Systematic analysis to identify a key role of CDK1 in mediating gene interaction networks in cervical cancer development

Hijacking and rewiring of host CircRNA/miRNA/mRNA competitive endogenous RNA (ceRNA) regulatory networks by oncoviruses during development of viral cancers

A significant portion of human cancers are caused by oncoviruses (12%-25%). Oncoviruses employ various strategies to promote their replication and induce tumourigenesis in host cells, one of which involves modifying the gene expression patterns of the host cells, leading to the rewiring of genes and resulting in significant changes in cellular processes and signalling pathways. In recent studies, a specific mode of gene regulation known as circular RNA (circRNA)-mediated competing endogenous RNA (ceRNA) networks has emerged as a key player in this context. CircRNAs, a class of non-coding RNA molecules, can interact with other RNA molecules, such as mRNAs and microRNAs (miRNAs), through a process known as ceRNA crosstalk. This interaction occurs when circRNAs, acting as sponges, sequester miRNAs, thereby preventing them from binding to their target mRNAs and modulating their expression. By rewiring the host cell genome, oncoviruses have the ability to manipulate the expression and activity of circRNAs, thereby influencing the ceRNA networks that can profoundly impact cellular processes such as cell proliferation, differentiation, apoptosis, and immune responses. This review focuses on a comprehensive evaluation of the latest findings on the involvement of virus-induced reprogramming of host circRNA-mediated ceRNA networks in the development and pathophysiology of human viral cancers, including cervical cancer, gastric cancer, nasopharyngeal carcinoma, Kaposi's sarcoma, hepatocellular carcinoma, and diffuse large B cell lymphoma. Understanding these mechanisms can improve our knowledge of how oncoviruses contribute to human tumourigenesis and identify potential targets for developing optimised therapies and diagnostic tools for viral cancers.

Curcumin targets miR-134-5p to suppress the progression of colorectal cancer through regulating the CDCA3/CDK1 pathway

It has been reported the anti-tumor action of curcumin on colorectal cancer. In this study, we aimed to explore the potential mechanisms underlying curcumin in the development of colorectal cancer. CCK-8, EdU, flow cytometry, and transwell invasion assays were conducted to investigate the function role of curcumin in cell proliferation, apoptosis, and invasion. The level of miR-134-5p and CDCA3 was determined using RT-qPCR analysis. Western blot was applied for detecting the levels of c-myc, MMP9, CDCA3, and CDK1. Dual-luciferase reporter assay was used to evaluate the relationship between miR-134-5p and CDCA3, and IP assay was performed to examine the interaction between CDCA3 and CDK1. Additionally, SW620 cells were injected into the mice to form the xenograft tumor model. Curcumin treatment repressed cell growth and invasion, and induced cell apoptosis in HCT-116 and SW620 cells. Curcumin elevated miR-134-5p expression and restrained CDCA3 expression in HCT-116 and SW620 cells. MiR-134-5p inhibitor or CDCA3 overexpression could restore the effects of curcumin on cell growth, apoptosis, and invasion in HCT-116 and SW620 cells. MiR-134-5p targeted CDCA3, and CDCA3 could rescue the repressive effects of miR-134-5p on the progression of colorectal cancer. Moreover, CDCA3 interacted with CDK1, and CDK1 overexpression blocked the suppressive effects of CDCA3 downregulation on the development of colorectal cancer. In addition, curcumin treatment repressed tumor growth in colorectal cancer via increasing miR-134-5p and downregulating CDCA3 and CDK1 expression in vivo. Our findings provided the evidence that curcumin upregulated miR-134-5p to inhibit the progression of colorectal cancer by regulating CDCA3/CDK1 pathway.

Molecular Actions of Enicostemma hyssopifolium Whole Plant Extract on HPV18-Infected Human Cervical Cancer (HeLa) Cells

OBJECTIVE

Enicostemma hyssopifolium (E. hyssopifolium) contains several bioactive compounds with anti-cancer activities. This study was performed to investigate the molecular effects of E. hyssopifolium on HPV18-containing HeLa cells.

METHODS

The methanol extract of E. hyssopifolium whole plant was tested for cytotoxicity by MTT assay. A lower and higher dose (80 and 160 μg/mL) to IC50 were analyzed for colonization inhibition (Clonogenic assay), cell cycle arrest (FACS analysis), and induction of apoptosis (AO/EtBr staining fluorescent microscopy and FACS analysis) and DNA fragmentation (comet assay). The HPV 18 E6 gene expression in treated cells was analyzed using RT-PCR and qPCR.

RESULTS

A significant dose-dependent anti-proliferative activity (IC50 - 108.25±2 μg/mL) and inhibition of colony formation cell line were observed using both treatments. Treatment with 80 μg/mL of extract was found to result in a higher percent of cell cycle arrest at G0/G1 and G2M phases with more early apoptosis, while 160 μg/mL resulted in more cell cycle arrest at SUBG0 and S phases with late apoptosis for control. The comet assay also demonstrated a highly significant increase in DNA fragmentation after treatment with 160 μg/mL of extract (tail moments-19.536 ± 17.8), while 80 μg/mL of extract treatment showed non-significant tail moment (8.152 ± 13.0) compared to control (8.038 ± 12.0). The RT-PCR and qPCR results showed a significant reduction in the expression of the HPV18 E6 gene in HeLa cells treated with 160 μg/mL of extract, while 80 μg/mL did not show a significant reduction.

CONCLUSION

The 160 μg/mL methanol extract of E. hyssopifolium demonstrated highly significant anti-cancer molecular effects in HeLa cells.

A Mini-review on Helicobacter pylori with Gastric Cancer and Available Treatments

Helicobacter pylori (H. pylori) is the most thoroughly researched etiological component for stomach inflammation and malignancies. Even though there are conventional recommendations and treatment regimens for eradicating H. pylori, failure rates continue to climb. Antibiotic resistance contributes significantly to misdiagnoses, false positive results, and clinical failures, all of which raise the chance of infection recurrence. This review aims to explore the molecular mechanisms underlying drug resistance in H. pylori and discuss novel approaches for detecting genotypic resistance. Modulation of drug uptake/ efflux, biofilm, and coccoid development. Newer genome sequencing approaches capable of detecting H. pylori genotypic resistance are presented. Prolonged infection in the stomach causes major problems such as gastric cancer. The review discusses how H. pylori causes stomach cancer, recent biomarkers such as miRNAs, molecular pathways in the development of gastric cancer, and diagnostic methods and clinical trials for the disease. Efforts have been made to summarize the recent advancements made toward early diagnosis and novel therapeutic approaches for H. pylori-induced gastric cancer.

Expression of selected long non-coding RNAs in gastric cancer cells treated with coumarin: Possible mechanisms for anti-cancer activity

Long non-coding RNAs (lncRNAs) can be utilized as prognostic indicators of gastric cancer since they can affect several cancer-related processes. Coumarin is a natural product with some useful anti-cancer properties. Here, we measured the expression of selected lncRNAs (RuPAR, SNHG6, CASC11, and their targets, miR-340-5p, p21, E-cadherin, and CDK1) in AGS gastric cancer cells treated with coumarin. MTT test has been utilized for assessing the AGS cells' cell viability after exposure to coumarin. The expression of the lncRNAs (RuPAR, SNHG6, and CASC11) and miR-340-5p was evaluated via qRT-PCR. Western blot analysis has been utilized to determine changes in p21, E-cadherin, and CDK1 expression. Coumarin decreased AGS viability in a dose-dependent manner. The coumarin treated cells had lower levels of the mRNAs known to be targets of lncRNAs SNHG6 and CASC11 compared to control. Additionally, the coumarin group had increased levels of lncRNA RuPAR expression when compared with the control group. Some lncRNA targets, including p21, E-cadherin, and CDK1, showed lower expression in the coumarin group compared to the control by Western blotting. Coumarin could be a promising pharmacological candidate to be included in gastric cancer treatment regimens because it modulates lncRNAs and their targets.

Fu Fang Gang Liu aqueous extract inhibits the proliferation of HeLa cells by causing deoxyribonucleic acid damage

ETHNOPHARMACOLOGICAL RELEVANCE

Fu Fang Gang Liu (FFGL) is an effective formula for treating wart proliferation caused by human papillomavirus (HPV) infection and has the potential to treat HPV-related cancers. However, scientific evidence of its anti-tumor activity against cervical cancer, the most common cancer caused by HPV, is lacking.

AIM OF THE STUDY

To clarify the anti-tumor effect of an FFGL aqueous extract on human cervical cancer and its possible mechanism of cell cycle arrest in HeLa cells.

MATERIALS AND METHODS

The anti-proliferative effect of FFGL on cervical cancer cells was assessed using the cell counting kit-8 assay. The proportion of apoptotic cells, cell cycle distribution, and cell division rate were determined using flow cytometry. Quantitative proteomics was used to identify differentially expressed proteins after FFGL treatment, and bioinformatics analysis was used to identify key nodal proteins affected by FFGL. Immunofluorescence and western blot analyses were used to explore changes in the expression of related proteins in the cell cycle and DNA damage pathways to elucidate the potential mechanism of action of FFGL against HeLa cell proliferation.

RESULTS

FFGL inhibited cervical cancer cell proliferation and caused cell cycle arrest. According to quantitative proteomics, CyclinB1 may play an important role in the anti-proliferative effect of FFGL on HeLa cells. Additional experiments showed that FFGL aqueous extract caused ATM-mediated DNA damage, further phosphorylated CHK2, led to the inactivation of Cdc25C, inhibited the activity of the CDK1/CyclinB1 complex, and resulted in cell cycle arrest.

CONCLUSIONS

FFGL can inhibit cervical cancer cell proliferation. Furthermore, it can increase CDK1 phosphorylation, block the cell cycle by causing DNA damage, and inhibit HeLa cell proliferation.

Prognostic Value and Immune Infiltration of HPV-Related Genes in the Immune Microenvironment of Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Mounting evidence has highlighted the immune environment as a critical feature in the development of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). However, the relationship between the clinical characteristics of the immune environment and CESC remain unclear. Therefore, the aim of this study was to further characterize the relationship between the tumor and immune microenvironment and the clinical features of CESC using a variety of bioinformatic methods. Expression profiles (303 CESCs and three control samples) and relevant clinical data were obtained from The Cancer Genome Atlas. We divided CESC cases into different subtypes and performed a differential gene expression analysis. In addition, gene ontology (GO) and gene set enrichment analysis (GSEA) were performed to identify potential molecular mechanisms. Furthermore, data from 115 CESC patients from East Hospital were used to help identify the relationship between the protein expressions of key genes and disease-free survival using tissue microarray technology. Cases of CESC (n = 303) were divided into five subtypes (C1-C5) based on their expression profiles. A total of 69 cross-validated differentially expressed immune-related genes were identified. Subtype C4 demonstrated a downregulation of the immune profile, lower tumor immune/stroma scores, and worse prognosis. In contrast, the C1 subtype showed an upregulation of the immune profile, higher tumor immune/stroma scores, and better prognosis. A GO analysis suggested that changes in CESC were primarily enriched nuclear division, chromatin binding, and condensed chromosomes. In addition, GSEA demonstrated that cellular senescence, the p53 signaling pathway, and viral carcinogenesis are critical features of CESC. Moreover, high FOXO3 and low IGF-1 protein expression were closely correlated with decreased clinical prognosis. In summary, our findings provide novel insight into the relationship between the immune microenvironment and CESC. As such, our results may provide guidance for developing potential immunotherapeutic targets and biomarkers for CESC.

CDK1 bridges NF-κB and β-catenin signaling in response to H. pylori infection in gastric tumorigenesis

Infection with Helicobacter pylori (H. pylori) is the main risk factor for gastric cancer, a leading cause of cancer-related death worldwide. The oncogenic functions of cyclin-dependent kinase 1 (CDK1) are not fully understood in gastric tumorigenesis. Using public datasets, quantitative real-time PCR, western blot, and immunohistochemical (IHC) analyses, we detect high levels of CDK1 in human and mouse gastric tumors. H. pylori infection induces activation of nuclear factor κB (NF-κB) with a significant increase in CDK1 in in vitro and in vivo models (p < 0.01). We confirm active NF-κB binding sites on the CDK1 promoter sequence. CDK1 phosphorylates and inhibits GSK-3β activity through direct binding with subsequent accumulation and activation of β-catenin. CDK1 silencing or pharmacologic inhibition reverses these effects and impairs tumor organoids and spheroid formation. IHC analysis demonstrates a positive correlation between CDK1 and β-catenin. The results demonstrate a mechanistic link between infection, inflammation, and gastric tumorigenesis where CDK1 plays a critical role.

Methanolic neem (Azadirachta indica) stem bark extract induces cell cycle arrest, apoptosis and inhibits the migration of cervical cancer cells in vitro

Background

Cervical cancer remains one of the significant causes of mortality in women due to the limitations of current treatment strategies and their associated side effects. Investigation of alternative medicine, including phytomedicine, has shown effective anti-cancer potential with fewer side effects. Azadirachta indica (commonly known as neem) is known for its medicinal properties. The present study investigated the anti-cancer potential of methanolic neem stem bark extract (MNBE) against cervical cancer using HeLa, SiHa, and ME-180 cell lines.

Methods

Cytotoxic effect of MNBE on cultured cell lines was evaluated by MTT and clonogenic assay. The growth-inhibiting effect of MNBE was further confirmed by performing cell cycle analysis and apoptosis assay using flow cytometry. The anti-migratory effect of MNBE was evaluated by using wound healing and Boyden chamber assay. Real-time PCR was used to determine the mRNA expression, and western blot and flow cytometry was used to determine the protein levels of growth and migration-related genes.

Results

MNBE significantly suppressed the growth and survival of cervical cancer cells in a dose-dependent manner by inducing cell cycle arrest and apoptosis. In addition, the growth inhibitory effect of MNBE was specific to cervical cancer cells than normal cells. Cell cycle arrest was correlated to transcriptional downregulation of cyclin dependent kinase 1 (CDK1), cyclin A, and cyclin B. Additionally, MNBE treatment resulted in the upregulation of active caspase-3 protein and downregulation of prosurvival genes, Bcl2, and survivin at mRNA level and NFkB-p65 at the protein level. Furthermore, MNBE inhibited the migration of cervical cancer cells accompanied by modulation of migration-related genes, including zona occludens-1 (ZO-1), matrix metalloproteinase 2 (MMP2), focal adhesion kinase (FAK), N-cadherin, snail, and E-cadherin.

Conclusion

In summary, the present study provides the first evidence of MNBE in restricting cervical cancer cell growth and migration, which warrants further investigation for developing novel anti-cancer drugs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03718-7.

Identification of Novel Multi-Omics Expression Landscapes and Meta-Analysis of Landscape-Based Competitive Endogenous RNA Networks in ALDH+ Lung Adenocarcinoma Stem Cells

ALDH+ H1975 lung adenocarcinoma stem cells (LSCs) are a rare cell population identified in lung adenocarcinoma (LUAD). LSCs can self-renew, drive tumor initiation, growth, metastasis, and recurrence and are also the predominant cause of poor prognosis due to their intrinsic resistance to drugs and chemotherapy. Consequently, LSCs are a promising target for LUAD therapy. Noncoding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), exert many significant regulatory functions in the pathogenesis of human cancers, showing the necessity for a comprehensive understanding of the mechanisms that underlie lung carcinogenesis. Nonetheless, research on many known transcripts and messenger RNAs (mRNAs) has already generated new information. Unknown biomarkers in ncRNAs and systematic and comprehensive interrelation with unknown ncRNAs and mRNAs may provide further insights into the biology of LUAD. Herein, a set of novel ncRNAs that include miRNAs, lncRNAs, and circRNAs were identified, and differentially expressed patterns of ncRNAs and mRNAs in LSCs and ALDH-H1975 LUAD tumor cells (LTCs) were obtained using stringent bioinformatics pipelines. Through a meta-analysis of the identified landscapes, novel competitive endogenous RNA (ceRNA) networks were constructed to reveal the potential molecular mechanisms that regulate the hallmarks of LSCs and LTCs. This study presents a summary of novel ncRNAs and the fundamental roles of differentially expressed ncRNAs implicated in the activity of LSCs and LTCs. In addition, the study also provides a comprehensive resource for the future identification of diagnostic, therapeutic, and prognostic biomarkers in LUAD.

Comprehensive Analysis of circRNA Expression Profiles During Cervical Carcinogenesis

Circular RNAs (circRNAs) are regulatory molecules that participate in the occurrence, development and progression of tumors. To obtain a complete blueprint of cervical carcinogenesis, we analyzed the temporal transcriptomic landscapes of mRNAs and circRNAs. Microarrays were performed to identify the circRNA and mRNA expression profiles of cervical squamous cell carcinoma (CSCC) and high-grade squamous intraepithelial lesion (HSIL) patients compared with normal controls (NC). Short time-series expression miner (STEM) was utilized to characterize the time-course expression patterns of circRNAs and mRNAs from NC to HSIL and CSCC. A total of 3 circRNA profiles and 3 mRNA profiles with continuous upregulated patterns were identified and selected for further analysis. Furthermore, functional annotation showed that the mRNAs were associated with DNA repair and cell division. The protein-protein interaction (PPI) network analysis revealed that the ten highest-degree genes were considered to be hub genes. Subsequently, a competing endogenous RNA (ceRNA) network analysis and real-time PCR validation indicated that hsa_circ_0001955/hsa-miR-6719-3p/CDK1, hsa_circ_0001955/hsa-miR-1277-5p/NEDD4L and hsa_circ_0003954/hsa-miR-15a-3p/SYCP2 were highly correlated with cervical carcinogenesis. Silencing of hsa_circ_0003954 inhibited SiHa cell proliferation and perturb the cell cycle in vitro. This study provides insight into the molecular events regulating cervical carcinogenesis, identifies functional circRNAs in CSCC, and improves the understanding of the pathogenesis and molecular biomarkers of CSCC and HSIL.

MiR-495-3p and miR-143-3p co-target CDK1 to inhibit the development of cervical cancer

PURPOSE

The GEO database and KEGG database-based analyses identified the differential expression of cyclin-dependent kinase 1 (CDK1) in cervical cancer and its involvement in the cell cycle pathway. In the present study, we aim to clarify the role of CDK1 in cervical cancer and the function of upstream microRNA (miR)-143-3p/miR-495-3p.

METHODS

The expression of miR-143-3p, miR-495-3p, and CDK1 in cervical cancer tissues and cells was determined using RT-qPCR. Cell bioactivities were examined by CCK-8 and flow cytometry. The binding affinity between CDK1 and miR-143-3p/miR-495-3p was investigated using dual luciferase gene reporter assay. A xenograft mouse model of cervical cancer was then established to explore their effect on the tumorigenicity of cervical cancer cells in vivo.

RESULTS

CDK1 was found to be the common target gene of miR-143-3p and miR-495-3p. CDK1 overexpression occurred in cervical cancer tissues and cells, while expression of miR-495-3p and miR-143-3p was down-regulated. The viability was inhibited while the apoptosis was promoted in cervical cancer cells in response to miR-143-3p or miR-495-3p overexpression, or CDK1 silencing. Further, miR-143-3p or miR-495-3p overexpression was also substantiated to inhibit the tumorigenicity of cervical cancer cells in vivo, while CDK1 overexpression counteracted their effect.

CONCLUSION

Taken together, miR-143-3p and miR-495-3p co-target CDK1, thereby inhibiting the occurrence and development of cervical cancer.

Identification of potential core genes in esophageal carcinoma using bioinformatics analysis

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a common human malignancy worldwide. The tumorigenesis mechanism in ESCC is unclear.

MATERIALS AND METHODS

To explore potential therapeutic targets for ESCC, we analyzed 3 microarray datasets (GSE20347, GSE38129, and GSE67269) derived from the gene expression omnibus (GEO) database. Then, the GEO2R tool was used to screen out differently expressed genes (DEGs) between ESCC and normal tissue. Gene ontology function and kyoto encyclopedia of genes and genomes pathway enrichment analysis were performed using the database for annotation, visualization and integrated discovery to identify the pathways and functional annotation of DEGs. Protein-protein interaction of these DEGs was analyzed based on the search tool for the retrieval of interacting genes database and visualized by Cytoscape software. In addition, we used encyclopedia of RNA interactomes (ENCORI), gene expression profiling interactive analysis (GEPIA), and the human protein atlas to confirm the expression of hub genes in ESCC. Finally, GEPIA was used to evaluate the prognostic value of hub genes expression in ESCC patients and we estimated the associations between hub genes expression and immune cell populations (B Cell, CD8+ T Cell, CD4+ T Cell, Macrophage, Neutrophil, and Dendritic Cell) in esophageal carcinoma (ESCA) using tumor immune estimation resource (TIMER).

RESULTS

In this study, 707 DEGs (including 385 upregulated genes and 322 downregulated genes) and 6 hub genes (cyclin B1 [CCNB1], cyclin dependent kinase 1 [CDK1], aurora kinase A [AURKA], ubiquitin conjugating enzyme E2C [UBE2C], cyclin A2 [CCNA2], and cell division cycle 20 [CDC20]) were identified. All of the 6 hub genes were highly expressed in ESCC tissues. Among of them, only CCNB1 and CDC20 were associated with stage of ESCC and all of them were not associated with survival time of patients.

CONCLUSION

DEGs and hub genes were confirmed in our study, providing a thorough, scientific and comprehensive research goals for the pathogenesis of ESCC.

Bioinformatics analysis of differentially expressed genes and pathways in the development of cervical cancer

Background

This study aimed to explore and identify key genes and signaling pathways that contribute to the progression of cervical cancer to improve prognosis.

Methods

Three gene expression profiles (GSE63514, GSE64217 and GSE138080) were screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were screened using the GEO2R and Venn diagram tools. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Gene set enrichment analysis (GSEA) was performed to analyze the three gene expression profiles. Moreover, a protein–protein interaction (PPI) network of the DEGs was constructed, and functional enrichment analysis was performed. On this basis, hub genes from critical PPI subnetworks were explored with Cytoscape software. The expression of these genes in tumors was verified, and survival analysis of potential prognostic genes from critical subnetworks was conducted. Functional annotation, multiple gene comparison and dimensionality reduction in candidate genes indicated the clinical significance of potential targets.

Results

A total of 476 DEGs were screened: 253 upregulated genes and 223 downregulated genes. DEGs were enriched in 22 biological processes, 16 cellular components and 9 molecular functions in precancerous lesions and cervical cancer. DEGs were mainly enriched in 10 KEGG pathways. Through intersection analysis and data mining, 3 key KEGG pathways and related core genes were revealed by GSEA. Moreover, a PPI network of 476 DEGs was constructed, hub genes from 12 critical subnetworks were explored, and a total of 14 potential molecular targets were obtained.

Conclusions

These findings promote the understanding of the molecular mechanism of and clinically related molecular targets for cervical cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08412-4.

SNX10 and PTGDS are associated with the progression and prognosis of cervical squamous cell carcinoma

Background

Cervical cancer (CC) is the primary cause of death in women. This study sought to investigate the potential mechanism and prognostic genes of CC.

Methods

We downloaded four gene expression profiles from GEO. The RRA method was used to integrate and screen differentially expressed genes (DEGs) between CC and normal samples. Functional analysis was performed by clusterprofiler. We built PPI network by Search Tool for the Retrieval of Interacting Genes Database (STRING) and selected hub modules via Molecular COmplex Detection (MCODE). CMap database was used to find molecules with therapeutic potential for CC. The hub genes were validated in GEO datasets, Gene Expession Profiling Interactive Analysis (GEPIA), immunohistochemistry, Cox regression analysis, TCGA methylation analysis and ONCOMINE were carried out. ROC curve analysis and GSEA were also performed to describe the prognostic significance of hub genes.

Results

Functional analysis revealed that 147 DEGs were significantly enriched in binding, cell proliferation, transcriptional activity and cell cycle regulation. PPI network screened 30 hub genes, with CDK1 having the strongest connectivity with CC. Cmap showed that apigenin, thioguanine and trichostatin A might be used to treat CC(P < 0.05). Eight genes (APOD, CXCL8, MMP1, MMP3, PLOD2, PTGDS, SNX10 and SPP1) were screened out through GEPIA. Of them, only PTGDS and SNX10 had not appeared in previous studies about CC. The validation in GEO showed that PTGDS showed low expression while SNX10 presented high expression in tumor tissues. Their expression profiles were consistent with the results in immunohistochemistry. ROC curve analysis indicated that the model had a good diagnostic efficiency (AUC = 0.738). GSEA analysis demonstrated that the two genes were correlated with the chemokine signaling pathway (P < 0.05). TCGA methylation analysis showed that patients with lowly-expressed and highly-methylated PTGDS had a worse prognosis than those with highly-expressed and lowly-methylated PTGDS (p = 0.037). Cox regression analysis showed that SNX10 and PTGDS were independent prognostic indicators for OS among CC patients (P = 0.007 and 0.003).

Conclusions

PTGDS and SNX10 showed abnormal expression and methylation in CC. Both genes might have high prognostic value of CC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08212-w.

Glucocappasalin Induces G2/M-Phase Arrest, Apoptosis, and Autophagy Pathways by Targeting CDK1 and PLK1 in Cervical Carcinoma Cells

Glucocappasalin (GCP), a natural product derived from the seeds of Descurainia sophia (L.) Webb. ex Prantl, exhibits potential antitumor activity in HeLa cervical carcinoma cells. In this study, we investigated the anti-cervical cancer property of GCP through the induction of cell cycle arrest, apoptosis, and autophagy in vitro and in vivo, and elucidated the underlying molecular mechanisms. We demonstrated that treatment with GCP inhibited the growth of HeLa, Siha, and Ca Ski cell lines in a dose-dependent manner, with HeLa cells displaying particular sensitivity to the GCP treatment. Subsequently, the expression of cyclin-dependent kinase 1 (CDK1) and polo like kinase 1 (PLK1) were evaluated in HeLa cells using the CDK1 kinase assay kit, the fluorescence polarization assay, real-time quantitative PCR, and western blotting. Our results demonstrate that GCP could be employed to attenuate the expression of CDK1 and PLK1 in a dose- and time-dependent manner. The complementary results obtained by flow cytometry and western blotting allowed us to postulate that GCP may exhibit its antitumor effects by inducing G2/M cell cycle arrest. Moreover, HeLa cells treated with GCP exhibited a loss in mitochondrial membrane potential, together with the activation of caspases 3 and 9, and poly ADP-ribose polymerase (PARP). Additionally, we found that GCP could increase the formation of acidic vesicular organelles (AVOs), as well as the levels of Beclin1, LC3-II, p62, and Atg5 proteins in HeLa cells. Further studies indicated that GCP triggered autophagy via the suppression of the PI3K/AKT/mTOR signaling pathways. The autophagy inhibitor 3-methyladenine (3-MA) was used to determine whether autophagy affects the apoptosis induced by GCP. Interestingly, the inhibition of autophagy attenuated apoptosis. In vivo anti-tumor experiments indicated that GCP (60 mg/kg, i.p.) markedly reduced the growth of HeLa xenografts in nude mice without apparent toxicity. Taken together, we demonstrate that GCP induces cell cycle G2/M-phase arrest, apoptosis, and autophagy by acting on the PI3K/AKT/mTOR signaling pathways in cervical carcinoma cells. Thus, GCP may represent a promising agent in the eradication of cervical cancer.

The dysregulation of microarray gene expression in cervical cancer is associated with overexpression of a unique messenger RNA signature

Background and Objectives:

Human papillomavirus (HPV) is the fourth most common cause of cervical cancer (CC). The aim of the present study was to investigate gene expression levels of previously identified transcriptional signatures for malignant and non-malignant CC.

Materials and Methods:

To validate of previously analyzed microarray gene expression data, we selected two hub genes (CDK1 and PLK1) and four differentially expressed mRNAs that were common in pre-malignant-normal and malignant-pre-malignant networks (SMS, NNT, UHMK1 and DEPDC1). To this purpose, the study included women diagnosed histologically with malignant CC (n=15), pre-malignant (n=15), and normal subjects (n=15). The expression of six host genes and viral E6/E7 genes were measured by quantitative Real-Time PCR.

Results:

The results showed higher expression of CDK1/PLK1 hub genes and SMS, NNT and UHMK1 genes in malignant CC group than non-malignant CC group and normal group. A positive correlation was observed between gene expression of viral E6/E7 oncogenes and UHMK1 gene.

Conclusion:

Dysregulation of several mRNA signatures are a common feature of CC and can be potentially used as diagnostic and prognostic biomarkers as well as can be applied to therapeutic targets for CC treatment.

Identification of key genes and pathways in endometriosis by integrated expression profiles analysis

The purpose of this study was to integrate the existing expression profile data on endometriosis (EM)-related tissues in order to identify the differentially expressed genes. In this study, three series of raw expression data were downloaded from GEO database. Differentially expressed genes (DEGs) in three tissue types were screened. GO, KEGG pathway enrichment analysis, core differential genes (CDGs) protein–protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA) were performed, finally, the dysregulation of Hippo pathway in ectopic endometrium (EC) was detected by Western blotting. A total of 1,811 DEGs between eutopic (EU) and normal endometrium (NE), 5,947 DEGs between EC and EU, and 3,192 DEGs between EC and NE datasets were identified. After screening, 394 CDGs were obtained, and 5 hub genes identified in the PPI network. CDGs enrichment and WGCNA network analysis revealed cell proliferation, differentiation, migration and other biological processes, Hippo and Wnt signaling pathways, and a variety of tumor-related pathways. Western blotting results showed that YAP/TAZ was upregulated, and MOB1, pMOB1, SAV1, LATS1 and LATS2 were downregulated in EC. Moreover, CDGs, especially the hub genes, are potential biomarkers and therapeutic targets. Finally, the Hippo pathway might play a key role in the development of endometriosis.

Identification of candidate aberrantly methylated and differentially expressed genes in Esophageal squamous cell carcinoma

Aberrant methylated genes (DMGs) play an important role in the etiology and pathogenesis of esophageal squamous cell carcinoma (ESCC). In this study, we aimed to integrate three cohorts profile datasets to ascertain aberrant methylated-differentially expressed genes and pathways associated with ESCC by comprehensive bioinformatics analysis. We downloaded data of gene expression microarrays (GSE20347, GSE38129) and gene methylation microarrays (GSE52826) from the Gene Expression Omnibus (GEO) database. Aberrantly differentially expressed genes (DEGs) were obtained by GEO2R tool. The David database was then used to perform Gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome pathway enrichment analyses on selected genes. STRING and Cytoscape software were used to construct a protein-protein interaction (PPI) network, then the modules in the PPI networks were analyzed with MCODE and the hub genes chose from the PPI networks were verified by Oncomine and TCGA database. In total, 291 hypomethylation-high expression genes and 168 hypermethylation-low expression genes were identified at the screening step, and finally found six mostly changed hub genes including KIF14, CDK1, AURKA, LCN2, TGM1, and DSG1. Pathway analysis indicated that aberrantly methylated DEGs mainly associated with the P13K-AKT signaling, cAMP signaling and cell cycle process. After validation in multiple databases, most hub genes remained significant. Patients with high expression of AURKA were associated with shorter overall survival. To summarize, we have identified six feasible aberrant methylated-differentially expressed genes and pathways in ESCC by bioinformatics analysis, potentially providing valuable information for the molecular mechanisms of ESCC. Our data combined the analysis of gene expression profiling microarrays and gene methylation profiling microarrays, simultaneously, and in this way, it can shed a light for screening and diagnosis of ESCC in future.

Identification of Key Genes and Prognostic Value Analysis in Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

Emerging evidence indicates that various functional genes with altered expression are involved in the tumor progression of human cancers. This study is aimed at identifying novel key genes that may be used for hepatocellular carcinoma (HCC) diagnosis, prognosis, and targeted therapy. This study included 3 expression profiles (GSE45267, GSE74656, and GSE84402), which were obtained from the Gene Expression Omnibus (GEO). GEO2R was used to analyze the differentially expressed genes (DEGs) between HCC and normal samples. The functional and pathway enrichment analysis was performed by the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of the identified DEGs was constructed using the Search Tool for the Retrieval of Interacting Gene, and hub genes were identified. ONCOMINE and CCLE databases were used to verify the expression of the hub genes in HCC tissues and cells. Kaplan-Meier plotter was used to assess the effects of the hub genes on the overall survival of HCC patients. A total of 99 DEGs were identified from the 3 expression profiles. These DEGs were enriched with functional processes and pathways related to HCC pathogenesis. From the PPI network, 5 hub genes were identified. The expression of the 5 hub genes was all upregulated in HCC tissues and cells compared with the control tissues and cells. Kaplan-Meier survival curves indicated that high expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), cyclin B2 (CCNB2), MAD2 mitotic arrest deficient-like 1 (MAD2L1), and topoisomerase IIα (TOP2A) predicted poor overall survival in HCC patients (all log-rank P < 0.01). These results revealed that the DEGs may serve as candidate key genes during HCC pathogenesis. The 5 hub genes, including CDK1, CCNB1, CCNB2, MAD2L1, and TOP2A, may serve as promising prognostic biomarkers in HCC.

Prediction of a miRNA-mRNA functional synergistic network for cervical squamous cell carcinoma

Cervical squamous cell carcinoma (CSCC) accounts for a significant proportion of cervical cancer; thus, there is a need for novel and noninvasive diagnostic biomarkers for this malignancy. In this study, we performed integrated analysis of a dataset from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between CSCC, cervical intraepithelial neoplasia (CIN) and healthy control subjects. We further established protein-protein interaction and DEmiRNA-target gene interaction networks, and performed functional annotation of the target genes of DEmiRNAs. In total, we identified 1375 DEGs and 19 DEmiRNAs in CIN versus normal control, and 2235 DEGs and 33 DEmiRNAs in CSCC versus CIN by integrated analysis. Our protein-protein interaction network indicates that the common DEGs, Cyclin B/cyclin-dependent kinase 1 (CDK1), CCND1, ESR1 and Aurora kinase A (AURKA), are the top four hub genes. P53 and prostate cancer were identified as significantly enriched signaling pathways of common DEGs and DEmiRNA targets, respectively. We validated that expression levels of three DEGs (TYMS, SASH1 and CDK1) and one DEmiRNA of hsa-miR-99a were altered in blood samples of patients with CSCC. In conclusion, a total of four DEGs (TYMS, SASH1, CDK1 and AURKA) and two DEmiRNAs (hsa-miR-21 and hsa-miR-99a) may be involved in the pathogenesis of CIN and the progression of CIN into CSCC. Of these, TYMS is predicted to be regulated by hsa-miR-99a and SASH1 to be regulated by hsa-miR-21.

Integrated analysis of circular RNA-associated ceRNA network in cervical cancer: Observational Study

BACKGROUND

Circular RNAs (circRNAs) have displayed dysregulated expression in several types of cancer. Nevertheless, their function and underlying mechanisms in cervical cancer remains largely unknown. This study aimed to describe the regulatory mechanisms in cervical cancer.

METHODS

We downloaded the circRNAs expression profiles from Gene Expression Omnibus database, and RNAs expression profiles from The Cancer Genome Atlas database. We established a circRNA-miRNA-mRNA and circRNA-miRNA-hubgene network. The interactions between proteins were analyzed using the STRING database and hubgenes were identified using MCODE plugin. Then, we conducted a circRNA-miRNA-hubgenes regulatory module. Functional and pathway enrichment analyses were conducted using R packages "Clusterprofile".

RESULTS

Six circRNAs, 15 miRNAs, and 158 mRNAs were identified to construct the ceRNA network of cervical cancer. PPI (protein-protein interaction) network and module analysis identified 7 hubgenes. Then, a circRNA-miRNA-hubgene subnetwork was constructed based on the 1 DEcircRNAs, 3 DEmiRNAs, and 3 DEmRNAs. The KEGG pathway analysis indicated DEmRNAs are involved in progesterone-mediated oocyte maturation, cell cycle, and oocyte meiosis.

CONCLUSION

These ceRNAs are critical in the pathogenesis of cervical and may serve as future therapeutic biomarkers.

Bioinformatics prediction and analysis of hub genes and pathways of three types of gynecological cancer

Cervical, endometrial and vulvar cancer are three common types of gynecological tumor that threaten the health of females worldwide. Since their underlying mechanisms and associations remain unclear, a comprehensive and systematic bioinformatics analysis is required. The present study downloaded GSE63678 from the GEO database and then performed functional enrichment analyses, including gene ontology and pathway analysis. To further investigate the molecular mechanisms underlying the three types of gynecological cancer, protein-protein interaction (PPI) analysis was performed. A biological network was generated with the guidance of the Kyoto Encyclopedia of Genes and Genomes database and was presented in Cytoscape. A total of 1,219 DEGs were identified for the three types of cancer, and 25 hub genes were revealed. Pathway analysis and the PPI network indicated that four main types of pathway participate in the mechanism of gynecological cancer, including viral infections and cancer formation, tumorigenesis and development, signal transduction, and endocrinology and metabolism. A preliminary gynecological cancer biological network was constructed. Notably, following all analysis, the phosphoinositide 3-kinase (PI3K)/Akt pathway was identified as a potential biomarker pathway. Seven pivotal hub genes (CCNA2, CDK1, CCND1, FGF2, IGF1, BCL2 and VEGFA) of the three gynecological cancer types were proposed. The seven hub genes may serve as targets in gynecological cancer for prevention and early intervention. The PI3K/Akt pathway was identified as a critical biomarker of the three types of gynecological cancer, which may serve a role in the pathogenesis. In summary, the present study provided evidence that could support the treatment of gynecologic tumors in the future.

Identification of Key Genes and Pathways in Cervical Cancer by Bioinformatics Analysis

Cervical cancer is a common malignant tumour of the female reproductive system that seriously threatens the health of women. The aims of this study were to identify key genes and pathways and to illuminate new molecular mechanisms underlying cervical cancer. Altogether, 1829 DEGs were identified, including 794 significantly down-regulated DEGs and 1035 significantly up-regulated DEGs. GO analysis suggested that the up-regulated DEGs were mainly enriched in mitotic cell cycle processes, including DNA replication, organelle fission, chromosome segregation and cell cycle phase transition, and that the down-regulated DEGs were primarily enriched in development and differentiation processes, such as tissue development, epidermis development, skin development, keratinocyte differentiation, epidermal cell differentiation and epithelial cell differentiation. KEGG pathway analysis showed that the DEGs were significantly enriched in cell cycle, DNA replication, the p53 signalling pathway, pathways in cancer and oocyte meiosis. The top 9 hub genes with a high degree of connectivity (over 72 in the PPI network) were down-regulated TSPO, CCND1, and FOS and up-regulated CDK1, TOP2A, CCNB1, PCNA, BIRC5 and MAD2L1. Module analysis indicated that the top 3 modules were significantly enriched in mitotic cell cycle, DNA replication and regulation of cell cycle (P < 0.01). The heat map based on TCGA database preliminarily demonstrated the expression change of the key genes in cervical cancer. GSEA results were basically coincident with the front enrichment analysis results. By comprehensive analysis, we confirmed that cell cycle was a key biological process and a critical driver in cervical cancer. In conclusion, this study identified DEGs and screened the key genes and pathways closely related to cervical cancer by bioinformatics analysis, simultaneously deepening our understanding of the molecular mechanisms underlying the occurrence and progression of cervical cancer. These results might hold promise for finding potential therapeutic targets of cervical cancer.

Novel Genomic Biomarker Candidates for Cervical Cancer As Identified by Differential Co-Expression Network Analysis

Cervical cancer is the second most common malignancy and the third reason for mortality among women in developing countries. Although infection by the oncogenic human papilloma viruses is a major cause, genomic contributors are still largely unknown. Network analyses, compared with candidate gene studies, offer greater promise to map the interactions among genomic loci contributing to cervical cancer risk. We report here a differential co-expression network analysis in five gene expression datasets (GSE7803, GSE9750, GSE39001, GSE52903, and GSE63514, from the Gene Expression Omnibus) in patients with cervical cancer and healthy controls. Kaplan-Meier Survival and principle component analyses were employed to evaluate prognostic and diagnostic performances of biomarker candidates, respectively. As a result, seven distinct co-expressed gene modules were identified. Among these, five modules (with sizes of 9-45 genes) presented high prognostic and diagnostic capabilities with hazard ratios of 2.28-11.3, and diagnostic odds ratios of 85.2-548.8. Moreover, these modules were associated with several key biological processes such as cell cycle regulation, keratinization, neutrophil degranulation, and the phospholipase D signaling pathway. In addition, transcription factors ETS1 and GATA2 were noted as common regulatory elements. These genomic biomarker candidates identified by differential co-expression network analysis offer new prospects for translational cancer research, not to mention personalized medicine to forecast cervical cancer susceptibility and prognosis. Looking into the future, we also suggest that the search for a molecular basis of common complex diseases should be complemented by differential co-expression analyses to obtain a systems-level understanding of disease phenotype variability.

LncRNA CASC11 promoted gastric cancer cell proliferation, migration and invasion in vitro by regulating cell cycle pathway

In this study, we aimed to investigate the effects of lncRNA CASC11 on gastric cancer (GC) cell progression through regulating miR-340-5p and cell cycle pathway. Expressions of lncRNA CASC11 in gastric cancer tissues and cell lines were determined by qRT-PCR. Differentially expressed lncRNAs, mRNAs and miRNAs were screened through microarray analysis. The relationship among CASC11, CDK1 and miR-340-5p was predicted by TargetScan and validated through dual luciferase reporter assay. Western blot assay examined the protein level of CDK1 and several cell cycle regulatory proteins. GO functional analysis and KEGG pathway analysis were used to predict the association between functions and related pathways. Cell proliferation was determined by CCK-8 assays. Cell apoptosis and cell cycle were detected by flow cytometry assay. CASC11 was highly expressed in GC tissues and cell lines. Knockdown of CASC11 inhibited GC cell proliferation, promoted cell apoptosis and blocked cell cycle. KEGG further indicated an enriched cell cycle pathway involving CDK1. QRT-PCR showed that miR-340-5p was down-regulated in GC cells tissues, while CDK1 was up-regulated. Furthermore, CASC11 acted as a sponge of miR-340-5p which directly targeted CDK1. Meanwhile, miR-340-5p overexpression promoted GC cell apoptosis and induced cell cycle arrest, while CDK1 overexpression inhibited cell apoptosis and accelerated cell cycle. Our study revealed the mechanism of CASC11/miR-340-5p/CDK1 network in GC cell line, and suggested that CASC11 was a novel facilitator that exerted a biological effect by activating the cell cycle signaling pathway. This finding provides a potential therapeutic target for GC.

Bioinformatics approach reveals the key role of C‑X‑C motif chemokine receptor 2 in endometriosis development

Endometriosis is a common gynecological disease, affecting 6‑10% of women of reproductive age. The precise mechanisms underlying the development of endometriosis remain unclear. In the present study, a bioinformatics approach was applied to systematically identify the pathways and genes involved in the development of endometriosis and to discover potential biomarkers. The gene expression profiles of GSE6364, a microarray dataset of endometrial biopsies obtained from women with or without endometriosis, was downloaded from the Gene Expression Omnibus DataSets database that stores original submitter‑supplied records (series, samples and platforms), as well as curated datasets. Differentially expressed gene (DEG) analysis was performed with GEO2R. DAVID was used to analyze the gene ontology enrichment of the DEGs. Gene Set Enrichment Analysis (GSEA) was conducted using the GSEA v3.0 software. Protein‑protein interactions (PPI) were evaluated with the Search Tool for the Retrieval of Interacting Genes, and PPI network visualization was performed with Cytoscape. In addition, Cell Counting kit‑8 and Transwell assays were performed on human endometrial stromal cells (HESCs). A total of 172 DEGs were extracted. Inflammatory response genes were significantly upregulated in the endometriosis tissues and C‑X‑C motif chemokine receptor 2 (CXCR2), was one of the most up‑regulated genes according to DEG analysis. Cell‑based experiments confirmed that CXCR2 promoted the proliferation, migration and invasion of HESCs. In conclusion, a bioinformatics approach combined with in vitro experiments in the present study revealed that CXCR2 may be associated with the development of endometriosis and has potential as a biomarker for the diagnosis of endometriosis.

Identification of key pathways and genes in the progression of cervical cancer using bioinformatics analysis

The aim of the present study was to investigate the key pathways and genes in the progression of cervical cancer. The gene expression profiles GSE7803 and GSE63514 were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using GEO2R and the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery. The hub genes were identified using Cytoscape and protein-protein interaction (PPI) networks were constructed using the STRING database. A total of 127 and 99 DEGs were identified in the pre-invasive and invasive stages of cervical cancer, respectively. GO enrichment analysis indicated that the DEGs in pre-invasive cervical cancer were primarily associated with the ‘protein binding’, ‘single-stranded DNA-dependent ATPase activity’, ‘DNA replication origin binding’ and ‘microtubule binding’ terms, whereas the DEGs in invasive cervical cancer were associated with the ‘extracellular matrix (ECM) structural constituent’, ‘heparin binding’ and ‘integrin binding’. KEGG enrichment analysis revealed that the pre-invasive DEGs were significantly enriched in the ‘cell cycle’, ‘DNA replication’ and ‘p53 signaling pathway’ terms, while the invasive DEGs were enriched in the ‘amoebiasis’, ‘focal adhesion’, ‘ECM-receptor interaction’ and ‘platelet activation’ terms. The PPI network identified 4 key genes (PCNA, CDK2, VEGFA and PIK3CA), which were hub genes for pre-invasive and invasive cervical cancer. In conclusion, bioinformatics analysis identified 4 key genes in cervical cancer progression (PCNA, CDK2, VEGFA and PIK3CA), which may be potential biomarkers for differentiating normal cervical epithelial tissue from cervical cancer.

Network analysis revealed aurora kinase dysregulation in five gynecological types of cancer

Gene markers are crucial for cancer prognosis and treatment. Previous studies have placed greater emphasis on individual diagnostic genes, thereby ignoring systemic-level attributes across diseases. Female-specific cells namely, breast, endometrium, cervical, ovarian and vulvar cells are highly susceptible to cancer. To date, a limited number of molecular studies have been performed that evaluate common biological processes across gynecological types of cancer. Differentially expressed genes in breast, cervical, endometrial, vulvar and ovarian cancer were utilized to construct protein-protein interaction networks, and to identify a common module across the five cancer types. A single common module with 8 nodes and 26 edges was mined among the five cancer systems. In total, four hub genes were present across the five cancer gene sets. Genes in the common module were enriched for the common pathways and associated diseases. The aurora kinase pathway was revealed to be conserved across the five cancer types surveyed. The present study, therefore, revealed that the aurora kinase pathway has a crucial function in the pathogenesis of the five aforementioned gynecological types of cancer through cross-tumor conservation.