Clinical significance and biological roles of cyclins in gastric cancer

Expression and function of NF-Y subunits in cancer

NF-Y is a Transcription Factor (TF) targeting the CCAAT box regulatory element. It consists of the NF-YB/NF-YC heterodimer, each containing an Histone Fold Domain (HFD), and the sequence-specific subunit NF-YA. NF-YA expression is associated with cell proliferation and absent in some post-mitotic cells. The review summarizes recent findings impacting on cancer development. The logic of the NF-Y regulome points to pro-growth, oncogenic genes in the cell-cycle, metabolism and transcriptional regulation routes. NF-YA is involved in growth/differentiation decisions upon cell-cycle re-entry after mitosis and it is widely overexpressed in tumors, the HFD subunits in some tumor types or subtypes. Overexpression of NF-Y -mostly NF-YA- is oncogenic and decreases sensitivity to anti-neoplastic drugs. The specific roles of NF-YA and NF-YC isoforms generated by alternative splicing -AS- are discussed, including the prognostic value of their levels, although the specific molecular mechanisms of activity are still to be deciphered.

Fabrication, optimization, and characterization of pH-responsive PEGylated nanoniosomes containing gingerol for enhanced treatment of breast cancer

Multiple potential drug delivery strategies have emerged as a result of recent advances in nanotechnology and nanomedicine. The aim of this research was to prepare an optimized system of PEGylated gingerol-loaded niosomes (Nio-Gin@PEG) as an excellent candidate for the treatment of human breast cancer cells. The preparation procedure was modified by adjusting the drug concentration, lipid content, and Span60/Tween60 ratio, resulting in high encapsulation efficacy (EE%), rapid release rate, and reduced size. The Nio-Gin@PEG exhibited significantly improved storage stability compared to the gingerol-loaded niosomes formulation (Nio-Gin), with minimal changes in EE%, release profile, and size during storage. Furthermore, Nio-Gin@PEG demonstrated pH-dependent release behavior, with delayed drug diffusion at physiological pH and significant drug diffusion under acidic conditions (pH = 5.4), making it a promising option for cancer treatment. Cytotoxicity tests indicated that Nio-Gin@PEG possessed excellent biocompatibility with human fibroblast cells while exerting a remarkable inhibitory effect on MCF-7 and SKBR3 breast cancer cells, attributed to the presence of gingerol and the PEGylated structure in the preparation. Nio-Gin@PEG also exhibited the ability to modulate the expression of target genes. We observed statistically significant down-regulation of the expression of BCL2, MMP2, MMP9, HER2, CCND1, CCNE1, BCL2, CDK4, and VEGF genes, along with up-regulation of the expression of BAX, CASP9, CASP3, and P21 genes. Flow cytometry results revealed that Nio-Gin@PEG could induce a higher rate of apoptosis in both cancerous cells compared to gingerol and Nio-Gin, owing to the optimal encapsulation and efficient drug release from the formulation, as confirmed by cell cycle tests. ROS generation demonstrated the superior antioxidant effect of Nio-Gin@PEG compared to other prepared formulations. The results of this study emphasize the potential of formulating highly biocompatible niosomes in the future of nanomedicine, enabling more precise and effective treatment of cancers.

RGMb expression in goat uterine tissues: possible role of RGMb in the proliferation and apoptosis of endometrial epithelial cells

Context Bone morphogenetic proteins (BMPs) play an important role in the uteri. Repulsive guidance molecule b (RGMb; a.k.a. Dragon) has been confirmed as the coreceptor of BMPs to function through drosophila mothers against decapentaplegic protein (Smads) and mitogen-activated protein kinases (MAPK) pathways. We hypothesise that RGMb regulates the uterine function through the Smads and MAPK pathways. Aims This study aimed to investigate the expression of RGMb in goat uteri and the potential role of RGMb in the endometrial epithelial cells (EECs). Methods The localisation of RGMb in goat uterine tissues was detected by immunohistochemistry (IHC), EECs were isolated and transfected with siRNA to investigate the role of RGMb in proliferation, and apoptosis. The expression levels of Smads and MAPK members was measured by western blot (WB) and real-time PCR (RT-PCR). Key results IHC showed that RGMb was localised in goat endometrial luminal cells, glandular epithelial cells, and circular muscle fibres, but not in stromal cells. RT-PCR results showed that treatment with RGMb siRNA suppressed the expressions of proliferation-related genes cyclin D1 (CCND1 , P =0.0291), cyclin-dependent kinase 2 (CDK2 P =0.0107), and proliferating cell nuclear antigen (PCNA, P =0.0508), leading to the reduced viability of EECs (P =0.0010). WB results showed that the expression ratio of cleaved-caspase 3/caspase 3 (P =0.0013) was markedly increased after RGMb siRNA transfection. Likewise, the level of phospho-extracellular signal-regulated kinase 1/2 (p-ERK1/2, P =0.0068) and p-Smad1/5/8 (P =0.0011) decreased significantly, while there were no appreciable differences in the level of p-P38 MAPK expression (P >0.05). Conclusions RGMb might participate in the regulation of cell proliferation and apoptosis through Smads and ERK signalling pathways in goat EECs. Implications RGMb is involved in regulating the proliferation and apoptosis in goat endometrial epithelial cells.

Genomic alterations of cerebrospinal fluid cell-free DNA in leptomeningeal metastases of gastric cancer

BACKGROUND

Leptomeningeal metastases (LM) were rare in gastric cancer (GC), and GC patients with LM (GCLM) generally suffer from poor prognosis. Nevertheless, the clinical utility of cerebrospinal fluid (CSF) circulating tumor DNA (ctDNA) was underinvestigated in GCLM.

METHODS

We retrospectively studied 15 GCLM patients, and all patients had paired primary tumor tissue samples and post-LM CSF samples while 5 patients also had post-LM plasma samples. All samples were analyzed using next-generation sequencing (NGS), and the molecular and clinical features were correlated with clinical outcomes.

RESULTS

CSF had higher mutation allele frequency (P = 0.015), more somatic mutations (P = 0.032), and more copy-number variations (P < 0.001) than tumor or plasma samples. Multiple genetic alterations and aberrant signal pathways were enriched in post-LM CSF, including CCNE1 amplification and cell cycle-related genes, and CCNE1 amplification was significantly associated with patients' overall survival (P = 0.0062). More potential LM progression-related markers were detected in CSF samples than in tumor samples, including PREX2 mutation (P = 0.014), IGF1R mutation (P = 0.034), AR mutation (P = 0.038), SMARCB1 deletion (P < 0.001), SMAD4 deletion (P = 0.0034), and TGF-beta pathway aberration (P = 0.0038). Additionally, improvement in intracranial pressure (P < 0.001), improvement in CSF cytology (P = 0.0038), and relatively low levels of CSF ctDNA (P = 0.0098) were significantly associated with better PFS. Lastly, we reported a GCLM case whose CSF ctDNA dynamic changes were well correlated with his clinical assessment.

CONCLUSIONS

CSF ctDNA could more sensitively detect molecular markers and metastasis-related mechanisms than tumor tissues in GCLM patients, and our study sheds light on utilizing CSF ctDNA in prognostic estimation and clinical assessment in GCLM.

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.

The Regulation of Cyclins and Cyclin-Dependent Kinases in the Development of Gastric Cancer

Gastric cancer predominantly occurs in adenocarcinoma form and is characterized by uncontrolled growth and metastases of gastric epithelial cells. The growth of gastric cells is regulated by the action of several major cell cycle regulators including Cyclins and Cyclin-dependent kinases (CDKs), which act sequentially to modulate the life cycle of a living cell. It has been reported that inadequate or over-activity of these molecules leads to disturbances in cell cycle dynamics, which consequently results in gastric cancer development. Manny studies have reported the key roles of Cyclins and CDKs in the development and progression of the disease in either in vitro cell culture studies or in vivo models. We aimed to compile the evidence of molecules acting as regulators of both Cyclins and CDKs, i.e., upstream regulators either activating or inhibiting Cyclins and CDKs. The review entails an introduction to gastric cancer, along with an overview of the involvement of cell cycle regulation and focused on the regulation of various Cyclins and CDKs in gastric cancer. It can act as an extensive resource for developing new hypotheses for future studies.

Screening of Key Prognosis Genes of Lung Adenocarcinoma Based on Expression Analysis on TCGA Database

Objective

The data of lung adenocarcinoma- (LUAD-) related gene expression profiles were mined from the Cancer Genome Atlas (TCGA) database using bioinformatics methods and potential biomarkers related to the occurrence, development, and prognosis of LUAD were screened out to explore the key prognostic genes and clinical significance.

Methods

Following the LUAD gene expression profile data that were initially exported from the TCGA database, R software DESeq2 was employed to analyze the difference between the expression profiles of LUAD and normal tissues. The R package "clusterProfiler" was subsequently utilized to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the differential genes. A protein-protein interaction (PPI) network was constructed via the String database, and cytohubba, a plugin of Cytoscape, was applied to screen hub genes using the MCC algorithm. The Gene Expression Profile Data Interactive Analysis (GEPIA) was used to analyze expressions of 10 candidate genes in LUAD samples and healthy lung samples, and the selected genes were employed for survival analysis.

Results

A total of 1,598 differential genes were identified through differential analyses and data mining, with 1,394 genes upregulated and 204 downregulated. A total of 10 hub genes CCNA2, CDC20, CCNB2, KIF11, TOP2A, BUB1, BUB1B, CENPF, TPX2, and KIF2C were obtained using the cytohubba plugin. The results of the GEPIA analysis indicated that compared with normal lung tissue, the mRNA expression level of the described hub genes in LUAD tissue was significantly increased (P < 0.05). Survival analysis revealed that these genes had a significant impact on the overall survival time of LUAD patients (P < 0.05).

Conclusion

The previously described key genes related to LUAD identified in the TCGA database may be used as potential prognostic biomarkers, which will contribute to further comprehension of the occurrence and development of LUAD and provide references for its diagnosis and treatment.

pH-Responsive PEGylated Niosomal Nanoparticles as an Active-Targeting Cyclophosphamide Delivery System for Gastric Cancer Therapy

A PEGylated niosomal formulation of cyclophosphamide (Nio-Cyclo-PEG) was prepared using a central composite design and characterized in terms of drug loading, size distribution, and average size. The stability of formulations was also studied at different conditions. In vitro cytotoxicity of drug delivery formulations was assessed on gastric cancer cells using MTT assay. The mechanism of cytotoxicity was studied at the transcriptional level by real-time PCR on Caspase3, Caspase9, CyclinD, CyclinE, MMP-2, and MMP-9 genes, while apoptosis was investigated with flow cytometry. The anti-metastatic property was evaluated using the scratch method. Propidium iodide staining was used to study the cell cycle. The results indicated that the as-designed nanocarrier exhibited a controlled drug release pattern with improved nanoparticle stability. It was found that the living cancer cells treated with Nio-Cyclo-PEG showed a significant decrease in number when compared with the niosomal carrier without PEG (Nio-Cyclo) and free drug (Cyclo). Moreover, the drug-loaded nanocarrier induced planned death (apoptosis) in the cancer cells through the regulation of Caspase3, Caspase9, CyclinD, CyclinE, MMP-9, and MMP-2 gene expression, indicating that the Nio-Cyclo-PEG formulation could significantly inhibit the cell cycle at the sub G1 phase as well as prevent the migration of cancer cells. In conclusion, Nio-Cyclo-PEG as developed in this study could serve as an active-targeting drug delivery nanocarriers for gastric cancer therapy with high efficacy and minimal side effects on healthy tissues/cells.

The Predictive Competing Endogenous RNA Regulatory Networks and Potential Prognostic and Immunological Roles of Cyclin A2 in Pan-Cancer Analysis

Although accumulating evidence has verified the relationship between CCNA2 and cancers, no pan-cancer analysis about the function and the upstream molecular mechanism of CCNA2 is available. For the first time, we analyzed potential oncogenic roles of CCNA2 in 33 cancer types via The Cancer Genome Atlas (TCGA) database. Overexpression of CCNA2 is widespread in almost all cancer types, and it is related to poor prognosis and advanced pathological stages in most cases. Moreover, we conducted upstream miRNAs and lncRNAs of CCNA2 to establish upstream regulatory networks in kidney renal clear cell carcinoma (LINC00997/miR-27b-3p/CCNA2), liver hepatocellular carcinoma (SNHG16, GUSBP11, FGD5-AS1, LINC00630, CD27-AS1, LINC00997/miR-22-3p/CCNA2, miR-29b-3p/CCNA2, miR-29c-3p/CCNA2, and miR-204-5p/CCNA2), and lung adenocarcinoma (miRNA-218-5p/CCNA2 and miR-204-5p/CCNA2) by expression analysis, survival analysis, and correlation analysis. The CCNA2 expression is positively correlated with Th2 cell infiltration and negatively correlated with CD4+ central memory and effector memory T-cell infiltration in different cancer types. Furthermore, CCNA2 is positively associated with expressions of immune checkpoints (CD274, CTLA4, HAVCR2, LAG3, PDCD1, and TIGIT) in most cancer types. Our first CCNA2 pan-cancer study contributes to understanding the prognostic and immunological roles and potential upstream molecular mechanisms of CCNA2 in different cancers.

Identification of key regulators associated with colon cancer prognosis and pathogenesis

Colon cancer (CC) is the fourth deadliest cancer in the world. New insights into prognostication might be helpful to define the optimal adjuvant treatments for patients in routine clinical practice. Here, a microarray dataset with 30 primary tumors and 30 normal samples was analyzed using GEO2R to find differentially expressed genes (DEGs). Then, DAVID, KEGG, ChEA and X2K were used to analyze DEGs-related Gene Ontology, pathways, transcription factors (TFs) and kinases, respectively. Protein-protein interaction (PPI) networks were constructed using the STRING database and Cytoscape. The modules and hub genes of DEGs was determined through MCODE and CytoHubba plugins, and the expression of hub genes was verified using GEPIA. To find microRNAs and metabolites associated with DEGs, miRTarBase and HMDB were used, respectively. It was found that 233 and 373 genes were upregulated and downregulated in CC, respectively. GO analysis showed that the upregulated DEGs were mainly involved in mitotic nuclear division and cell division. Top 10 hub genes were identified, including AURKB, CDK1, DLGAP5, AURKA, CCNB2, CCNB1, BUB1B, CCNA2, KIF20A and BUB1. Whereas, FOMX1, E2F7, E2F1, E2F4 and AR were identified as top 5 TFs in CC. Moreover, CDK1, CDC2, MAPK14, ATM and CK2ALPHA was identified as top 5 kinases in CC. miRNAs analysis showed that Hsa-miR-215-5p hsa-miR-193b-3p, hsa-miR-192-5p and hsa-miR-16-5p could target the largest number of CC genes. Taken together, CC-related genes, especially the hub genes, TFs, and metabolites might be used as novel biomarkers for CC, as well as for diagnosis and guiding therapeutic strategies for CC.

Prognostic Significance of CCNB2 Expression in Triple-Negative Breast Cancer

Purpose

The aim of this study was to explore potential gene therapy targets for triple-negative breast cancer (TNBC).

Patients and Methods

Three gene expression profiles (GSE64790, GSE62931, and GSE38959) from the Gene Expression Omnibus (GEO) database were analyzed. The GEO2R analysis tool was used to screen for differentially expressed genes (DEGs) between TNBC and normal tissues, followed by Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of the DEGs. The protein–protein interaction network of DEGs was visualized using Metascape to identify the core genes. Subsequently, transcriptional data for the core genes in patients with breast cancer were investigated in the ONCOMINE database. Kaplan–Meier survival analysis was used to evaluate the prognostic value of core gene expression levels in patients with TNBC. Finally, the clinicopathological and long-term follow-up data of 39 patients with TNBC were retrospectively analyzed at the First Affiliated Hospital of the Bengbu Medical College between January 2014 and July 2020. Immunohistochemistry was used to evaluate the expression and subcellular localization of CCNB2 in TNBC tissues.

Results

A total of 66 DEGs were identified between TNBC and normal tissues, including 33 upregulated and 33 downregulated genes in TNBC. Furthermore, a potential protein complex was identified for five core genes. The high expression of these core genes, especially the overexpression of CCNB2, was correlated with a poor prognosis of patients with TNBC. The CCNB2 protein was expressed in the cytoplasm, and its expression was significantly higher in TNBC tissues than that in the adjacent nontumor tissues. Overall survival of patients was significantly correlated with the expression of CCNB2 (p < 0.05).

Conclusion

CCNB2 may play a crucial role in the development of TNBC and has the potential to be used as a prognostic biomarker for TNBC.

Comprehensive Analysis of E2F Family Members in Human Gastric Cancer

Gastric cancer (GC) is the second most common cancer and the third most frequent cause of cancer-related deaths in China. E2Fs are a family of transcription factors reported to be involved in the tumor progression of various cancer types; however, the roles of individual E2Fs are still not known exactly in tumor progression of GC. In this study, we examined the expression of E2Fs to investigate their roles in tumor progression in GC patients using multiple databases, including ONCOMINE, GEPIA2, Kaplan-Meier plotter, cBioPortal, Metascape, LinkedOmics, GeneMANIA, STRING and UCSC Xena. We also performed real-time polymerase chain reaction (RT-PCR) to validate the expression levels of individual E2Fs in several GC cell lines. Our results demonstrated that the mRNA levels of E2F1/2/3/5/8 were significantly higher both in GC tissues and cell lines. The expression levels of E2F1 and E2F4 were correlated with poor overall survival (OS), decreased post-progression survival (PPS), and decreased progression-free survival (FP) in patients with GC. However, overexpression of E2F2, E2F5, E2F7 and E2F8 is significantly associated with disease-free survival and overall survival in patients with GC. In addition, higher E2F3 and E2F6 mRNA expression was found to increase GC patients' OS and PPS. 224 of 415 patients with STAD (54%) had gene mutations that were associated with longer disease-free survival (DFS) but not OS. Cell cycle pathway was closely associated with mRNA level of more than half of E2Fs (E2F1/2/3/7/8). There were close and complicated interactions among E2F family members. Finally, our results indicated the gene expressions of E2Fs had a positive relationship with its copy numbers. Taken together, E2F1/2/3/5/8 can serve as biomarkers for GC patients with high prognostic value for OS of GC patients or therapeutic targets for GC.

An Integrative Systems Biology Approach Identifies Molecular Signatures Associated with Gallbladder Cancer Pathogenesis

Gallbladder cancer (GBC) has a lower incidence rate among the population relative to other cancer types but is a major contributor to the total number of biliary tract system cancer cases. GBC is distinguished from other malignancies by its high mortality, marked geographical variation and poor prognosis. To date no systemic targeted therapy is available for GBC. The main objective of this study is to determine the molecular signatures correlated with GBC development using integrative systems level approaches. We performed analysis of publicly available transcriptomic data to identify differentially regulated genes and pathways. Differential co-expression network analysis and transcriptional regulatory network analysis was performed to identify hub genes and hub transcription factors (TFs) associated with GBC pathogenesis and progression. Subsequently, we assessed the epithelial-mesenchymal transition (EMT) status of the hub genes using a combination of three scoring methods. The identified hub genes including, CDC6, MAPK15, CCNB2, BIRC7, L3MBTL1 were found to be regulators of cell cycle components which suggested their potential role in GBC pathogenesis and progression.

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.

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.

Four Novel Prognostic Genes Related to Prostate Cancer Identified Using Co-expression Structure Network Analysis

Prostate cancer (PCa) is one of the most common malignancies for males, but very little is known about its pathogenesis. This study aimed to identify novel biomarkers associated with PCa prognosis and elucidate the underlying molecular mechanism. First, The Cancer Genome Atlas (TCGA) RNA-sequencing data were utilized to identify differentially expressed genes (DEGs) between tumor and normal samples. The DEGs were then applied to construct a co-expression and mined using structure network analysis. The magenta module that was highly related to the Gleason score (r = 0.46, p = 3e-26) and tumor stage (r = 0.38, p = 2e-17) was screened. Subsequently, all genes of the magenta module underwent function annotation. From the key module, CCNA2, CKAP2L, NCAPG, and NUSAP1 were chosen as the four candidate genes. Finally, internal (TCGA) and external data sets (GSE32571, GSE70770, and GSE141551) were combined to validate and predict the value of real hub genes. The results show that the above genes are up-regulated in PCa samples, and higher expression levels show significant association with higher Gleason scores and tumor T stage. Moreover, receiver operating characteristic curve and survival analysis validate the excellent value of hub genes in PCa progression and prognosis. In addition, the protein levels of these four genes also remain higher in tumor tissues when compared with normal tissues. Gene set enrichment analysis and gene set variation analysis for a single gene reveal the close relation with cell proliferation. Meanwhile, 11 small molecular drugs that have the potential to treat PCa were also screened. In conclusion, our research identified four potential prognostic genes and several candidate molecular drugs for treating PCa.

Bruceine D inhibits Cell Proliferation Through Downregulating LINC01667/MicroRNA-138-5p/Cyclin E1 Axis in Gastric Cancer

Objective: Gastric cancer is one of the most common malignant tumors. Bruceine D (BD) is one of the extracts of Brucea javanica. In recent years, it has been reported that BD has anti-tumor activity in some human cancers through different mechanisms. Here, this study try to explore the effect of BD on gastric cancer and its regulatory mechanism.

Methods: Cell proliferation ability was detected by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assays, 5-bromo-2-deoxyuridine (BrdU) staining and soft agar colony formation assay, respectively. The tumor xenograft model was used to verify the effect of BD on the tumorigenicity of gastric cancer cells in vivo. Flow cytometry analysis and Western blot assay were performed to detect cell cycle and apoptosis. Gastric cancer cells were analyzed by transcriptome sequencing. The interaction between LINC01667, microRNA-138-5p (miR-138-5p) and Cyclin E1 was verified by dual luciferase experiment and RT-PCR assays.

Results: We found that BD significantly inhibited cell proliferation and induced cell cycle arrest at S phase in gastric cancer cells. Transcriptome analysis found that the expression of a long non-coding RNA, LINC01667, were significantly down-regulated after BD treatment. Mechanically, it was discovered that LINC01667 upregulated the expression of Cyclin E1 by sponging miR-138-5p. Furthermore, BD enhanced the chemosensitivity of gastric cancer cells to doxorubicin, a clinically used anti-cancer agent.

Conclusion: BD inhibit the growth of gastric cancer cells by downregulating the LINC01667/miR-138-5p/Cyclin E1 axis. In addition, BD enhances the chemosensitivity of gastric cancer cells to doxorubicin. This study indicates that BD may be used as a candidate drug for the treatment of patients with gastric cancer.

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.

Aberrant brain-expressed X-linked 4 (BEX4) expression is a novel prognostic biomarker in gastric cancer

BACKGROUND

This study aimed to investigate the expression level of X-linked 4 (BEX4) in patients with gastric cancer (GC) and to investigate the prognostic significance of BEX4.

METHODS

The mRNA expression of BEX4 was analyzed using the Cancer Genome Atlas (TCGA) datasets. The relationship between the expression of BEX4 and GC patient survival was assessed using a Kaplan-Meier plot and Log Rank test. Multivariate cox regression analysis was used to evaluate prognostic factor. The diagnostic value of BEX4 expression in GC tissue was determined through receiver operating characteristic (ROC) curve analysis. Gene set enrichment analysis (GSEA) was used to explore BEX-4 related signaling pathways in GC. Furthermore, the Human Protein Atlas (HPA) database and GSE62254 dataset were used for further validation.

RESULTS

BEX4 was expressed at lower level in GC tissues than normal gastric tissues. The lower expression of BEX4 was also validated at protein level in HPA database. The area under the ROC curve for BEX4 expression in normal gastric tissue and GC was 0.791, which presented modest diagnostic value. Kaplan-Meier survival analysis revealed that patients in low BEX4 expression group had a worse prognosis than those with high BEX4 expression (P = .009). Multivariate analysis showed that BEX4 is an independent risk factor for overall survival both in TCGA and GSE62254 (P = .0142, .013, respectively). GSEA identified that the expression of BEX4 was related to DNA replication, RNA polymerase, cell cycle, and P53 signaling pathway.

CONCLUSION

BEX4 is expressed at low levels in GC. BEX4 expression independently predicted poor OS for GC. It is a promising independent molecular predictor for the diagnosis and prognosis of GC.

Novel Potential Therapeutic Target for E2F1 and Prognostic Factors of E2F1/2/3/5/7/8 in Human Gastric Cancer

E2F transcription factors (E2Fs) were found to be related with cell activities and disease progression among a variety of different tumors, including regulating cell division and cell proliferation. In the analysis, it aimed to focus on transcriptional and survival information of E2Fs in gastric cancer (GC) from Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier plotter, cBioPortal, Database for Annotation, Visualization and Integrated Discovery (DAVID), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Oncomine databases. It was found that the expression of E2F1/2/3/5/7/8 in GC tissues was obviously higher than the normal. Of interest, none of the E2Fs was related with pathological stages. Nevertheless, high expression of E2F2/3/5/7/8 was related with better survival data, except E2F6 regarding shorter first-progression (FP) survival. High expression levels of E2F2/5/7/8 have significant correlations with overall survival (OS) in patients with intestinal and diffuse GC, and this prognostic value is not affected by gender. Oppositely, the lower level of E2F1/4 illustrated superior survival data. Moreover, increased expression of E2F1 in GC tissues might play an important role in the development of GC. Collectively, E2F1 could be a potential therapeutic target for patients with GC. E2F1/2/3/5/7/8 might be original prognostic predictors of GC.

MiR-29c-3p Suppresses the Migration, Invasion and Cell Cycle in Esophageal Carcinoma via CCNA2/p53 Axis

Objective

In the present study, we tried to describe the role of miR-29c-3p in esophageal carcinoma (EC) and the relationship of miR-29c-3p with CCNA2 as well as cell cycle, accordingly revealing the potential molecular mechanism across cell proliferation, migration and invasion.

Methods

Expression profiles of EC miRNAs and matched clinical data were accessed from TCGA database for differential and survival analyses. Bioinformatics databases were employed to predict the downstream targets of the potential miRNA, and enrichment analysis was performed on the miRNA and corresponding target gene using GSEA software. qRT-PCR was conducted to detect the expression levels of miR-29c-3p and CCNA2 mRNA in EC tissues and cells, and Western blot was performed for the examination of CCNA2, CDK1 and p53 protein levels. Subsequently, cells were harvested for MTT, Transwell as well as flow cytometry assays to examine cell viability, migration, invasion and cell cycle. Dual-luciferase reporter gene assay and RIP were carried out to further investigate and verify the targeted relationship between miR-29c-3p and CCNA2.

Results

MiR-29c-3p was shown to be significantly down-regulated in EC tissues and able to predict poor prognosis. CCNA2 was found to be a downstream target of miR-29c-3p and mainly enriched in cell cycle and p53 signaling pathway, whereas miR-29c-3p was remarkably activated in cell cycle. MiR-29c-3p overexpression inhibited cell proliferation, migration and invasion, as well as arrested cells in G0/G1 phase. As suggested by dual-luciferase reporter gene assay and RIP, CCNA2 was under the regulation of miR-29c-3p, and the negative correlation between the two genes was verified. Silencing CCNA2 could suppress cell proliferation, migration and invasion, as well as activate p53 pathway, even was seen to reverse the inhibitory effect of PFTβ on p53. Besides, in the presence of low miR-29c-3p, CCNA2 was up-regulated while p53 was simultaneously inhibited, resulting in the promotion of cell migration, invasion and cell cycle arrest.

Conclusion

MiR-29c-3p plays a regulatory role in EC tumorigenesis and development. MiR-29c-3p can target CCNA2 to mediate p53 signaling pathway, finally attributing to the inhibition of cell proliferation, migration and invasion, and making cells arrest in G0/G1 phase.