Upregulation of cyclin B1 plays potential roles in the invasiveness of pituitary adenomas

Clinical and Molecular Characteristics of Gonadotroph Pituitary Tumors According to the WHO Classification

Since 2017, hormone-negative pituitary neuroendocrine tumors expressing the steroidogenic factor SF1 have been recognized as gonadotroph tumors (GnPT) but have been poorly studied. To further characterize their bio-clinical spectrum, 54 GnPT defined by immunostaining for FSH and/or LH (group 1, n = 41) or SF1 only (group 2, n = 13) were compared and studied for SF1, βFSH, βLH, CCNA2, CCNB1, CCND1, caspase 3, D2R, and AIP gene expression by qRT-PCR. Immunohistochemistry for AIP and/or D2R was performed in representative cases. Overall, patients were significantly younger in group 1 (P = 0.040 vs group 2), with a similar trend excluding recurrent cases (P = 0.078), and no significant difference in gender, tumor size, invasion or Ki67. SF1 expression was similar in both groups but negatively correlated with the patient's age (P = 0.013) and positively correlated with βLH (P < 0.001) expression. Beta-FSH and AIP were significantly higher in group 1 (P = 0.042 and P = 0.024, respectively). Ki67 was unrelated to gonadotroph markers but positively correlated with CCNB1 (P = 0.001) and negatively correlated with CCND1 (P = 0.008). D2R and AIP were strongly correlated with each other (P < 0.001), and both positively correlated with SF1, βFSH, βLH, and CCND1. AIP immunopositivity was frequently observed in both groups, with a similar median score, and unrelated to Ki67. D2R immunostaining was best detected with a polyclonal antibody and mostly cytoplasmic. This study indicates that hormone-negative GnPT tend to occur in older patients but do not significantly differ from other GnPT in terms of invasion or proliferation. It also points out the current limits of D2R immunostaining in such tumors.

Regulation of long noncoding RNAs in the pathogenesis and clinical implications of pituitary adenomas

BACKGROUND

Pituitary adenoma (PA) is a type of tumor that develops in the sella turcica and is one of the most frequent intracranial tumors. It belongs to a type of adenoma derived from a single clone of cells in the pituitary gland. PA ranks third among all intracranial tumors, following only gliomas and meningioma. The average prevalence rate is approximately 15% at autopsy and 22.5% at radiological examinations.

OBJECTIVE AND SIGNIFICANCE

Most PAs are benign and non-invasive adenomas that can be removed surgically or controlled with medication. However, approximately 35% of them show invasion into nearby anatomical structures and cannot be completely resected. 0.1%~0.2% of PA cases eventually develop into pituitary carcinomas. Additionally, PA may cause severe morbidity due to mass effects and the disorder of pituitary hormone secretion. Therefore, there is an urgent need to clarify the pathological mechanism of PA, improve the accuracy of diagnosis, and develop targeted therapies.

RESEARCH STATUS

Although current knowledge about the pathogenesis of PA remains limited, epigenetic modulation of PA has been increasingly implicated. Long non-coding RNAs (lncRNAs) are known to regulate gene expression post-transcriptionally and exert substantial roles in the initiation, progression, or suppression of various tumors. Accumulating evidence has shown close relationships between lncRNA dysregulation and PA development.

CONCLUSIONS

This review highlights recent progress in the study of lncRNAs in PA pathogenesis and their potential as diagnostic/prognostic biomarkers or therapeutic targets for PA patients.

Non-coding RNAs and exosomal non-coding RNAs in pituitary adenoma

Pituitary adenoma (PA) is the third most common primary intracranial tumor in terms of overall disease incidence. Although they are benign tumors, they can have a variety of clinical symptoms, but are mostly asymptomatic, which often leads to diagnosis at an advanced stage when surgical intervention is ineffective. Earlier identification of PA could reduce morbidity and allow better clinical management of the affected patients. Non-coding RNAs (ncRNAs) do not generally code for proteins, but can modulate biological processes at the post-transcriptional level through a variety of molecular mechanisms. An increased number of ncRNA expression profiles have been found in PAs. Therefore, understanding the expression patterns of different ncRNAs could be a promising method for developing non-invasive biomarkers. This review summarizes the expression patterns of dysregulated ncRNAs (microRNAs, long non-coding RNAs, and circular RNAs) involved in PA, which could one day serve as innovative biomarkers or therapeutic targets for the treatment of this neoplasia. We also discuss the potential molecular pathways by which the dysregulated ncRNAs could cause PA and affect its progression.

Identification of functional genes regulating gastric cancer progression using integrated bioinformatics analysis

BACKGROUND

Gastric cancer (GC) is one of the most common cancers and has a poor prognosis. Treatment of GC has remained unchanged over the past few years.

AIM

To investigate the potential therapeutic targets and related regulatory biomarkers of GC.

METHODS

We obtained the public GC transcriptome sequencing dataset from the Gene Expression Omnibus database. The datasets contained 348 GC tissues and 141 healthy tissues. In total, 251 differentially expressed genes (DEGs) were identified, including 187 down-regulated genes and 64 up-regulated genes. The DEGs' enriched functions and pathways include Progesterone-mediated oocyte maturation, cell cycle, and oocyte meiosis, Hepatitis B, and the Hippo signaling pathway. Survival analysis showed that BUB1, MAD2L1, CCNA2, CCNB1, and BIRC5 may be associated with regulation of the cell cycle phase mitotic spindle checkpoint pathway. We selected 26 regulated genes with the aid of the protein-protein interaction network analyzed by Molecular Complex Detection.

RESULTS

We focused on three critical genes, which were highly expressed in GC, but negatively related to patient survival. Furthermore, we found that knockdown of BIRC5, TRIP13 or UBE2C significantly inhibited cell proliferation and induced cell apoptosis. In addition, knockdown of BIRC5, TRIP13 or UBE2C increased cellular sensitivity to cisplatin.

CONCLUSION

Our study identified significantly upregulated genes in GC with a poor prognosis using integrated bioinformatics methods.

Analysis of the Prognostic and Immunological Role of HSPB1 in Pituitary Adenoma: A Potential Target for Therapy

Background and Objectives: The diagnosis and treatment of pituitary adenomas with cavernous sinus invasion pose significant challenges for clinicians. The objective of this study is to investigate the expression profile and prognostic value of HSPB1 (heat shock protein beta-1) in pituitary adenomas with invasive and non-invasive features. Additionally, we aim to explore the potential relationship between HSPB1 expression and immunological functions in pituitary adenoma. Materials and Methods: A total of 159 pituitary adenoma specimens (73 invasive tumours and 86 non-invasive tumours) underwent whole-transcriptome sequencing. Differentially expressed genes and pathways in invasive and non-invasive tumours were analysed. HSPB1 was subjected to adequate bioinformatics analysis using various databases such as TIMER, Xiantao and TISIDB. We investigated the correlation between HSPB1 expression and immune infiltration in cancers and predicted the target drug of HSPB1 using the TISIDB database. Results: HSPB1 expression was upregulated in invasive pituitary adenomas and affected immune cell infiltration. HSPB1 was significantly highly expressed in most tumours compared to normal tissues. High expression of HSPB1 was significantly associated with poorer overall survival. HSPB1 was involved in the regulation of the immune system in most cancers. The drugs DB11638, DB06094 and DB12695 could act as inhibitors of HSPB1. Conclusions: HSPB1 may serve as an important marker for invasive pituitary adenomas and promote tumour progression by modulating the immune system. Inhibitors of HSPB1 expression are currently available, making it a potential target for therapy in invasive pituitary adenoma.

Identifying M1-like macrophage related genes for prognosis prediction in lung adenocarcinoma based on a gene co-expression network

Macrophages are one of the most important players in the tumor microenvironment. But the contribution of macrophages to lung adenocarcinoma (LUAD) is still controversial. The current study aimed to display an immune landscape to clarify the function of macrophages and detect prognostic hub genes in LUAD. The transcriptome data were adopted to screen differently expressed genes (DEGs) in The Cancer Genome Atlas database (TCGA). The cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was used to reveal the immune landscape. Weighted gene co-expression network analysis (WGCNA) analysis was performed to identify the hub module associated with macrophages. Function Enrichment analysis was conducted on hub module genes. Moreover, univariate and multivariate Cox regression analyses were performed to identify prognostic hub genes. Kaplan-Meier (KM) and Time-dependent receiver operating characteristic (ROC) curves were plotted to assess the prognostic capacity of the four prognostic hub genes. The GES1196959 dataset from the Gene Expression Omnibus (GEO) database was downloaded to verify the differential expression of the 4 prognostic hub genes.

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.

Differentially Expressed Cell Cycle Genes and STAT1/3-Driven Multiple Cancer Entanglement in Psoriasis, Coupled with Other Comorbidities

Psoriasis is a persistent T-cell-supported inflammatory cutaneous disorder, which is defined by a significant expansion of basal cells in the epidermis. Cell cycle and STAT genes that control cell cycle progression and viral infection have been revealed to be comorbid with the development of certain cancers and other disorders, due to their abnormal or scanty expression. The purpose of this study is to evaluate the expression of certain cell cycle and STAT1/3 genes in psoriasis patients and to determine the types of comorbidities associated with these genes. To do so, we opted to adopt the in silico methodology, since it is a quick and easy way to discover any potential comorbidity risks that may exist in psoriasis patients. With the genes collected from early research groups, protein networks were created in this work using the NetworkAnalyst program. The crucial hub genes were identified by setting the degree parameter, and they were then used in gene ontology and pathway assessments. The transcription factors that control the hub genes were detected by exploring TRRUST, and DGIdb was probed for remedies that target transcription factors and hubs. Using the degree filter, the first protein subnetwork produced seven hub genes, including STAT3, CCNB1, STAT1, CCND1, CDC20, HSPA4, and MAD2L1. The hub genes were shown to be implicated in cell cycle pathways by the gene ontology and Reactome annotations. The former four hubs were found in signaling pathways, including prolactin, FoxO, JAK/STAT, and p53, according to the KEGG annotation. Furthermore, they enhanced several malignancies, including pancreatic cancer, Kaposi's sarcoma, non-small cell lung cancer, and acute myeloid leukemia. Viral infections, including measles, hepatitis C, Epstein-Barr virus, and HTLV-1 and viral carcinogenesis were among the other susceptible diseases. Diabetes and inflammatory bowel disease were conjointly annotated. In total, 129 medicines were discovered in DGIdb to be effective against the transcription factors BRCA1, RELA, TP53, and MYC, as opposed to 10 medications against the hubs, STAT3 and CCND1, in tandem with 8 common medicines. The study suggests that the annotated medications should be tested in suitable psoriatic cell lines and animal models to optimize the drugs used based on the kind, severity, and related comorbidities of psoriasis. Furthermore, a personalized medicine protocol must be designed for each psoriasis patient that displays different comorbidities.

A systematic review of molecular alterations in invasive non-functioning pituitary adenoma

PURPOSE

Invasive non-functional pituitary adenomas (NFPAs) constitute 35% of NFPAs. Despite a relatively large body of molecular investigations on the invasiveness of NFPA, the underlying molecular mechanisms of invasiveness are yet to be determined. Herein, we aimed to provide an overview of gene/microRNA(miRNAs) expression alterations in invasive NFPA.

METHODS

This article describes a systematic literature review of articles published up to March 23, 2021, on the transcriptional alterations of invasive NFPA. Five digital libraries were searched, and 42 articles in total fulfilled the eligibility criteria. Pathway enrichment was conducted, and protein interactions among the identified deregulated genes were inferred.

RESULTS

In total 133 gene/protein transcriptional alterations, comprising 87 increased and 46 decreased expressions, were detected in a collective number of 1001 invasive compared with 1007 non-invasive patients with NFPA. Deregulation of CDH1, PTTG1, CCNB1, SNAI1, SLUG, EZR, and PRKACB, which are associated with epidermal-mesenchymal transition (EMT), was identified. Moreover, six members of the angiogenesis pathway, i.e., VEGFA, FLT1, CCND1, CTNNB1, MYC(c-MYC), and PTTG1, were detected. SLC2A1, FLT1, and VEGFA were also recognized in the hypoxia pathway. Physical interactions of CTNNB1 with FLT1, CCND1, and EZR as well as its indirect interactions with VEGFA, MYC, CCNB1, and PCNA indicate the tight interplay between EMT, angiogenesis, and hypoxia pathways in invasive NFPAs. In addition, Hippo, JAK-STAT, MAPK, Wnt, PI3K-Akt, Ras, TGF-b, VEGF, and ErbB were identified as interwoven signaling pathways.

CONCLUSION

In conclusion, invasive NFPA shares very common deregulated signaling pathways with invasive cancers. A large amount of heterogeneity in the reported deregulations in different studies necessitates the validation of the expressional changes of the suggested biomarkers in a large number of patients with invasive NFPA.

Long noncoding RNA PTTG3P/miR-192-3p/CCNB1 axis is a potential biomarker of childhood asthma

BACKGROUND

Increasing evidence suggests that long non-coding RNAs (lncRNAs) affect the regulation of immune responses, airway inflammation, and other pathological processes involved in asthma. LncRNA PTTG3P is associated with the development of various tumors, but its role in childhood asthma remains unknown. In this study, we investigated the functions of the lncRNA PTTG3P in the progression of childhood asthma.

METHODS

Twenty-six healthy children and 26 asthmatic children were monitored for disease progression for 2 years. We obtained blood samples during the chronic phase of disease for lncRNA/mRNA expression microarray analysis. A competitive endogenous RNA network (PTTG3P/miR-192-3p/CCNB1) was identified using bioinformatics analyses. Real-time qPCR and western blot were used to quantify gene and protein expression levels, respectively. Cell counting kit‑8 and transwell assays were used to evaluate the proliferation and migration of bronchial epithelial (16HBE) cells. Double luciferase reporter gene assay was used to validate the predictive targets in PTTG3P, miR-192-3p, and CCNB1.

RESULTS

PTTG3P was highly expressed in the peripheral blood of asthmatic children. Knocking down PTTG3P inhibited epithelial-mesenchymal transition, proliferation, and migration of 16HBE cells. PTTG3P promoted progression of childhood asthma by targeting the miR-192-3p/CCNB1 axis.

CONCLUSIONS

Childhood asthma was associated with the PTTG3P/miR-192-3p/CCNB1 axis. This study provides potential diagnostic and treatment biomarkers for childhood asthma.

CircNFIX promotes progression of pituitary adenoma via CCNB1 by sponging miR-34a -5p

Previous studies have shown that CCNB1 affects the invasiveness of pituitary adenomas, and it is of great significance to find the upstream mechanism of regulating CCNB1.In this study, we explored a significantly overexpressed circRNA in invasive pituitary adenomas. Based on bioinformatics analysis and mechanism experiments, we determined that circNFIX (has-circ_0005660) affects cell invasion, migration and proliferation in pituitary adenomas by sponging miR-34a-5p through CCNB1. In pituitary adenoma tissues, the expression of circNFIX and CCNB1 was upregulated, while miR-34a-5p expression was downregulated. The silencing of circNFIX or overexpression of miR-34a-5p inhibited cell invasion, migration and proliferation. Inhibition of miR-34a-5p expression reversed the inhibitory effect of circNFIX silencing on the progression of pituitary adenoma. In conclusion, CircNFIX affects cell invasion, migration, and proliferation in pituitary adenomas by sponging miR-34a-5p through CCNB1. Therefore, circNFIX is expected to serve as a potential target for the treatment of pituitary adenomas.

Identification and validation of three core genes in p53 signaling pathway in hepatitis B virus-related hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common cancer and the leading cause is persistent hepatitis B virus (HBV) infection. We aimed to identify some core genes and pathways for HBV-related HCC.

METHODS

Gene expression profiles of GSE62232, GSE121248, and GSE94660 were available from Gene Expression Omnibus (GEO). The GSE62232 and GSE121248 profiles were the analysis datasets and GSE94660 was the validation dataset. The GEO2R online tool and Venn diagram software were applied to analyze commonly differentially expressed genes between HBV-related HCC tissues and normal tissues. Then, functional enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Gene and Genome (KEGG) as well as the protein-protein interaction (PPI) network was conducted. The overall survival rates and the expression levels were detected by Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA). Next, gene set enrichment analysis (GSEA) was performed to verify the KEGG pathway analysis. Furthermore, quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was performed to validate the levels of these three core genes in tumor tissues and adjacent non-tumor liver tissues from 12 HBV related HCC patients, HBV-associated liver cancer cell lines and normal liver cell lines, and HepG2 with p53 knockdown or deletion, respectively.

RESULTS

Fifteen highly expressed genes associated with significantly worse prognoses were selected and CCNB1, CDK1, and RRM2 in the p53 signaling pathway were identified as core genes. GSEA results showed that samples highly expressing three core genes were all enriched in the p53 signaling pathway in a validation dataset (P < 0.0001). The expression of these three core genes in tumor tissue samples was higher than that in relevant adjacent non-tumor liver tissues (P < 0.0001). Furthermore, we also found that the above genes were highly expressed in liver cancer cell lines compared with normal liver cells. In addition, we found that the expression of these three core genes in p53 knockdown or knockout HCC cell lines was lower than that in negative control HCC cell lines (P < 0.05).

CONCLUSIONS

CCNB1, CDK1, and RRM2 were enriched in the p53 signaling pathway and could be potential biomarkers and therapeutic targets for HBV-related HCC.

Identification of CDC25C as a Potential Biomarker in Hepatocellular Carcinoma Using Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is the most aggressive type of gastrointestinal tumor, with a high rate of mortality. However, identifying biomarkers for the treatment of HCC remains to be developed. We aimed to determine whether cell division cycle 25C (CDC25C) could be used as a novel diagnostic and therapeutic biomarker in HCC. Expression of CDC25C in HCC was analyzed by using GEPIA (Gene Expression Profiling Interactive Analysis) and UALCAN databases. GEPIA and CBioPortal databases were applied to analyze patients’survival and CDC25C mutations, respectively. PPI (Protein-Protein Interaction) network was further built by STRING (Search Tool for the Retrieval of Interacting Genes) and Metascape Web portals. To the best of our knowledge, the novel observations identified in the present study reveal that the expression of CDC25C in HCC was significantly enhanced when compare to that in normal liver tissues (P < 0.001). A higher CDC25C expression resulted in a remarkably shorter disease free survival as well as overall survival. Moreover, the expression of CDC25C in HCC was related to HCC patients’grade and race, but not gender. The expression levels of CDC25C elevated gradually from stage 1 to 3 but decreased in stage 4. The specific gene mutations V41A, L87 H, N222 K and X309-splice of CDC25C occurred in HCC samples and these unique mutations were not detected in any other tumor tissues. Finally, PPI networks and GO enrichment analysis suggested that CDC25C might be associated with cell cycle and p53 signaling pathway. Taken together, bioinformatics analysis revealed that CDC25C might be a potential diagnostic predictor for HCC.

Molecular differences across invasive lung adenocarcinoma morphological subgroups

Background

Lung adenocarcinomas (ADCs) show heterogeneous morphological patterns that are classified into five subgroups: lepidic predominant, papillary predominant, acinar predominant, micropapillary predominant and solid predominant. The morphological classification of ADCs has been reported to be associated with patient prognosis and adjuvant chemotherapy response. However, the molecular mechanisms underlying the morphology differences among different subgroups remain largely unknown.

Methods

Using the molecular profiling data from The Cancer Genome Atlas (TCGA) lung ADC (LUAD) cohort, we studied the molecular differences across invasive ADC morphological subgroups.

Results

We showed that the expression of proteins and mRNAs, but not the gene mutations copy number alterations (CNA), were significantly associated with lung ADC morphological subgroups. In addition, expression of the FOXM1 gene (which is negatively associated with patient survival) likely plays an important role in the morphological differences among different subgroups. Moreover, we found that protein abundance of PD-L1 were associated with the malignancy of subgroups. These results were validated in an independent cohort.

Conclusions

This study provides insights into the molecular differences among different lung ADC morphological subgroups, which could lead to potential subgroup-specific therapies.

Comprehensive Analysis of Candidate Diagnostic and Prognostic Biomarkers Associated with Lung Adenocarcinoma

Background

We aimed to screen and identify central genetic and molecular targets involved in advancement of lung adenocarcinoma (LUAD) and to perform an integrated analysis and clinical validation.

Material/Methods

The GEO2R technique was utilized to assess differentially expressed genes (DEGs) among the gene sets GSE75037, GSE85716, and GSE118370. Subsequently, gene Ontology (GO) analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) analytical methods were executed to determine related biofunctions and signaling pathways, which were annotated with tools from the Database for Annotation, Visualization and Integrated Discovery (DAVID) resource. Then, a protein-protein interaction (PPI) network complex consisting of all detected DEGs was built with the STRING web interface. Cytohubba and MCODE plug-ins for Cytoscape software and Gene Expression Profiling Interactive Analysis (GEPIA) were employed to identify the hub genes. Finally, the mRNA expression of the identified hub genes was quantitatively validated by The Cancer Genome Atlas (TCGA) database analysis and real-time quantitative polymerase chain reaction (RT-qPCR).

Results

We screened 146 upregulated DEGs and 431 downregulated DEGs with the criteria of |logFC| >1 and P<0.05, and the GO analysis indicated that DEGs were implicated in mitotic nuclear division (biological process, BP), the nucleus (cellular component, CC), and protein binding (molecular function, MF) and were associated with multiple KEGG pathways, such as the p53 signaling pathway in cancer. Then, the top 8 genes that predicted significantly different outcomes in LUAD patients were filtered from the DEGs and selected as hub genes. The TCGA database analysis and RT-qPCR results demonstrated that these genes were differentially expressed with the same trends in LUAD tissues compared with normal tissues.

Conclusions

Overall, we propose that 8 genes (PECAM1, CDK1, MKI67, SPP1, TOP2A, CHEK1, CCNB1, and RRM2) might be novel hub genes strongly associated with the progression and prognosis of LUAD.

Cancer classification from time series microarray data through regulatory Dynamic Bayesian Networks

Genomic profiling of cancer studies has generated comprehensive gene expression patterns for diverse phenotypes. Computational methods which employ transcriptomics datasets have been proposed to model gene expression data. Dynamic Bayesian Networks (DBNs) have been used for modeling time series datasets and for the inference of regulatory networks. Furthermore, cancer classification through DBN-based approaches could reveal the importance of exploiting knowledge from statistically significant genes and key regulatory molecules. Although microarray datasets have been employed extensively by several classification methods for decision making, the use of new knowledge from the pathway level has not been addressed adequately in the literature in terms of DBNs for cancer classification. In the present study, we identify the genes that act as regulators and mediate the activity of transcription factors that have been found in all promoters of our differentially expressed gene sets. These features serve as potential priors for distinguishing tumor from normal samples using a DBN-based classification approach. We employed three microarray datasets from the Gene Expression Omnibus (GEO) public functional repository and performed differential expression analysis. Promoter and pathway analysis of the identified genes revealed the key regulators which influence the transcription mechanisms of these genes. We applied the DBN algorithm on selected genes and identified the features that can accurately classify the samples into tumors and controls. Both accuracy and Area Under the Curve (AUC) were high for the gene sets comprising of the differentially expressed genes along with their master regulators (accuracy: 70.8%-98.5%; AUC: 0.562-0.985).

CCNB1 affects cavernous sinus invasion in pituitary adenomas through the epithelial-mesenchymal transition

BACKGROUND

To investigate the relationship between cyclin B1 (CCNB1) gene expression and cavernous sinus invasion in pituitary adenomas.

METHODS

Twenty-four pituitary adenoma tissue samples were examined by RT-qPCR and Western blot to assess the mRNA expression levels and protein levels of CCNB1, E-cadherin and N-cadherin. Correlation analyses between the expression levels of E-cadherin, N-cadherin and CCNB1 were performed. After lentivirus-mediated knockdown of CCNB1 in rat pituitary adenoma cell lines (GH3 and GT1-1), cell function changes were studied. The relationship between CCNB1 and epithelial-mesenchymal transition (EMT) was further verified by animal experiments.

RESULTS

CCNB1 and N-cadherin gene expression were significantly higher in the invasive pituitary adenomas than in the non-invasive pituitary adenomas. Conversely, E-cadherin expression in the invasive pituitary adenomas was significantly lower. CCNB1 gene expression was downregulated in the GH3 and GT1-1 pituitary adenoma cell lines; N-cadherin expression was also decreased, but E-cadherin expression was increased. These results were confirmed in vivo. After downregulation of CCNB1, cell invasion and migration was significantly reduced in Transwell experiments.

CONCLUSION

High CCNB1 expression in pituitary adenoma affects cavernous sinus invasion through EMT.

Regulating the CCNB1 gene can affect cell proliferation and apoptosis in pituitary adenomas and activate epithelial-to-mesenchymal transition

The aim of the present study was to investigate the role and potential regulatory mechanisms of cyclin B1 (CCNB1) in the proliferation, apoptosis and epithelial-to-mesenchymal transition (EMT) in pituitary adenomas. A total of 24 specimens were included in the present study. The expression levels of CCNB1 protein in two normal pituitary and 22 pituitary adenoma tissues were determined by western blotting. CCNB1 was knocked-down by lentiviral-mediated infection of short hairpin RNA (shRNA) in GH3 and MMQ cell lines. The proliferation, cell cycle and apoptosis of GH3 and MMQ cell lines were detected using a Cell Counting Kit-8 and flow cytometer. Reverse transcription-quantitative PCR was utilized to detect the expression level of CCNB1 gene and EMT markers. In the present study, resveratrol (RES) was used as an inhibitor of CCNB1. The protein expression level of CCNB1 in pituitary adenomas was higher than that in normal pituitary tissue, as assessed by western blot analysis. In addition, the expression level of CCNB1 in invasive pituitary adenomas was higher when comparing invasive pituitary adenomas and non-invasive pituitary adenomas. Knockdown of CCNB1 resulted in significant decreases in cell viability and proliferation, arrested cell cycle at the G₂/M phase and increased apoptosis. In addition, knockdown of CCNB1 significantly decreased the expression levels of the mesothelial cell marker N-cadherin (P<0.001), but significantly increased the expression levels of the epithelial cell markers E-cadherin (P<0.01) and p120-catenin (P<0.001). Further analyses identified that RES inhibited the expression level of CCNB1, and RES treatment exhibited a similar effect as CCNB1 shRNA infection. The present study suggested that suppressing the expression level of CCNB1 could regulate the proliferation and apoptosis of pituitary tumor cells and alter the expression level of various EMT markers. In addition, RES treatment could be used as an inhibitor of CCNB1. The present study also identified the molecular mechanisms underlying CCNB1 role in EMT.

Identification of significant genes with poor prognosis in ovarian cancer via bioinformatical analysis

Ovarian cancer (OC) is the highest frequent malignant gynecologic tumor with very complicated pathogenesis. The purpose of the present academic work was to identify significant genes with poor outcome and their underlying mechanisms. Gene expression profiles of GSE36668, GSE14407 and GSE18520 were available from GEO database. There are 69 OC tissues and 26 normal tissues in the three profile datasets. Differentially expressed genes (DEGs) between OC tissues and normal ovarian (OV) tissues were picked out by GEO2R tool and Venn diagram software. Next, we made use of the Database for Annotation, Visualization and Integrated Discovery (DAVID) to analyze Kyoto Encyclopedia of Gene and Genome (KEGG) pathway and gene ontology (GO). Then protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). There were total of 216 consistently expressed genes in the three datasets, including 110 up-regulated genes enriched in cell division, sister chromatid cohesion, mitotic nuclear division, regulation of cell cycle, protein localization to kinetochore, cell proliferation and Cell cycle, progesterone-mediated oocyte maturation and p53 signaling pathway, while 106 down-regulated genes enriched in palate development, blood coagulation, positive regulation of transcription from RNA polymerase II promoter, axonogenesis, receptor internalization, negative regulation of transcription from RNA polymerase II promoter and no significant signaling pathways. Of PPI network analyzed by Molecular Complex Detection (MCODE) plug-in, all 33 up-regulated genes were selected. Furthermore, for the analysis of overall survival among those genes, Kaplan–Meier analysis was implemented and 20 of 33 genes had a significantly worse prognosis. For validation in Gene Expression Profiling Interactive Analysis (GEPIA), 15 of 20 genes were discovered highly expressed in OC tissues compared to normal OV tissues. Furthermore, four genes (BUB1B, BUB1, TTK and CCNB1) were found to significantly enrich in the cell cycle pathway via re-analysis of DAVID. In conclusion, we have identified four significant up-regulated DEGs with poor prognosis in OC on the basis of integrated bioinformatical methods, which could be potential therapeutic targets for OC patients.

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.