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Develop a circular RNA-related regulatory network associated with prognosis of gastric cancer.

ABSTRACT: BACKGROUND:In gastric cancer (GC), circular RNAs (circRNAs) mainly play an important role in miRNA sponge, which not only indicate long-term survival and prognosis but also increase resistance to the apoptosis. The purpose of the study is to explore new circRNAs and their underlying mechanisms in GC. METHOD:Through rigorous retrieval strategies, we used the sva package to analyze and identify differentially expressed circRNAs (DECs) from three Gene Expression Omnibus microarray datasets (GSE83521, GSE89143, and GSE78092). Online website CSCD and CircInteractome were used to reveal the binding sites between miRNAs and DECs. The possible target miRNAs of the DECs identified based on miRNAs, and Cytoscape was used to create a regulatory network of circRNA-miRNA-mRNA and identified the hub genes which were further validated using The Cancer Genome Atlas database and Human Protein Atlas. RESULTS:Twenty-eight DECs were obtained using the sva package. A regulatory network of circRNA-miRNA-mRNA (competing endogenous RNA) containing 15 circRNAs, 24 miRNAs, and 158 genes was identified. A protein-protein interaction network based on the 158 genes was established, and further determined that 10 hub genes (SKA1, ANLN, CHEK1, SKA3, TOP2A, BIRC5, RRM2, NCAPG2, FANCI, and RAD51) were associated with some cancer-related pathways based on the functional enrichment analysis. Finally, six hub genes (BIRC5, TOP2A, FANCI, NCAPG2, RAD51, and RRM2) were proven to influence the overall survival of GC. CONCLUSION:Our study established a circRNA-miRNA-mRNA regulatory network and defined six circRNA-related hub genes in GC, which could serve as potential therapeutic targets or prognostic biomarker for GC treatment.

SUBMITTER: Wei S

PROVIDER: S-EPMC7666747 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Develop a circular RNA-related regulatory network associated with prognosis of gastric cancer.

Wei Shuxun S Teng Shifeng S Yao Jun J Gao Wenchao W Zang Jia J Wang Guangyong G Hu Zhiqian Z

Cancer medicine 20200909 22

<h4>Background</h4>In gastric cancer (GC), circular RNAs (circRNAs) mainly play an important role in miRNA sponge, which not only indicate long-term survival and prognosis but also increase resistance to the apoptosis. The purpose of the study is to explore new circRNAs and their underlying mechanisms in GC.<h4>Method</h4>Through rigorous retrieval strategies, we used the sva package to analyze and identify differentially expressed circRNAs (DECs) from three Gene Expression Omnibus microarray da ...[more]

PMID: 32902196

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Project description:PurposeThe morbidity and mortality of gastric cancer (GC) remain high worldwide. In recent years, circular RNAs (circRNAs) have attracted widespread attention among cancer researchers due to the stable ring structure. The present work aims to find serum circRNA biomarkers that can be used in clinical applications and effective diagnosis.MethodsHsa_circ_0007507 was extracted through circRNA sequencing. Exonuclease digestion assay, actinomycin D, agarose gel electrophoresis (AGE), and Sanger sequencing verified the potential of hsa_circ_0007507 as a biomarker. Besides, a real-time fluorescent quantitative polymerase chain reaction (RT-qPCR) was established to detect the level of expression of hsa_circ_0007507. Twenty cases of GC and the paired adjacent tissues were collected to verify its overexpression. Then, serum samples from 30 cases of colorectal cancer, 30 cases of thyroid cancer, and 30 cases of breast cancer were collected to verify their organ specificity. Additionally, serum samples from 80 healthy people, 62 gastritis patients, 31 intestinal metaplasia patients, and 100 GC patients were collected, and the diagnostic efficacy was evaluated through analysis of the receiver operating characteristic (ROC) curve. Furthermore, 16 post-operative GC samples, samples of 65 relapsed patients and 36 non-relapsed patients were collected to evaluate the prognosis of GC.ResultsThe level of expression of hsa_circ_0007507 in GC tissues was up-regulated (p = 0.0121), which was consistent with the results of circRNA sequencing. Exonuclease digestion assay and actinomycin D confirmed that hsa_circ_0007507 had a stable structure and a longer half-life. In the analysis of organ specificity experiments, serum hsa_circ_0007507 did not have specificity for patients with colorectal cancer (p = 0.5319), thyroid cancer (p = 0.5422), or breast cancer (p = 0.5178). Analysis of diagnostic efficacy indicated that the expression of hsa_circ_0007507 was significantly higher than that of normal people (p <0.0001); the area under the ROC (AUC) was 0.832 (95% CI: 0.771-0.892); the diagnostic power of hsa_circ_0007507 was higher than that of CEA (AUC = 0.765, 95% CI: 0.697-0.833) and CA199 (AUC = 0.587, 95% CI: 0.504-0.67). Through diagnosis using a combination of the three, GC patients could be distinguished from normal people (AUC = 0.849), and higher diagnostic efficiency could be achieved. The expression of serum hsa_circ_0007507 in GC patients significantly decreased after surgery (p = 0.001). Besides, the expression of serum hsa_circ_0007507 in patients with post-operative recurrence was significantly up-regulated again (p = 0.0139).ConclusionsSerum hsa_circ_0007507 is differentially expressed in GC patients, post-operative GC patients, gastritis patients, intestinal metaplasia patients and relapsed patients, suggesting that serum hsa_circ_0007507 can be used as a new diagnostic and dynamic monitoring biomarker for GC.

Project description:BackgroundGastric cancer (GC) is one of the most common causes of cancer-related fatalities worldwide, and its progression is associated with RNA modifications. Here, using RNA modification-related genes (RNAMRGs), we aimed to construct a prognostic model for patients with GC.MethodsBased on RNAMRGs, RNA modification scores (RNAMSs) were obtained for GC samples from The Cancer Genome Atlas and were divided into high- and low-RNAMS groups. Differential analysis and weighted correlation network analysis were performed for the differential expressed genes (DEGs) to obtain the key genes. Next, univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses were performed to obtain the model. According to the model risk score, samples were divided into high- and low-risk groups. Enrichment analysis and immunoassays were performed for the DEGs in these groups. Four external datasets from Gene Expression Omnibus data base were used to test the accuracy of the predictive model.ResultsWe identified SELP and CST2 as key DEGs, which were used to generate the predictive model. The high-risk group had a worse prognosis compared to the low-risk group (p < 0.05). Enrichment analysis and immunoassays revealed that 144 DEGs related to immune cell infiltration were associated with the Wnt signaling pathway and included hub genes such as ELN. Overall mutation levels, tumor mutation burden, and microsatellite instability were lower, but tumor immune dysfunction and exclusion scores were greater (p < 0.05) in the high-risk group than in the low-risk group. The validation results showed that the prediction model score can accurately predict the prognosis of GC patients. Finally, a nomogram was constructed using the risk score combined with the clinicopathological characteristics of patients with GC.ConclusionThis risk score from the prediction model related to the tumor microenvironment and immunotherapy could accurately predict the overall survival of GC patients.

Project description:Aim: To identify the pyroptosis-related long non-coding RNAs (lncRNAs) in ovarian cancer and construct a prognostic signature based on them. Methods: Expression data from TCGA was used to explore differentially expressed pyroptosis-related lncRNAs in ovarian cancer. A risk signature was established by LASSO and cox regression analysis and then validated. Databases such as ESTIMATE, CIBERSORT, TIMER, XCELL were used to identify the relation between this signature and the immune microenvironment of ovarian cancer. Gene Set Enrichment Analysis was introduced to identify the pathways and functions that the signature may participate in. Based on miRcode and starBase databases, microRNAs related to the lncRNAs in our signature and the positively co-expressed pyroptosis- related genes were screened and a competing endogenous RNA (ceRNA) network was then constructed. Quantitative reverse transcription PCR was conducted to validate the expression levels of two lncRNAs in this ceRNA network. Results: A 13 pyroptosis-related lncRNA prognostic signature (MYCNOS, AL161772.1, USP30-AS1, ZNF32-AS2, AC068733.3, AC012236.1, AC015802.5, KIAA1671-AS1, AC013403.2, MIR223HG, KRT7-AS, PTPRD-AS1 and LINC01094) was constructed. Patients in high-risk group had a significantly worse prognosis than that of low-risk (P<0.0001). Immune infiltration analysis found that patients identified as high-risk had a higher infiltration of macrophages and tumor-associated fibroblasts. Further pathway analysis revealed that the signature may be involved in epithelial mesenchymal transition, extracellular matrix receptor interaction, and focal adhesion. Finally, a competitive endogenous inhibition relationship was discovered between LINC01094, KRT7-AS, MYCNOS, ZNF32-AS2, AC012236.1 and pyroptosis- related genes such as IRF1, NOD1, GSDMC, NLRP1, PLCG1, GSDME and GZMB, in which LINC01094 and KRT7-AS were found to be overexpressed in three ovarian cancer cell lines. Conclusion: We constructed a pyroptosis-related lncRNA signature and correlate it to the immune microenvironment. A ceRNA regulatory network related to pyroptosis was also constructed, which provides novel insights useful for the study of pyroptosis in ovarian cancer.

Project description:BackgroundEmerging evidence has shown that circular RNAs (circRNAs) play a crucial regulatory role in the occurrence and development of cancer. Exploring the roles and mechanisms of circRNAs in tumorigenesis and progression may help to identify new diagnostic markers and therapeutic targets. In the present study, we investigated the role and regulatory mechanism of hsa_circ_0004872 in gastric cancer (GC).MethodsqRT-PCR was used to determine the expression of hsa_circ_0004872 in GC tissues and cells. EdU, CCK-8, transwell and scratch wound healing assays were used to assess the role of hsa_circ_0004872 in GC cell proliferation, invasion and migration, respectively. Subcutaneous and tail vein tumor injections in nude mice were used to assess the role of hsa_circ_0004872 in vivo. RIP assay, biotin-coupled probe pull-down assay, FISH and luciferase reporter assay were performed to confirm the relationship between hsa_circ_0004872 and the identified miRNA. ChIP assay, luciferase reporter assay and western blot were used to determine the direct binding of Smad4 to the promoter of the ADAR1 gene.ResultsIn this study, we found that hsa_circ_0004872 was dramatically downregulated in GC tissues compared with adjacent noncancerous tissues. The expression level of hsa_circ_0004872 was associated with tumor size and local lymph node metastasis. Enforced expression of hsa_circ_0004872 inhibited the proliferation, invasion and migration of GC cells, whereas knockdown of hsa_circ_0004872 had the opposite effects. Nude mice experiments showed that ectopic expression of hsa_circ_0004872 dramatically inhibited tumor growth and metastasis in vivo. Moreover, we demonstrated that hsa_circ_0004872 acted as a "molecular sponge" for miR-224 to upregulate the expression of the miR-224 downstream targets p21 and Smad4. Importantly, we found that the RNA-editing enzyme ADAR1 inhibited hsa_circ_0004872 expression and further led to the upregulation of miR-224. Smad4, the downstream target of miR-224, could further affect hsa_circ_0004872 levels by directly binding to the promoter region of ADAR1 to inhibit ADAR1 expression.ConclusionsOur findings showed that hsa_circ_0004872 acted as a tumor suppressor in GC by forming a negative regulatory loop consisting of hsa_circ_0004872/miR-224/Smad4/ADAR1. Thus, hsa_circ_0004872 may serve as a potential biomarker and therapeutic target for GC.

Project description:BackgroundPatients with non-small cell lung cancer (NSCLC) are diagnosed in advanced stages and with a poor 5-year survival rate. There is a critical need to identify novel biomarkers to improve the therapy and overall prognosis of this disease.MethodsDifferentially expressed genes (DEGs) were identified from three profiles of GSE101586, GSE101684 and GSE112214 using Venn diagrams. hsa_circ_0043256 were validated using quantitative real-time polymerase chain reaction (RT-qPCR). The circular RNA-microRNA-messenger RNA (circRNA-miRNA-mRNA) regulatory network was constructed with Cytoscape 3.7.0. Hub genes were identified with protein interaction (PPI) and validated with the Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas (HPA) databases, and immunohistochemistry. Survival analyses were also performed using a Kaplan-Meier (KM) plotter. The effects of hsa_circ_0043256 on cell proliferation and cell cycles were evaluated by EdU staining and flow cytometry, respectively.Resultshsa_circ_0043256, hsa_circ_0029426 and hsa_circ_0049271 were obtained. Following RT-qPCR validation, hsa_circ_0043256 was selected for further analysis. In addition, functional experiment results indicated that hsa_circ_0043256 could inhibit cell proliferation and cell-cycle progression of NSCLC cells in vitro. Prediction by three online databases and combining with DEGs identified from The Cancer Genome Atlas (TCGA), a network containing one circRNAs, three miRNAs, and 209 mRNAs was developed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated DEGs might be associated with lung cancer onset and progression. A PPI network based on the 209 genes was established, and five hub genes (BIRC5, SHCBP1, CCNA2, SKA3, and GINS1) were determined. Following verification of five hub genes using GEPIA database, HPA database, and immunohistochemistry. High expression of all five hub genes led to poor overall survival.ConclusionOur study constructed a circRNA-miRNA-mRNA network of hsa_circ_0043256. hsa_circ_0043256 may be a potential therapeutic target for lung cancer.

Project description:Background: Genetic characteristics remain underutilized for establishing prognostic models for colorectal cancer (CRC). We explored the underlying regulatory mechanisms of circular RNAs (circRNAs) that act as competing endogenous RNAs (ceRNAs) and constructed a gene-based nomogram to predict overall survival (OS) in patients with CRC. Methods: We obtained circRNA expression profiling data from the Gene Expression Omnibus (GEO) database. MicroRNA (miRNA) and mRNA expression profiles, with associated clinical data, were obtained from The Cancer Genome Atlas (TCGA). A ceRNA network was established using Cytoscape. Interactions between differential genes were analyzed, and hub genes were identified using the cytoHubba application. The R package "clusterProfiler" was used to evaluate the Gene Ontology (GO) annotations of the differentially expressed mRNAs and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Database-extracted patients were randomized into a training and validation cohorts. A prognostic model was developed using the training set based on multivariate Cox analyses and was then assessed in the validation set. The accuracy of the model was evaluated using discrimination and calibration plots. Results: Thirteen circRNAs, 62 miRNAs, and 301 mRNAs were used to construct the ceRNA network; 10 hub genes were identified via the PPI network. Next, a circRNA- miRNA hub of gene-regulatory modules was established based on four differentially expressed circRNAs, eight differentially expressed miRNAs, and nine differentially expressed mRNAs (DEmRNAs). GO and KEGG pathway analyses indicated the possible association of DEmRNAs with CRC onset and progression. Multivariate analyses revealed that age, tumor stage, and CXCR5 expression were independent risk factors for OS. A CXCR5-based model was developed to predict the OS of patients with CRC in our training set. Our nomogram showed relatively good accuracy, with C-indices of 0.757 and 0.702 in the training and validation sets, respectively. The areas under the curve of the nomograms predicting 3- and 5-years OS were 0.749 and 0.805 in the training set and 0.706 and 0.779 in the validation set, respectively. Conclusions: Our data suggested that the hsa_circ_00001666/has-mir-1229/CXCR5 axis plays an important role in the pathogenesis of CRC, thereby identifying a potential therapeutic target. The proposed CXCR5-based nomogram may also assist surgeons in devising personalized treatments for patients with this disease.

Dataset Information

Develop a circular RNA-related regulatory network associated with prognosis of gastric cancer.

Publications

Develop a circular RNA-related regulatory network associated with prognosis of gastric cancer.

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