle and oocyte meiosis. Sixteen hub genes were identified and biological process analysis revealed that these genes were mainly enriched in cell division, cell cycle and nuclear division. Survival analysis showed that BUB1, CDC20, KIF20A, RACGAP1 and CEP55 may be involved in the carcinogenesis, invasion or recurrence of HCC. In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the carcinogenesis and progression of HCC, and provide candidate targets for diagnosis and treatment of HCC.

Bioinformatics analysis of key genes and pathways for hepatocellular carcinoma transformed from cirrhosis

OBJECTIVE

We aimed to identify some pivotal genes and pathways for hepatocellular carcinoma (HCC) transformation from cirrhosis and explore potential targets for treatment of the disease.

METHODS

The GSE17548 microarray data were downloaded from Gene Expression Omnibus database, and 37 samples (20 cirrhosis and 17 HCC samples) were used for analysis. The differentially expressed genes (DEGs) in HCC tissues were compared with those in cirrhosis tissues and analyzed using the limma package. Gene ontology-biological process and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were performed using ClueGO and CluePedia tool kits, and the key KEGG pathway was analyzed using the R package pathview. The regulatory factor miRNA of DEGs was extracted from 3 verified miRNAs-target databases using the multiMiR R package. Moreover, a protein-protein interaction (PPI) network was constructed using the Cytoscape software.

RESULTS

DEGs including cyclin-dependent Kinase 1 (CDK1), PDZ-binding kinase (PBK), ribonucleotide reductase M2 (RRM2), and abnormal spindle homolog, and microcephaly-associated drosophila (ASPM) were the hub proteins with higher degrees in the PPI network. The cell cycle pathway (CDK1 enriched) and p53 signaling pathway (CDK1 and RRM2 enriched) were significantly enriched by DEGs.

CONCLUSION

CDK1, PBK, RRM2, and ASPM may be key genes for HCC transformation from cirrhosis. Furthermore, cell cycle and p53 signaling pathways may play vital mediatory roles; CDK1 may play crucial roles in HCC transformed from cirrhosis via cell cycle and p53 signaling pathways, and RRM2 might be involved in HCC transformed from cirrhosis via the p53 signaling pathway.

Phosphorylation of nucleophosmin at threonine 234/237 is associated with HCC metastasis

Hepatocellular carcinoma (HCC) is frequently complicated by the occurrence of intrahepatic and extrahepatic metastases, leading to poor prognosis. To improve the prognosis for HCC patients, there is an urgent need to understand the molecular mechanisms of metastasis in HCC. Since protein Serine/Threonine phosphorylation emerges to be an important posttranslational modification critical in signaling process associated with cell proliferation, survival and metastasis, we employed a pair of primary tumor-derived and corresponding lung-metastatic counterparts (PLC/PRF/5-PT and PLC/PRF/5-LM) and aimed to identify these changes using CelluSpot™ Serine/Threonine kinase peptide array. Upon analysis, we found phosphorylated level of nucleophosmin (NPM) at Threonine 234/237 (p-NPM-Thr^234/237) had remarkably high level in metastatic HCC cells (PLC-LM) than the corresponding primary HCC cell line (PLC-PT). Similar observation was observed in another match primary and their metastatic counterparts (MHCC-97L and MHCC-97H). By immunohistochemical staining, p-NPM-Thr^234/237 was consistently found to be preferentially expressed in metastatic HCCs when compared with primary HCC in 28 HCC cases (p < 0.0001). By overexpressing Flag-tagged NPM and its phosphorylation site mutant (Thr234/237A) into low p-NPM-Thr^234/237 expressing cells (Hep3B and Huh7) using a lentiviral based approach, we demonstrated that p-NPM-Thr^234/237 is critical in invasion and migration of HCC cells, and this effect was mediated by cyclin-dependent kinase 1 (CDK1). Wild-type NPM was found to physically interact with a metastatic gene, ROCK2, and defective in Thr234/237 phosphorylation decreased its binding affinity, resulting in decrease in ROCK2 mediated signaling pathway. Identification of CDK1/p-NPM/ROCK2 signaling pathway provides a novel target for molecular therapy against HCC metastasis.

Dipeptide-functionalized polyamidoamine dendrimer-mediated apoptin gene delivery facilitates apoptosis of human primary glioma cells

Glioblastoma multiform (GBM) is the most frequent and aggressive form of brain tumors in adults. However, the development of more efficient and safe nonviral vector gene therapy represents a promising therapeutic approach, using a tumor-specific killer gene, named apoptin. In this study, we describe the efficacy of non-viral gene delivery vectors, the amino acid-conjugated PAMAM derivatives (PAMAM-H-R and PAMAM-H-K) in delivering a therapeutic gene, displaying affinity toward human primary glioma cells (GBL-14 cells) and dermal fibroblasts. We analyzed transfection efficiency, using luciferase (Luci) and a pDNA encoding for enhanced fluorescent protein (EGFP), and cytotoxicity in both cells. The results show that transfection efficiency of PAMAM-H-R improved compared to native PAMAM dendrimer, but cytotoxicity of PAMAM-H-R and PAMAM-H-K were very low. We treated both cells with a polyplex formation of PAMAM-H-R or PAMAM-H-K/apoptin, and analyzed their cellular uptake and localization by flow cytometry and confocal microscopy. Furthermore, we analyzed the endosomal escape effect using TEM images, and found that PAMAM-H-R showed very fast escape from endosome to the cytosol. Caspase 3 activity assay, cell cycle distribution, and JC-1 analysis showed apoptosis induced by apoptin in GBL-14 cells. This indicates that PAMAM-H-R can be a potential nonviral vector gene delivery carrier for brain tumor therapy. The present study demonstrates that PAMAM-H-R/apoptin gene polyplex can be used as an effective therapeutic candidate for GBM due to its selective induction of apoptosis in primary glioma cells as a potential nonviral gene delivery carrier for brain tumor therapy.

Recurrent CDK1 overexpression in laryngeal squamous cell carcinoma

In this study, we analyzed the expression profile of four genes (CCNA2, CCNB1, CCNB2, and CDK1) in laryngeal squamous cell carcinoma (LSCC) cell lines and tumor samples. With the application of microarray platform, we have shown the overexpression of these genes in all analyzed LSCC samples in comparison to non-cancer controls from head and neck region. We have selected CDK1 for further analysis, due to its leading role in cell cycle regulation. It is a member of the Ser/Thr protein kinase family of proven oncogenic properties. The results obtained for CDK1 were further confirmed with the application of reverse transcription quantitative polymerase chain reaction (RT-qPCR) technique, Western blot, and immunohistochemistry (IHC). The observed upregulation of CDK1 in laryngeal squamous cell carcinoma has encouraged us to analyze for genetic mechanisms that can be responsible this phenomenon. Therefore, with the application of array-CGH, sequencing analysis and two methods for epigenetic regulation analysis (DNA methylation and miRNA expression), we tried to identify such potential mechanisms. Our attempts to identify the molecular mechanisms responsible for observed changes failed as we did not observe significant alterations neither in the DNA sequence nor in the gene copy number that could underline CDK1 upregulation. Similarly, the pyrosequencing and miRNA expression analyses did not reveal any differences in methylation level and miRNA expression, respectively; thus, these mechanisms probably do not contribute to elevation of CDK1 expression in LSCC. However, our results suggest that alteration of CDK1 expression on both mRNA and protein level probably appears on the very early step of carcinogenesis.

miR-582-5p inhibits proliferation of hepatocellular carcinoma by targeting CDK1 and AKT3

microRNAs play an important role in the progression of hepatocellular carcinoma (HCC). In this study, we found that miR-582-5p expression was downregulated in hepatoma tissues and HCC cell lines. Upregulation of miR-582-5p reduced colony number, inhibited cellular proliferation, and arrested cell cycle in G0/G1 phase. When miR-582-5p was inhibited, the colony number was increased and cellular proliferation and cell cycle were promoted. Further studies showed that miR-582-5p regulated the progression of HCC through directly inhibiting the expression of CDK1 and AKT3, and indirectly inhibiting the expression of cyclinD1.