Dataset Information

The New Biomarker for Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) Based on Public Database Mining.

ABSTRACT: To reconstruct the ceRNA biological network of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) and to select an appropriate mRNA as a biomarker that could be used for CESC early diagnosis and prognosis evaluation. We downloaded CESC data from the TCGA public database, and statistical analysis was conducted with the R software to find out differential expressed genes encoding for lncRNAs, miRNAs, and mRNAs. The differentially expressed mRNAs (DEmRNAs) screened in the ceRNA network were analyzed for survival to find the mRNAs with significantly linked to the survival prognosis. These mRNAs were searched in the Pathological Atlas to identify the final appropriate mRNAs. Differential expression analysis revealed 773 lncRNAs, 94 miRNAs, and 2466 mRNAs. Survival analysis of DEmRNAs in the ceRNA network indicated that ADGRF4, ANXA8L1, HCAR3, IRF6, and PDE2A (P < 0.05) were negatively correlated with survival time. Verification of these six DEmRNAs in the Pathology Atlas indicated that PDE2A was a possible biomarker for CESC patients. PDE2A might be a biomarker for early diagnosis and prognosis evaluation of CESC patients, but due to the lack of available data, further studies may be needed for confirmation.

SUBMITTER: Ding H

PROVIDER: S-EPMC7174939 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The New Biomarker for Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) Based on Public Database Mining.

Ding Hao H Xiong Xiao-Xing XX Fan Guan-Lan GL Yi Yue-Xiong YX Chen Yu-Rou YR Wang Jing-Tao JT Zhang Wei W

BioMed research international 20200412

To reconstruct the ceRNA biological network of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) and to select an appropriate mRNA as a biomarker that could be used for CESC early diagnosis and prognosis evaluation. We downloaded CESC data from the TCGA public database, and statistical analysis was conducted with the R software to find out differential expressed genes encoding for lncRNAs, miRNAs, and mRNAs. The differentially expressed mRNAs (DEmRNAs) screened in the ceRNA ...[more]

PMID: 32351997

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Project description:BackgroundCervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are among the most prevalent gynecologic malignancies globally. The prognosis is abysmal once cervical cancer progresses to lymphatic metastasis. Anoikis, a specialized form of apoptosis induced by loss of cell adhesion to the extracellular matrix, plays a critical role. The prediction model based on anoikis-related genes (ARGs) expression and clinical data could greatly aid clinical decision-making. However, the relationship between ARGs and CESC remains unclear.MethodsARGs curated from the GeneCards and Harmonizome portals were instrumental in delineating CESC subtypes and in developing a prognostic framework for patients afflicted with this condition. We further delved into the intricacies of the immune microenvironment and pathway enrichment across the identified subtypes. Finally, our efforts culminated in the creation of an innovative nomogram that integrates ARGs. The utility of this prognostic tool was underscored by Decision Curve Analysis (DCA), which illuminate its prospective benefits in guiding clinical interventions.ResultsIn our study, We discerned a set of 17 survival-pertinent, anoikis-related differentially expressed genes (DEGs) in CESC, from which nine were meticulously selected for the construction of prognostic models. The derived prognostic risk score was subsequently validated as an autonomous prognostic determinant. Through comprehensive functional analyses, we observed distinct immune profiles and drug response patterns among divergent prognostic stratifications. Further, we integrated the risk scores with the clinicopathological characteristics of CESC to develop a robust nomogram. DCA corroborated the utility of our model, demonstrating its potential to enhance patient outcomes through tailored clinical treatment strategies.ConclusionThe predictive signature, encompassing nine pivotal genes, alongside the meticulously constructed nomogram developed in this research, furnishes clinicians with a sophisticated tool for tailoring treatment strategies to individual patients diagnosed with CESC.

Project description:BackgroundInvasion and metastasis of cervical cancer are the main factors affecting the prognosis of patients with cervical squamous cell carcinoma (CESC). Therefore, it is of vital importance to find novel biomarkers that are associated with CESC invasion and metastasis, which will aid in the amelioration of individualized therapeutic methods for advanced patients.MethodsThe gene expression profiles of 10 metastatic and 116 non-metastatic samples were downloaded from The Cancer Genome Atlas (TCGA), where differentially expressed genes (DEGs) were defined. Weighted gene correlation network analysis (WGCNA) was employed to identify the stemness-related genes (SRGs). Univariate and multivariate regression analyses were used to identify the most significant prognostic key genes. Differential expression analysis of transcription factor (TF) and Gene Set Variation Analysis (GSVA) were utilized to explore the potential upstream regulation of TFs and downstream signaling pathways, respectively. Co-expression analysis was performed among significantly enriched TFs, key SRGs, and signaling pathways to construct a metastasis-specific regulation network in CESC. Connectivity Map (CMap) analysis was performed to identify bioactive small molecules which might be potential inhibitors for the network. Additionally, direct regulatory patterns of key genes were validated by ChIP-seq and ATAC-seq data.ResultsDEGs in yellow module acquired via WGCNA were defined as key genes which were most significantly related to mRNAsi. A multivariate Cox regression model was constructed and then utilized to explore the prognostic value of key SRGs by risk score. Area under curve (AUC) of the receiver operating characteristic (ROC) curve was 0.842. There was an obvious co expression pattern between the TF NR5A2 and the key gene VIM (R = 0.843, p < 0.001), while VIM was also significantly co-expressed with hallmark epithelial mesenchymal transition (EMT) signaling pathway (R = 0.318, p < 0.001). Naringenin was selected as the potential bioactive small molecule inhibitor for metastatic CESC based on CMap analysis.ConclusionsVIM positively regulated by NR5A2 affected EMT signaling pathways in metastatic CESC, and naringenin was the inhibitor for the treatment of metastatic CESC via suppressing cancer stemness. This hypothetical signaling axis and potential inhibitors provide biomarkers and novel therapeutic targets for metastatic CESC.

Project description:BackgroundThe purpose of this study was to investigate the prognostic signature of necroptosis-related lncRNAs (NRLs) and explore their association with immune-related functions and sensitivity of the therapeutic drug in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC).MethodsUCSC Xena provided lncRNA sequencing and clinical data about CESC, and a necroptosis gene list was obtained from the KEGG database. NRLs were selected by structuring a co-expression network of lncRNAs and necroptosis-related genes. To further screen lncRNAs, we used the univariate Cox regression method, Lasso regression, and multivariate Cox regression. Afterward, an NRL signature was established. We used the xCell algorithm and single-sample gene set enrichment analysis (ssGSEA) to clarify the pertinence between immune infiltration and NRL expressions in CESC patients and explored the relationship between the target lncRNAs and immune-related genes. By leveraging the GDSC database, the therapy-sensitive response of the prognostic signature was forecasted and an experimental validation was performed. We performed GSEA with the aim of recognizing the potential pathway related to the individual prognostic signature.ResultsThe two prognostic NRLs (AC009095.1 and AC005332.4) showed significant diversity and constituted the NRL signature. On the grounds of our signature, risk score was an independent element which was bound up with patient outcome (HR = 4.97 CI: 1.87-13.2, P = 0.001). The CESC patients were classified by the median risk score. Immune infiltration analysis revealed significant increases in CD4 + Tcm, eosinophils, epithelial cells, fibroblasts, NKT, plasma cells, platelets, and smooth muscle in the high-risk group (P< 0.05). Target lncRNAs also showed some correlation with NRGs. The estimated IC50 values of bicalutamide, CHIR.99021, and imatinib were lower in the high-risk group. Through the subsequent experimental validation, both AC009095.1 and AC005332.4 were significantly more highly expressed in SiHa than in Hela. AC009095.1 was expressed more highly in SiHa than in HUCEC, but the expression of AC005332.4 was reversed.ConclusionsThis study elucidated that NRLs, as a novel signature, were indispensable factors which can significantly influence the prognosis of patients with CESC and could provide novel clinical evidence to serve as a potential molecular biomarker for future therapeutic targets.

Project description:BackgroundIn this study, we aimed to investigate the signature of the autophagy-related lncRNAs (ARLs) and perform integrated analysis with immune infiltration in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC).Methods and resultsThe UCSC Xena and HADb databases provided the corresponding data. The ARLs were selected via constructing a co-expression network of autophagy-related genes (ARGs) and lncRNAs. Univariate Cox regression analysis combined with LASSO regression and multivariate Cox regression analysis were utilized to screen lncRNAs. The ARL risk signature was established by Cox regression and tested if it was an independent element bound up with patient prognosis. We used the xCell algorithm and ssGSEA to clarify the pertinence between immune infiltration and the expression of ARLs. Finally, we predicted the sensitivity of drug treatment as well as the immune response. Results indicated that the three prognostic ARLs (SMURF2P1, MIR9-3HG, and AC005332.4) possessed significant diversity and constituted the ARL signature. Risk score was an individual element (HR = 2.82, 95% CI = 1.87-4.30; p < 0.001). Immune infiltration analysis revealed significant increases in central memory CD8+ T cells, endothelial cells, CD8+ naive T cells, and preadipocytes in the high-risk group (p < 0.05). There were 10 therapeutic agents that varied significantly in their estimated half-maximal inhibitory concentrations in the two groups. According to the experimental validation, we found that SMURF2P1 belongs to the co-stimulatory genes and might assume greater importance in the development of cervical adenocarcinoma. MIR9-3HG and AC005332.4 belonged to the tumor-suppressor genes and they may play a more positive role in cervical squamous cell carcinoma.ConclusionsThis research explored and validated a novel signature of the ARLs, which can be applied to forecast the prognosis of patients with CESC and is closely associated with immune infiltration.

Dataset Information

The New Biomarker for Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) Based on Public Database Mining.

Publications

The New Biomarker for Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) Based on Public Database Mining.

Similar Datasets

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