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Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis
This study is aimed at screening prognostic biomarkers in cholangiocarcinoma (CHOL) based on competitive endogenous RNA (ceRNA) regulatory network analysis. Microarray data for lncRNAs, mRNA, and miRNAs were downloaded from the GEO and TCGA databases. Differentially expressed RNAs (DERs) were identi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9499749/ https://www.ncbi.nlm.nih.gov/pubmed/36158120 http://dx.doi.org/10.1155/2022/7102736 |
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author | Jin, Haili Liu, Wei Xu, Weiming Zhou, Liping Luo, Huarong Xu, Cheng Chen, Xi Chen, Wenbin |
author_facet | Jin, Haili Liu, Wei Xu, Weiming Zhou, Liping Luo, Huarong Xu, Cheng Chen, Xi Chen, Wenbin |
author_sort | Jin, Haili |
collection | PubMed |
description | This study is aimed at screening prognostic biomarkers in cholangiocarcinoma (CHOL) based on competitive endogenous RNA (ceRNA) regulatory network analysis. Microarray data for lncRNAs, mRNA, and miRNAs were downloaded from the GEO and TCGA databases. Differentially expressed RNAs (DERs) were identified in CHOL and normal liver tissue samples. WGCNA was used to identify disease-related gene modules. By integrating the information from the starBase and DIANA-LncBasev2 databases, we constructed a ceRNA network. Survival analysis was performed, and a prognostic gene-based prognostic score (PS) model was generated. The correlation between gene expression and immune cell infiltration or immune-related feature genes was analyzed using TIMER. Finally, real-time quantitative PCR (RT-qPCR) was used to verify the expression of the 10 DERs with independent prognosis. A large cohort of DERs was identified in the CHOL and control samples. The ceRNA network consisted of 6 lncRNAs, 2 miRNAs, 90 mRNAs, and 98 nodes. Ten genes were identified as prognosis-related genes, and a ten-gene signature PS model was constructed, which exhibited a good prognosis predictive ability for risk assessment of CHOL patients (AUC value = 0.975). Four genes, ELF4, AGXT, ABCG2, and LDHD, were associated with immune cell infiltration and closely correlated with immune-related feature genes (CD14, CD163, CD33, etc.) in CHOL. Additionally, the consistency rate of the RT-qPCR results and bioinformatics analysis was 80%, implying a relatively high reliability of the bioinformatic analysis results. Our findings suggest that the ten-signature gene PS model has significant prognostic predictive value for patients with CHOL. These four immune-related DERs are involved in the progression of CHOL and may be useful prognostic biomarkers for CHOLs. |
format | Online Article Text |
id | pubmed-9499749 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-94997492022-09-23 Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis Jin, Haili Liu, Wei Xu, Weiming Zhou, Liping Luo, Huarong Xu, Cheng Chen, Xi Chen, Wenbin Comput Math Methods Med Research Article This study is aimed at screening prognostic biomarkers in cholangiocarcinoma (CHOL) based on competitive endogenous RNA (ceRNA) regulatory network analysis. Microarray data for lncRNAs, mRNA, and miRNAs were downloaded from the GEO and TCGA databases. Differentially expressed RNAs (DERs) were identified in CHOL and normal liver tissue samples. WGCNA was used to identify disease-related gene modules. By integrating the information from the starBase and DIANA-LncBasev2 databases, we constructed a ceRNA network. Survival analysis was performed, and a prognostic gene-based prognostic score (PS) model was generated. The correlation between gene expression and immune cell infiltration or immune-related feature genes was analyzed using TIMER. Finally, real-time quantitative PCR (RT-qPCR) was used to verify the expression of the 10 DERs with independent prognosis. A large cohort of DERs was identified in the CHOL and control samples. The ceRNA network consisted of 6 lncRNAs, 2 miRNAs, 90 mRNAs, and 98 nodes. Ten genes were identified as prognosis-related genes, and a ten-gene signature PS model was constructed, which exhibited a good prognosis predictive ability for risk assessment of CHOL patients (AUC value = 0.975). Four genes, ELF4, AGXT, ABCG2, and LDHD, were associated with immune cell infiltration and closely correlated with immune-related feature genes (CD14, CD163, CD33, etc.) in CHOL. Additionally, the consistency rate of the RT-qPCR results and bioinformatics analysis was 80%, implying a relatively high reliability of the bioinformatic analysis results. Our findings suggest that the ten-signature gene PS model has significant prognostic predictive value for patients with CHOL. These four immune-related DERs are involved in the progression of CHOL and may be useful prognostic biomarkers for CHOLs. Hindawi 2022-09-15 /pmc/articles/PMC9499749/ /pubmed/36158120 http://dx.doi.org/10.1155/2022/7102736 Text en Copyright © 2022 Haili Jin et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Jin, Haili Liu, Wei Xu, Weiming Zhou, Liping Luo, Huarong Xu, Cheng Chen, Xi Chen, Wenbin Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis |
title | Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis |
title_full | Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis |
title_fullStr | Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis |
title_full_unstemmed | Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis |
title_short | Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis |
title_sort | identification of prognostic factors in cholangiocarcinoma based on integrated cerna network analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9499749/ https://www.ncbi.nlm.nih.gov/pubmed/36158120 http://dx.doi.org/10.1155/2022/7102736 |
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