The decrease of cyclin B2 expression inhibits invasion and metastasis of bladder cancer

From Plant Based Therapy to Plant-Derived Vesicle-Like Nanoparticles for Cancer Treatment: Past, Present and Future

Cancer stands as a formidable malady profoundly impacting human health. Throughout history, plant-based therapies have remained pivotal in the arsenal against cancer, evolving alongside the epochs. Presently, challenges such as the arduous extraction of active components and potential safety concerns impede the progression of plant-based anticancer therapies. The isolation of plant-derived vesicle-like nanoparticles (PDVLNs), a kind of lipid bilayer capsules isolated from plants, has brought plant-based anticancer therapy into a novel realm and has led to decades of research on PDVLNs. Accumulating evidence indicates that PDVLNs can deliver plant-derived active substances to human cells and regulate cellular functions. Regulating immunity, inducing cell cycle arrest, and promoting apoptosis in cancer cells are the most commonly reported mechanisms of PDVLNs in tumor suppression. Low immunogenicity and lack of tumorigenicity make PDVLNs a good platform for drug delivery. The molecules within the PDVLNs are all from source plants, so the selection of source plants is crucial. In recent years, there has been a clear trend that the source plants have changed from vegetables or fruits to medicinal plants. This review highlights the mechanisms of medicinal plant-based cancer therapies to identify candidate source plants. More importantly, the current research on PDVLN-based cancer therapy and the applications of PDVLNs for drug delivery are systematically discussed.

Identification of Key Genes and Related Drugs of Adrenocortical Carcinoma by Integrated Bioinformatics Analysis

Adrenocortical carcinoma (ACC) is a malignant carcinoma with an extremely poor prognosis, and its pathogenesis remains to be understood to date, necessitating further investigation. This study aims to discover biomarkers and potential therapeutic agents for ACC through bioinformatics, enhancing clinical diagnosis and treatment strategies. Differentially expressed genes (DEGs) between ACC and normal adrenal cortex were screened out from the GSE19750 and GSE90713 datasets available in the GEO database. An online Venn diagram tool was utilized to identify the common DEGs between the two datasets. The identified DEGs were subjected to functional assessment, pathway enrichment, and identification of hub genes by performing the protein-protein interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The differences in the expressions of hub genes between ACC and normal adrenal cortex were validated at the GEPIA2 website, and the association of these genes with the overall patient survival was also assessed. Finally, on the QuartataWeb website, drugs related to the identified hub genes were determined. A total of 114 DEGs, 10 hub genes, and 69 known drugs that could interact with these genes were identified. The GO and KEGG analyses revealed a close association of the identified DEGs with cellular signal transduction. The 10 hub genes identified were overexpressed in ACC, in addition to being significantly associated with adverse prognosis in ACC. Three genes and the associated known drugs were identified as potential targets for ACC treatment.

Identification of potential biomarkers for colorectal cancer by clinical database analysis and Kaplan-Meier curves analysis

This study aimed to explore critical genes as potential biomarkers for the diagnosis and prognosis of colorectal cancer (CRC) for clinical utility. To identify and screen candidate genes involved in CRC carcinogenesis and disease progression, we downloaded microarray datasets GSE89076, GSE73360, and GSE32323 from the GEO database identified differentially expressed genes (DEGs), and performed a functional enrichment analysis. A protein-protein interaction network was constructed, and correlated module analysis was performed using STRING and Cytoscape. The Kaplan-Meier survival curve shows the survival of the hub genes. The expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), and PCNA in tissues and changes in tumor grade were analyzed. A total of 329 DEGs were identified, including 264 upregulated and 65 downregulated genes. The functions and pathways of DEGs include the mitotic cell cycle, poly(A) RNA binding replication, ATP binding, DNA replication, ribosome biogenesis in eukaryotes, and RNA transport. Forty-seven Hub genes were identified, and biological process analysis showed that these genes were mainly enriched in cell cycle and DNA replication. Patients with mutations in CDK1, PCNA, and CCNB1 had poorer survival rates. CDK1, PCNA, and CCNB1 were significantly overexpressed in the tumor tissues. The expression of CDK1 and CCNB1 gradually decreased with increasing tumor grade. CDK1, CCNB1, and PCNA can be used as potential markers for the diagnosis and prognosis of CRC. These genes are overexpressed in colon cancer tissues and are associated with low survival rates in CRC patients.

Identification of a transcription factor‑cyclin family genes network in lung adenocarcinoma through bioinformatics analysis and validation through RT‑qPCR

Lung adenocarcinoma (LUAD) is the predominant pathological subtype of lung cancer, which is the most prevalent and lethal malignancy worldwide. Cyclins have been reported to regulate the physiology of various types of tumors by controlling cell cycle progression. However, the key roles and regulatory networks associated with the majority of the cyclin family members in LUAD remain unclear. In total, 556 differentially expressed genes were screened from the GSE33532, GSE40791 and GSE19188 mRNA microarray datasets by R software. Subsequently, protein-protein interaction network containing 499 nodes and 4,311 edges, in addition to a significant module containing 76 nodes and 2,631 edges, were extracted through the MCODE plug-in of Cytoscape. A total of four cyclin family genes [cyclin (CCNA2, CCNB1, CCNB2 and CCNE2] were then found in this module. Further co-expression analysis and associated gene prediction revealed forkhead box M1 (FOXM1), the common transcription factor of CCNB2, CCNB1 and CCNA2. In addition, using GEPIA database, it was found that the high expression of these four genes were simultaneously associated with poorer prognosis in patients with LUAD. Experimentally, it was proved that these four hub genes were highly expressed in LUAD cell lines (Beas-2B and H1299) and LUAD tissues through qPCR, western blot analysis and immunohistochemical studies. The diagnostic value of these 4 hub genes in LUAD was analyzed by logistic regression, CCNA2 was deleted, following which a nomogram diagnostic model was constructed accordingly. The area under the curve values of CCNB1, CCNB2 and FOXM1 diagnostic models were calculated to be 0.92, 0.91 and 0.96 in the training set (Combined dataset of GSE33532, GSE40791 and GSE19188) and two validation sets (GSE10072 and GSE75037), respectively. To conclude, data from the present study suggested that the FOXM1/cyclin (CCNA2, CCNB1 and/or CCNB2) axis may serve a regulatory role in the development and prognosis of LUAD. Specifically, CCNB1, CCNB2 and FOXM1 have potential as diagnostic markers and/or therapeutic targets for LUAD treatment.

Identification of hub genes and biological pathways in glioma via integrated bioinformatics analysis

OBJECTIVE

Glioma is the most common intracranial primary malignancy, but its pathogenesis remains unclear.

METHODS

We integrated four eligible glioma microarray datasets from the gene expression omnibus database using the robust rank aggregation method to identify a group of significantly differently expressed genes (DEGs) between glioma and normal samples. We used these DEGs to explore key genes closely associated with glioma survival through weighted gene co-expression network analysis. We then constructed validations of prognosis and survival analyses for the key genes via multiple databases. We also explored their potential biological functions using gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA).

RESULTS

We selected DLGAP5, CDCA8, NCAPH, and CCNB2, as four genes that were abnormally up-regulated in glioma samples, for verification. They showed high levels of isocitrate dehydrogenase gene mutation and tumor grades, as well as good prognostic and diagnostic value for glioma. Their methylation levels were generally lower in glioma samples. GSEA and GSVA analyses suggested the genes were closely involved with glioma proliferation.

CONCLUSION

These findings provide new insights into the pathogenesis of glioma. The hub genes have the potential to be used as diagnostic and therapeutic markers.

Cyclin B2 overexpression promotes tumour growth by regulating jagged 1 in hepatocellular carcinoma

Background: Our previous study showed that Cyclin B2 (CCNB2) is closely related to the occurrence and progression of hepatocellular carcinoma (HCC).

Aim of the study: This study aimed to clarify the effect of CCNB2 gene silencing on tumorigenesis in nude mice and to detect the potential mechanism.

Methods: The effect of CCNB2 on HCC was tested in vivo. The downstream target genes of CCNB2 were predicted by proteomics and confirmed by western blot assay. The regulatory functions of CCNB2 in the proliferation and migration of HCC cells were determined through functional recovery experiments. The expression of the downstream target genes of CCNB2 was detected by immunohistochemistry.

Results: Knockdown of CCNB2 decreased tumour formation rate and tumour volume and weight and inhibited tumour proliferation. A total of 130 differentially expressed proteins were detected by proteomics, and Jagged 1 (JAG1) was predicted as the potential downstream target of CCNB2. Western blot assay revealed that CCNB2 and JAG1 expression was significantly correlated in HCC cells. The results of functional recovery experiments suggested that CCNB2 knockdown weakened the proliferation and migration ability of HCC cells, while JAG1 overexpression restored this ability of HCC cells that was weakened by CCNB2 knockdown. Immunohistochemistry showed that JAG1 expression was higher in HCC tissues than in paracancerous tissues and was related to tumour size and number and tumour thrombus formation.

Conclusions: The proliferation of HCC cells in vivo was inhibited by CCNB2 knockdown. CCNB2 may accelerate the proliferation and metastasis of HCC cells by increasing JAG1 expression.

Screening of Potential Key Biomarkers for Ewing Sarcoma: Evidence from Gene Array Analysis

Background

Ewing’s sarcoma (ES) is a common bone cancer in children and adolescents. There are ethnic differences in the incidence and treatment effects. People have made great efforts to clarify the cause; however, the molecular mechanism of ES is still poorly understood.

Methods

We download the microarray datasets GSE68776, GSE45544 and GSE17674 from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) of the three datasets were screened and enrichment analysis was performed. STRING and Cytoscape were used to carry out module analysis, building a protein–protein interaction (PPI) network. Finally, a series of analyses such as survival analysis and immune infiltration analysis were performed on the selected genes.

Results

A total of 629 differentially expressed genes were screened, including 206 up-regulated genes and 423 down-regulated genes. The pathways and rich-functions of DEGs include protein activation cascade, carbohydrate binding, cell-cell adhesion junctions, mitotic cell cycle, p53 pathway, and cancer pathways. Then, a total of 10 hub genes were screened out. Biological process analysis showed that these genes were mainly enriched in mitotic nuclear division, protein kinase activity, cell division, cell cycle, and protein phosphorylation.

Conclusion

Survival analysis and multiple gene comparison analysis showed that CDCA8, MAD2L1 and FANCI may be involved in the occurrence and prognosis of ES. The purpose of our study is to clarify the DEG and key genes, which will help us know more about the molecular mechanisms of ES, provide potential pathway or targets for the diagnosis and treatment.

CCNB2 is a novel prognostic factor and a potential therapeutic target in Low-grade glioma (LGG)

Background: Cyclin B2 (CCNB2) is an important component of the cyclin pathway and plays a key role in the occurrence and development of cancer. However, the correlation between prognosis of low-grade glioma (LGG), CCNB2, and tumor infiltrating lymphocytes is not clear. Methods: The expression of CCNB2 in LGG was queried in Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and TIMER databases. The relationships between CCNB2 and the clinicopathological features of LGG were analyzed using the Chinese Glioma Genome Atlas (CGGA) database. The relationship between CCNB2 expression and overall survival (OS) was evaluated by GEPIA2. The correlation between CCNB2 and LGG immune infiltration was analyzed by the TIMER database. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect CCNB2 expression. Results: The expression of CCNB2 differed across different tumor tissues, but was higher in LGG than in normal tissues. LGG patients with high expression of CCNB2 have poorer prognosis. The expression of CCNB2 was correlated with age, WHO grade, IDH mutational status, 1p/19q codeletion status, and other clinicopathological features. The expression of CCNB2 in LGG was positively correlated with the infiltration level of B cells, dendritic cells, and macrophages. qRT-PCR results revealed that the expression of CCNB2 in LGG tissues was higher than normal tissues and higher expression of CCNB2 was associated with worse prognosis. Conclusion: CCNB2 may be used as a potential biomarker to determine the prognosis of LGG and is also related to immune infiltration.

Identification of CCNB2 as A Potential Non-Invasive Breast Cancer Biomarker in Peripheral Blood Mononuclear Cells Using The Systems Biology Approach

OBJECTIVE

Breast cancer (BC) still remains an imperative clinical issue, despite advances in the diagnosis, prognosis and treatment modalities of this malignancy. Hence, progress has been made to identify non-invasive, high sensitive and specific biomarkers. Since immune system affects development of breast cancer, peripheral blood mononuclear cells (PBMCs) -a subpopulation of immune cells- can be considered as a promising tool in the field of BC biomarker research. In the current study, we initially attempted to use concept of the present shared biomarkers in solid tumors and systemic immune profile and then evaluate correlation of these biomarkers to clinical use in cancer research.

MATERIALS AND METHODS

In this experimental study, available microarray gene expression datasets of BC as well as the related PBMCs were retrieved and downloaded from the Gene Expression Omnibus (GEO) database, followed by analysis using GEO2R along with affylmGUI, a R-based package, to obtain differentially expressed genes (DEGs). Signature genes from 20 types of cancer were also applied to validate DEGs. Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was carried out to assess mRNA level of CCNB2 in PBMC of the BC patients and healthy subjects.

RESULTS

DEGs analysis for the transcription profile of BC cells and PBMCs showed two shared targets, CCNB2 and PGK1. Validation with systems biology using reweighted 20 types of cancer signature genes revealed that CCNB2 is the only common target in BC and its related PBMCs, which was further validated by qRT-PCR implying a significant increase in the level of CCNB2 in the BC patients.

CONCLUSION

Results of this study demonstrated that PBMCs are affected by BC cells and CCNB2 may be of value as a diagnostic biomarker for breast cancer. However, verification would require future detailed experimental plans.

Identification of Three Key Genes Associated with Hepatocellular Carcinoma Progression Based on Co-expression Analysis

Hepatocellular carcinoma (HCC) is the fifth most common cancer and one of the leading causes of cancer-related death in the world. Due to the recurrence of HCC, its survival rate is still low. Therefore, it is vital to seek prognostic biomarkers for HCC. In this study, differential analysis was conducted on gene expression data in The Cancer Genome Atlas -LIHC, and 4482 differentially expressed genes in tumor tissue were selected. Then, weighted gene co-expression network analysis was used to analyze the co-expression of the gained differential genes. By module-trait correlation analysis, the turquoise gene module that was significantly related to tumor grade, pathologic_T stage, and clinical stage was identified. Thereafter, enrichment analysis of genes in this module uncovered that the genes were mainly enriched in the signaling pathways involved in spliceosome and cell cycle. After that, through correlation analysis, 18 hub genes highly correlated with tumor grade, clinical stage, pathologic_T stage, and the turquoise module were selected. Meanwhile, protein-protein interaction (PPI) network was constructed by using genes in the module. Finally, three key genes, heterogeneous nuclear ribonucleoprotein L, serrate RNA effector molecule, and cyclin B2, were identified by intersecting the top 30 genes with the highest connectivity in PPI network and the previously obtained 18 hub genes in the turquoise module. Further survival analysis revealed that high expression of the three key genes predicted poor prognosis of HCC. These results indicated the direction for further research on clinical diagnosis and prognostic biomarkers of HCC.

Cyclin B2 (CCNB2) Stimulates the Proliferation of Triple-Negative Breast Cancer (TNBC) Cells In Vitro and In Vivo

Triple-negative breast cancer (TNBC) is the most aggressive type of breast cancer. Currently, targeting therapy makes great advances for the treatment of TNBC, whereas more effective therapeutic targets are urgently needed. Cyclin B2 (CCNB2), which belongs to B-type cyclins, is known as a cell cycle regulator. CCNB2 is synthesized at G1 phase in cancer cells and downregulated at anaphase. The defects of CCNB2 led to the abnormal cell cycle and tumorigenesis. Though there are wide effects of CCNB2 on multiple types of tumors, the potential role of CCNB2 in TNBC progression is still unclear. Herein, we found that CCNB2 was highly expressed in human TNBC tissues and correlated with the prognosis and clinical pathological features including tumor size (p = 0.022^∗) and pTNM stage (p = 0.021^∗) of patients with TNBC. CCNB2 could promote the proliferation of TNBC cells in vitro and in mice. Our findings therefore confirmed the involvement of CCNB2 in TNBC progression and provided the evidence that CCNB2 could serve as a promising molecular target of TNBC.

Single-cell chromatin accessibility landscape of human umbilical cord blood in trisomy 18 syndrome

BACKGROUND

Trisomy 18 syndrome (Edwards syndrome, ES) is a type of aneuploidy caused by the presence of an extra chromosome 18. Aneuploidy is the leading cause of early pregnancy loss, intellectual disability, and multiple congenital anomalies. The research of trisomy 18 is progressing slowly, and the molecular characteristics of the disease mechanism and phenotype are still largely unclear.

RESULTS

In this study, we used the commercial Chromium platform (10× Genomics) to perform sc-ATAC-seq to measure chromatin accessibility in 11,611 single umbilical cord blood cells derived from one trisomy 18 syndrome patient and one healthy donor. We obtained 13 distinct major clusters of cells and identified them as 6 human umbilical cord blood mononuclear cell types using analysis tool. Compared with the NC group, the ES group had a lower ratio of T cells to NK cells, the ratio of monocytes/DC cell population did not change significantly, and the ratio of B cell nuclear progenitor and megakaryocyte erythroid cells was higher. The differential genes of ME-0 are enriched in Human T cell leukemia virus 1 infection pathway, and the differential peak genes of ME-1 are enriched in apopotosis pathway. We found that CCNB2 and MCM3 may be vital to the development of trisomy 18. CCNB2 and MCM3, which have been reported to be essential components of the cell cycle and chromatin.

CONCLUSIONS

We have identified 6 cell populations in cord blood. Disorder in megakaryocyte erythroid cells implicates trisomy 18 in perturbing fetal hematopoiesis. We identified a pathway in which the master differential regulatory pathway in the ME-0 cell population involves human T cell leukemia virus 1 infection, a pathway that is dysregulated in patients with trisomy 18 and which may increase the risk of leukemia in patients with trisomy 18. CCNB2 and MCM3 in progenitor may be vital to the development of trisomy 18. CCNB2 and MCM3, which have been reported to be essential components of the cell cycle and chromatin, may be related to chromosomal abnormalities in trisomy 18.

Screening and identification of hub genes in bladder cancer by bioinformatics analysis and KIF11 is a potential prognostic biomarker

Bladder cancer (BC) is the ninth most common lethal malignancy worldwide. Great efforts have been devoted to clarify the pathogenesis of BC, but the underlying molecular mechanisms remain unclear. To screen for the genes associated with the progression and carcinogenesis of BC, three datasets were obtained from the Gene Expression Omnibus. A total of 37 tumor and 16 non-cancerous samples were analyzed to identify differentially expressed genes (DEGs). Subsequently, 141 genes were identified, including 55 upregulated and 86 downregulated genes. The protein-protein interaction network was established using the Search Tool for Retrieval of Interacting Genes database. Hub gene identification and module analysis were performed using Cytoscape software. Hierarchical clustering of hub genes was conducted using the University of California, Santa Cruz Cancer Genomics Browser. Among the hub genes, kinesin family member 11 (KIF11) was identified as one of the most significant prognostic biomarkers among all the candidates. The Kaplan Meier Plotter database was used for survival analysis of KIF11. The expression profile of KIF11 was analyzed using the ONCOMINE database. The expression levels of KIF11 in BC samples and bladder cells were measured using reverse transcription-quantitative pCR, immunohistochemistry and western blotting. In summary, KIF11 was significantly upregulated in BC and might act as a potential prognostic biomarker. The present identification of DEGs and hub genes in BC may provide novel insight for investigating the molecular mechanisms of BC.

Grapefruit-Derived Micro and Nanovesicles Show Distinct Metabolome Profiles and Anticancer Activities in the A375 Human Melanoma Cell Line

Fruit juice is one of the most easily accessible resources for the isolation of plant-derived vesicles. Here we found that micro- and nano-sized vesicles (MVs and NVs) from four Citrus species, C. sinensis, C. limon, C. paradisi and C. aurantium, specifically inhibit the proliferation of lung, skin and breast cancer cells, with no substantial effect on the growth of non-cancer cells. Cellular and molecular analyses demonstrate that grapefruit-derived vesicles cause cell cycle arrest at G2/M checkpoint associated with a reduced cyclins B1 and B2 expression levels and the upregulation of cell cycle inhibitor p21. Further data suggest the inhibition of Akt and ERK signalling, reduced intercellular cell adhesion molecule-1 and cathepsins expressions, and the presence of cleaved PARP-1, all associated with the observed changes at the cellular level. Gas chromatography-mass spectrometry-based metabolomics reveals distinct metabolite profiles for the juice and vesicle fractions. NVs exhibit a high relative amount of amino acids and organic acids whereas MVs and fruit juice are characterized by a high percentage of sugars and sugar derivatives. Grapefruit-derived NVs are in particular rich in alpha–hydroxy acids and leucine/isoleucine, myo-inositol and doconexent, while quininic acid was detected in MVs. Our findings reveal the metabolite signatures of grapefruit-derived vesicles and substantiate their potential use in new anticancer strategies.

[Spindle assembly checkpoint complex-related genes TTK and MAD2L1 are over-expressed in lung adenocarcinoma: a big data and bioinformatics analysis]

OBJECTIVE

To screen the key genes related to the prognosis of lung adenocarcinoma through big data analysis and explore their clinical value and potential mechanism.

METHODS

We analyzed GSE18842, GSE27262, and GSE33532 gene expression profile data obtained from the Gene Expression Omnibus (GEO). Bioinformatics methods were used to screen the differentially expressed genes in lung adenocarcinoma tissues and KEGG and GO enrichment analysis was performed, followed by PPI interaction network analysis, module analysis, differential expression analysis, and prognosis analysis. The expressions of MAD2L1 and TTK by immunohistochemistry were verified in 35 non-small cell lung cancer specimens and paired adjacent tissues.

RESULTS

We identified a total of 256 genes that showed significant differential expressions in lung adenocarcinoma, including 66 up-regulated and 190 down-regulated genes. Thirty-two up-regulated core genes were screened by functional analysis, and among them 29 were shown to significantly correlate with a poor prognosis of patients with lung adenocarcinoma. All the 29 genes were highly expressed in lung adenocarcinoma tissues compared with normal lung tissues and were mainly enriched in cell cycle pathways. Seven of these key genes were closely related to the spindle assembly checkpoint (SAC) complex and responsible for regulating cell behavior in G2/M phase. We selected SAC-related proteins TTK and MAD2L1 to test their expressions in clinical tumor samples, and detected their overexpression in lung adenocarcinoma tissues as compared with the adjacent tissues.

CONCLUSIONS

Seven SAC complex-related genes, including TTK and MAD2L1, are overexpressed in lung adenocarcinoma tissues with close correlation with the prognosis of the patients.

Identification of Potential Hub Genes and Therapeutic Drugs in Malignant Pleural Mesothelioma by Integrated Bioinformatics Analysis

INTRODUCTION

Malignant pleural mesothelioma (MPM) is closely linked to asbestos exposure and is an extremely aggressive tumor with poor prognosis.

OBJECTIVE

Our study aimed to elucidate hub genes and potential drugs in MPM by integrated bioinformatics analysis.

METHODS

GSE42977 was download from the Gene Expression Omnibus (GEO) database; the differentially expressed genes (DEGs) with adj.p value <0.05 and |logFC| ≥2 were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed by DAVID database. The STRING database was used to construct a protein-protein interaction network, and modules analysis and hub genes acquisition were performed by Cytoscape. The Gene Expression Profiling Interactive Analysis (GEPIA) database was used to assess the impact of hub genes on the prognosis of MPM patients. The Drug-Gene Interaction database (DGIdb) was used to select the related drugs.

RESULTS

A total of 169 upregulated and 70 downregulated DEGs were identified. These DEGs are enriched in the pathway of extracellular matrix-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and PPAR signaling pathway. Finally, 10 hub genes (CDC20, CDK1, UBE2C, TOP2A, CCNB2, NUSAP1, KIF20A, AURKA, CEP55, and ASPM) were identified, which are considered to be closely related to the poor prognosis of MPM. In addition, 119 related drugs that may have a therapeutic effect on MPM were filtered out.

CONCLUSION

These discovered genes and small-molecule drugs provide some new ideas for further research on MPM.

Co-expression Network Analysis Identifies Fourteen Hub Genes Associated with Prognosis in Clear Cell Renal Cell Carcinoma

Renal cancer is a common genitourinary malignance, of which clear cell renal cell carcinoma (ccRCC) has high aggressiveness and leads to most cancer-related deaths. Identification of sensitive and reliable biomarkers for predicting tumorigenesis and progression has great significance in guiding the diagnosis and treatment of ccRCC. Here, we identified 2397 common differentially expressed genes (DEGs) using paired normal and tumor ccRCC tissues from GSE53757 and The Cancer Genome Atlas (TCGA). Then, we performed weighted gene co-expression network analysis and protein-protein interaction network analysis, 17 candidate hub genes were identified. These candidate hub genes were further validated in GSE36895 and Oncomine database and 14 real hub genes were identified. All the hub genes were up-regulated and significantly positively correlated with pathological stage and histologic grade of ccRCC. Survival analysis showed that the higher expression level of each hub gene tended to predict a worse clinical outcome. ROC analysis showed that all the hub genes can accurately distinguish between tumor and normal samples, and between early stage and advanced stage ccRCC. Moreover, all the hub genes were positively associated with distant metastasis, lymph node infiltration, tumor recurrence and the expression of MKi67, suggesting these genes might promote tumor proliferation, invasion and metastasis. Furthermore, the functional annotation demonstrated that most genes were enriched in cell-cycle related biological function. In summary, our study identified 14 potential biomarkers for predicting tumorigenesis and progression, which might contribute to early diagnosis, prognosis prediction and therapeutic intervention.

miR-335-5p Regulates Cell Cycle and Metastasis in Lung Adenocarcinoma by Targeting CCNB2

Background

Lots of studies have shown that cyclin disorders can promote tumor development. This study aims to investigate the biological function and molecular mechanism of CCNB2 in lung adenocarcinoma (LUAD).

Methods

LUAD data were downloaded from GEO database and TCGA-LUAD database. Differential analysis was conducted to find the differentially expressed miRNAs and mRNAs, while targeted prediction was done for the access of potential target mRNAs. Gene expression level was detected by qRT-PCR and Western blot in human LUAD cell lines A-427, A549, Calu-3, PC-9 and human bronchial epithelial cell line BEAS-2B. MTT, colony formation, Transwell and flow cytometry assays were used to detect cell proliferation, metastasis, and cell cycle changes of PC-9 cell line. The dual-luciferase reporter gene was used to detect the targeted binding relationship of the target miRNA and mRNA.

Results

CCNB2 was highly expressed and served as a biomarker indicating poor prognosis in LUAD patients. Cell function experiments confirmed the inhibitory effects of silencing CCNB2 on the proliferation, migration and invasion of LUAD cells and cell cycle was blocked in the G0/G1 phase. In addition, with regard to the regulatory mechanism, we demonstrated that miR-335-5p had binding sites with 3ʹ-UTR of CCNB2, indicating that miR-335-5p could target the regulation expression of CCNB2. In subsequent cell function tests, overexpression of miR-335-5p inhibited the proliferation and metastasis of cancer cells, and the rescue experiments also verified that miR-335-5p could reverse the promotion of CCNB2 overexpression on the progress of cancer cells.

Conclusion

In summary, our results revealed that miR-335-5p could target the down-regulation of CCNB2 to inhibit the occurrence and development of LUAD.

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.

Integrative module analysis of HCC gene expression landscapes

Despite hepatocellular carcinoma (HCC) being a common cancer globally, its initiation and progression are not well understood. The present study was designed to investigate the hub genes and biological processes of HCC, which change substantially during its progression. Three gene expression profiles of 480 patients with HCC were obtained from the Gene Expression Omnibus database. Subsequent to performing functional annotations and constructing protein-protein interaction (PPI) networks, 657 differentially expressed genes were identified, which were subsequently used to screen candidate hub genes. PPI networks were modularized using the weighted gene correlation network analysis algorithm, the topological overlapping matrix and the hierarchical cluster tree, which were utilized via STRING. Clinical data obtained from The Cancer Genome Atlas were then analyzed to validate the experiments performed using six hub genes. Additionally, a transcription factor and microRNA-mRNA network were constructed to determine the potential regulatory mechanisms of six hub genes. The results revealed that the oxidation-reduction process and cell cycle associated processes were markedly involved in HCC progression. Six highly expressed genes, including cyclin B2, cell division cycle 20, mitotic arrest deficient 2 like 1, minichromosome maintenance complex component 2, centromere protein F and BUB mitotic checkpoint serine/threonine kinase B, were confirmed as hub genes and validated via experiments associated with cell division. These hub genes are necessary for confirmatory experiments and may be used in clinical gene therapy as biomarkers or drug targets.

Effect of miR-205 on proliferation and migration of thyroid cancer cells by targeting CCNB2 and the mechanism

This study explored the target of miR-205 and the effect of miR-205 on the proliferation and migration regulating its target in thyroid cancer cells (TC). Twenty-five pairs of TC and adjacent tissues were collected after surgical resection. Real-time fluorescence quantitative PCR (qRT-PCR) was used to detect the expression of miR-205 in TC tissues and cells (SW579, B-CPAP, TPC-1, WRO). SW579 cells were transfected with miR-205 mimic, and SW579 cells with overexpression of miR-205 were constructed. The effects of miR-205 overexpression on the proliferation and migration of SW579 cells were observed by cell counting kit-8 (CCK-8) and Transwell assays, respectively. Luciferase reporter assay was further used to look for the target of miR-205 and to study the mechanism of miR-205 in the proliferation and migration of TC cells. Compared with normal tissues and cells, the expression of miR-205 was significantly reduced in TC tissues (t=3.47, P=0.031) and cells (t=5.41, P=0.016). Overexpression of miR-205 inhibited the proliferation (t=4.12, P=0.035) and migration (t=4.47, P=0.027) of SW579 cells. Luciferase reporter assays found that CCNB2 was a target gene of miR-205 (t=4.63, P=0.024), qRT-PCR and western blot assays confirmed there was negatively correlation between CCNB2 and miR-205 (t=3.55, P=0.029; t=2.86, P=0.043). CCNB2 overexpression reversed the inhibition of miR-205 on the proliferation (t=3.70, P=0.031) and migration (t=4.12, P=0.022) of SW579 cells. In conclusion, miR-205 inhibits the proliferation and migration of TC cells by targeting CCNB2, which may be a potential target of TC therapy.

Identification of key protein-coding genes in lung adenocarcinomas based on bioinformatic analysis

Background

Lung cancer is one of the most common cancers and the primary cause of cancer-related deaths in the world. The 5-year survival of lung cancer patients is lower than 15%. As a common subtype of lung cancer, lung adenocarcinoma still has a high morbidity and mortality, although many strategies have been made, such as surgical operation, chemotherapy, targeted therapy. The use of gene expression microarray has provided a feasible and effective approach for the study on lung cancer. However, the biomarkers and potential therapeutic targets of lung adenocarcinomas are still not completely identified. Our study is aimed to find biomarkers and therapeutic targets of lung adenocarcinomas by identifying the key protein-coding gene in lung adenocarcinomas by bioinformatical approaches.

Methods

We selected and obtained messenger RNA microarray datasets from Gene Expression Omnibus database to identify differentially expressed genes between lung adenocarcinomas and normal lung tissue. The differentially expressed genes were clarified by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, the protein-protein interaction (PPI) network and statistical analyses. Subsequently, quantitative real-time PCR was used to verify the results of bioinformatic analysis.

Results

We obtained 1,264, 896 and 408 differentially expressed genes from GSE32863, GSE43458 and GSE63459, respectively. The 242 common differentially expressed genes in three datasets were related to cell adhesion molecules, ECM-receptor interaction, leukocyte transendothelial migration according to KEGG analysis. GO analysis showed that these common differentially expressed genes were enriched in tumor-related functions. ASPM, CCNB2, CDC20, CDC45, MELK, TOP2A and UBE2T and KIAA0101 have the strongest protein-protein interaction relationships based on protein-protein interaction networks. Survival analysis showed that these nine genes were closely related to the survival of lung adenocarcinomas. The further qRT-PCR assays indicated that seven key genes (ASPM, CCNB2, CDC20, CDC45, MELK, TOP2A and UBE2T) display differential profile between clinical lung adenocarcinoma specimens and their matched normal tissues.

Conclusions

ASPM, CCNB2, CDC20, CDC45, MELK, TOP2A and UBE2T may be key protein coding genes in lung adenocarcinoma, and deserve further study to verify their feasibility and effectiveness as biomarkers and therapeutic targets for lung adenocarcinomas.

Screening of potential biomarkers and their predictive value in early stage non-small cell lung cancer: a bioinformatics analysis

BACKGROUND

Non-small cell lung cancer (NSCLC) remains the first leading cause of death in malignancies worldwide. Despite the early screening of NSCLC by low-dose spiral computed tomography (CT) in high-risk individuals caused a 20% reduction in the mortality, there still exists imperative needs for the identification of novel biomarkers for the diagnosis and treatment of lung cancer.

METHODS

mRNA microarray datasets GSE19188, GSE33532, and GSE44077 were searched, and the differentially expressed genes (DEGs) were obtained using GEO2R. Functional and pathway enrichment analyses were performed for the DEGs using DAVID database. Protein-protein interaction (PPI) network was plotted with STRING and visualized by Cytoscape. Module analysis of the PPI network was done through MCODE. The overall survival (OS) analysis of genes from MCODE was performed with the Kaplan Meier-plotter.

RESULTS

A total of 221 DEGs were obtained, which were mainly enriched in the terms related to cell division, cell proliferation, and signal transduction. A PPI network was constructed, consisting of 221 nodes and 739 edges. A significant module including 27 genes was identified in the PPI network. Elevated expression of these genes was associated with poor OS of NSCLC patients, including UBE2T, UNF2, CDKN3, ANLN, CCNB2, and CKAP2L. The enriched functions and pathways included protein binding, ATP binding, cell cycle, and p53 signaling pathway.

CONCLUSIONS

The DEGs in NSCLC have the potential to become useful targets for the diagnosis and treatment of NSCLC.

Screening and identification of key biomarkers in lung squamous cell carcinoma by bioinformatics analysis

The high mortality rate of lung squamous cell carcinoma (LUSC) is in part due to the lack of early detection of its biomarkers. The identification of key molecules involved in LUSC is therefore required to improve clinical diagnosis and treatment outcomes. The present study used the microarray datasets GSE31552, GSE6044 and GSE12428 from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were conducted to construct the protein-protein interaction network of DEGs and hub genes module using STRING and Cytoscape. The 67 DEGs identified consisted of 42 upregulated genes and 25 downregulated genes. The pathways predicted by KEGG and GO enrichment analyses of DEGs mainly included cell cycle, cell proliferation, glycolysis or gluconeogenesis, and tetrahydrofolate metabolic process. Further analysis of the University of California Santa Cruz and ONCOMINE databases identified 17 hub genes. Overall, the present study demonstrated hub genes that were closely associated with clinical tissue samples of LUSC, and identified TYMS, CCNB2 and RFC4 as potential novel biomarkers of LUSC. The findings of the present study contribute to an improved understanding of the molecular mechanisms of carcinogenesis and progression of LUSC, and assist with the identification of potential diagnostic and therapeutic targets of LUSC.

Aberrantly expressed PLOD1 promotes cancer aggressiveness in bladder cancer: a potential prognostic marker and therapeutic target

Bladder cancer (BC) is the ninth most malignant tumor worldwide. Some BC patients will develop muscle‐invasive BC (MIBC), which has a 5‐year survival rate of approximately 60% due to metastasis. As such, there is an urgent need for novel therapeutic and diagnostic targets for MIBC. Analysis of novel antitumor microRNA (miRNA)‐mediated cancer networks is an effective strategy for exploring therapeutic targets and prognostic markers in cancers. Our previous miRNA analysis revealed that miR‐140‐5p acts as an antitumor miRNA in BC cells. Here, we investigated miR‐140‐5p regulation of BC molecular pathogenesis. Procollagen‐lysine, 2‐oxoglutarate 5‐dioxygenase 1 (PLOD1) was found to be directly regulated by miR‐140‐5p, and aberrant expression of PLOD1 was observed in BC clinical specimens. High PLOD1 expression was significantly associated with a poor prognosis (disease‐free survival: P = 0.0204; overall survival: P = 0.000174). Multivariate analysis showed PLOD1 expression to be an independent prognostic factor in BC patients (hazard ratio = 1.51, P = 0.0099). Furthermore, downregulation of PLOD1 by siRNAs and a specific inhibitor significantly decreased BC cell aggressiveness. Aberrant expression of PLOD1 was closely associated with BC pathogenesis. In summary, the present study showed that PLOD1 may be a potential prognostic marker and therapeutic target for BC.

[Screening of cell cycle-related genes regulated by KIAA0101 in gastric cancer]

OBJECTIVE

To screen the genes related to cell cycle under regulation by KIAA0101 in gastric cancer.

METHODS

RT-PCR was used to detect the expression level of KIAA0101 gene in gastric cancer tissue and paired adjacent tissues. GO function enrichment analysis and KEGG pathway enrichment analysis were carried out using DAVID database. KEGG was used to map the pathways and the corresponding genes were analyzed. The list of genes associated with the KIAA0101 expression pattern was imported into TCGA cBioPortal to analyze the relationship between the interacting genes and generate a genetic topology map. The candidate genes were screened by RT-PCR.

RESULTS

The expression level of KIAA0101 mRNA was significantly higher in cancer tissues than in paired adjacent tissues (1.104 ± 0.379 vs 0.421 ± 0.172; P=0.0179). The system screened genes related with KIAA0101 from 478 tissues by pooled analysis of the expression intensity of all the gene probes. GO function analysis showed that the differential genes were mainly enriched in protein phosphorylation, RNA processing, cell cycle, DNA metabolism, protein transport, acetylation, apoptosis, proteolysis, and redox. The changes in the expression level of KIAA0101 mainly affect the gastric cancer-related pathways including cell cycle, spliceosome, DNA replication, and p53 signal transduction pathway. KEGG pathway maps and gene topology maps showed that the genes related to KIAA0101 (such as BUB1B, MAD2L1, CDC45, CDK1, CCNE1 and CCNB2) were also related to cell cycle. RT-PCR results confirmed significant increments of the expression levels of BUB1B, MAD2L, CDK1, CCNE1, and CCNB2 mRNA in gastric cancer tissues as compared with the paired adjacent gastric tissues (P &lt; 0.05), but CDC45 mRNA did not show significant differential expression in gastric cancer tissues (P &gt; 0.05).

CONCLUSIONS

KIAA0101 may affect cell cycle by regulating the expression of BUB1B, MAD2L1, CDK1, CCNE1 and CCNB2, and this finding may provide evidence for understanding how KIAA0101 affects cell cycle and for screening of tumor markers and selection of drug targets.

Cyclin B2 Overexpression in Human Hepatocellular Carcinoma is Associated with Poor Prognosis

BACKGROUND AND AIMS

Cyclin B2 (CCNB2) has been reported to be highly expressed in a few malignancies. However, the biological function of CCNB2 in hepatocellular carcinoma (HCC) is largely unknown. We aimed to investigate the effect of CCNB2 in HCC.

METHODS

The expression of CCNB2 in HCC and normal liver tissues and connection of its expression with prognosis and clinical parameters were studied. The effect of knocking down CCNB2 on cell proliferation, migration, cell cycle distribution, and apoptosis were estimated in BEL-7404 cells.

RESULTS

Compared to normal liver tissues, the level of CCNB2 was higher in HCC tissues from the Gene Expression Profiling Interactive Analysis (GEPIA). The 5 year overall survival and disease-free survival of HCC patients with high CCNB2 levels were shorter than that of those with low CCNB2 levels. Immunohistochemistry analysis also discovered the expression differences of CCNB2 in HCC and normal liver tissues and showed that CCNB2 expression was significantly associated with tumor number, tumor size, tumor thrombus, and alanine aminotransferase level. CCNB2 expression was higher in HCC cell lines (BEL-7404, Hep3B, BEL-7402, and SMMC-7721) than that in the normal hepatic cell line (HL-7702). Knockdown of CCNB2 inhibited cell proliferation and migration, promoted cell apoptosis, and caused S phase arrest in BEL-7404 cells. Finally, CCNB2 was associated with Polo Like Kinase 1 (PLK1) in the GEPIA database and BEL-7404 cells.

CONCLUSIONS

CCNB2 may serve as a prognostic factor and participated in the development and progression and promote cell proliferation and migration through CCNB2/PLK1 pathway in HCC.

Identification of key candidate genes and biological pathways in bladder cancer

Background

Bladder cancer is a malignant tumor in the urinary system with high mortality and recurrence rates. However, the causes and recurrence mechanism of bladder cancer are not fully understood. In this study, we used integrated bioinformatics to screen for key genes associated with the development of bladder cancer and reveal their potential molecular mechanisms.

Methods

The GSE7476, GSE13507, GSE37815 and GSE65635 expression profiles were downloaded from the Gene Expression Omnibus database, and these datasets contain 304 tissue samples, including 81 normal bladder tissue samples and 223 bladder cancer samples. The RobustRankAggreg (RRA) method was utilized to integrate and analyze the four datasets to obtain integrated differentially expressed genes (DEGs), and the gene ontology (GO) functional annotation and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. Protein-protein interaction (PPI) network and module analyses were performed using Cytoscape software. The OncoLnc online tool was utilized to analyze the relationship between the expression of hub genes and the prognosis of bladder cancer.

Results

In total, 343 DEGs, including 111 upregulated and 232 downregulated genes, were identified from the four datasets. GO analysis showed that the upregulated genes were mainly involved in mitotic nuclear division, the spindle and protein binding. The downregulated genes were mainly involved in cell adhesion, extracellular exosomes and calcium ion binding. The top five enriched pathways obtained in the KEGG pathway analysis were focal adhesion (FA), PI3K-Akt signaling pathway, proteoglycans in cancer, extracellular matrix (ECM)-receptor interaction and vascular smooth muscle contraction. The top 10 hub genes identified from the PPI network were vascular endothelial growth factor A (VEGFA), TOP2A, CCNB1, Cell division cycle 20 (CDC20), aurora kinase B, ACTA2, Aurora kinase A, UBE2C, CEP55 and CCNB2. Survival analysis revealed that the expression levels of ACTA2, CCNB1, CDC20 and VEGFA were related to the prognosis of patients with bladder cancer. In addition, a KEGG pathway analysis of the top 2 modules identified from the PPI network revealed that Module 1 mainly involved the cell cycle and oocyte meiosis, while the analysis in Module 2 mainly involved the complement and coagulation cascades, vascular smooth muscle contraction and FA.

Conclusions

This study identified key genes and pathways in bladder cancer, which will improve our understanding of the molecular mechanisms underlying the development and progression of bladder cancer. These key genes might be potential therapeutic targets and biomarkers for the treatment of bladder cancer.

Emerging Biomarkers in Bladder Cancer Identified by Network Analysis of Transcriptomic Data

Bladder cancer is a very common malignancy. Although new treatment strategies have been developed, the identification of new therapeutic targets and reliable diagnostic/prognostic biomarkers for bladder cancer remains a priority. Generally, they are found among differentially expressed genes between patients and healthy subjects or among patients with different tumor stages. However, the classical approach includes processing these data taking into consideration only the expression of each single gene regardless of the expression of other genes. These complex gene interaction networks can be revealed by a recently developed systems biology approach called Weighted Gene Co-expression Network Analysis (WGCNA). It takes into account the expression of all genes assessed in an experiment in order to reveal the clusters of co-expressed genes (modules) that, very probably, are also co-regulated. If some genes are co-expressed in controls but not in pathological samples, it can be hypothesized that a regulatory mechanism was altered and that it could be the cause or the effect of the disease. Therefore, genes within these modules could play a role in cancer and thus be considered as potential therapeutic targets or diagnostic/prognostic biomarkers. Here, we have reviewed all the studies where WGCNA has been applied to gene expression data from bladder cancer patients. We have shown the importance of this new approach in identifying candidate biomarkers and therapeutic targets. They include both genes and miRNAs and some of them have already been identified in the literature to have a role in bladder cancer initiation, progression, metastasis, and patient survival.

MGMT inhibition in ER positive breast cancer leads to CDC2, TOP2A, AURKB, CDC20, KIF20A, Cyclin A2, Cyclin B2, Cyclin D1, ERα and Survivin inhibition and enhances response to temozolomide

The DNA damage repair enzyme, O6-methylguanine DNA methyltransferase (MGMT) is overexpressed in breast cancer, correlating directly with estrogen receptor (ER) expression and function. In ER negative breast cancer the MGMT promoter is frequently methylated. In ER positive breast cancer MGMT is upregulated and modulates ER function. Here, we evaluate MGMT's role in control of other clinically relevant targets involved in cell cycle regulation during breast cancer oncogenesis. We show that O6-benzylguanine (BG), an MGMT inhibitor decreases CDC2, CDC20, TOP2A, AURKB, KIF20A, cyclin B2, A2, D1, ERα and survivin and induces c-PARP and p21 and sensitizes ER positive breast cancer to temozolomide (TMZ). Further, siRNA inhibition of MGMT inhibits CDC2, TOP2A, AURKB, KIF20A, Cyclin B2, A2 and survivin and induces p21. Combination of BG+TMZ decreases CDC2, CDC20, TOP2A, AURKB, KIF20A, Cyclin A2, B2, D1, ERα and survivin. Temozolomide alone inhibits MGMT expression in a dose and time dependent manner and increases p21 and cytochrome c. Temozolomide inhibits transcription of TOP2A, AURKB, KIF20A and does not have any effect on CDC2 and CDC20 and induces p21. BG+/-TMZ inhibits breast cancer growth. In our orthotopic ER positive breast cancer xenografts, BG+/-TMZ decreases ki-67, CDC2, CDC20, TOP2A, AURKB and induces p21 expression. In the same model, BG+TMZ combination inhibits breast tumor growth in vivo compared to single agent (TMZ or BG) or control. Our results show that MGMT inhibition is relevant for inhibition of multiple downstream targets involved in tumorigenesis. We also show that MGMT inhibition increases ER positive breast cancer sensitivity to alkylator based chemotherapy.

Identification of molecular target genes and key pathways in hepatocellular carcinoma by bioinformatics analysis

Background and aim

Hepatocellular carcinoma (HCC) is a major cause of cancer mortality and is increasing incidence worldwide. The aim of this study was to identify the key genes and microRNAs in HCC and explore their potential mechanisms.

Methods

The gene expression profiles of GSE76427, GSE64041, GSE57957, and the microRNA dataset GSE67882 were downloaded from the Gene Expression Omnibus database. The online tool GEO2R was used to obtain differentially expressed genes (DEGs) and miRNAs (DEMs). The gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed for DEGs using the Database for Annotation, Visualization, and Integrated Discovery. A protein–protein interaction (PPI) network of the DEGs was constructed by Search Tool for the Retrieval of Interacting Genes and visualized by Cytoscape. Moreover, miRecords was used to predict the target genes of DEMs.

Results

In total, 106 DEGs were screened out in HCC, consisting of 89 upregulated genes and 17 downregulated genes, which were mainly enriched in biological processes associated with oxidation–reduction process. Besides, the Kyoto Encyclopedia of Genes and Genomes pathways including chemical carcinogenesis, drug metabolism-cytochrome P450, tryptophan metabolism, and retinol metabolism were involved. A PPI network was constructed consisting of 105 nodes and 66 edges. A significant module including nine hub genes, ASPM, AURKA, CCNB2, CDKN3, MELK, NCAPG, NUSAP1, PRC1, and TOP2A, was detected from the PPI network by Molecular Complex Detection. The enriched functions were mainly associated with the mitotic cell cycle process, cell division, and mitotic cell cycle. In addition, a total of 21 DEMs were identified, including 9 upregulated and 12 downregulated miRNAs. Interestingly, ZBTB41 was the potential target of seven miRNAs. Finally, the nine hub genes and three miRNA-target genes expression levels were validated by reverse transcription-polymerase chain reaction. The relative expression levels of nine genes (ASPM, AURKA, CDKN3, MELK, NCAPG, PRC1, TOP2A, ZBTB41, and ZNF148) were significantly upregulated in cancer tissues.

Conclusion

This study identified the key genes and potential molecular mechanisms underlying the development of HCC, which could provide new insight for HCC interventional strategies.

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.

Identification of genes and pathways in nasopharyngeal carcinoma by bioinformatics analysis

Nasopharyngeal carcinoma is a metastatic malignant tumor originating from nasopharyngeal epithelium. Lacking or nonspecific symptoms of patients with early stage nasopharyngeal carcinoma have significantly reduced the accuracy of diagnosing and predicting nasopharyngeal carcinoma development. This study aimed to identify gene signatures of nasopharyngeal carcinoma and uncover potential mechanisms. Two gene expression profiles (GSE12452 and GSE13597) containing 56 nasopharyngeal carcinoma samples and 13 normal control samples were analyzed to identify the differentially expressed genes. In total, 179 up-regulated genes and 238 down-regulated genes were identified. Functional and pathway enrichment analysis showed that up-regulated genes were significantly involved in cell cycle, oocyte meiosis, DNA replication and p53 signaling pathway, while down-regulated genes were enriched in Huntington's disease,metabolic pathways. Subsequently, the top 10 hub genes, TOP2A (topoisomerase (DNA) II alpha), CDK1 (cyclin-dependent kinase 1), CCNB1 (cyclin B1), PCNA (proliferating cell nuclear antigen), MAD2L1 (mitotic arrest deficient 2 like 1), BUB1 (budding uninhibited by benzimidazoles 1 homolog), CCNB2 (cyclin B2), AURKA (aurora kinase A), CCNA2 (cyclin A2), CDC6 (cell division cycle 6 homolog), were identified from protein-protein interaction network. Furthermore, Module analysis revealed that the ten hub genes except TOP2A were belonged to module 1, indicating the upregulation of these hub genes associated molecular pathways in nasopharyngeal carcinoma might activate nasopharyngeal carcinoma pathogenesis. In conclusion, this study indicated that the identified differentially expressed genes and hub genes enrich our understanding of the molecular mechanisms of nasopharyngeal carcinoma, which could eventually translate into additional biomarkers to facilitate the early diagnosis and therapeutic approaches.

High Expression of Derlin-1 Is Associated with the Malignancy of Bladder Cancer in a Chinese Han Population

Derlin-1 is overexpressed in various types of solid tumors and has an important function in cancer progression. However, its expression pattern in and association with the clinicopathological characteristics of human bladder cancer remain unclear. In the present study, 3 pairs of fresh samples of bladder cancer tissue and paracancerous tissue were first detected by liquid chromatography tandem mass spectrometry (UPLC-MS/MS) to screen for differentially expressed proteins. Following bioinformatics analysis and assessments by qRT-PCR and western blotting, Derlin-1 was selected as a candidate protein and was then validated in samples from patients with bladder cancer by immunohistochemistry and western blotting. The results showed that the bladder cancer tissues exhibited higher levels of Derlin-1 expression than the paracancerous tissues (P < 0.05). Positive expression of Derlin-1 was significantly correlated with tumor stage, histological grade, and lymph node metastasis (P < 0.001) but was not correlated with other clinicopathological parameters including patient age (P = 0.758) and gender (P = 0.831). Besides, Derlin-1 was highly expressed in BC cell lines (um-uc-3 and T24), and the interference of Derlin-1 could reverse EMT progression, inhibit the tumor migration and invasion in T24 cells. Further, patients with positive Derlin-1 expression had shorter overall survival than those with negative expression (P < 0.001). Taken together, our results demonstrated that Derlin-1 was overexpressed in bladder cancer and was associated with the malignancy of bladder cancer.

Regulation of TPD52 by antitumor microRNA-218 suppresses cancer cell migration and invasion in lung squamous cell carcinoma

The development of targeted molecular therapies has greatly benefited patients with lung adenocarcinomas. In contrast, these treatments have had little benefit in the management of lung squamous cell carcinoma (lung SCC). Therefore, new treatment options based on current genomic approaches are needed for lung SCC. Aberrant microRNA (miRNA) expression has been shown to promote lung cancer development and aggressiveness. Downregulation of microRNA-218 (miR-218) was frequently observed in our miRNA expression signatures of cancers, and previous studies have shown an antitumor function of miR-218 in several types of cancers. However, the impact of miR-218 on lung SCC is still ambiguous. The present study investigated the antitumor roles of miR-218 in lung SCC to identify the target genes regulated by this miRNA. Ectopic expression of miR-218 greatly inhibited cancer cell migration and invasion in the lung SCC cell lines EBC-1 and SK-MES-1. Through a combination of in silico analysis and gene expression data searching, tumor protein D52 (TPD52) was selected as a putative target of miR-218 regulation. Moreover, direct binding of miR-218 to the 3'-UTR of TPD52 was observed by dual luciferase reporter assay. Overexpression of TPD52 was observed in lung SCC clinical specimens, and knockdown of TPD52 significantly suppressed cancer cell migration and invasion in lung SCC cell lines. Furthermore, the downstream pathways mediated by TPD52 involved critical regulators of genomic stability and mitotic checkpoint genes. Taken together, our data showed that downregulation of miR-218 enhances overexpression of TPD52 in lung SCC cells, promoting cancer cell aggressiveness. Identification of tumor-suppressive miRNA-mediated RNA networks of lung SCC will provide new insights into the potential mechanisms of the molecular pathogenesis of the disease.