Dataset Information

Screening of Therapeutic Candidate Genes of Quercetin for Cervical Cancer and Analysis of Their Regulatory Network.

ABSTRACT:

Purpose

To explore the therapeutic targets and regulatory mechanisms of the antitumor drug quercetin in the treatment of cervical cancer.

Methods

Cervical cancer (HeLa) cells were treated with quercetin and subjected to RNA sequencing using the BGISEQ-500 platform. By combined analysis of GEO database and RNA-seq results, the differentially expressed genes (DEGs) (namely, the genes in the GEO database that were upregulated/downregulated in cervical cancer compared with normal cervix and downregulated/upregulated after quercetin treatment) were identified. Functional enrichment and protein-protein interaction analyses were carried out for the DEGs. The candidate genes were identified using the Gentiscape2.2 and MCODE plug-ins for Cytoscape software, and the upstream miRNAs, lncRNAs, and circRNAs of the candidate genes were predicted using the online tools MirDIP, TarBase, and ENCORI. Finally, the regulatory network was constructed using Cytoscape software.

Results

Quercetin significantly inhibited the proliferation of cervical cancer cells. The combined analyses of the GEO database and RNA-seq results obtained 74 DEGs, and the functional enrichment analysis of the DEGs identified 861 biological processes, 32 cellular components, 50 molecular functions, and 56 KEGG pathways. Five therapeutic candidate genes, including EGFR, JUN, AR, CD44, and MUC1, were selected, and 10 miRNAs, 1 lncRNA, and 71 circRNAs upstream of these genes were identified. Finally, a lncRNA/circRNA-miRNA-mRNA-pathway regulatory network was constructed.

Conclusion

In this study, data mining was used to identify candidate genes and their regulatory network for the treatment of cervical cancer to provide a theoretical basis for targeted therapy of cervical cancer.

SUBMITTER: Li Y

PROVIDER: S-EPMC7873026 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Screening of Therapeutic Candidate Genes of Quercetin for Cervical Cancer and Analysis of Their Regulatory Network.

Li Yuanyuan Y Kou Jiushe J Wu Tao T Zheng Pengsheng P Chao Xu X

OncoTargets and therapy 20210205

<h4>Purpose</h4>To explore the therapeutic targets and regulatory mechanisms of the antitumor drug quercetin in the treatment of cervical cancer.<h4>Methods</h4>Cervical cancer (HeLa) cells were treated with quercetin and subjected to RNA sequencing using the BGISEQ-500 platform. By combined analysis of GEO database and RNA-seq results, the differentially expressed genes (DEGs) (namely, the genes in the GEO database that were upregulated/downregulated in cervical cancer compared with normal cerv ...[more]

PMID: 33574679

Similar Datasets

Project description:BackgroundCurrently, there are no efficient therapies for Alzheimer's disease (AD) among the elderly, although it is the most common etiology of dementia among the elderly. Quercetin, which has a variety of therapeutic properties, may pave the way for novel approaches to AD treatment. In the AD patients' frontal cortex, current study aims to identify the potential mechanisms of quercetin's pharmacological targets.Materials and methodsThe pharmacological targets of quercetin have been studied from DrugBank and SwissTarget. In order to distinguish AD-associated genes targeted by quercetin (Q-ADGs), we utilized an integrated intersection of gene expressions of the frontal cortex in combination with transcriptome analysis. To detect cortex-related Q-ADGs and immune-related Q-ADGs, a drug screening database and the immune infiltration analysis was utilized. The Q-ADGs were then linked with the AD severity scores (MMSE scores) to find severity-associated Q-ADGs. In addition, the miRNA-seq datasets were examined to identify severity-associated Q-ADG-miRNAs. Twelve genes, more frequently related to AD by previous studies among all the genes identified in the present study, were subjected to the verification of qRT-PCR in AD cell model.ResultsIn the frontal lobe of AD, 207 Q-ADGs were discovered and found that axonogenesis, glial differentiation, and other biological processes had been enriched. There were 155 immune-related Q-ADGs (e.g., COX2, NOS2, HMGB1) and 65 cortex-related Q-ADGs (e.g., FOXO1, CXCL16, NOTCH3). Sixteen Q-ADGs (e.g., STAT3, RORA, BCL6) and 28 miRNAs (e.g., miR-142-5p, miR-17-5p) were found to be related to MMSE scores. In the qRT-PCR results, six out of twelve genes were significantly regulated by quercetin. DYRK1A, FOXO1, NOS2, NGF, NQO1, and RORA genes were novel target of quercetin in AD. DYRK1A, NOS2, and NQO1 genes targeted by quercetin have benefits in the treatment of AD. However, FOXO1, NGF, and RORA genes targeted by quercetin might have a negative impact on AD.ConclusionThe role of quercetin in AD appears to be multifaceted, and it can affect patients' frontal cortex in a variety of pathways, such as axonogenesis, immune infiltration, and glial cell differentiation. DYRK1A, NOS2, and NQO1 might be potential novel effective drug targets for quercetin in AD.

Project description:PurposesCervical cancer (CC) is one of the highest frequently occurred malignant gynecological tumors with high rates of morbidity and mortality. Here, we aimed to identify significant genes associated with poor outcome. Materials and methods. Differentially expressed genes (DEGs) between CC tissues and normal cervical tissues were picked out by GEO2R tool and Venn diagram software. Database for Annotation, Visualization and Integrated Discovery (DAVID) was performed to analyze gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway. The protein-protein interactions (PPIs) of these DEGs were visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). Afterwards, Kaplan-Meier analysis was applied to analyze the overall survival among these genes. The Gene Expression Profiling Interactive Analysis (GEPIA) was applied for further validation of the expression level of these genes.ResultsThe mRNA expression profile datasets of GSE63514, GSE27678, and GSE6791 were downloaded from the Gene Expression Omnibus database (GEO). In total, 76 CC tissues and 35 normal tissues were collected in the three profile datasets. There were totally 73 consistently expressed genes in the three datasets, including 65 up-regulated genes and 8 down-regulated genes. Of PPI network analyzed by Molecular Complex Detection (MCODE) plug-in, all 65 up-regulated genes and 4 down-regulated genes were selected. The results of the Kaplan-Meier survival analysis showed that 3 of the 65 up-regulated genes had a significantly worse prognosis, while 3 of the 4 down-regulated genes had a significantly better outcome. For validation in GEPIA, 4 of 6 genes (PLOD2, ANLN, AURKA, and AR) were confirmed to be significantly deregulated in CC tissues compared to normal tissues.ConclusionWe have identified three up-regulated (PLOD2, ANLN, and AURKA) and a down-regulated DEGs (AR) with poor prognosis in CC on the basis of integrated bioinformatical methods, which could be regarded as potential therapeutic targets for CC patients.

Project description:Most physiological processes in mammals are temporally regulated by means of a master circadian clock in the brain and peripheral oscillators in most other tissues. A transcriptional-translation feedback network of clock genes produces near 24 h oscillations in clock gene and protein expression. Here, we aim to identify novel additions to the clock network using a meta-analysis of public chromatin immunoprecipitation sequencing (ChIP-seq), proteomics and protein-protein interaction data starting from a published list of 1000 genes with robust transcriptional rhythms and circadian phenotypes of knockdowns.We identified 20 candidate genes including nine known clock genes that received significantly high scores and were also robust to the relative weights assigned to different data types. Our scoring was consistent with the original ranking of the 1000 genes, but also provided novel complementary insights. Candidate genes were enriched for genes expressed in a circadian manner in multiple tissues with regulation driven mainly by transcription factors BMAL1 and REV-ERB ?,?. Moreover, peak transcription of candidate genes was remarkably consistent across tissues. While peaks of the 1000 genes were distributed uniformly throughout the day, candidate gene peaks were strongly concentrated around dusk. Finally, we showed that binding of specific transcription factors to a gene promoter was predictive of peak transcription at a certain time of day and discuss combinatorial phase regulation.Combining complementary publicly-available data targeting different levels of regulation within the circadian network, we filtered the original list and found 11 novel robust candidate clock genes. Using the criteria of circadian proteomic expression, circadian expression in multiple tissues and independent gene knockdown data, we propose six genes (Por, Mtss1, Dgat2, Pim3, Ppp1r3b, Upp2) involved in metabolism and cancer for further experimental investigation. The availability of public high-throughput databases makes such meta-analysis a promising approach to test consistency between sources and tap their entire potential.

Project description:BackgroundOur previous studies have confirmed that miR-154-5p can regulate pRb expression, and thus, play a tumor suppressor role in HPV16 E7-induced cervical cancer. However, its upstream molecules have not been elucidated in the progression of cervical cancer. This study aimed to explore the role of the miR-154-5p upstream molecule, hsa_circ_0000276 in cervical cancer development and its possible mechanisms of action.MethodsWe detected differences in whole transcriptome expression profiles of cervical squamous carcinoma and tissues adjacent to cervical cancer tissues from patients using microarray technology to predict circular RNAs (circRNAs) with binding sites to miR-154-5p. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to detect the expression of hsa_circ_0000276 (which had the strongest binding capacity to miR-154 and was selected as the target molecule) in cervical cancer tissues, followed by in vitro functional assays. Downstream microRNAs (miRNAs) and mRNAs of hsa_circ_0000276 were identified using transcriptome microarray data and databases, while the protein-protein interaction networks were obtained using STRING. A competing endogenous RNA (ceRNA) network centered on hsa_circ_0000276 was constructed using Cytoscape and GO and KEGG databases. Abnormal expression and prognosis of critical downstream molecules were analyzed using gene databases and molecular experiments. qRT-PCR and western blot analysis was performed to verify the expression of candidate genes.ResultsWe identified 4,001 differentially expressed circRNAs between HPV16-positive cervical squamous carcinoma and benign cervical tissues and 760 circRNAs targeting miR-154-5p, including hsa_circ_0000276. hsa_circ_0000276 and miR-154-5p directly bound, and hsa_circ_0000276 was upregulated, in cervical precancerous lesions and cervical cancer tissues and cells. Silencing hsa_circ_0000276 inhibited G1/S transition and cell proliferation and promoted apoptosis in SiHa and CaSki cells. Bioinformatics analysis showed that the hsa_circ_0000276 ceRNA network included 17 miRNAs and seven mRNAs, and downstream molecules of hsa_circ_0000276 were upregulated in cervical cancer tissues. These downstream molecules were associated with a poor prognosis and affected cervical cancer-associated immune infiltration. Of these, expression of CD47, LDHA, PDIA3, and SLC16A1 was downregulated in sh_hsa_circ_0000276 cells.ConclusionsOur findings show that hsa_circ_0000276 exerts cancer-promoting effects in cervical cancer and is an underlying biomarker for cervical squamous cell carcinoma.

Dataset Information

Screening of Therapeutic Candidate Genes of Quercetin for Cervical Cancer and Analysis of Their Regulatory Network.

Purpose

Methods

Results

Conclusion

Publications

Screening of Therapeutic Candidate Genes of Quercetin for Cervical Cancer and Analysis of Their Regulatory Network.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets