Identification of Key Genes Associated With the Process of Hepatitis B Inflammation and Cancer Transformation by Integrated Bioinformatics Analysis

CCNA2 and NEK2 regulate glioblastoma progression by targeting the cell cycle

Glioblastoma (GBM) is characterized by significant heterogeneity, leading to poor survival outcomes for patients, despite the implementation of comprehensive treatment strategies. The roles of cyclin A2 (CCNA2) and NIMA related kinase 2 (NEK2) have been extensively studied in numerous cancers, but their specific functions in GBM remain to be elucidated. The present study aimed to investigate the potential molecular mechanisms of CCNA2 and NEK2 in GBM. CCNA2 and NEK2 expression and prognosis in glioma were evaluated by bioinformatics methods. In addition, the distribution of CCNA2 and NEK2 expression in GBM subsets was determined using pseudo-time analysis and tricycle position of single-cell sequencing. Gene Expression Omnibus and Kyoto Encyclopedia of Genes and Genome databases were employed and enrichment analyses were conducted to investigate potential signaling pathways in GBM subsets and a nomogram was established to predict 1-, 2- and 3-year overall survival probability in GBM. CCNA2 and NEK2 expression levels were further validated by western blot analysis and immunohistochemical staining in GBM samples. High expression of CCNA2 and NEK2 in glioma indicates poor clinical outcomes. Single-cell sequencing of GBM revealed that these genes were upregulated in a subset of positive neural progenitor cells (P-NPCs), which showed significant proliferation and progression properties and may activate G2M checkpoint pathways. A comprehensive nomogram predicts 1-, 2- and 3-year overall survival probability in GBM by considering P-NPCs, age, chemotherapy and radiotherapy scores. CCNA2 and NEK2 regulate glioblastoma progression by targeting the cell cycle, thus indicating the potential of novel therapy directed to CCNA2 and NEK2 in GBM.

Comprehensive analysis and validation reveal DEPDC1 as a potential diagnostic biomarker associated with tumor immunity in non-small-cell lung cancer

Current evidence suggests that DEP domain containing 1 (DEPDC1) has an important effect on non-small-cell lung cancer (NSCLC). However, the diagnostic value and the regulatory function within NSCLC are largely unclear. This work utilized publicly available databases and in vitro experiments for exploring, DEPDC1 expression, clinical features, diagnostic significance and latent molecular mechanism within NSCLC. According to our results, DEPDC1 was remarkably upregulated in the tissues of NSCLC patients compared with non-carcinoma tissues, linked with gender, stage, T classification and N classification based on TCGA data and associated with smoking status and stage according to GEO datasets. Meanwhile, the summary receiver operating characteristic (sROC) curve analysis result showed that DEPDC1 had a high diagnostic value in NSCLC (AUC = 0.96, 95% CI: 0.94-0.98; diagnostic odds ratio = 99.08, 95%CI: 31.91-307.65; sensitivity = 0.89, 95%CI: 0.81-0.94; specificity = 0.92, 95%CI: 0.86-0.96; positive predictive value = 0.94, 95%CI: 0.89-0.98; negative predictive value = 0.78, 95%CI: 0.67-0.90; positive likelihood ratio = 11.77, 95%CI: 6.11-22.68; and negative likelihood ratio = 0.12, 95%CI: 0.06-0.22). Subsequently, quantitative real-time PCR (qRT-PCR) and western blotting indicated that DEPDC1 was high expressed in NSCLC cells. According to the in vitro MTS and apoptotic assays, downregulated DEPDC1 expression targeting P53 signaling pathway inhibited the proliferation of NSCLC cells while promoting apoptosis of NSCLC cells. Moreover, DEPDC1 was significantly correlated with immune cell infiltrating levels in NSCLC based on TCGA data, which were primarily associated with T cells CD4 memory activated, macrophages M1, B cells memory, mast cells resting, T cells regulatory, monocytes, and T cells CD4 memory resting. Compared with the group with high expression of DEPDC1, the group with low expression level had higher scores for immune checkpoint inhibitors (ICIs) treatment. GSEA confirmed that DEPDC1 was involved in gene expression and tumor-related signaling pathways. Finally, DEPDC1 and its associated immune-related genes were shown to be enriched in 'receptor ligand activity', 'external side of plasma membrane', 'regulation of innate immune response', and 'Epstein-Barr virus infection' pathways. The present study demonstrates that DEPDC1 may contribute to NSCLC tumorigenesis and can be applied as the biomarker for diagnosis and immunology.

AhR may be involved in Th17 cell differentiation in chronic hepatitis B

Th17 cells which are crucial for host immunity have been demonstrated to increase HBV infection. However, the mechanism of the Th17 cell increase is unknown. Hence, the mechanism of Th17 cell enhancement is important to provide a theoretical foundation for chronic hepatitis B immunotherapy. This study included 15 instances in the healthy control (HC) and 15 cohorts in the chronic hepatitis B (CHB). Their CD4+ T cells were isolated from their peripheral blood and then subjected to RNA transcriptome sequencing. Then, to identify target genes linked to Th17-cell differentiation, DEGs associated with CHB were convergent with the Th17-cell-associated genes from the KEGG database. Hub genes of DEG and target genes linked to Th17 cells were analysed for correlation. The AhR-related genes were located using the GeneMANIA database. To analyse the function of the genes, GO and KEGG pathways were employed. Protein-protein interaction network analysis employed the Metascape, STRING and Cytoscape databases. Finally, Western blotting and RT-qPCR were used to validate AhR. A total of 348 differential genes were identified in CHB patients. CytoHubba was used for screening five hub genes associated with CHB: CXCL10, RACGAP1, TPX2, FN1 and GZMA. This study aimed to determine the mechanism of elevated Th17 cells in CHB. As a result, further investigation using the convergence of DGEs and Th17 cell-related genes identified three target genes: AhR, HLA-DQA1 and HLA-DQB1, all of which were elevated in CHB. The three genes were primarily involved in immune response-related processes, according to the GO enrichment analysis. Correlation analysis of CXCL10, RACGAP1, TPX2, FN1 and GZMA genes with AhR, HLA-DQA1 and HLA-DQB1 revealed that AhR was positively associated with CXCL10 and GZMA genes, which best respond to the severity of CHB disease. Combined with the role of AhR in Th17 cell differentiation, the genes AhR was chosen for confirmation by RT-qPCR and WB in this study. The results showed that the CHB group had higher expression levels of AhR at both RT-qPCR and WB levels. Furthermore, this study's findings revealed that AhR may contribute to the development of CHB by affecting the differentiation of Th17 cells.

Chromosome hyperploidy induced by chronic hepatitis B virus infection and its targeted therapeutic strategy

Chronic hepatitis B virus (HBV) infection induces chromosomal hyperploidy (including aneuploidy and polyploidy) and chromosomal instability in hepatocytes, which is one of the main causes of primary hepatocellular carcinoma (HCC). Although hepatocytes can regulate polyploidization of chromosomes under normal conditions, it is difficult to regulate hyperploidization caused by HBV infection and thus carcinogenesis. Studies have shown that HBV can cause dysregulation of many signal pathways such as PLK1/PRC1, and induce chromosome hyperploidy and malignant transformation of hepatocytes. Herein we review the mechanism of HBV infection-induced chromosomal hyperploidy of hepatocytes to cuase hepatocarcinogenesis and the advances in research of drugs targeting chromosomal hyperploidy.

Key genes associated with non-alcoholic fatty liver disease and hepatocellular carcinoma with metabolic risk factors

Background: Hepatocellular carcinoma (HCC) has become the world's primary cause of cancer death. Obesity, hyperglycemia, and dyslipidemia are all illnesses that are part of the metabolic syndrome. In recent years, this risk factor has become increasingly recognized as a contributing factor to HCC. Around the world, non-alcoholic fatty liver disease (NAFLD) is on the rise, especially in western countries. In the past, the exact pathogenesis of NAFLD that progressed to metabolic risk factors (MFRs)-associated HCC has not been fully understood. Methods: Two groups of the GEO dataset (including normal/NAFLD and HCC with MFRs) were used to analyze differential expression. Differentially expressed genes of HCC were verified by overlapping in TCGA. In addition, functional enrichment analysis, modular analysis, Receiver Operating Characteristic (ROC) analysis, LASSO analysis, and Genes with key survival characteristics were analyzed. Results: We identified six hub genes (FABP5, SCD, CCL20, AGPAT9(GPAT3), PLIN1, and IL1RN) that may be closely related to NAFLD and HCC with MFRs. We constructed survival and prognosis gene markers based on FABP5, CCL20, AGPAT9(GPAT3), PLIN1, and IL1RN.This gene signature has shown good diagnostic accuracy in both NAFLD and HCC and in predicting HCC overall survival rates. Conclusion: As a result of the findings of this study, there is some guiding significance for the diagnosis and treatment of liver disease associated with NAFLD progression.

The Core-Targeted RRM2 Gene of Berberine Hydrochloride Promotes Breast Cancer Cell Migration and Invasion via the Epithelial-Mesenchymal Transition

Berberine hydrochloride (BBR) could inhibit the proliferation, migration, and invasion of various cancer cells. As the only enzyme for the de novo synthesis of ribonucleotides, RRM2 is closely related to the development of tumorigenesis. However, not much is currently known about the functional roles of RRM2 in breast cancer (BRCA), and whether BBR regulates the migration and invasion of BRCA cells by regulating the expression of RRM2 remains to be determined. We study the effects of BBR on BRCA cell proliferation in vitro and tumorigenesis in vivo by using colony formation assays, EdU assays, and xenograft models. Transcriptome sequencing, the random forest algorithm, and KEGG analysis were utilized to explore the therapeutic target genes and relative pathways. The expression of RRM2 in BRCA patients was analyzed with The Cancer Genome Atlas (TCGA) dataset, the GEPIA website tool, the Gene Expression Omnibus (GEO) database, and the UALCAN database. The survival probability of BRCA patients could be predicted by survival curve and nomogram analysis. Molecular docking was used to explore the affinity between BBR and potential targets. Gain- and loss-of-function methods were employed to explore the biological process in RRM2 participants. We comprehensively investigated the pharmacological characteristics of BBR on BRCA cell lines and discovered that BBR could inhibit the proliferation of BRCA cells in vitro and in vivo. Combining transcriptome sequencing and KEGG analysis, we found that BBR mainly affected the biological behavior of BRCA cells via HIF-1α and AMPK signal pathways. Additionally, by using bioinformatics and molecular docking, we demonstrated that RRM2 plays an oncogenic role in BRCA samples and that it acts as the hub gene of BBR on BRCA cells. Knockdown and overexpression studies indicated that RRM2 promoted BRCA cell migration as well as invasion in vitro by affecting the epithelial-to-mesenchymal transition (EMT). Our study demonstrated the significance of BBR regulating HIF-1α and AMPK signaling pathways in BRCA cells. Moreover, we revealed the carcinogenic role and potential mechanism of RRM2 as a core regulatory factor of BBR in BRCA in controlling BRCA invasion, migration, and EMT, suggesting that RRM2 may be a therapeutic target and prognostic biomarker for BRCA therapy.

Significance of Identifying Key Genes Involved in HBV-Related Hepatocellular Carcinoma for Primary Care Surveillance of Patients with Cirrhosis

Cirrhosis is frequently the final stage of disease preceding the development of hepatocellular carcinoma (HCC) and is one of the risk factors for HCC. Preventive surveillance for early HCC in patients with cirrhosis is advantageous for achieving early HCC prevention and diagnosis, thereby enhancing patient prognosis and reducing mortality. However, there is no highly sensitive diagnostic marker for the clinical surveillance of HCC in patients with cirrhosis, which significantly restricts its use in primary care for HCC. To increase the accuracy of illness diagnosis, the study of the effective and sensitive genetic biomarkers involved in HCC incidence is crucial. In this study, a set of 120 significantly differentially expressed genes (DEGs) was identified in the GSE121248 dataset. A protein-protein interaction (PPI) network was constructed among the DEGs, and Cytoscape was used to extract hub genes from the network. In TCGA database, the expression levels, correlation analysis, and predictive performance of hub genes were validated. In total, 15 hub genes showed increased expression, and their positive correlation ranged from 0.80 to 0.90, suggesting they may be involved in the same signaling pathway governing HBV-related HCC. The GSE10143, GSE25097, GSE54236, and GSE17548 datasets were used to investigate the expression pattern of these hub genes in the progression from cirrhosis to HCC. Using Cox regression analysis, a prediction model was then developed. The ROC curves, DCA, and calibration analysis demonstrated the superior disease prediction accuracy of this model. In addition, using proteomic analysis, we investigated whether these key hub genes interact with the HBV-encoded oncogene X protein (HBx), the oncogenic protein in HCC. We constructed stable HBx-expressing LO2-HBx and Huh-7-HBx cell lines. Co-immunoprecipitation coupled with mass spectrometry (Co-IP/MS) results demonstrated that CDK1, RRM2, ANLN, and HMMR interacted specifically with HBx in both cell models. Importantly, we investigated 15 potential key genes (CCNB1, CDK1, BUB1B, ECT2, RACGAP1, ANLN, PBK, TOP2A, ASPM, RRM2, NEK2, PRC1, SPP1, HMMR, and DTL) participating in the transformation process of HBV infection to HCC, of which 4 hub genes (CDK1, RRM2, ANLN, and HMMR) probably serve as potential oncogenic HBx downstream target molecules. All these findings of our study provided valuable research direction for the diagnostic gene detection of HBV-related HCC in primary care surveillance for HCC in patients with cirrhosis.

FOXM1 is regulated by DEPDC1 to facilitate development and metastasis of oral squamous cell carcinoma

The Disheveled, EGL-10, Pleckstrin domain containing 1 (DEPDC1) is a new oncogene that has recently been described. The mechanisms and functions of its expression are yet to be determined in oral squamous cell carcinoma (OSCC). In the present study, the impact of DEPDC1 on the growth and development of OSCC was investigated using animal models, cell lines and human tissue samples. Elevated DEPDC1 expression within cancer cell lines and human OSCC has been identified. Mechanistic examination showed that restored DEPDC1 expression in vivo and in vitro stimulated OSCC tumour development. In addition, FOXM1 interacts with DEPDC1 as indicated by co-immunoprecipitation and immunofluorescence testing. Functionally, DEPDC1 facilitated Wnt/β-catenin signal transduction and β-catenin protein nuclear expression. In summary, the DEPDC1, interacting with FOXM1 via Wnt/β-catenin signaling, the closely regulated OSCC pathogenesis, suggesting that targeting the novel DEPDC1/FOXM1/β-catenin complex is an essential OSCC therapeutic approach.

Identification and Validation of Inflammatory Response-Related Gene Signatures to Predict the Prognosis of Neuroblastoma

Background. Neuroblastoma (NB) is the third most common malignant tumor in children. The inflammation is believed to be closely related to NB patients’ prognosis. However, there is no comprehensive research to study the role of inflammatory response-related gene (IRRG) in NB patients. Methods. We downloaded the gene expression profiles of NB patients from GEO and TARGET database, and the expression of 200 IRRGs was extracted. Then, we performed differentially analysis between INSS stage 4 and INSS stage 4S NB patients. The univariate and multivariate Cox regression analyses were performed to screen out the overall survival- (OS-) and event-free survival- (EFS-) related IRRGs in GSE49710, and two signatures were constructed; both signatures were evaluated by Kaplan-Meier (K-M) survival curve and receiver operating characteristic (ROC) curve. Finally, the TARGET cohort was used to validate IRRG signatures, and the independence of the prognostic IRRG signatures was evaluated by integrating clinical information. Results. We screened out 10 OS-related IRRGs and 11 EFS-related IRRGs. Then, we identified that OS- and EFS-related IRRG signatures and found that the OS and EFS of NB patients in the low-risk group were significantly superior than those in the high-risk group (both $P$ value < 0.0001). The AUC values of 3-, 5-, and 7-year OS are 0.910, 0.933, and 0.921, respectively, and 3-, 5-, and 7-year EFS are 0.840, 0.835, and 0.837, respectively. In addition, we found that both IRRG signatures can be used as independent prognostic indicators for patients with NB. Both IRRG signatures still have good predictive ability in validation cohort. Conclusions. We constructed and validated two prognostic gene signatures based on IRRGs. Our study helped us to better understand the role of inflammation in NB and provided new insights for the prognosis assessment and treatment strategy for NB patients.