Development of a two-circular RNA panel as potential prognostic biomarker for gastric cancer
Abstract Background Circular RNAs (circRNAs) have attracted increasing attention in recent years for their potential application as disease biomarkers due to their high abundance and stability. In this study, we attempted to screen circRNAs that can be used to predict postoperative recurrence and su...
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doaj-8b70f88483164b99980e56e2edd928f82021-10-03T11:08:44ZengBMCJournal of Translational Medicine1479-58762021-10-0119111310.1186/s12967-021-03075-yDevelopment of a two-circular RNA panel as potential prognostic biomarker for gastric cancerJing Liu0Xingwu Zhu1Meinan Yan2Hui Li3Department of Gastrointestinal Cancer Biology, Tianjin Medical University Cancer Institute and HospitalDepartment of Gastrointestinal Cancer Biology, Tianjin Medical University Cancer Institute and HospitalDepartment of Gastrointestinal Cancer Biology, Tianjin Medical University Cancer Institute and HospitalDepartment of Gastrointestinal Cancer Biology, Tianjin Medical University Cancer Institute and HospitalAbstract Background Circular RNAs (circRNAs) have attracted increasing attention in recent years for their potential application as disease biomarkers due to their high abundance and stability. In this study, we attempted to screen circRNAs that can be used to predict postoperative recurrence and survival in patients with gastric cancer (GC). Methods High-throughput RNA sequencing was used to identify differentially expressed circRNAs in GC patients with different prognoses. The expression level of circRNAs in the training set (n = 136) and validation set (n = 167) was detected by quantitative real-time PCR (qRT-PCR). Kaplan–Meier estimator, receiver operating characteristic (ROC) curve and cox regression analysis were used to evaluate the prognostic value of circRNAs on recurrence-free survival (RFS) and overall survival (OS) in GC patients. CeRNA network prediction, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for the circRNAs with prognostic significance. Results A total of 259 differentially expressed circRNAs were identified in GC patients with different RFS. We found two circRNAs (hsa_circ_0005092 and hsa_circ_0002647) that highly expressed in GC patients with good prognoses, and subsequently established a predictive model for postoperative recurrence and prognosis evaluation, named circPanel. Patients with circPanellow might have shorter recurrence-free survival (RFS) and overall survival (OS). We also performed circRNA-miRNA-mRNA network prediction and functional analysis for hsa_circ_0005092 and hsa_circ_0002647. Conclusions CircPanel has the potential to be a prognostic biomarker in GC patients with greater accuracy than a single circRNA and certain traditional tumor markers (e.g., CEA, CA19-9 and CA724).https://doi.org/10.1186/s12967-021-03075-yGastric cancerCircular RNABiomarkerPrognostic assessmentcircPanel |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jing Liu Xingwu Zhu Meinan Yan Hui Li |
spellingShingle |
Jing Liu Xingwu Zhu Meinan Yan Hui Li Development of a two-circular RNA panel as potential prognostic biomarker for gastric cancer Journal of Translational Medicine Gastric cancer Circular RNA Biomarker Prognostic assessment circPanel |
author_facet |
Jing Liu Xingwu Zhu Meinan Yan Hui Li |
author_sort |
Jing Liu |
title |
Development of a two-circular RNA panel as potential prognostic biomarker for gastric cancer |
title_short |
Development of a two-circular RNA panel as potential prognostic biomarker for gastric cancer |
title_full |
Development of a two-circular RNA panel as potential prognostic biomarker for gastric cancer |
title_fullStr |
Development of a two-circular RNA panel as potential prognostic biomarker for gastric cancer |
title_full_unstemmed |
Development of a two-circular RNA panel as potential prognostic biomarker for gastric cancer |
title_sort |
development of a two-circular rna panel as potential prognostic biomarker for gastric cancer |
publisher |
BMC |
series |
Journal of Translational Medicine |
issn |
1479-5876 |
publishDate |
2021-10-01 |
description |
Abstract Background Circular RNAs (circRNAs) have attracted increasing attention in recent years for their potential application as disease biomarkers due to their high abundance and stability. In this study, we attempted to screen circRNAs that can be used to predict postoperative recurrence and survival in patients with gastric cancer (GC). Methods High-throughput RNA sequencing was used to identify differentially expressed circRNAs in GC patients with different prognoses. The expression level of circRNAs in the training set (n = 136) and validation set (n = 167) was detected by quantitative real-time PCR (qRT-PCR). Kaplan–Meier estimator, receiver operating characteristic (ROC) curve and cox regression analysis were used to evaluate the prognostic value of circRNAs on recurrence-free survival (RFS) and overall survival (OS) in GC patients. CeRNA network prediction, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for the circRNAs with prognostic significance. Results A total of 259 differentially expressed circRNAs were identified in GC patients with different RFS. We found two circRNAs (hsa_circ_0005092 and hsa_circ_0002647) that highly expressed in GC patients with good prognoses, and subsequently established a predictive model for postoperative recurrence and prognosis evaluation, named circPanel. Patients with circPanellow might have shorter recurrence-free survival (RFS) and overall survival (OS). We also performed circRNA-miRNA-mRNA network prediction and functional analysis for hsa_circ_0005092 and hsa_circ_0002647. Conclusions CircPanel has the potential to be a prognostic biomarker in GC patients with greater accuracy than a single circRNA and certain traditional tumor markers (e.g., CEA, CA19-9 and CA724). |
topic |
Gastric cancer Circular RNA Biomarker Prognostic assessment circPanel |
url |
https://doi.org/10.1186/s12967-021-03075-y |
work_keys_str_mv |
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