Identification of genes and pathways in nasopharyngeal carcinoma by bioinformatics analysis

Using the genomic adjusted radiation dose (GARD) to personalize the radiation dose in nasopharyngeal cancer

BACKGROUND

Locally advanced nasopharyngeal cancer (NPC) patients undergoing radiotherapy are at risk of treatment failure, particularly locoregional recurrence. To optimize the individual radiation dose, we hypothesize that the genomic adjusted radiation dose (GARD) can be used to correlate with locoregional control.

METHODS

A total of 92 patients with American Joint Committee on Cancer / International Union Against Cancer stage III to stage IVB recruited in a randomized phase III trial were assessed (NPC-0501) (NCT00379262). Patients were treated with concurrent chemo-radiotherapy plus (neo) adjuvant chemotherapy. The primary endpoint is locoregional failure free rate (LRFFR).

RESULTS

Despite the homogenous physical radiation dose prescribed (Median: 70 Gy, range 66-76 Gy), there was a wide range of GARD values (median: 50.7, range 31.1-67.8) in this cohort. In multivariable analysis, a GARD threshold (GARDT) of 45 was independently associated with LRFFR (p = 0.008). By evaluating the physical dose required to achieve the GARDT (RxRSI), three distinct clinical subgroups were identified: (1) radiosensitive tumors that RxRSI at dose < 66 Gy (N = 59, 64.1 %) (b) moderately radiosensitive tumors that RxRSI dose within the current standard of care range (66-74 Gy) (N = 20, 21.7 %), (c) radioresistant tumors that need a significant dose escalation above the current standard of care (>74 Gy) (N = 13, 14.1 %).

CONCLUSION

GARD is independently associated with locoregional control in radiotherapy-treated NPC patients from a Phase 3 clinical trial. GARD may be a potential framework to personalize radiotherapy dose for NPC patients.

Construction of diagnostic and prognostic models based on gene signatures of nasopharyngeal carcinoma by machine learning methods

Background

Diagnostic models based on gene signatures of nasopharyngeal carcinoma (NPC) were constructed by random forest (RF) and artificial neural network (ANN) algorithms. Least absolute shrinkage and selection operator (Lasso)-Cox regression was used to select and build prognostic models based on gene signatures. This study contributes to the early diagnosis and treatment, prognosis, and molecular mechanisms associated with NPC.

Methods

Two gene expression datasets were downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) associated with NPC were identified by gene expression differential analysis. Subsequently, significant DEGs were identified by a RF algorithm. ANN were used to construct a diagnostic model for NPC. The performance of the diagnostic model was evaluated by area under the curve (AUC) values using a validation set. Lasso-Cox regression examined gene signatures associated with prognosis. Overall survival (OS) and disease-free survival (DFS) prediction models were constructed and validated from The Cancer Genome Atlas (TCGA) database and the International Cancer Genome Consortium (ICGC) database.

Results

A total of 582 DEGs associated with NPC were identified, and 14 significant genes were identified by the RF algorithm. A diagnostic model for NPC was successfully constructed using ANN, and the validity of the model was confirmed on the training set AUC =0.947 [95% confidence interval (CI): 0.911-0.969] and the validation set AUC =0.864 (95% CI: 0.828-0.901). The 24-gene signatures associated with prognosis were identified by Lasso-Cox regression, and prediction models for OS and DFS of NPC were constructed on the training set. Finally, the ability of the model was validated on the validation set.

Conclusions

Several potential gene signatures associated with NPC were identified, and a high-performance predictive model for early diagnosis of NPC and a prognostic prediction model with robust performance were successfully developed. The results of this study provide valuable references for early diagnosis, screening, treatment and molecular mechanism research of NPC in the future.

Effects of SENP1-induced deSUMOylation of STAT1 on proliferation and invasion in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is the most common nasopharyngeal squamous cell carcinoma, and recurrence and metastasis are still difficult problems in its current treatment. This study aimed to investigate the effect of SUMO modification of STAT1 protein on the proliferation and invasion of NPC, and to reveal the underlying mechanism. Two gene expression profiles (GSE12452 and GSE53819) of 49 nasopharyngeal carcinomas and 28 normal controls were analyzed to identify differentially expressed genes. In total, 448 up-regulated genes and 622 down-regulated genes were identified. In addition, 16 SUMO-related molecules in the NPC dataset GSE102349 with survival data were analyzed, and it was found that the high expression of SENP1 and SENP2 was closely related to the poor prognosis of NPC. GO and GSEA analysis suggested that immune-related biological processes, IFN-γ-STAT signaling pathway and protein modification-related molecules were significantly enriched in NPC, resulting in poor survival prognosis. In order to verify the results of bioinformatics analysis and explore its underlying molecular mechanisms, western blot, Immunofluorescence, Immunoprecipitation and Immunohistochemistry are conducted in NPC cells, animals and clinical samples. SENP1 and STAT protein levels were increased in NPC tissues. SENP1 inhibited SUMOylation of STAT1, thereby promoting the protein level of STAT1 and the nuclear translocation. SENP1 promoted the proliferation and invasion of NPC by inducing STAT1. Overall, SENP1-induced deSUMOylation of STAT1, resulting in an increased proliferation and invasion of nasopharyngeal carcinoma.

Whole exome sequencing identifies the potential role of genes involved in p53 pathway in Nasopharyngeal Carcinoma from Northeast India

Nasopharyngeal Carcinoma (NPC) found to be dependent on geographical and racial variation and is more prevalent in Northeast (NE) India. WES-based study was conducted in three states (tribes); Nagaland (Naga), Mizoram (Mizo) and Manipur (Manipuri), which provided an overview of germline variants involved inthemajor signaling pathways. Validation and recurrence assessment of WES data confirmed the risk effect of STEAP3_rs138941861 and JAG1_rs2273059, and the protective role of PARP4_rs17080653 and TGFBR1_rs11568778 variants, where STEAP3_rs138941861conferring Arg290His substitution was the only exonic non-synonymous variant and to be located in proximity to the linking region between the transmembrane and oxidoreductasedomainsof STEAP3 protein, andaffectedits structural and functional dynamics by altering the Electrostatic Potential around this connecting region. Moreover, these significantly associated variants having deleterious effect were observed to have interactions in p53 signaling pathway which emphasizes the importance of this pathway in the causation of NPC.

Cell Proliferation and Apoptosis-Related Genes Affect the Development of Human Nasopharyngeal Carcinoma Through PI3K/AKT Signaling Pathway

Nasopharyngeal carcinoma (NPC) is one of the common malignant tumors in China, which occurs on the top and sidewalls of the nasopharyngeal cavity. The incidence of malignant tumors of the ear, nose and throat is the highest. However, little is known about the growth of the cells. Therefore, this study constructed a multi-regulator-driven NPC cell growth-related module, aiming to explore the mechanism of functional pathways regulating the proliferation of NPC cells in an all-round way. Firstly, differential expression analysis, co-expression analysis, enrichment analysis and connectivity analysis were synthesized to identify the intrinsic genes of expression disorder module. Subsequently, we analyzed the module by crosstalk, and observed the interaction between modules intuitively. Finally, based on hypergeometric test, the significance of multi-regulators on the regulation of potential modules is calculated. We obtained 17 cell growth-related expression disorder modules by 2148 gene modules focusing. These modules are mainly involved in the growth cycle of NPC cells, including cell proliferation, migration and apoptosis. At the same time, they mainly affect the proliferation and apoptosis of NPC cells through PI3K-AKT signaling pathway, NF-kappa B signaling pathway and Wnt signaling pathway. Based on the growth-related modules of NPC cells, we have obtained a series of non-coding RNAs (ncRNAs) including microRNA-92a-3p, microRNA-19a-3p and microRNA-130a-3p, play an important role in regulating the growth of NPC cells. Similarly, we also predicted transcription factors (involving E2F1, NFKB1, SP1, etc.) that may play a key role in cell growth-related modules. This study is based on cell growth-related expression disorder module to explore the regulatory role of its functional pathway on cell proliferation mechanism, which will help researchers to have a deeper understanding of the potential pathogenesis of NPC.

ΔNp63α is a super enhancer-enriched master factor controlling the basal-to-luminal differentiation transcriptional program and gene regulatory networks in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) originates via malignant transformation of the pseudostratified nasopharyngeal epithelium, composed of basal and luminal cells. Super enhancers (SEs) are large clusters of cis-elements involved in the regulation of gene expression through epigenetic regulatory mechanisms. In this study, we demonstrated that basal cell-specific proteins are highly expressed, whereas luminal cell proteins are downregulated in NPC, implying a perturbation of basal-to-luminal differentiation during NPC development. We characterized NPC cell models according to different molecular signatures associated with their differentiation status and found that distinct SE landscapes are tightly associated with basal or luminal-like molecular signatures in NPC cells. Furthermore, the transcription of ΔNP63α, a prominent isoform of TP63, was found to be driven by SEs in NPC cells. Data from chromatin immunoprecipitation (ChIP)-sequencing showed that ΔNP63α largely occupied regions of SEs associated with basal cell-specific genes. Silencing of ΔNP63α led to a loss of H3K27ac occupancy at basal-type SEs and triggered a basal-to-luminal gene expression signature switch, suggesting that ΔNP63α is a master factor contributing to the perturbation of luminal differentiation. Integrative transcriptomics analysis also revealed that ΔNP63α acts as a core factor involved in the dysregulation of gene expression in NPC. Furthermore, ΔNP63α enhanced EGF-stimulated NF-κB activation in NPC cells by activating SE-mediated EGFR transcription. Finally, depletion of ΔNP63α in NPC cells induced robust growth inhibition of NPC cells in vitro and in vivo. Our data revealed that ΔNP63α-dependent SE reprogramming contributes to the blockade of luminal differentiation and uncontrolled proliferation in NPC.

RNA-binding protein YBX1 promotes cell proliferation and invasiveness of nasopharyngeal carcinoma cells via binding to AURKA mRNA

Background: RNA-binding proteins (RBPs) play essential roles in post-transcriptional control of gene expression. Dysregulation of RBPs is intensively implicated in development and progression of human diseases, including cancers. However, the roles of RBPs in nasopharyngeal carcinoma (NPC), which is a distinct subtype of head and neck cancer, remain elusive. Methods: NPC-related RBPs were explored by analyzing GEO database and high-throughput proteomic data obtained from crosslinking immunoprecipitation. The expression levels of Y box binding protein 1 (YBX1) protein in NPC samples were measured by immunohistochemistry (IHC) staining. The association of YBX1 protein levels with prognosis of NPC patients was analyzed by Kaplan-Meier Plotter. The expression levels of YBX1 in NPC cells were inhibited by RNA interference. Cell growth was measured by CCK-8 assay. Cell mobility and invasiveness were measured by transwell assays. Tumorigenicity was measured by using a xenograft tumor assay. The expression levels of mRNAs or proteins were determined by qPCR or western blot assays, respectively. The mRNAs binding to YBX1 were determined by RNA immunoprecipitation (RIP) and qPCR. The effect of YBX1 on mRNA translation was measured by luciferase reporter assay. Results: In the present study, we demonstrated a differentially expressed RBPs profile between NPC and its normal counterpart. Among these aberrantly expressed RBPs, YBX1 was overexpressed in NPC. We found that YBX1 is mainly localized in the cytoplasm of NPC cells. Loss of YBX1 led to reduced cell proliferation, migration and invasiveness in vitro, and reduced tumorigenicity in vivo. Overexpression of YBX1 associates with high expression of cell cycle G2/M checkpoint modulators. In addition, YBX1 promotes AURKA protein expression by directly binding to its mRNA. Loss of YBX1 leads to reduction of AURKA protein level. Forced expression of AURKA rescues cell proliferation and invasiveness in YBX1-silenced NPC cell. Conclusions: The current study indicated that YBX1 promotes NPC cell proliferation and invasiveness through enhancing protein synthesis of AURKA.

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.

Prediction of a competing endogenous RNA co-expression network as a prognostic marker in glioblastoma

Due to its high proliferation capacity and rapid intracranial spread, glioblastoma (GBM) has become one of the least curable malignant cancers. Recently, the competing endogenous RNAs (ceRNAs) hypothesis has become a focus in the researches of molecular biological mechanisms of cancer occurrence and progression. However, there is a lack of correlation studies on GBM, as well as a lack of comprehensive analyses of GBM molecular mechanisms based on high‐throughput sequencing and large‐scale sample sizes. We obtained RNA‐seq data from The Cancer Genome Atlas (TCGA) and Genotype‐Tissue Expression (GTEx) databases. Further, differentially expressed mRNAs were identified from normal brain tissue and GBM tissue. The similarities between the mRNA modules with clinical traits were subjected to weighted correlation network analysis (WGCNA). With the mRNAs from clinical‐related modules, a survival model was constructed by univariate and multivariate Cox proportional hazard regression analyses. Thereafter, we carried out Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, we predicted interactions between lncRNAs, miRNAs and mRNAs by TargetScan, miRDB, miRTarBase and starBase. We identified 2 lncRNAs (NORAD, XIST), 5 miRNAs (hsa‐miR‐3613, hsa‐miR‐371, hsa‐miR‐373, hsa‐miR‐32, hsa‐miR‐92) and 2 mRNAs (LYZ, PIK3AP1) for the construction of a ceRNA network, which might act as a prognostic biomarker of GBM. Combined with previous studies and our enrichment analysis results, we hypothesized that this ceRNA network affects immune activities and tumour microenvironment variations. Our research provides novel aspects to study GBM development and treatment.

Cellular expression profiles of Epstein-Barr virus-transformed B-lymphoblastoid cell lines

Epstein-Barr virus (EBV) can infect human B cells and is associated with various types of B cell lymphomas. Studies on the global alterations of the cellular pathways mediated by EBV-induced B cell transformation are limited. In the present study, microarray analysis was performed following generation of two EBV-infected B-lymphoblastoid cell lines (BLCL), in which normal B cells obtained from two healthy Thai individuals and transcriptomic profiles were compared with their respective normal B cells. The two EBV-transformed BLCL datasets exhibited a high degree of similarity between their RNA expression profiles, whereas the two normal B-cell datasets did not exhibit the same degree of similarity in their RNA expression profiles. Differential gene expression analysis was performed, and the results showed that EBV infection was able to dysregulate several cellular pathways in the human B-cell genes involved in cancer and cell activation, such as the MAPK, WNT and PI3K-Akt signaling pathways, which were upregulated in the BLCL and were associated with increased cellular proliferation and immortalization of EBV-infected B cells. Expression of proteins located in the plasma membrane, which initiate a biological response to ligand binding, were also notably upregulated. Expression of genes involved in cell cycle control, the p53 signaling pathway and cellular senescence were downregulated. In conclusion, genes that were markedly upregulated by EBV included those involved in the acquisition of a tumorigenic phenotype of BLCL, which was positively correlated with several hallmarks of cancer.

Investigating the Role of Telomere and Telomerase Associated Genes and Proteins in Endometrial Cancer

Endometrial cancer (EC) is the commonest gynaecological malignancy. Current prognostic markers are inadequate to accurately predict patient survival, necessitating novel prognostic markers, to improve treatment strategies. Telomerase has a unique role within the endometrium, whilst aberrant telomerase activity is a hallmark of many cancers. The aim of the current in silico study is to investigate the role of telomere and telomerase associated genes and proteins (TTAGPs) in EC to identify potential prognostic markers and therapeutic targets. Analysis of RNA-seq data from The Cancer Genome Atlas identified differentially expressed genes (DEGs) in EC (568 TTAGPs out of 3467) and ascertained DEGs associated with histological subtypes, higher grade endometrioid tumours and late stage EC. Functional analysis demonstrated that DEGs were predominantly involved in cell cycle regulation, while the survival analysis identified 69 DEGs associated with prognosis. The protein-protein interaction network constructed facilitated the identification of hub genes, enriched transcription factor binding sites and drugs that may target the network. Thus, our in silico methods distinguished many critical genes associated with telomere maintenance that were previously unknown to contribute to EC carcinogenesis and prognosis, including NOP56, WFS1, ANAPC4 and TUBB4A. Probing the prognostic and therapeutic utility of these novel TTAGP markers will form an exciting basis for future research.

Emerging radiotherapy technologies and trends in nasopharyngeal cancer

Technology has always driven advances in radiotherapy treatment. In this review, we describe the main technological advances in radiotherapy over the past decades for the treatment of nasopharyngeal cancer (NPC) and highlight some of the pressing issues and challenges that remain. We aim to identify emerging trends in radiation medicine. These include advances in personalized medicine and advanced imaging modalities, standardization of planning and delineation, assessment of treatment response and adaptive re‐planning, impact of particle therapy, and role of artificial intelligence or automation in clinical care. In conclusion, we expect significant improvement in the therapeutic ratio of radiotherapy treatment for NPC over the next decade.

Identification of Potential Therapeutic Gene Markers in Nasopharyngeal Carcinoma Based on Bioinformatics Analysis

Nasopharyngeal carcinoma (NPC) is a common cancer found in the nasopharynx with high metastatic and invasive nature. Increasing evidences have identified the critical role of gene therapy in NPC treatment. Hence, this study was designed to identify specific gene markers that affected NPC progression through gene expression profile analysis. NPC‐related gene expression data set gene set enrichment (GSE)53819 were retrieved and analyzed to screen out differentially expressed genes (DEGs), followed by determination of their expression in noncancerous tissues and NPC specimens. Next, weighted gene co‐expression network analysis (WGCNA) was conducted on DEGs to obtain tumor‐associated gene modules. Genes in those modules were intersected with DEGs for gene ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis. Then protein‐protein interaction network of tumor‐associated genes was constructed to select genes most closely linked to NPC. Afterward, expression of chromosome 9 open reading frame 24 (c9orf24), primary ciliary dyskinesia protein 1 (PCDP1), and leucine‐rich repeat‐containing protein 46 (LRRC46) was detected in GSE53819 and further verified in GSE12452 and GSE64634. Differential analysis on GSE53819 found that 2,173 genes were aberrantly expressed in NPC, among which 917 genes are upregulated and 1,256 genes are downregulated. WGCNA showed that genes were enriched in 17 modules and 727 genes exhibited ectopic expression in NPC and enriched in cytokine‐cytokine receptor interaction, cytochrome P450, and chemical carcinogenesis signaling pathways, among which c9orf24, PCDP1, and LRRC46 were poorly expressed in NPC. Therefore, c9orf24, PCDP1, and LRRC46 might serve as prominent diagnostic markers for NPC, which presents new insights for NPC therapy.

miR-30a-3p Targets MAD2L1 and Regulates Proliferation of Gastric Cancer Cells

Purpose

This study was done to investigate the inhibition effects of miR-30a-3p on mitotic arrest deficient 2 like 1 (MAD2L1) expression and the proliferation of gastric cancer cells.

Patients and methods

Cluster analysis and the TCGA database were used to screen the key genes highly expressed in gastric cancer. Based on the LinkedOmics website, the correlation between the miR-30a-3p and the cell cycle-related target gene MAD2L1 in gastric cancer was analyzed. The mRNA and protein expression levels were detected with the quantitative real-time PCR and Western blot analysis. The cell proliferation and cell cycle were also detected and analyzed.

Results

Bioinformatics analysis showed that MAD2L1 was highly expressed in tumor tissues compared with normal tissues. Compared with normal tissues, the miR-30a-3p was significantly decreased in the gastric cancer tissues. Moreover, MAD2L1 was significantly negatively correlated with the miR-30a-3p expression. Furthermore, over-expression of miR-30a-3p decreased the expression of MAD2L1 at the protein level, which inhibited the proliferation of AGS and BGC-823 gastric cancer cells. In addition, the cell cycles of AGS and BGC-823 cells were arrested at the G0/G1 phase.

Conclusion

MAD2L1 is a pro-oncogene which is up-regulated in gastric cancer. The miR-30a-3p can down-regulate the MAD2L1 expression, inhibiting the proliferation of gastric cancer cells and affect the cell cycle.

Bioinformatics analysis to screen key genes in papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common type of thyroid carcinoma, and its incidence has been on the increase in recent years. However, the molecular mechanism of PTC is unclear and misdiagnosis remains a major issue. Therefore, the present study aimed to investigate this mechanism, and to identify key prognostic biomarkers. Integrated analysis was used to explore differentially expressed genes (DEGs) between PTC and healthy thyroid tissue. To investigate the functions and pathways associated with DEGs, Gene Ontology, pathway and protein-protein interaction (PPI) network analyses were performed. The predictive accuracy of DEGs was evaluated using the receiver operating characteristic (ROC) curve. Based on the four microarray datasets obtained from the Gene Expression Omnibus database, namely GSE33630, GSE27155, GSE3467 and GSE3678, a total of 153 DEGs were identified, including 66 upregulated and 87 downregulated DEGs in PTC compared with controls. These DEGs were significantly enriched in cancer-related pathways and the phosphoinositide 3-kinase-AKT signaling pathway. PPI network analysis screened out key genes, including acetyl-CoA carboxylase beta, cyclin D1, BCL2, and serpin peptidase inhibitor clade A member 1, which may serve important roles in PTC pathogenesis. ROC analysis revealed that these DEGs had excellent predictive performance, thus verifying their potential for clinical diagnosis. Taken together, the findings of the present study suggest that these genes and related pathways are involved in key events of PTC progression and facilitate the identification of prognostic biomarkers.

Bioinformatics analysis identifies hub genes and pathways in nasopharyngeal carcinoma

The aim of the present study was to identify genes associated with and the underlying mechanisms in nasopharyngeal carcinoma (NPC) using microarray data. GSE12452 and GSE34573 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. GEO2R was utilized to obtain differentially expressed genes (DEGs). In addition, the Database for Annotation, Visualization and Integrated Discovery was used to perform pathway enrichment analyses for DEGs using the Gene Ontology (GO) annotation along with the Kyoto Encyclopedia of Genes and Genomes (KEGG). Furthermore, Cytoscape was used to perform module analysis of the protein-protein interaction (PPI) network and pathways of the hub genes were studied. A total of 298 genes were ascertained as DEGs in the two datasets. To functionally categorize these DEGs, we obtained 82 supplemented GO terms along with 7 KEGG pathways. Subsequently, a PPI network consisting of 10 hub genes with high degrees of interaction was constructed. These hub genes included cyclin-dependent kinase (CDK) 1, structural maintenance of chromosomes (SMC) 4, kinetochore-associated (KNTC) 1, kinesin family member (KIF) 23, aurora kinase A (AURKA), ATAD (ATPase family AAA domain containing) 2, NDC80 kinetochore complex component, enhancer of zeste 2 polycomb repressive complex 2 subunit, BUB1 mitotic checkpoint serine/threonine kinase and protein regulator of cytokinesis 1. CDK1, SMC4, KNTC1, KIF23, AURKA and ATAD2 presented with high areas under the curve in receiver operator curves, suggesting that these genes may be diagnostic markers for nasopharyngeal carcinoma. In conclusion, it was proposed that CDK1, SMC4, KNTC1, KIF23, AURKA and ATAD2 may be involved in the tumorigenesis of NPC. Furthermore, they may be utilized as molecular biomarkers in early diagnosis of NPC.

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.

Bioinformatic identification of candidate biomarkers and related transcription factors in nasopharyngeal carcinoma

Background

The incidence of nasopharyngeal carcinoma (NPC) is rare, but a certain amount of mortality remains in NPC patients. Our study aimed to identify candidate genes as biomarkers for NPC screening, diagnosis, and therapy.

Methods

We investigated two microarray profile datasets GSE64634 and GSE12452 to screen the potential differentially expressed genes (DEGs) in NPC. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEGs were also performed. A protein-protein interaction (PPI) network of DEGs was constructed by STRING and visualized by Cytoscape software. The associated transcriptional factor regulatory network of the DEGs was also constructed.

Results

A total of 152 DEGs were identified from the GSE64634 and GSE12452 datasets, including 10 upregulated and 142 downregulated genes. Gene functional enrichment analysis indicated that these DEGs were enriched in the cilium movement, antimicrobial humoral response, O-glycan processing, mucosal immune response, carbohydrate transmembrane transporter activity, hormone biosynthetic process, neurotransmitter biosynthetic process, and drug metabolism-cytochrome P450 pathway. Five hub genes (DNALI1, RSPH4A, RSPH9, DNAI2, and ALDH3A1) and one significant module (score = 5.6) were obtained from the PPI network. Key transcriptional factors, such as SPI1, SIN3B, and GATA2, were identified with close interactions with these five hub DEGs from the gene-transcriptional factor network.

Conclusions

With the integrated bioinformatic analysis, numerous DEGs related to NPC were screened, and the hub DEGs we identified may be potential biomarkers for NPC.

Identification of key candidate genes and miRNA‑mRNA target pairs in chronic lymphocytic leukemia by integrated bioinformatics analysis

Chronic lymphocytic leukemia (CLL) is a malignant clonal proliferative disorder of B cells. Inhibition of cell apoptosis and cell cycle arrest are the main pathological causes of this disease, but its molecular mechanism requires further investigation. The purpose of the present study was to identify biomarkers for the early diagnosis and treatment of CLL, and to explore the molecular mechanisms of CLL progression. A total of 488 differentially expressed genes (DEGs) and 32 differentially expressed microRNAs (miRNAs; DEMs) for CLL were identified by analyzing the gene chips GSE22529, GSE39411 and GSE62137. Functional and pathway enrichment analyses of DEGs demonstrated that DEGs were mainly involved in transcriptional dysregulation and multiple signaling pathways, such as the nuclear factor‑κB and mitogen‑activated protein kinase signaling pathways. In addition, Cytoscape software was used to visualize the protein‑protein interactions of these DEGs in order to identify hub genes, which could be used as biomarkers for the early diagnosis and treatment of CLL. Cytoscape software was also used to analyze the association between the predicted target mRNAs of DEMs and DEGs and increase knowledge about the miRNA‑mRNA regulatory network associated with the progression of CLL. Taken together, the present study provided a bioinformatics basis for advancing our understanding of the pathogenesis of CLL by identifying differentially expressed hub genes, miRNA‑mRNA target pairs and molecular pathways. In addition, hub genes may be used as novel biomarkers for the diagnosis of CLL and to guide the selection of CLL drug combinations.

MicroRNA expression in cervical cancer: Novel diagnostic and prognostic biomarkers

Growing evidence has shown that a large number of miRNAs are abnormally expressed in cervical cancer (CC) tissues and play irreplaceable roles in tumorigenesis, progression, and metastasis. This study aimed to identify new biomarkers and pivotal genes associated with CC prognosis through comprehensive bioinformatics analysis. At first, the data of gene expression microarray (GSE30656) was downloaded from GEO database and differential miRNAs were obtained. Additionally, 4 miRNAs associated with the survival time of patients with CC were screened through TCGA differential data analysis, Kaplan-Meier, and Landmark analysis. Among them, the low expression of miR-188 and high expression of miR-223 correlated with the short survival of CC patients, while the down-regulation of miR-99a and miR-125b was closely related to the 5-year survival rate of patients. Then, based on the correspondence between the differentially expressed genes (DEGs) in CC from the TCGA data and the 4 miRNAs target genes, 58 target genes were screened to perform the analysis of function enrichment and the visualization of protein-protein interaction (PPI) networks. The seven pivotal genes of the PPI network as the target genes of four miRNAs related to prognosis, they were directly or indirectly involved in the development of CC. In this study, based on high-throughput data mining, differentially expressed miRNAs and related target genes were analyzed to provide an effective bioinformatics basis for further understanding of the pathogenesis and prognosis of CC. And the results may be a promising biomarker for the early screening of high-risk populations and early diagnosis of cervical cancer.

Microarray‑based bioinformatics analysis of the prospective target gene network of key miRNAs influenced by long non‑coding RNA PVT1 in HCC

The long non-coding RNA (lncRNA) PVT1 plays vital roles in the tumorigenesis and development of various types of cancer. However, the potential expression profiling, functions and pathways of PVT1 in HCC remain unknown. PVT1 was knocked down in SMMC-7721 cells, and a miRNA microarray analysis was performed to detect the differentially expressed miRNAs. Twelve target prediction algorithms were used to predict the underlying targets of these differentially expressed miRNAs. Bioinformatics analysis was performed to explore the underlying functions, pathways and networks of the targeted genes. Furthermore, the relationship between PVT1 and the clinical parameters in HCC was confirmed based on the original data in the TCGA database. Among the differentially expressed miRNAs, the top two upregulated and downregulated miRNAs were selected for further analysis based on the false discovery rate (FDR), fold-change (FC) and P-values. Based on the TCGA database, PVT1 was obviously highly expressed in HCC, and a statistically higher PVT1 expression was found for sex (male), ethnicity (Asian) and pathological grade (G3+G4) compared to the control groups (P<0.05). Furthermore, Gene Ontology (GO) analysis revealed that the target genes were involved in complex cellular pathways, such as the macromolecule biosynthetic process, compound metabolic process, and transcription. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the MAPK and Wnt signaling pathways may be correlated with the regulation of the four candidate miRNAs. The results therefore provide significant information on the differentially expressed miRNAs associated with PVT1 in HCC, and we hypothesized that PVT1 may play vital roles in HCC by regulating different miRNAs or target gene expression (particularly MAPK8) via the MAPK or Wnt signaling pathways. Thus, further investigation of the molecular mechanism of PVT1 in HCC is needed.