Identification and validation of immune-related methylated genes as diagnostic and prognostic biomarkers of nasopharyngeal carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a common malignancy occurring in the head and neck. Identification of immune-related methylated biomarkers might be helpful for NPC detection and prognostic evaluation. METHODS: A co-methylation network based on WGCNA was constructed to identify modules associated with NPC and immune cells. In combination with differentially expressed genes (DEGs) and immune-related genes from ImmPort database, the candidate immune-related methylated genes (IRMGs) were obtained. RESULTS: Our combined analysis identified 12 IRMGs. Among them, both the methylation and mRNA expression of CCL28, CSK, and PRKCB were correlated with the infiltration of B cells. CD1D, CR2, and GDF10 were favorable markers. Demethylation experiments validated that downregulation of GDF10, PRKCB, SLC40A1, and TGFBR3 in NPC resulted from promoter hypermethylation. Additionally, a diagnostic model was developed and exhibited high discriminative accuracy. CONCLUSIONS: These results provided a group of immune-related methylated biomarkers that may help with the diagnosis and prognosis of NPC.

Integrated network pharmacology, bioinformatics, and molecular docking to explore the mechanisms of berberine regulating autophagy in breast cancer.

Berberine exhibits anticancer efficacy against a variety of malignancies, including breast cancer (BRCA). However, the underlying mechanism is ambiguous. This study sought to explore the targets and the probable mechanism of berberine regulating autophagy in BRCA through network pharmacology, bioinformatics, and molecular docking. The targets of berberine and autophagy-modulated genes were derived from online databases, and the Cancer Genome Atlas database was used to identify the differentially expressed genes of BRCA. Then, through intersections, the autophagy-modulated genes regulated by berberine (AMGRBs) in BRCA were obtained. Next, we established a protein-protein interaction network using the Search Tool for the Retrieval of Interacting Genes database. Afterward, gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were employed to explore the targets' biological functions. Additionally, molecular docking was conducted to verify the binding ability of berberine to the targets. Finally, to determine the prognostic value of AMGRBs in BRCA, we performed overall survival analyses. We identified 29 AMGRBs in BRCA, including CASP3, MTOR, AKT1, GSK3B, PIK3CA, and others. Gene ontology enrichment analysis showed that the AMGRBs in BRCA were associated with autophagy regulation, negative regulation of catabolic process, macroautophagy, and other biological processes. Kyoto encyclopedia of genes and genomes enrichment analyses indicated that AMGRBs in BRCA were involved in epidermal growth factor receptor tyrosine kinase inhibitor resistance, PI3K/Akt signaling pathway, JAK-STAT signaling pathway, and others. Molecular docking results proved that berberine had strong binding affinities with AMGRBs in BRCA. Survival analyses indicated that ATM, HTR2B, LRRK2, PIK3CA, CDK5, and IFNG were associated with the prognosis of BRCA. This study identified the targets and pathways of berberine for regulating autophagy in BRCA, which contributed to a better understanding of berberine's function in BRCA and serve as a foundation and reference for further study and therapeutic application of berberine.

Prevalence and Risk Factors Associated with Hyperuricemia in the Pearl River Delta, Guangdong Province, China.

BACKGROUND: In China, the prevalence of HUA in the Pearl River Delta (PRD) region of Guangdong Province has not been extensively investigated. Therefore, this study investigated the prevalence of HUA and its related factors among people aged 20-99 years in nine cities in the PRD. MATERIALS AND METHODS: We selected 6491 health check participants from 9 cities in the PRD and collected participants' anthropometric and biochemical test results for a cross-sectional study. We included 6491 participants and assessed their blood pressure (BP), body mass index (BMI), total cholesterol (TC), triglycerides (TG), glucose (Glu) and serum uric acid (UA) to analyze the regional prevalence of HUA and its related factors. HUA was indicated when fasting serum UA level was >420 µmol/L in men and >360 µmol/L in women. RESULTS: Overall prevalence of HUA in our cohort was 34.05%; prevalence was higher in men than in women (41.53% vs 26.14%, P < 0.001). Characteristics associated with HUA were hypertension (odds ratio (OR), 5.506; 95% confidence interval (CI), 4.402-6.889), higher body mass index (BMI; OR: 1.746; 95% CI: 1.560-1.954), age 31-40 years (OR: 0.829; 95% CI: 0.706-0.973), age 61-70 years (OR: 1.434; 95% CI: 1.194-1.722) and age ≥71 years (OR: 1.742; 95% CI: 1.397-2.173). In all subjects, serum UA was positively correlated with Glu, TG and TC. After we adjusted for age, BMI and BP, multivariate logistic regression analysis showed that HUA risk factors were high TC (OR: 1.770; 95% CI: 1.459-2.147) and TG (OR: 1.961; 95% CI: 1.632-2.357) in men; and high Glu (OR: 1.508; 95% CI: 1.084-2.099), TC (OR: 1.341; 95% CI: 1.084-1.660) and TG (OR: 1.680; 95% CI: 1.290-2.187) in women. CONCLUSION: The prevalence of HUA was relatively high in the PRD of Guangdong Province. Relevant governmental bodies should focus on early diagnosis, early treatment and early intervention.

Prediction Biomarkers Associated with Lymph Node Metastasis and Prognosis were Identified in Papillary Thyroid Carcinoma via Integrated Bioinformatics Analysis.

BACKGROUND: Prediction biomarkers associated with prognosis and lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) are needed to facilitate clinicians in choosing appropriate therapies. OBJECTIVE: We hope to identify key genes associated with LNM and prognosis in PTC. METHODS: GSE29265, GSE33630, GSE3467, GSE3678 and GSE58545 gene expression profiles were acquired from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between PTC tissues and normal thyroid tissues were selected with the GEO2R tool, and common DEGs among the five datasets were integrated with Venn software online. A proteinprotein interaction (PPI) network of the common DEGs was visualized. We analyzed the PPI network and determined core genes using the Cytoscape software. Furthermore, we employed UALCAN to verify the expression and promoter methylation status of the core genes in thyroid carcinoma (THCA). Additionally, the Kaplan-Meier plotter online tool was used to analyze the relationship between overall survival and core gene expressions in THCA. RESULTS: TNS3, DUSP6, DUSP4 and PTPRE were identified as core genes. Expression of these 4 genes and the promoter methylation status of DUSP4 and PTPRE were strongly associated with LNM (P<0.05). High expression of 3 genes (DUSP6, DUSP4 and PTPRE) was related to a significantly better survival than low expression of the 3 genes in THCA. In contrast, high TNS3 expression was related to significantly worse survival (P<0.05). CONCLUSION: TNS3, DUSP6, DUSP4, PTPRE and DUSP4 and PTPRE promoter methylation status might be useful predictive biomarkers of LNM in PTC. Additionally, these genes may be prognostic biomarkers in PTC.

Construction and Analysis of lncRNA-Mediated ceRNA Network in Nasopharyngeal Carcinoma Based on Weighted Correlation Network Analysis.

Increasing evidence indicated that aberrant expression of long noncoding RNAs (lncRNAs) are involved in tumorigenesis of nasopharyngeal carcinoma (NPC). The purpose of this study was to construct a lncRNA-mediated ceRNA network based on weighted correlation network analysis (WGCNA). First, modules with highly correlated genes were identified from GSE102349 via WGCNA, and the preservation of the modules was evaluated by GSE68799. Then, the differentially expressed lncRNAs and mRNAs identified from GSE12452 which belonged to the same WGCNA modules and the differentially expressed miRNAs identified from GSE32960 were used to construct a ceRNA network. The prognostic value of the network was evaluated by survival analysis. Furthermore, a risk score model for predicting progression-free survival (PFS) of NPC patients was established via LASSO-penalized Cox regression, and the differences in the expression of the lncRNAs between high- and low-risk groups were investigated. Finally, 14 stable modules were identified, and a ceRNA network composed of 11 lncRNAs, 15 miRNAs, and 40 mRNAs was established. The lncRNAs and mRNAs in the network belonged to the turquoise and salmon modules. Survival analysis indicated that ZNF667-AS1, LDHA, LMNB2, TPI1, UNG, and hsa-miR-142-3p were significantly correlated with the prognosis of NPC. Gene set enrichment analysis indicated that the upregulation of ZNF667-AS1 was associated with some immune-related pathways. Besides, a risk score model consisting of 12 genes was constructed and showed a good performance in predicting PFS for NPC patients. Among the 11 lncRNAs in the ceRNA network, SNHG16, SNHG17, and THAP9-AS1 were upregulated in the high-risk group of NPC, while ZNF667-AS1 was downregulated in the high-risk group of NPC. These results will promote our understanding of the crosstalk among lncRNAs, miRNAs, and mRNAs in the tumorigenesis and progression of NPC.

Identification of tumor-infiltrating immune cells and microenvironment-relevant genes in nasopharyngeal carcinoma based on gene expression profiling.

AIMS: The purpose of this study was to investigate the prognostic significance of tumor-infiltrating immune cells and microenvironment-relevant genes in nasopharyngeal carcinoma (NPC) and their correlations. MATERIALS AND METHODS: The "xCell" algorithm was used to calculate the enrichment scores for 33 immune cells in the samples of GSE12452, GSE40290, GSE53819, GSE68799, and GSE102349. The difference of immune cells between NPC group and non-cancerous group and the prognostic value of the immune cells were analyzed. Besides, based on the Microenvironment scores, the differentially expressed genes (DEGs) between the high- and low-score groups were screened to identify the microenvironment-relevant hub genes. Furthermore, the DEGs were used to establish a risk score model for predicting progression-free survival (PFS) via LASSO penalized Cox regression. KEY FINDINGS: The scores of B-cells and Memory B-cells of NPC were significantly lower than those of non-cancerous tissues, and they were positively associated with PFS. Moreover, 10 hub genes (PTPRC, CD19, CD79B, BTK, CD79A, SELL, MS4A1, CD38, CD52, and CD22) were identified and positively correlated with B-cells, Memory B-cells, and Microenvironment scores in GSE12452, GSE68799, and GSE102349. High expression levels of CD22, CD38, CD79B, MS4A1, SELL, and PTPRC were associated with longer PFS. Besides, a risk score model composed of DARC, IL33, IGHG1, and SLC6A8 was established with a good performance for PFS prediction. SIGNIFICANCE: These results enhance our understanding of the composition and prognostic significance of tumor-infiltrating immune cells in NPC lesions, and provide potential targets for prognostication and immunotherapy for NPC patients.

Key genes involved in cell cycle arrest and DNA damage repair identified in anaplastic thyroid carcinoma using integrated bioinformatics analysis.

BACKGROUND: Since anaplastic thyroid carcinoma (ATC) has rapid progression and a poor outcome, identification of the key genes and underlying mechanisms of ATC is required. METHODS: Gene expression profiles of GSE29265 and GSE33630 were available from the Gene Expression Omnibus database. The two profile datasets included 19 ATC tissues, 55 normal thyroid tissues and 59 papillary thyroid cancer (PTC) tissues. Differentially expressed genes (DEGs) between ATC tissues and normal thyroid tissues as well as ATC tissues and PTC tissues were identified using the GEO2R tool. Common DEGs between the two datasets were selected via Venn software online. Then, we applied the Database for Annotation, Visualization and Integrated Discovery for Kyoto Encyclopedia of Gene and Genome pathway and gene ontology (GO) analyses. Additionally, protein-protein interactions (PPIs) of these DEGs were visualized via Cytoscape with Search Tool for the Retrieval of Interacting Genes. In the PPI networks analyzed by the Molecular Complex Detection plug-in, all 54 upregulated core genes were selected. Furthermore, Kaplan-Meier analysis was applied to analyze overall survival based on these 54 genes. Then, we used the DrugBank database to identify drug relationships for the 54 genes. Additionally, we validated the correlations between genes enriched in pathways and genes identified as prognosis biomarkers of THCA by Gene Expression Profiling Interactive Analysis. RESULTS: Four genes (CCNB1, CCNB2, CDK1 and CHEK1) involved cell cycle arrest and DNA repair were significantly enriched in the G2/M phase of the cell cycle pathway and before G2 phase arrest of the P53 pathway. Inhibitors of CHEK1, CDK1 and TOP2A were identified in the DrugBank database. ANLN, DEPDC1, KIF2C, CENPN, TACC3 CCNB2 and CDC6 were hypothesized to be prognostic biomarkers of ATC. Furthermore, CCNB1, CCNB2, CDK1 and CHEK1 were significantly positively associated with these prognosis genes. CONCLUSIONS: CCNB1, CCNB2, CDK1 and CHEK1 may be key genes involved cell cycle arrest and DNA damage repair in ATC. Further studies are required to confirm the contributions of the identified genes to ATC progression and survival.

Investigation of differentially expressed genes in nasopharyngeal carcinoma by integrated bioinformatics analysis.

Nasopharyngeal carcinoma (NPC) is a common malignancy of the head and neck. The aim of the present study was to conduct an integrated bioinformatics analysis of differentially expressed genes (DEGs) and to explore the molecular mechanisms of NPC. Two profiling datasets, GSE12452 and GSE34573, were downloaded from the Gene Expression Omnibus database and included 44 NPC specimens and 13 normal nasopharyngeal tissues. R software was used to identify the DEGs between NPC and normal nasopharyngeal tissues. Distributions of DEGs in chromosomes were explored based on the annotation file and the CYTOBAND database of DAVID. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied. Additionally, a protein-protein interaction (PPI) network, constructed using the STRING database and visualized by Cytoscape, was used to identify hub genes, key modules and important transcription factors (TFs). A total of 906 DEGs were identified; 434 (47.90%) DEGs were upregulated and 472 (52.10%) were downregulated. The DEGs were demonstrated to be enriched in chromosome 7p15-p14, 2q31, 1q21-q22, 1q21, 4q21 and 1p31-p22. DEGs were mainly enriched for the following GO terms: 'Cilium movement', 'microtubule bundle formation' and 'axoneme assembly'. KEGG pathway enrichment analysis revealed that pathways for 'cell cycle', 'DNA replication', 'interleukin-17 signaling', 'amoebiasis' and 'glutathione metabolism' were enriched. In addition, a PPI network comprising 867 nodes and 1,241 edges was constructed. Finally, five hub genes (aurora kinase A, cell division cycle 6, mitotic arrest deficient 2-like 1, DNA topoisomerase 2α and TPX2 microtubule nucleation factor), 8 modules, and 14 TFs were identified. Modules analysis revealed that cyclin-dependent kinase 1 and exportin 1 were involved in the pathway of Epstein-Barr virus infection. In summary, the hub genes, key modules and TFs identified in this study may promote our understanding of the pathogenesis of NPC and require further in-depth investigation.

[Prognostic value of circulating tumor cells and disseminated tumor cells in patients with esophageal cancer: a meta-analysis].

OBJECTIVE: To explore the correlations of circulating tumor cells (CTCs) and disseminated tumor cells (DTCs) with the clinicopathological characteristics, prognostic events, and survival outcomes in esophageal cancer (EC) patients. METHODS: The PubMed, Web of Science, Embase database and Cochrane database were searched for studies reporting the outcomes of interest. The studies were selected according to established inclusion/exclusion criteria. Meta-analysis of the studies was performed using Review Manager 5.3 and Stata12.0 software with the odds ratio (OR), risk ratio (RR) , hazard ratio (HR) , and 95% confidence interval (95% CI) as the effect indexes. RESULTS: Nineteen studies involving a total of 1766 patients were included in the analysis. Significant correlations of CTCs and DTCs were found with the clinicopathological parameters including the tumor stage (OR=1.95), depth of invasion (OR=1.99), lymph node metastasis (OR=2.44SEN), distal metastasis (OR=5.98SEN), histological differentiation (OR=1.67) and lymphovascular invasion (OR=4.48). CTCs and DTCs were also correlated with the prognostic events including relapse (RR=6.86SEN) and metastasis (RR=3.22) and with the survival outcomes including the overall survival (OS) overall analysis (HR=3.46) and disease-free survival/progression-free survival (DFS/PFS) overall analysis (HR=3.00). CONCLUSION: CTCs and DTCs are significantly associated with an advanced tumor stage, depth of tumor invasion, lymph node metastasis, distant metastasis before therapy, differentiation, lymphovascular invasion, relapse and metastasis in patients with EC. They are also significantly correlated with a poorer survival for OS and DFS/PFS to serve as clinical and prognostic predictors in patients with EC.

Malignant transformation rate and p53, and p16 expression in teratomatous skin of ovarian mature cystic teratoma.

OBJECTIVE: To investigate the incidence of malignant transformation and P53 and P16 expression in teratomatous skin of ovarian mature cystic teratoma. MATERIALS AND METHODS: Data on ovarian teratoma specimens in nearly 10 years were reviewed. P53 and P16 expression were detected by immunohistochemistry in 25 cases of teratomatous skin of ovarian mature cystic teratoma, 20 cases of squamous cell carcinoma and 2 cases of squamous cell carcinoma originated from teratomatous skin. RESULTS: Of 1913 cases of ovarian mature cystic teratoma in nearly 10 years, only two cases of squamous cell carcinoma were found in teratomatous skin, with malignant transformation rate of 0.1045%. P53 expression was detected in 2 cases squamous cell carcinoma originated from teratomatous skin and P16 overexpression in one. There were no expressions of P53 and P16 in 25 cases of teratomatous skin of ovarian mature cystic teratoma. Of 20 cases of squamous cell carcinoma P53 overexpression (positive rate of 55%) was detected in 11 cases, P16 overexpression (positive rate of 35%) in 7 cases. The positive rates of P53 and P16 expression in squamous cell carcinomas were significantly higher than that in the teratomatous skins (p< 0.001, p= 0.002). CONCLUSIONS: There was low risk of malignant transformation in teratomatous skin of ovarian mature cystic teratoma which can be explained by lower P53 and P16 expressionin teratomas than that in squamous cell carcinoma.

XPD Lys751Gln and Asp312Asn polymorphisms and susceptibility to skin cancer: a meta-analysis of 17 case-control studies.

BACKGROUND: Numerous studies have explored the influence of XPD Lys751Gln and/or Asp312Asn polymorphisms on skin cancer susceptibility. However, the results remain inconclusive. To derive a more precise estimation, we conducted a comprehensive search to identify all available published studies and performed a meta-analysis. MATERIALS AND METHODS: Electronic literature searches of the PubMed, CBM and CNKI databases were performed up to March 2014. Odds ratios (ORs) with 95% confidence intervals (CIs) were applied to assess the strength of associations. RESULTS: Seventeen case-control studies were included with a total sample size of 6, 113 cases and 11, 074 controls for the XPD Lys751Gln polymorphism, and 10 studies (3, 840cases and 7, 637 controls) for the XPD Asp312Asn polymorphism were pooled for analysis. Overall, no significant associations were found between the XPD Lys751Gln polymorphism and skin cancer risk in any genetic model. On stratified analysis by tumor type, XPD Lys751Gln polymorphism was not associated with increased risk of non-melanoma skin cancer, but was significantly related with increased risk of cutaneous melanoma (Gln/Gln vs Lys/Lys: OR=1.15, 95%CI=1.02-1.29, p=0.023; dominant model: OR=1.09, 95%CI=1.01-1.18, p=0.036). For the XPD Asp312Asn polymorphism, no significant association with skin cancer risk was observed in overall or subgroup analyses. CONCLUSIONS: The present meta-analysis suggests that the XPD Lys751Gln polymorphism may contribute to the risk of cutaneous melanoma from currently available evidence. Further investigations are needed to obtain more insight into possible roles of these two polymorphisms in skin carcinogenesis.