ISL1, a novel regulator of CCNB1, CCNB2 and c-MYC genes, promotes gastric cancer cell proliferation and tumor growth

Integrated GMPS and RAMP3 as a signature to predict prognosis and immune heterogeneity in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a highly fatal malignant worldwide. As different expression levels of specific genes can lead to different HCC outcomes, we aimed to develop a gene signature capable of predicting HCC prognosis.

METHODS

In this study, transcriptomic sequencing and relevant clinical data were extracted from public platforms. The guanine monophosphate synthase (GMPS)|receptor activity-modifying protein 3 (RAMP3) gene pair was developed based on the relative values of gene expression levels. Nomograms were developed using R software. Immune status was assessed through single-sample gene set enrichment analysis. GMPS knockdown was achieved through siRNA transfection. Quantitative reverse transcription PCR, apoptosis assays, and cell proliferation were performed to verify the function of GMPS|RAMP3 in HCC cells.

RESULTS

Here, a gene pair containing GMPS and RAMP3 was successfully constructed. We demonstrated that the GMPS|RAMP3 gene pair was an independent predictor with strong prognostic prediction power, based on which a nomogram was established. Functional analysis revealed that the enrichment of cell cycle-related pathways and immune status differed considerably between the two groups, with cell cycle-related genes highly expressed in the high GMPS|RAMP3 value group. Finally, cell experiments indicated that GMPS knockdown significantly repressed proliferation, promoted apoptosis, and enhanced the sensitivity of HCC cells to gemcitabine.

CONCLUSIONS

The gene pair GMPS|RAMP3 is a novel prognostic predictor of HCC, providing a promising approach to the treatment and assessment of immune heterogeneity in HCC.

Suppression of N-Glycosylation of Zinc Finger Protein 471 Affects Proliferation, Invasion, and Docetaxel Sensitivity of Tongue Squamous Cell Carcinoma via Regulation of c-Myc

Zinc finger protein 471 (ZNF471) is a member of the Krüppel-related domain zinc finger protein family, and has recently attracted attention because of its anti-cancer effects. N-glycosylation regulates expression and functions of the protein. This study aimed to investigate the effects of ZNF471 N-glycosylation on the proliferation, invasion, and docetaxel sensitivity of tongue squamous cell carcinoma (TSCC). It analyzed the expression, function, and prognostic significance of ZNF471 in TSCC using bioinformatics techniques such as gene differential expression analysis, univariate Cox regression analysis, functional enrichment analysis, and gene set enrichment analysis. Using site-specific mutagenesis, this study generated three mutant sites for ZNF471 N-glycosylation to determine the effect of N-glycosylation on ZNF471 protein levels and function. Quantitative real-time PCR, Western blot analysis, and immunohistochemistry tests confirmed the down-regulation of ZNF471 expression in TSCC. Low expression of ZNF471 is associated with poor prognosis of patients with TSCC. Overexpression of ZNF471 in vitro retarded the proliferation of TSCC cells and suppressed cell invasion and migration ability. Asparagine 358 was identified as a N-glycosylation site of ZNF471. Suppressing N-glycosylation of ZNF471 enhanced the protein stability and promoted the translocation of protein to the cell nucleus. ZNF471 binding to c-Myc gene promoter suppressed oncogene c-Myc expression, thereby playing the anti-cancer effect and enhancing TSCC sensitivity to docetaxel. In all, N-glycosylation of ZNF471 affects the proliferation, invasion, and docetaxel sensitivity of TSCC via regulation of c-Myc.

Comprehensive analysis of the potential pathogenesis of COVID-19 infection and liver cancer

BACKGROUND

A growing number of clinical examples suggest that coronavirus disease 2019 (COVID-19) appears to have an impact on the treatment of patients with liver cancer compared to the normal population, and the prevalence of COVID-19 is significantly higher in patients with liver cancer. However, this mechanism of action has not been clarified.

AIM

To investigate the disease relevance of COVID-19 in liver cancer.

METHODS

Gene sets for COVID-19 (GSE180226) and liver cancer (GSE87630) were obtained from the Gene Expression Omnibus database. After identifying the common differentially expressed genes (DEGs) of COVID-19 and liver cancer, functional enrichment analysis, protein-protein interaction network construction and screening and analysis of hub genes were performed. Subsequently, the validation of the differential expression of hub genes in the disease was performed and the regulatory network of transcription factors and hub genes was constructed.

RESULTS

Of 518 common DEGs were obtained by screening for functional analysis. Fifteen hub genes including aurora kinase B, cyclin B2, cell division cycle 20, cell division cycle associated 8, nucleolar and spindle associated protein 1, etc., were further identified from DEGs using the "cytoHubba" plugin. Functional enrichment analysis of hub genes showed that these hub genes are associated with P53 signalling pathway regulation, cell cycle and other functions, and they may serve as potential molecular markers for COVID-19 and liver cancer. Finally, we selected 10 of the hub genes for in vitro expression validation in liver cancer cells.

CONCLUSION

Our study reveals a common pathogenesis of liver cancer and COVID-19. These common pathways and key genes may provide new ideas for further mechanistic studies.

The benign nature and rare occurrence of cardiac myxoma as a possible consequence of the limited cardiac proliferative/ regenerative potential: a systematic review

BACKGROUND

Cardiac Myxoma is a primary tumor of heart. Its origins, rarity of the occurrence of primary cardiac tumors and how it may be related to limited cardiac regenerative potential, are not yet entirely known. This study investigates the key cardiac genes/ transcription factors (TFs) and signaling pathways to understand these important questions.

METHODS

Databases including PubMed, MEDLINE, and Google Scholar were searched for published articles without any date restrictions, involving cardiac myxoma, cardiac genes/TFs/signaling pathways and their roles in cardiogenesis, proliferation, differentiation, key interactions and tumorigenesis, with focus on cardiomyocytes.

RESULTS

The cardiac genetic landscape is governed by a very tight control between proliferation and differentiation-related genes/TFs/pathways. Cardiac myxoma originates possibly as a consequence of dysregulations in the gene expression of differentiation regulators including Tbx5, GATA4, HAND1/2, MYOCD, HOPX, BMPs. Such dysregulations switch the expression of cardiomyocytes into progenitor-like state in cardiac myxoma development by dysregulating Isl1, Baf60 complex, Wnt, FGF, Notch, Mef2c and others. The Nkx2-5 and MSX2 contribute predominantly to both proliferation and differentiation of Cardiac Progenitor Cells (CPCs), may possibly serve roles based on the microenvironment and the direction of cell circuitry in cardiac tumorigenesis. The Nkx2-5 in cardiac myxoma may serve to limit progression of tumorigenesis as it has massive control over the proliferation of CPCs. The cardiac cell type-specific genetic programming plays governing role in controlling the tumorigenesis and regenerative potential.

CONCLUSION

The cardiomyocytes have very limited proliferative and regenerative potential. They survive for long periods of time and tightly maintain the gene expression of differentiation genes such as Tbx5, GATA4 that interact with tumor suppressors (TS) and exert TS like effect. The total effect such gene expression exerts is responsible for the rare occurrence and benign nature of primary cardiac tumors. This prevents the progression of tumorigenesis. But this also limits the regenerative and proliferative potential of cardiomyocytes. Cardiac Myxoma develops as a consequence of dysregulations in these key genes which revert the cells towards progenitor-like state, hallmark of CM. The CM development in carney complex also signifies the role of TS in cardiac cells.

Identification of early diagnostic biomarkers for breast cancer through bioinformatics analysis

In the realm of clinical practice, there is currently an insufficiency of distinct biomarkers available for the detection of breast cancer. It is of utmost importance to promptly employ bioinformatics methodologies to investigate prospective biomarkers for breast cancer, with the ultimate goal of achieving early diagnosis of the disease. The initial phase of this investigation involved the identification of 2 breast cancer gene chips meeting the specified criteria within the gene expression omnibus database. Subsequently, paired data analysis was conducted on these datasets, leading to the identification of differentially expressed genes (DEGs). In addition, this study executed Gene Ontology enrichment analysis and Kyoto encyclopedia of genes and genomes pathway enrichment analysis. The subsequent stage involved the construction of a protein-protein interaction network graph using the STRING website and Cytoscape software, facilitating the calculation of Hub genes. Lastly, the UALCAN database and Kaplan-Meier survival plots were utilized to perform differential expression and survival analysis on the selected Hub genes. A total of 733 DEGs were identified from the combined analysis of 2 datasets. Among these DEGs, 441 genes were found to be downregulated, while 292 genes were upregulated. The selected DEGs underwent comprehensive analysis, including gene ontology enrichment analysis, Kyoto encyclopedia of genes and genomes pathway enrichment analysis, and establishing a protein-protein interaction network. As a result, 10 Hub genes closely associated with early diagnosis of breast cancer were identified: PDZ-binding kinase, cell cycle protein A2, cell division cycle-associated protein 8, maternal embryonic leucine zipper kinase, nucleolar and spindle-associated protein 1, BIRC5, cell cycle protein B2, hyaluronan-mediated motility receptor, mitotic arrest deficient 2-like 1, and protein regulator of cytokinesis 1. The findings of this study unveiled the significant involvement of the identified 10 Hub genes in facilitating the growth and proliferation of cancer cells, particularly cell cycle protein A2, cell division cycle-associated protein 8, maternal embryonic leucine zipper kinase, nucleolar and spindle-associated protein 1, hyaluronan-mediated motility receptor, and protein regulator of cytokinesis 1, which demonstrated a more pronounced connection with the onset and progression of breast cancer. Further analysis through differential expression and survival analysis reaffirmed their strong correlation with the incidence of breast cancer. Consequently, the investigation of these 10 pertinent Hub genes presents novel prospects for potential biomarkers and valuable insights into the early diagnosis of breast cancer.

The cancer/testis antigen HORMAD1 promotes gastric cancer progression by activating the NF-κB signaling pathway and inducing epithelial-mesenchymal transition

OBJECTIVES

HORMAD1 is a cancer/testis antigen (CTAs) that regulates DNA homologous recombination, mismatch repair, and other tumor characteristics. However, its role and regulatory mechanisms in gastric cancer remain unclear.

METHODS

We performed transcriptomic profiling on seven gastric cancers and paired tissues; HORMAD1 was significantly upregulated in gastric cancer samples and was related to poor prognosis survival. Furthermore, cancer pathway microarray, bioinformatic analysis, western blot, and immunochemistry assay demonstrated that HORMAD1 affected the NF-κB signaling pathway.

RESULTS

In vitro and vivo studies confirmed that HORMAD1 knockdown inhibited cell growth and invasion, whereas overexpression reversed these effects. Mechanistically, HORMAD1 regulates the epithelial-mesenchymal transition process (EMT) via the NF-κB pathway by increasing the phosphorylation levels of NF-κB (p-65) and Iκκ-β. Downstream target genes of the NF-κB signaling pathway, such as c-Myc, CyclinD1, may be involved in HORMAD1-induced tumorigenesis in gastric cancer (GC).

CONCLUSIONS

HORMAD1 plays an important role in gastric cancer progression and could be a promising prognostic biomarker and therapeutic target.

Genome-wide DNA methylation analysis of Astragalus and Danshen on the intervention of myofibroblast activation in idiopathic pulmonary fibrosis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF), a chronic progressive interstitial lung disease of unknown etiology, is characterized by continuous damage to alveolar epithelial cells, abnormal repair of alveolar tissue, and alveolar wall scar formation. Currently, the recommended treatment for IPF in Western medicine is relatively limited. In contrast, traditional Chinese medicine and compound prescriptions show advantages in the diagnosis and treatment of IPF, which can be attributed to their multi-channel and multi-target characteristics and minimal side-effects. The purpose of this study was to further corroborate the effectiveness and significance of the traditional Chinese medications Astragalus and Danshen in IPF treatment.

METHODS

We performed whole-genome methylation analysis on nine rat lung tissue samples to determine the epigenetic variation between IPF and non-fibrotic lungs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and quantitative reverse transcription polymerase chain reactions.

RESULTS

We identified differentially methylated regions and 105 associated key functional genes in samples related to IPF and Chinese medicine treatment. Based on the methylation levels and gene expression profiles between the Chinese medicine intervention and pulmonary fibrosis model groups, we speculated that Astragalus and Salvia miltiorrhiza (traditionally known as Danshen) act on the Isl1, forkhead box O3, and Sonic hedgehog genes via regulation at transcriptional and epigenetic levels during IPF.

CONCLUSIONS

These findings provide novel insights into the epigenetic regulation of IPF, indicate the effectiveness of Astragalus and Danshen in treating IPF, and suggest several promising therapeutic targets for preventing and treating IPF.

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.

Network and functional analyses of differentially expressed genes in gastric cancer provide new biomarkers associated with disease pathogenesis

BACKGROUND

Gastric cancer is a dominant source of cancer-related death around the globe and a serious threat to human health. However, there are very few practical diagnostic approaches and biomarkers for the treatment of this complex disease.

METHODS

This study aimed to evaluate the association between differentially expressed genes (DEGs), which may function as potential biomarkers, and the diagnosis and treatment of gastric cancer (GC). We constructed a protein-protein interaction network from DEGs followed by network clustering. Members of the two most extensive modules went under the enrichment analysis. We introduced a number of hub genes and gene families playing essential roles in oncogenic pathways and the pathogenesis of gastric cancer. Enriched terms for Biological Process were obtained from the "GO" repository.

RESULTS

A total of 307 DEGs were identified between GC and their corresponding normal adjacent tissue samples in GSE63089 datasets, including 261 upregulated and 261 downregulated genes. The top five hub genes in the PPI network were CDK1, CCNB1, CCNA2, CDC20, and PBK. They are involved in focal adhesion formation, extracellular matrix remodeling, cell migration, survival signals, and cell proliferation. No significant survival result was found for these hub genes.

CONCLUSIONS

Using comprehensive analysis and bioinformatics methods, important key pathways and pivotal genes related to GC progression were identified, potentially informing further studies and new therapeutic targets for GC treatment.

Relationship between the deep features of the full-scan pathological map of mucinous gastric carcinoma and related genes based on deep learning

Background

Long-term differential expression of disease-associated genes is a crucial driver of pathological changes in mucinous gastric carcinoma. Therefore, there should be a correlation between depth features extracted from pathology-based full-scan images using deep learning and disease-associated gene expression. This study tried to provides preliminary evidence that long-term differentially expressed (disease-associated) genes lead to subtle changes in disease pathology by exploring their correlation, and offer a new ideas for precise analysis of pathomics and combined analysis of pathomics and genomics.

Methods

Full pathological scans, gene sequencing data, and clinical data of patients with mucinous gastric carcinoma were downloaded from TCGA data. The VGG-16 network architecture was used to construct a binary classification model to explore the potential of VGG-16 applications and extract the deep features of the pathology-based full-scan map. Differential gene expression analysis was performed and a protein-protein interaction network was constructed to screen disease-related core genes. Differential, Lasso regression, and extensive correlation analyses were used to screen for valuable deep features. Finally, a correlation analysis was used to determine whether there was a correlation between valuable deep features and disease-related core genes.

Result

The accuracy of the binary classification model was 0.775 ± 0.129. A total of 24 disease-related core genes were screened, including ASPM, AURKA, AURKB, BUB1, BUB1B, CCNA2, CCNB1, CCNB2, CDCA8, CDK1, CENPF, DLGAP5, KIF11, KIF20A, KIF2C, KIF4A, MELK, PBK, RRM2, TOP2A, TPX2, TTK, UBE2C, and ZWINT. In addition, differential, Lasso regression, and extensive correlation analyses were used to screen eight valuable deep features, including features 51, 106, 109, 118, 257, 282, 326, and 487. Finally, the results of the correlation analysis suggested that valuable deep features were either positively or negatively correlated with core gene expression.

Conclusion

The preliminary results of this study support our hypotheses. Deep learning may be an important bridge for the joint analysis of pathomics and genomics and provides preliminary evidence for long-term abnormal expression of genes leading to subtle changes in pathology.

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 hub genes and construction of prognostic nomogram for patients with Wilms tumors

Background

In children, Wilms' tumors are the most common urological cancer with unsatisfactory prognosis, but few molecular prognostic markers have been discovered for it. With the rapid development of high-throughput quantitative proteomic and transcriptomic approaches, the molecular mechanisms of various cancers have been comprehensively explored. This study aimed to uncover the molecular mechanisms underlying Wilms tumor and build predictive models by use of microarray and RNA-seq data.

Methods

Gene expression datasets were downloaded from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. Bioinformatics methods wereutilized to identified hub genes, and these hub genes were validated by experiment. Nomogram predicting OS was developed using genetic risk score model and clinicopathological variables.

Results

CDC20, BUB1 and CCNB2 were highly expressed in tumor tissues and able to affect cell proliferation and the cell cycle of SK-NEP-1 cells. This may reveal molecular biology features and a new therapeutic target of Wilms tumour.7 genes were selected as prognostic genes after univariate, Lasso, and multivariate Cox regression analyses and had good accuracy, a prognostic nomogram combined gene model with clinical factors was completed with high accuracy.

Conclusions

The current study discovered CDC20,BUB1 and CCNB2 as hub-genes associated with Wilms tumor, providing references to understand the pathogenesis and be considered a novel candidate to target therapy and construct novel nomogram, incorporating both clinical risk factors and gene model, could be appropriately applied in preoperative individualized prediction of malignancy in patients with Wilms tumor.

Eight hub genes as potential biomarkers for breast cancer diagnosis and prognosis: A TCGA-based study

BACKGROUND

Breast cancer (BC) is the most common malignant tumor in women.

AIM

To investigate BC-associated hub genes to obtain a better understanding of BC tumorigenesis.

METHODS

In total, 1203 BC samples were downloaded from The Cancer Genome Atlas database, which included 113 normal samples and 1090 tumor samples. The limma package of R software was used to analyze the differentially expressed genes (DEGs) in tumor tissues compared with normal tissues. The cluster Profiler package was used to perform Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of upregulated and downregulated genes. Univariate Cox regression was conducted to explore the DEGs with statistical significance. Protein-protein interaction (PPI) network analysis was employed to investigate the hub genes using the CytoHubba plug-in of Cytoscape software. Survival analyses of the hub genes were carried out using the Kaplan-Meier method. The expression level of these hub genes was validated in the Gene Expression Profiling Interactive Analysis database and Human Protein Atlas database.

RESULTS

A total of 1317 DEGs (fold change > 2; P < 0.01) were confirmed through bioinformatics analysis, which included 744 upregulated and 573 downregulated genes in BC samples. KEGG enrichment analysis indicated that the upregulated genes were mainly enriched in the cytokine-cytokine receptor interaction, cell cycle, and the p53 signaling pathway (P < 0.01); and the downregulated genes were mainly enriched in the cytokine-cytokine receptor interaction, peroxisome proliferator-activated receptor signaling pathway, and AMP-activated protein kinase signaling pathway (P < 0.01).

CONCLUSION

In view of the results of PPI analysis, which were verified by survival and expression analyses, we conclude that MAD2L1, PLK1, SAA1, CCNB1, SHCBP1, KIF4A, ANLN, and ERCC6L may act as biomarkers for the diagnosis and prognosis in BC patients.

Comprehensive Multiomics Analysis Reveals Potential Diagnostic and Prognostic Biomarkers in Adrenal Cortical Carcinoma

Adrenal cortical carcinoma (ACC) is a severe malignant tumor with low early diagnosis rates and high mortality. In this study, we used a variety of bioinformatic analyses to find potential prognostic markers and therapeutic targets for ACC. Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data sets were used to perform differential expressed analysis. WebGestalt was used to perform enrichment analysis, while String was used for protein-protein analysis. Our study first detected 28 up-regulation and 462 down-regulation differential expressed genes through the GEO and TCGA databases. Then, GO functional analysis, four pathway analyses (KEGG, REACTOME, PANTHER, and BIOCYC), and protein-protein interaction network were performed to identify these genes by WebGestalt tool and KOBAS website, as well as String database, respectively, and finalize 17 hub genes. After a series of analyses from GEPIA, including gene mutations, differential expression, and prognosis, we excluded one candidate unrelated to the prognosis of ACC and put the remaining genes into pathway analysis again. We screened out CCNB1 and NDC80 genes by three algorithms of Degree, MCC, and MNC. We subsequently performed genomic analysis using the TCGA and cBioPortal databases to better understand these two hub genes. Our data also showed that the CCNB1 and NDC80 genes might become ACC biomarkers for future clinical use.

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.

ISL1 promotes enzalutamide resistance in castration-resistant prostate cancer (CRPC) through epithelial to mesenchymal transition (EMT)

Abnormal expression of insulin gene enhancer-binding protein 1 (ISL1) has been demonstrated to be closely associated with cancer development and progression in several cancers. However, little is known about ISL1 expression in metastatic castration-resistant prostate cancer (CRPC). ISL1 has also been recognized as a positive modulator of epithelial-mesenchymal transition (EMT). In this study, we focused on ISL1 which showed maximum upregulation at the mRNA level in the enzalutamide-resistant cell line. Accordingly, we found that ISL1 was overexpressed in enzalutamide-resistant C4-2B cells and its expression was significantly related to EMT. Our findings reveal the important role of ISL1 in androgen receptor (AR)-dependent prostate cancer cell growth; ISL1 knockdown reduced the AR activity and cell growth. ISL1 knockdown using small-interfering RNA inhibited AR, PSA, and EMT-related protein expression in C4-2B ENZR cells. In addition, knock-down ISL1 reduced the levels of AKT and p65 phosphorylation in C4-2B ENZR cells and these suggest that knock-down ISL1 suppresses EMT in part by targeting the AKT/NF-κB pathway. Further, ISL1 downregulation could effectively inhibit tumor growth in a human CRPC xenograft model. Together, the present study shows that downregulation of ISL1 expression is necessary for overcoming enzalutamide resistance and improving the survival of CRPC patients.

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.

Bioinformatics Analysis of the Signaling Pathways and Genes of Gossypol Induce Death of Nasopharyngeal Carcinoma Cells

Gossypol has been reported to exhibit antitumor effects against several human cancers. However, the anticancer effects of gossypol on nasopharyngeal carcinoma (NPC) have not been investigated. Against this backdrop, the present study was designed to evaluate the anticancer effects of gossypol against NPC cells and to identify the signaling pathways involved through bioinformatic analysis. Gossypol-inhibited death of NPC cells is concentration-dependent. To explore the underlying mechanism for gossypol's antitumor effect, microarray of gossypol-treated and -untreated NPC cells was performed. A total of 836 differentially expressing genes (DEGs) were identified in gossypol-treated NPC cells, of which 461 genes were upregulated and 375 genes were downregulated. The cellular components, molecular functions, biological processes, and signal pathways, in which the DEGs were involved, were identified by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The Gene Set Enrichment Analysis (GSEA) predicted upstream transcription factors (TF) ETS2 and E2F1 that regulate DEGs. Weighted Gene Co-expression Network Analysis (WGCNA) was performed to identify a class of modules and genes related to DNA repair and cell cycle. TNFRSF10B, a receptor for death in NPC cells, was knocked down. The results suggested that the ability of NPC cells to resist gossypol killing was enhanced. In addition, to further investigate the possible molecular mechanisms, we constructed a transcriptional regulatory network of TNFRSF10B containing 109 miRNAs and 47 TFs. Taken together, our results demonstrated that gossypol triggered antitumor effects against NPC cells, indicating its applicability for the management of NPC.

Identification of novel hub genes associated with gastric cancer using integrated bioinformatics analysis

Background

Gastric cancer (GC) is one of the most common solid malignant tumors worldwide with a high-recurrence-rate. Identifying the molecular signatures and specific biomarkers of GC might provide novel clues for GC prognosis and targeted therapy.

Methods

Gene expression profiles were obtained from the ArrayExpress and Gene Expression Omnibus database. Differentially expressed genes (DEGs) were picked out by R software. The hub genes were screened by cytohubba plugin. Their prognostic values were assessed by Kaplan–Meier survival analyses and the gene expression profiling interactive analysis (GEPIA). Finally, qRT-PCR in GC tissue samples was established to validate these DEGs.

Results

Total of 295 DEGs were identified between GC and their corresponding normal adjacent tissue samples in E-MTAB-1440, GSE79973, GSE19826, GSE13911, GSE27342, GSE33335 and GSE56807 datasets, including 117 up-regulated and 178 down-regulated genes. Among them, 7 vital upregulated genes (HMMR, SPP1, FN1, CCNB1, CXCL8, MAD2L1 and CCNA2) were selected. Most of them had a significantly worse prognosis except SPP1. Using qRT-PCR, we validated that their transcriptions in our GC tumor tissue were upregulated except SPP1 and FN1, which correlated with tumor relapse and predicts poorer prognosis in GC patients.

Conclusions

We have identified 5 upregulated DEGs (HMMR, CCNB1, CXCL8, MAD2L1, and CCNA2) in GC patients with poor prognosis using integrated bioinformatical methods, which could be potential biomarkers and therapeutic targets for GC treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08358-7.

Single-cell RNA sequencing in human lung cancer: Applications, challenges, and pathway towards personalized therapy

Lung cancer is one of the most prevalent human cancers, and single-cell RNA sequencing (scRNA-seq) has been widely used to study human lung cancer at the cellular, genetic, and molecular level. Even though there are published reviews, which summarized the applications of scRNA-seq in human cancers like breast cancer, there is lack of a comprehensive review, which could effectively highlight the broad use of scRNA-seq in studying lung cancer. This review, therefore, was aimed to summarize the various applications of scRNA-seq in human lung cancer research based on the findings from different published in vitro, in vivo, and clinical studies. The review would first briefly outline the concept and principle of scRNA-seq, followed by the discussion on the applications of scRNA-seq in studying human lung cancer. Finally, the challenges faced when using scRNA-seq to study human lung cancer would be discussed, and the potential applications and challenges of scRNA-seq to facilitate the development of personalized cancer therapy in the future would be explored.

Phosphorylation of islet-1 serine 269 by CDK1 increases its transcriptional activity and promotes cell proliferation in gastric cancer

Background

Despite recent advances in diagnostic and therapeutic approaches for gastric cancer (GC), the survival of patients with advanced GC remains very low. Islet-1 (ISL1) is a LIM-homeodomain transcription factor, which is upregulated and promotes cell proliferation in GC. The exact mechanism by which ISL1 influences GC development is unclear.

Methods

Co-immunoprecipitation (co-IP) and glutathione S-transferase (GST)-pulldown assays were employed to evaluate the interaction of ISL1 with CDK1. Western blot and immunohistochemistry analyses were performed to evaluate the ability of CDK1 to phosphorylate ISL1 at Ser 269 in GC cell and tissue specimens. Chromatin immunoprecipitation (ChIP), ChIP re-IP, luciferase reporter, and CCK-8 assays were combined with flow cytometry cell cycle analysis to detect the transactivation potency of ISL1-S269-p and its ability to promote cell proliferation. The self-stability and interaction with CDK1 of ISL1-S269-p were also determined.

Results

ISL1 is phosphorylated by CDK1 at serine 269 (S269) in vivo. Phosphorylation of ISL1 by CDK1 on serine 269 strengthened its binding on the cyclin B1 and cyclin B2 promoters and increased its transcriptional activity in GC. Furthermore, CDK1-dependent phosphorylation of ISL1 correlated positively with ISL1 protein self-stability in NIH3T3 cells.

Conclusions

ISL1-S269-p increased ISL1 transcriptional activity and self-stability while binding to the cyclinB1 and cyclinB2 promoters promotes cell proliferation. ISL1-S269-p is therefore crucial for tumorigenesis and potentially a direct therapeutic target for GC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-021-00302-6.

Analysis of Gastric Cancer Transcriptome Allows the Identification of Histotype Specific Molecular Signatures With Prognostic Potential

Gastric cancer is the fifth most common malignancy but the third leading cause of cancer-associated mortality worldwide. Therapy for gastric cancer remain largely suboptimal making the identification of novel therapeutic targets an urgent medical need. In the present study we have carried out a high-throughput sequencing of transcriptome expression in patients with gastric cancers. Twenty-four patients, among a series of 53, who underwent an attempt of curative surgery for gastric cancers in a single center, were enrolled. Patients were sub-grouped according to their histopathology into diffuse and intestinal types, and the transcriptome of the two subgroups assessed by RNAseq analysis and compared to the normal gastric mucosa. The results of this investigation demonstrated that the two histopathology phenotypes express two different patterns of gene expression. A total of 2,064 transcripts were differentially expressed between neoplastic and non-neoplastic tissues: 772 were specific for the intestinal type and 407 for the diffuse type. Only 885 transcripts were simultaneously differentially expressed by both tumors. The per pathway analysis demonstrated an enrichment of extracellular matrix and immune dysfunction in the intestinal type including CXCR2, CXCR1, FPR2, CARD14, EFNA2, AQ9, TRIP13, KLK11 and GHRL. At the univariate analysis reduced levels AQP9 was found to be a negative predictor of 4 years survival. In the diffuse type low levels CXCR2 and high levels of CARD14 mRNA were negative predictors of 4 years survival. In summary, we have identified a group of genes differentially regulated in the intestinal and diffuse histotypes of gastric cancers with AQP9, CARD14 and CXCR2 impacting on patients' prognosis, although CXCR2 is the only factor independently impacting overall survival.

Valtrate as a novel therapeutic agent exhibits potent anti-pancreatic cancer activity by inhibiting Stat3 signaling

BACKGROUND

Valtrate is a novel epoxy iridoid ester isolated from Chinese herbal medicine Valeriana jatamansi Jones with anti-proliferative activity against various human cancer cell lines. However, its efficacy and molecular mechanisms against pancreatic cancer (PC) cells are largely unclear.

PURPOSE

To investigate the anti-cancer effects of valtrate on PC cell lines and its underlying mechanisms.

METHODS

MTT assay was first performed to detect the effect of valtrate on cell viability in human PC cell lines and normal pancreatic epithelial cells HPDE. Cell apoptosis and cycle phase assay were detected by flow cytometry. The relative mRNA expressions of Bax, Bcl-2, c-Myc, and CyclinB1 were tested by quantitative PCR (qPCR) assay. The expression of relative proteins was detected by Western blotting (WB). A PANC-1^luc cells xenograft mouse model in nu/nu female mice was used to elucidate the effect of valtrate on tumor growth in vivo.

RESULTS

Valtrate significantly inhibited the growth of PC cells without affecting the growth of normal pancreatic epithelial cells HPDE, induced significant apoptosis and cell cycle arrest in G2/M phase. Moreover, valtrate inhibited the tumor growth of PC cell PANC-1 in xenograft mice by 61%. Further mechanism study demonstrated that valtrate could increase the expression level of Bax, suppress Bcl-2 as well as c-Myc and Cyclin B1, inhibit the transcriptional activity of Stat3, while valtrate decreased the expression level of Stat3 and phosphated-Stat3 (Tyr705) and induced the high molecular aggregation of Stat3. Molecular docking analysis predicted that valtrate might interact with Cys712 of Stat3 protein. Valtrate could also induce a transient depleted intracellular glutathione (GSH) level and increased reactive oxygen species (ROS). NAC (N-acetylcysteine), a reducer reversed valtrate-induced the depletion of Stat3, p-Stat3, c-Myc, and Cyclin B1.

CONCLUSION

Valtrate exerts anti-cancer activity against PC cells by directly targeting Stat3 through a covalent linkage to inhibit Stat3 activity, which causes apoptosis and cell cycle arrest.

Expression of ISL1 and its partners in prostate cancer progression and neuroendocrine differentiation

INTRODUCTION AND OBJECTIVES

ISL1 serves as a biomarker of metastasis and neuroendocrine neoplasia in multiple tumors. However, the expression and relation of ISL1 to other biomarkers in prostate cancer have not been fully elucidated. Here, we characterize the expression of ISL1 and its partners in PCa and document its association to disease progression and post castration resistance neuroendocrine differentiation.

METHODS

The expression of ISL1 was interrogated in > 6000 primary samples from the Decipher GRID registry and 250 mCRPC samples to assess its prognostic value and relation to neuroendocrine differentiation.

RESULTS

ISL1 was highly correlated to MEIS genes and other genes related to cell motility. ISL1 down-regulation in PCa was associated with cancer progression, aggressive primary tumors, and metastatic outcome. We found that ISL1 is highly correlated to MEIS genes across multiple primary PCa and mCRPC cohorts. The expression of ISL1 and MEIS genes were significantly and inversely related to metastasis-free survival and lethal disease, and were downregulated in CRPC and hormone naïve metastatic tumors but showed upregulation in neuroendocrine tumors. Co-immunoprecipitation showed MEIS2 and ISL1 interacting with each supporting their role in modulating transcriptional regulation and nominating this complex for potential targeted therapy.

CONCLUSIONS

ISL1 complex with MEIS2 serves a critical role in prostate tumor progression and its upregulation in mCRPC/NE provides a rationale for assessing the role of ISL1 and its associated protein in treatment resistance.

Insulin gene enhancer protein 1 mediates glycolysis and tumorigenesis of gastric cancer through regulating glucose transporter 4

Background

Insulin gene enhancer protein 1, (ISL1), a LIM‐homeodomain transcription factor, is involved in multiple tumors and is associated with insulin secretion and metabolic phenotypes. However, the role of ISL1 in stimulating glycolysis to promote tumorigenesis in gastric cancer (GC) is unclear. In this study, we aimed to characterize the expression pattern of ISL1 in GC patients and explore its molecular biological mechanism in glycolysis and tumorigenesis.

Methods

We analyzed the expression and clinical significance of ISL1 in GC using immunohistochemistry and real‐time polymerase chain reaction (PCR). Flow cytometry and IncuCyte assays were used to measure cell proliferation after ISL1 knockdown. RNA‐sequencing was performed to identify differentially expressed genes, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA) to reveal key signaling pathways likely regulated by ISL1 in GC. Alteration of the glycolytic ability of GC cells with ISL1 knockdown was validated by measuring the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) and by detecting glucose consumption and lactate production. The expression of glucose transporter 4 (GLUT4) and ISL1 was assessed by Western blotting, immunohistochemistry, and immunofluorescent microscopy. The luciferase reporter activity and chromatin immunoprecipitation assays were performed to determine the transcriptional regulation of ISL1 on GLUT4.

Results

High levels of ISL1 and GLUT4 expression was associated with short survival of GC patients. ISL1 knockdown inhibited cell proliferation both in vitro and in vivo. KEGG analysis and GSEA for RNA‐sequencing data indicated impairment of the glycolysis pathway in GC cells with ISL1 knockdown, which was validated by reduced glucose uptake and lactate production, decreased ECAR, and increased OCR. Mechanistic investigation indicated that ISL1 transcriptionally regulated GLUT4 through binding to its promoter.

Conclusion

ISL1 facilitates glycolysis and tumorigenesis in GC via the transcriptional regulation of GLUT4.

Identification of biomarkers associated with diagnosis and prognosis of gastroesophageal junction adenocarcinoma-a study based on integrated bioinformatics analysis in GEO and TCGA database

Gastroesophageal junction adenocarcinoma (GEJAC) is a malignant tumor with high mortality. Its incidence has increased sharply all over the world in recent years. The study aims to search for potential biomarkers for the diagnosis and prognosis of GEJAC based on the Gene Expression Omnibus database (GEO) database and The Cancer Genome Atlas (TCGA) database.Microarray dataset (GSE96668 and GSE74553) of GEJAC was downloaded from the GEO. After screening overlapping differentially expressed genes (DEGs) by GEO2R and Wayne map, functional enrichment analysis of the DEGs was performed by the DAVID database. Then, a protein-protein interaction (PPI) network was constructed, and the hub gene was identified by using STRING and Cytoscape, as well as the diagnostic value of hub genes was evaluated by the receiver operating characteristic (ROC) curves. Finally, the gene transcriptome profiles of gastric cancer named TCGA-STAD were downloaded from TCGA database to screen the potential prognostic genes and construct the prognostic risk model using Cox proportional hazards regression. Meanwhile, the Kaplan-Meier curve and time-dependent ROC curve were adopted to test the prognostic value of the prognostic gene signature.In this study, we identified 10 hub genes that might have high diagnostic value for GEJAC, and inferred that they might be involved in the occurrence and development of GEJAC. Moreover, we conducted a survival prediction model consisting of 6 genes and proved that they have value to some extent in predicting prognosis for GEJAC patients.

Stemness Related Genes Revealed by Network Analysis Associated With Tumor Immune Microenvironment and the Clinical Outcome in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the leading fatal malignancy with high morbidity and mortality worldwide. However, due to its complicated mechanism and lack of effective clinical therapeutics, early diagnosis and prognosis are still unsatisfactory. Most of the previous studies focused on cancer stem cells (CSCs), the relationship between cancer stemness (stem-like characteristics) and anti-tumor immunity has not been clearly revealed. Therefore, this study aimed to comprehensively analyze the role of cancer stemness and tumor microenvironment (TME) in LUAD using weighted gene co-expression network analysis (WGCNA). We constructed a gene co-expression network, identified key modules, and hub genes, and further explored the relationship between hub gene expression and cancer immunological characteristics through a variety of algorithms, including Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and Gene Set Enrichment Analysis (GSEA). The hub genes were renamed stemness related genes (SRGs), whose functions were examined at the transcription and protein levels through survival analysis with additional samples, Oncomine database, immunohistochemistry, single cell RNA sequencing (scRNA-seq) and single-sample Gene Set Enrichment Analysis (ssGSEA). Subsequently, Tumor Immune Dysfunction and Exclusion (TIDE) and Connectivity Map (CMap) were implemented for treatment and prognosis analyses. As a result, 15 co-expressed SRGs (CCNA2, CCNB1, CDC20, CDCA5, CDCA8, FEN1, KIF2C, KPNA2, MCM6, NUSAP1, RACGAP1, RRM2, SPAG5, TOP2A, and TPX2) were identified. The overexpression of which was discovered to be associated with reduced immune infiltration in LUAD. It was discovered that there was a general negative correlation between cancer stemness and immunity. The expression of SRGs could probably affect our tumor occurrence, progression, the efficacy of chemotherapy and immunotherapy, and clinical outcomes. In conclusion, the 15 SRGs reported in our study may be used as potential candidate biomarkers for prognostic indicators and therapeutic targets after further validation.

Integrated Analysis of Hub Genes and Pathways In Esophageal Carcinoma Based on NCBI's Gene Expression Omnibus (GEO) Database: A Bioinformatics Analysis

BACKGROUND Esophageal carcinoma (ESCA) is a health challenge with poor prognosis and limited treatment options. Our aim is to screen for hub genes and pathways associated with ESCA pathology as diagnostic or therapeutic targets. MATERIAL AND METHODS We downloaded 2 ESCA-related datasets from the Gene Expression Omnibus (GEO) database. Subsequently, differentially expressed genes (DEGs) of ESCA were determined by statistical analysis. Both Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using online analytic tools. Network analysis was employed to construct a protein-protein interaction (PPI) network and to filter hub genes. We evaluated the expression level and impact of hub genes on survival of ESCA patients using the OncoLoc webserver. RESULTS A total of 210 DEGs were identified. The GO analysis showed that the DEGs were enriched in cell division. The KEGG pathway analysis showed DEGs that were enriched in cell cycle regulation, known cancer pathways, the PI3K-Akt signaling pathway, and the cGMP-PKG signaling pathway. The top 10 hub genes were markedly upregulated in ESCA tissue compared with normal esophageal tissue. Moreover, the expression level of the hub genes was different at different pathological stages of ESCA. Further prognostic analysis identified that the top 10 hub genes were related to late survival of ESCA patients, while exhibiting few associations with early survival time. CONCLUSIONS The signaling pathways involving the DEGs probably represent the pathological mechanism underlying ESCA. The hub genes were associated with survival of ESCA patients, and as such have the potential to serve as diagnostic indicators and therapeutic targets.

High-throughput sequencing-based analysis of gene expression of hepatitis B virus infection-associated human hepatocellular carcinoma

Hepatitis B virus (HBV) infection is a critical factor for the initiation and progression of hepatocellular carcinoma (HCC). Gene expression profiles for HBV-associated HCC may provide valuable insight for the diagnosis and treatment of this type of HCC. The present study aimed to screen the differential genes in human HCC tissues based on high-throughput sequencing and to predict the potential therapeutic targets. Total mRNA was extracted from human HCC tissues and paracancerous tissues and sequenced using the Hiseq4000 sequencing platform. Differential gene expressions were screened and further analyzed using quantitative PCR and immunohistochemistry. A total of 2,386 differentially expressed genes were screened. Of these, 1119 were upregulated and 1,267 were downregulated in paracancerous tissues compared with tumor tissues. Gene Ontology term analysis demonstrated that differentially expressed genes were involved in carboxylic acid catabolism, monocarboxylic acid metabolic processes and α-amino acid metabolic processes. Molecular functional analysis revealed that the differentially expressed genes functioned in oxidoreductase activity, for example acting on CH-OH group of donors and permitting identical protein binding, anion binding, coenzyme binding and monocarxylic acid transporter activity. The Kyoto Encyclopedia of Genes and Genomes analysis reported that the differentially expressed genes were primarily concentrated in 20 signaling pathways, such as valine, leucine and leucine degradation, retinol metabolism and the cell cycle. Differential expression of proteins regulating the cell cycle, including stratifin, cyclin B1 and cyclin-dependent kinase 1, were significantly higher in tumor tissue compared with those in paracancerous tissue at both the mRNA and protein levels. These results were consistent with those obtained from high-throughput sequencing, indicating the reliability of the high-throughput sequencing. Together, these results identified differentially expressed genes and predicted the subsequent signaling pathways, which may be involved in the occurrence and development of HCC. Therefore, the present study may provide novel implications in the therapeutic and diagnosis of HCC.

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.

Bioinformatics analysis and verification of gene targets for benign tracheal stenosis

Background

Tracheal injury could cause intratracheal scar hyperplasia which in turn causes benign tracheal stenosis (TS). With the increasing use of mechanical ventilation and ventilator, the incidence of TS is increasing. However, the molecular mechanisms of TS have not been elucidated. It is significant to further explore the molecular mechanisms of TS.

Methods

The repeatability of public data was verified. Differently expressed genes (DEGs) and most significant genes were identified between TS and normal samples. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed. The comparative toxicogenomics database were analyzed. TS patients were recruited and RT‐qPCR were performed to verify the most significant genes.

Results

There exist strong correlations among samples of TS and normal group. There was a total of 194 DEGs, including 61 downregulated DEGs and 133 upregulated DEGs. GO were significantly enriched in mitotic nuclear division, cell cycle, and cell division. Analysis of KEGG indicated that the top pathways were cell cycle, and p53 pathway. MKI67(OMIM:176741), CCNB1(OMIM:123836), and CCNB2(OMIM:602755) were identified as the most significant genes of TS, and validated by the clinical samples.

Conclusion

Bioinformatics methods might be useful method to explore the mechanisms of TS. In addition, MKI67, CCNB1, and CCNB2 might be the most significant genes of TS.

Upregulated expression of SAC3D1 is associated with progression in gastric cancer

SAC3 domain containing 1 (SAC3D1) has been reported to be involved in numerous types of cancer. However, the role of SAC3D1 in GC has not yet been elucidated. In the present study, the mRNA expression level of SAC3D1 between GC and normal tissues were assessed with a continuous variable meta-analysis based on multiple datasets from public databases. The protein expression level of SAC3D1 in GC and normal tissues was assessed by an in-house immunohistochem-istry (IHC). The association between SAC3D1 expression and some clinical parameters was assessed based on the TCGA and IHC data. Survival analysis was performed to assess the association between SAC3D1 expression and the survival of GC patients. The co-expressed genes of SAC3D1 were determined by integrating three online tools, and the enrichment analyses were performed to determine SAC3D1-related pathways and hub co-expressed genes. SAC3D1 was significantly upregulated in GC tumor tissues in comparison to normal tissues with the SMD being 0.45 (0.12, 0.79). The IHC results also indicated that SAC3D1 protein expression in GC tissues was markedly higher than in normal tissues. The SMD following the addition of the IHC data was 0.59 (0.11, 1.07). The protein levels of SAC3D1 were positively associated with the histological grade, T stage and N stage of GC (P<0.001). The TCGA data also revealed that the SAC3D1 mRNA level was significantly associated with the N stage (P<0.001). Moreover, prognosis analysis indicated that SAC3D1 was closely associated with the prognosis of patients with GC. Moreover, 410 co-expressed genes of SAC3D1 were determined, and these genes were mainly enriched in the cell cycle. In total, 4 genes (CDK1, CCNB1, CCNB2 and CDC20) were considered key co-expressed genes. On the whole, these findings demonstrate that SAC3D1 is highly expressed in GC and may be associated with the progression of GC.

Identification of biomarkers for the transition from low-grade glioma to secondary glioblastoma by an integrated bioinformatic analysis

Secondary glioblastoma (sGBM) is a type of glioblastoma multiforme that evolves from low-grade glioma (LGG). However, the mechanism of this transition still remains poorly understood. In this study, we used weighted gene co-expression network analysis (WGCNA) on the gene expression profiles of glioma samples from the Chinese Glioma Genome Atlas (CGGA) database to identify key genetic module related to distinguish histological characteristics. Here, the brown module was highly correlated with histological characteristics and was selected as the hub module. By applying functional annotation analysis, we found that biological processes related to the cell-cycle and DNA-replication were enriched in the genes of the brown module. After constructing a protein-protein interaction (PPI) network, validation of differential gene expression, and survival analyses, we ultimately identified five hub genes: CCNB2 (Cyclin B2), KIF2C (Kinesin Family Member 2C), CDC20 (Cell Division Cycle 20), TPX2 (TPX2 Microtubule Nucleation Factor), and PLK1 (Polo Like Kinase 1). In addition, a computational risk model was developed for predicting the clinical outcomes of sGBM patients by combining gene expression levels. This gene signature was demonstrated to be an independent predictor of survival by univariate and multivariable Cox regression analysis. Finally, we used the Genomics of Drug Sensitivity in Cancer (GDSC) database to predict the responses of sGBM patients to routine chemotherapeutic drugs. Patients from the high-risk group were more sensitive to common chemotherapies during clinical treatment. Our findings based on comprehensive analyses might advance the understanding of sGBM transition and aid the development of novel biomarkers for diagnosing and predicting the survival of sGBM patients.

Selective repression of the Drosophila cyclin B promoter by retinoblastoma and E2F proteins

The Cyclin B1 gene encodes a G2/M cyclin that is deregulated in various human cancers, however, the transcriptional regulation of this gene is incompletely understood. The E2F and retinoblastoma family of proteins are involved in this gene's regulation, but there is disagreement on which of the E2F and retinoblastoma proteins interact with the promoter to regulate this gene. Here, we dissect the promoter region of the Drosophila CycB gene, and study the role of Rbf and E2F factors in its regulation. This gene exhibits remarkable features that distinguish it from G1/S regulated promoters, such as PCNA. The promoter is comprised of modular elements with dedicated repressor and activator functions, including a segment spanning the first intron that interferes with a 5' activator element. A highly active minimal promoter (-464, +100) is repressed by the Rbf1 retinoblastoma protein, but much more potently repressed by the Rbf2 protein, which has been linked in other studies to control of cell growth genes. Unlike many other cell-cycle genes, which are activated by E2F1 and repressed by E2F2, CycB is potently activated by E2F2, and repressed by E2F1. Although the bulk of Rbf binding is associated with a region 5' of the core promoter, E2F and retinoblastoma proteins functionally interact with the basal promoter region, in part through a conserved E2F site at -80 bp. The specific regulatory requirements of this late cell cycle promoter appear to be linked to the unique activities of E2F and retinoblastoma family members acting on a complex cis-regulatory circuit.

Identification of hub genes and pathways in adrenocortical carcinoma by integrated bioinformatic analysis

Adrenocortical carcinoma (ACC), a rare malignant neoplasm originating from adrenal cortical cells, has high malignancy and few treatments. Therefore, it is necessary to explore the molecular mechanism of tumorigenesis, screen and verify potential biomarkers, which will provide new clues for the treatment and diagnosis of ACC. In this paper, three gene expression profiles (GSE10927, GSE12368 and GSE90713) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained using the Limma package. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched by DAVID. Protein‐protein interaction (PPI) network was evaluated by STRING database, and PPI network was constructed by Cytoscape. Finally, GEPIA was used to validate hub genes’ expression. Compared with normal adrenal tissues, 74 up‐regulated DEGs and 126 down‐regulated DEGs were found in ACC samples; GO analysis showed that up‐regulated DEGs were enriched in organelle fission, nuclear division, spindle, et al, while down‐regulated DEGs were enriched in angiogenesis, proteinaceous extracellular matrix and growth factor activity; KEGG pathway analysis showed that up‐regulated DEGs were significantly enriched in cell cycle, cellular senescence and progesterone‐mediated oocyte maturation; Nine hub genes (CCNB1, CDK1, TOP2A, CCNA2, CDKN3, MAD2L1, RACGAP1, BUB1 and CCNB2) were identified by PPI network; ACC patients with high expression of 9 hub genes were all associated with worse overall survival (OS). These hub genes and pathways might be involved in the tumorigenesis, which will offer the opportunities to develop the new therapeutic targets of ACC.

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.

Potential Prognostic Predictors and Molecular Targets for Skin Melanoma Screened by Weighted Gene Co-expression Network Analysis

AIMS AND OBJECTIVES

Among skin cancers, malignant skin melanoma is the leading cause of death. Identification of gene markers of malignant skin melanoma associated with survival may provide new clues for prognosis prediction and treatment. This research aimed to screen out potential prognostic predictors and molecular targets for malignant skin melanoma.

INTRODUCTION

Information regarding gene expression in skin melanoma and patients' clinical traits was obtained from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was applied to build co-expression modules and investigate the association between the modules and clinical traits. Moreover, functional enrichment analysis was performed for clinically significant co-expression modules. Hub genes of these modules were validated via Gene Expression Profiling Interactive Analysis (GEPIA) and the Human Protein Atlas (http:// www.proteinatlas.org).

METHODS

First, using WGCNA, 9 co-expression modules were constructed by the top 25% differentially expressed genes (4406 genes) from 77 human melanoma samples. Two co-expression modules (magenta and blue modules) were significantly correlated with survival months (r = -0.27, p = 0.02; r = 0.27, p = 0.02, respectively). The results of functional enrichment analysis demonstrated that the magenta module was mainly enriched in the cell cycle process and the blue module was mainly enriched in the immune response process. Additionally, the GEPIA and Human Protein Atlas results suggested that the hub genes CCNB2, ARHGAP30, and SEMA4D were associated with relapse-free survival and overall survival (all p-values < 0.05) and were differentially expressed in melanoma tumors and normal skin.

RESULTS AND CONCLUSION

The results provided the framework of co-expression gene modules of skin melanoma and screened out CCNB2, ARHGAP30, and SEMA4D associated with survival as potential prognostic predictors and molecular targets of treatment.

Five Novel Genes Related to the Pathogenesis and Progression of Pancreatic Neuroendocrine Tumors by Bioinformatics Analysis With RT-qPCR Verification

Objective

To explore novel related genes and potential biomarkers of pancreatic neuroendocrine tumors (PanNETs).

Materials and Methods

Two data sets from ICGC and two from the NCBI GEO database were used to identify the differentially expressed genes (DEGs) in PanNETs. The common DEGs among the four sources were analyzed; furthermore, the relationship of these gene expression patterns with different PanNET grades, their mutation status and corresponding impact on prognosis, the interaction network, and the relationship with three known PanNET genes (ATRX, DAXX, and MEN1) were analyzed by two other GEO data and cBioPortal database. Finally, the expressions of novel DEGs were validated in Chinese PanNET tissues by RT-qPCR.

Results

Five new DEGs (ABCC8, PCSK2, IL13RA2, KLKB1, and PART1) and one confirmed DEG-ISL1 were identified. The mutation counts of DEGs increased with the tumor grade increasing from G1 to G3, and PanNET patients present vascular invasion or are deceased. These DEG expression patterns in PanNETs are quite different from that of pancreatic ductal adenocarcinoma and are related to A–D–M (ATRX–DAXX–MEN1) mutation. ABCC8 and KLKB1 are co-occurrence with the A–D–M axis in PanNETs. Importantly, patients with DEG mutations have a lower survival rate. RT-qPCR verification results of KLKB1 (P < 0.01), IL13RA2 (P < 0.01), ABCC8 (P < 0.01), and PART1 (P < 0.0001) expressions in Chinese PanNET tissues are consistent with our database analysis, which were significantly up-regulated. However, the expression of PCSK2 (P < 0.01) was contrary to our bioinformatics analysis, which was significantly down-regulated, suggesting that the expression trend of PCSK2 may be different among different races. These results indicated that these five genes may play an important role in the occurrence and progression of PanNETs.

Conclusion

Five novel common DEGs identified are related to the development and prognosis of PanNETs and may serve as specific biomarkers and therapeutic targets.

Identification of Potential Crucial Genes and Key Pathways in Breast Cancer Using Bioinformatic Analysis

Background: The molecular mechanism of tumorigenesis remains to be fully understood in breast cancer. It is urgently required to identify genes that are associated with breast cancer development and prognosis and to elucidate the underlying molecular mechanisms. In the present study, we aimed to identify potential pathogenic and prognostic differentially expressed genes (DEGs) in breast adenocarcinoma through bioinformatic analysis of public datasets.

Methods: Four datasets (GSE21422, GSE29431, GSE42568, and GSE61304) from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) dataset were used for the bioinformatic analysis. DEGs were identified using LIMMA Package of R. The GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses were conducted through FunRich. The protein-protein interaction (PPI) network of the DEGs was established through STRING (Search Tool for the Retrieval of Interacting Genes database) website, visualized by Cytoscape and further analyzed by Molecular Complex Detection (MCODE). UALCAN and Kaplan–Meier (KM) plotter were employed to analyze the expression levels and prognostic values of hub genes. The expression levels of the hub genes were also validated in clinical samples from breast cancer patients. In addition, the gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD).

Results: In total, 203 up-regulated and 118 down-regulated DEGs were identified. Mitotic cell cycle and epithelial-to-mesenchymal transition pathway were the major enriched pathways for the up-regulated and down-regulated genes, respectively. The PPI network was constructed with 314 nodes and 1,810 interactions, and two significant modules are selected. The most significant enriched pathway in module 1 was the mitotic cell cycle. Moreover, six hub genes were selected and validated in clinical sample for further analysis owing to the high degree of connectivity, including CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK, and they were all correlated to worse overall survival (OS) in breast cancer.

Conclusion: These results revealed that mitotic cell cycle and epithelial-to-mesenchymal transition pathway could be potential pathways accounting for the progression in breast cancer, and CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK may be potential crucial genes. Further, it could be utilized as new biomarkers for prognosis and potential new targets for drug synthesis of breast cancer.

Joint bioinformatics analysis of underlying potential functions of hsa-let-7b-5p and core genes in human glioma

BACKGROUND

Glioma accounts for a large proportion of cancer, and an effective treatment for this disease is still lacking because of the absence of specific driver molecules. Current challenges in the treatment of glioma are the accurate and timely diagnosis of brain glioma and targeted treatment plans. To investigate the diagnostic biomarkers and prospective role of miRNAs in the tumorigenesis and progression of glioma, we analyzed the expression of miRNAs and key genes in glioma based on The Cancer Genome Atlas database.

METHODS

Of the 701 cases that were downloaded, five were normal and 696 were glioma. Then, 1626 differentially expressed genes were identified, and 173 aberrantly expressed miRNAs were calculated by edgeR. GO and KEGG pathway enrichment analyses were performed using Cytoscape software. A coexpression network was built by weighted correlation network analysis (WGCNA). A cell scratch test and transwell, cell apoptosis and cell cycle assays were performed to validate the function of hsa-let-7b-5p.

RESULTS

Based on crosstalk genes in the KEGG, PPI network, and WGCNA analyses, PLK1, CCNA2, cyclin B2 (CCNB2), and AURKA were screened as candidate diagnostic marker genes. The survival analysis revealed that high mRNA expression of PLK1, CCNA2, and AURKA was significantly associated with poor overall survival. Furthermore, hsa-let-7b-5p was identified as a core miRNA in the regulation of candidate genes involved in glioma development. We confirmed that hsa-let-7b-5p could inhibit the migration, invasion, and cell cycle of glioma cells.

CONCLUSIONS

This study provides four potential biomarkers for the diagnosis of glioma, offers a potential explanation of its pathogenesis, and proposes hsa-let-7b-5p as a therapeutic target.

Collaborative ISL1/GATA3 interaction in controlling neuroblastoma oncogenic pathways overlapping with but distinct from MYCN

Background: Transcription factor ISL1 plays a critical role in sympathetic neurogenesis. Expression of ISL1 has been associated with neuroblastoma, a pediatric tumor derived from sympatho-adrenal progenitors, however the role of ISL1 in neuroblastoma remains unexplored. Method: Here, we knocked down ISL1 (KD) in SH-SY5Y neuroblastoma cells and performed RNA-seq and ISL1 ChIP-seq analyses. Results: Analyses of these data revealed that ISL1 acts upstream of multiple oncogenic genes and pathways essential for neuroblastoma proliferation and differentiation, including LMO1 and LIN28B. ISL1 promotes expression of a number of cell cycle associated genes, but represses differentiation associated genes including RA receptors and the downstream target genes EPAS1 and CDKN1A. Consequently, Knockdown of ISL1 inhibits neuroblastoma cell proliferation and migration in vitro and impedes tumor growth in vivo, and enhances neuronal differentiation by RA treatment. Furthermore, genome-wide mapping revealed a substantial co-occupancy of binding regions by ISL1 and GATA3, and ISL1 physically interacts with GATA3, and together they synergistically regulate the aforementioned oncogenic pathways. In addition, analyses of the roles of ISL1 and MYCN in MYCN-amplified and MYCN non-amplified neuroblastoma cells revealed an epistatic relationship between ISL1 and MYCN. ISL1 and MYCN function in parallel to regulate common yet distinct oncogenic pathways in neuroblastoma. Conclusion: Our study has demonstrated that ISL1 plays an essential role in neuroblastoma regulatory networks and may serve as a potential therapeutic target in neuroblastoma.

Long Noncoding RNA (lncRNA) MIR22HG Suppresses Gastric Cancer Progression through Attenuating NOTCH2 Signaling

BACKGROUND Long noncoding RNAs (lncRNAs) are important regulators in human disease, including cancers. LncRNA MIR22HG has been shown to inhibit the progression of endometrial carcinoma, lung cancer, and hepatocellular carcinoma. Its role in gastric cancer is unclear. This study investigated MIR22HG effects on gastric cancer. MATERIAL AND METHODS Gastric cancer tissues (n=43) and adjacent normal tissues (n=21) were collected. Patients' 5-year overall survival rate was analyzed. Human normal gastric mucosal cell line (GES-1) and gastric cancer cell lines (MKN-45, AGS, SGC-7901) were cultured. AGS and MKN-45 cells were transfected by pcDNA3 empty vector, pcDNA3-MIR22HG overexpression vector, MIR22HG siRNA and its negative control, NOTCH2 siRNA and its negative control, respectively. Proliferation was explored by CCK-8 assay. Migration and invasion were explored by Transwell. qRT-PCR and western blot were used to investigate mRNA and proteins expression, respectively. RESULTS MIR22HG expression was decreased in gastric cancer tissues and cells (P<0.05). Low MIR22HG expression indicated lower 5-year overall survival rate (P<0.05). Upregulation of MIR22HG inhibited AGS and MKN-45 cell proliferation, migration and invasion (all P<0.05). Downregulation of MIR22HG elevated AGS and MKN-45 cell proliferation, migration, and invasion (all P<0.05). MIR22HG negatively regulated NOTCH2 signaling. Silencing MIR22HG elevated HEY1 and nucleus NOTCH2 expression. Silencing of NOTCH2 suppressed AGS and MKN-45 cells proliferation, migration and invasion (all P<0.05). CONCLUSIONS LncRNA MIR22HG suppressed gastric cancer progression through attenuating NOTCH2 signaling.

ISL1 predicts poor outcomes for patients with gastric cancer and drives tumor progression through binding to the ZEB1 promoter together with SETD7

ISL1, a LIM-homeodomain transcription factor, serves as a biomarker of metastasis in multiple tumors. However, the function and underlying mechanisms of ISL1 in gastric cancer (GC) have not been fully elucidated. Here we found that ISL1 was frequently overexpressed in GC FFPE samples (104/196, 53.06%), and associated with worse clinical outcomes. Furthermore, the overexpression of ISL1 and loss-of-function of ISL1 influenced cell proliferation, invasion and migration in vitro and in vivo, including GC patient-derived xenograft models. We used ChIP-seq and RNA-seq to identify that ISL1 influenced the regulation of H3K4 methylation and bound to ZEB1, a key regulator of the epithelial–mesenchymal transition (EMT). Meanwhile, we validated ISL1 as activating ZEB1 promoter through influencing H3K4me3. We confirmed that a complex between ISL1 and SETD7 (a histone H3K4-specific methyltransferase) can directly bind to the ZEB1 promoter to activate its expression in GC cells by immunoprecipitation, mass spectrometry, and ChIP-re-ChIP. Moreover, ZEB1 expression was significantly positively correlated with ISL1 and was positively associated with a worse outcome in primary GC specimens. Our paper uncovers a molecular mechanism of ISL1 promoting metastasis of GC through binding to the ZEB1 promoter together with co-factor SETD7. ISL1 might be a potential prognostic biomarker of GC.

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 putative drugs for gastric adenocarcinoma utilizing differentially expressed genes and connectivity map

Gastric adenocarcinoma (GAC) is a challenging disease with dim prognosis even after surgery; hence, novel treatments for GAC are in urgent need. The aim of the present study was to explore new potential compounds interfering with the key pathways related to GAC progression. The differentially expressed genes (DEGs) between GAC and adjacent tissues were identified from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) database. Connectivity Map (CMap) was performed to screen candidate compounds for treating GAC. Subsequently, pathways affected by compounds were overlapped with those enriched by the DEGs to further identify compounds which had anti-GAC potential. A total of 843 DEGs of GAC were identified. Via Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, 13 pathways were significantly enriched. Moreover, 78 compounds with markedly negative correlations with DEGs were revealed in CMap database (P<0.05 and Enrichment <0). Subpathways of cell cycle and p53 signaling pathways, and core genes of these compounds, cyclin B1 (CCNB1) and CDC6, were identified. This study further revealed seven compounds that may be effective against GAC; in particular methylbenzethonium chloride and alexidine have never yet been reported for GAC treatment. In brief, the candidate drugs identified in this study may provide new options to improve the treatment of patients with GAC. However, the biological effects of these drugs need further investigation.

Clinical significance and biological roles of cyclins in gastric cancer

Background and aim

Cyclins have been reported to be overexpressed with poor prognosis in several human cancers. However, limited numbers of studies evaluated the expressions and prognostic roles of cyclins in gastric cancer (GC). We aim to evaluate the expressions and prognostic roles of cyclins. Also, further efforts were made to explore biological function of the differentially expressed cyclins.

Methods

Cyclins expressions were analyzed by Oncomine and The Cancer Genome Atlas datasets, and the prognostic roles of cyclins in GC patients were investigated by the Kaplan–Meier Plotter database. Then, a comprehensive PubMed literature search was performed to identify expression and prognosis of cyclins in GC. Biological functions of the differentially expressed cyclins were explored through Enrich R platform, and KEGG and transcription factor were analyzed.

Results

The expression levels of CCNA2 (cyclin A2), CCNB1 (cyclin B1), CCNB2 (cyclin B2), and CCNE1 (cyclin E1) mRNAs were identified to be significantly higher in GC tissues than in normal tissues in both Oncomine and The Cancer Genome Atlas datasets. High expressions of CCNA2, CCNB1, and CCNB2 mRNAs were identified to be related with poor overall survival in Kaplan–Meier Plotter dataset. Evidence from clinical studies showed that CCNB1 was related with overall survival in GC patients. Cyclins were associated with several biological pathways, including cell cycle, p53 signaling pathway, FoxO signaling pathway, viral carcinogenesis, and AMPK signaling pathway. Enrichment analysis also showed that cyclins interacted with some certain transcription factors, such as FOXM1, SIN3A, NFYA, and E2F4.

Conclusion

Based on our results, high expressions of cyclins were related with poor prognosis in GC patients. The above information might be useful for better understanding the clinical and biological roles of cyclins mRNA and guiding individualized treatments for GC patients.

Prognostic Genes of Breast Cancer Identified by Gene Co-expression Network Analysis

Breast cancer is one of the most common malignancies. The molecular mechanisms of its pathogenesis are still to be investigated. The aim of this study was to identify the potential genes associated with the progression of breast cancer. Weighted gene co-expression network analysis (WGCNA) was used to construct free-scale gene co-expression networks to explore the associations between gene sets and clinical features, and to identify candidate biomarkers. The gene expression profiles of GSE1561 were selected from the Gene Expression Omnibus (GEO) database. RNA-seq data and clinical information of breast cancer from TCGA were used for validation. A total of 18 modules were identified via the average linkage hierarchical clustering. In the significant module (R² = 0.48), 42 network hub genes were identified. Based on the Cancer Genome Atlas (TCGA) data, 5 hub genes (CCNB2, FBXO5, KIF4A, MCM10, and TPX2) were correlated with poor prognosis. Receiver operating characteristic (ROC) curve validated that the mRNA levels of these 5 genes exhibited excellent diagnostic efficiency for normal and tumor tissues. In addition, the protein levels of these 5 genes were also significantly higher in tumor tissues compared with normal tissues. Among them, CCNB2, KIF4A, and TPX2 were further upregulated in advanced tumor stage. In conclusion, 5 candidate biomarkers were identified for further basic and clinical research on breast cancer with co-expression network analysis.