Construction and analysis of a survival-associated competing endogenous RNA network in breast cancer

被引:1
作者
Chen, Gang [1 ]
Li, Yalun [1 ]
Cao, Jianqiao [1 ]
Dai, Yuanping [2 ]
Cong, Yizi [1 ]
Qiao, Guangdong [1 ]
机构
[1] Qingdao Univ, Dept Breast Surg, Affiliated Yantai Yuhuangding Hosp, Yantai, Peoples R China
[2] Liuzhou Maternal & Child Hlth Hosp, Dept Med Genet, Liuzhou, Peoples R China
来源
FRONTIERS IN SURGERY | 2023年 / 9卷
关键词
bioinformatics; breast cancer; prognosis biomarker; GEO; ceRNAs; CELL-PROLIFERATION; CIRCULAR RNAS; EXPRESSION; CCNB1; BIOMARKERS; INVASION; LNCRNA;
D O I
10.3389/fsurg.2022.1021195
中图分类号
R61 [外科手术学];
学科分类号
摘要
BackgroundRecently, increasing studies have shown that non-coding RNAs are closely associated with the progression and metastasis of cancer by participating in competing endogenous RNA (ceRNA) networks. However, the role of survival-associated ceRNAs in breast cancer (BC) remains unknown. MethodsThe Gene Expression Omnibus database and The Cancer Genome Atlas BRCA_dataset were used to identify differentially expressed RNAs. Furthermore, circRNA-miRNA interactions were predicted based on CircInteractome, while miRNA-mRNA interactions were predicted based on TargetScan, miRDB, and miRTarBase. The survival-associated ceRNA networks were constructed based on the predicted circRNA-miRNA and miRNA-mRNA pairs. Finally, the mechanism of miRNA-mRNA pairs was determined. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of survival-related mRNAs were performed using the hypergeometric distribution formula in R software.The prognosis of hub genes was confirmed using gene set enrichment analysis. ResultsBased on the DE-circRNAs of the top 10 initial candidates, 162 DE-miRNAsand 34 DE-miRNAs associated with significant overall survival were obtained. The miRNA target genes were then identified using online tools and verified using the Cancer Genome Atlas (TCGA) database. Overall, 46 survival-associated DE-mRNAs were obtained. The results of GO and KEGG pathway enrichment analyses implied that up-regulated survival-related DE-mRNAs were mostly enriched in the "regulation of cell cycle" and "chromatin" pathways, while down-regulated survival-related DE-mRNAs were mostly enriched in "negative regulation of neurotrophin TRK receptor signaling" and "interleukin-6 receptor complex" pathways. Finally, the survival-associated circRNA-miRNA-mRNA ceRNA network was constructed using 34 miRNAs, 46 mRNAs, and 10 circRNAs. Based on the PPI network, two ceRNA axes were identified. These ceRNA axescould be considered biomarkers for BC.GSEA results revealed that the hub genes were correlated with "VANTVEER_BREAST_CANCER_POOR_PROGNOSIS", and the hub genes were verified using BC patients' tissues. ConclusionsIn this study, we constructed a circRNA-mediated ceRNA network related to BC. This network provides new insight into discovering potential biomarkers for diagnosing and treating BC.
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页数:11
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共 35 条
[1]   Predicting effective microRNA target sites in mammalian mRNAs [J].
Agarwal, Vikram ;
Bell, George W. ;
Nam, Jin-Wu ;
Bartel, David P. .
ELIFE, 2015, 4
[2]   NON-CODING RNAs IN DEVELOPMENT AND DISEASE: BACKGROUND, MECHANISMS, AND THERAPEUTIC APPROACHES [J].
Beermann, Julia ;
Piccoli, Maria-Teresa ;
Viereck, Janika ;
Thum, Thomas .
PHYSIOLOGICAL REVIEWS, 2016, 96 (04) :1297-1325
[3]   Circular RNAs: Biogenesis, Function, and a Role as Possible Cancer Biomarkers [J].
Bolha, Luka ;
Ravnik-Glavac, Metka ;
Glavac, Damjan .
INTERNATIONAL JOURNAL OF GENOMICS, 2017, 2017
[4]  
Cheadle Chris, 2003, Appl Bioinformatics, V2, P209
[5]   Identification of candidate biomarkers correlated with poor prognosis of breast cancer based on bioinformatics analysis [J].
Chen, Gang ;
Yu, Mingwei ;
Cao, Jianqiao ;
Zhao, Huishan ;
Dai, Yuanping ;
Cong, Yizi ;
Qiao, Guangdong .
BIOENGINEERED, 2021, 12 (01) :5149-5161
[6]   miRDB: an online database for prediction of functional microRNA targets [J].
Chen, Yuhao ;
Wang, Xiaowei .
NUCLEIC ACIDS RESEARCH, 2020, 48 (D1) :D127-D131
[7]   miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions [J].
Chou, Chih-Hung ;
Shrestha, Sirjana ;
Yang, Chi-Dung ;
Chang, Nai-Wen ;
Lin, Yu-Ling ;
Liao, Kuang-Wen ;
Huang, Wei-Chi ;
Sun, Ting-Hsuan ;
Tu, Siang-Jyun ;
Lee, Wei-Hsiang ;
Chiew, Men-Yee ;
Tai, Chun-San ;
Wei, Ting-Yen ;
Tsai, Tzi-Ren ;
Huang, Hsin-Tzu ;
Wang, Chung-Yu ;
Wu, Hsin-Yi ;
Ho, Shu-Yi ;
Chen, Pin-Rong ;
Chuang, Cheng-Hsun ;
Hsieh, Pei-Jung ;
Wu, Yi-Shin ;
Chen, Wen-Liang ;
Li, Meng-Ju ;
Wu, Yu-Chun ;
Huang, Xin-Yi ;
Ng, Fung Ling ;
Buddhakosai, Waradee ;
Huang, Pei-Chun ;
Lan, Kuan-Chun ;
Huang, Chia-Yen ;
Weng, Shun-Long ;
Cheng, Yeong-Nan ;
Liang, Chao ;
Hsu, Wen-Lian ;
Huang, Hsien-Da .
NUCLEIC ACIDS RESEARCH, 2018, 46 (D1) :D296-D302
[8]   Long non-coding RNA linc00665 promotes lung adenocarcinoma progression and functions as ceRNA to regulate AKR1B10-ERK signaling by sponging miR-98 [J].
Cong, Zhuangzhuang ;
Diao, Yifei ;
Xu, Yang ;
Li, Xiaokun ;
Jiang, Zhisheng ;
Shao, Chenye ;
Ji, Saiguang ;
Shen, Yi ;
De, Wei ;
Qiang, Yong .
CELL DEATH & DISEASE, 2019, 10 (2)
[9]   CCNB1 is a prognostic biomarker for ER plus breast cancer [J].
Ding, Kun ;
Li, Wenqing ;
Zou, Zhiqiang ;
Zou, Xianzhi ;
Wang, Chengru .
MEDICAL HYPOTHESES, 2014, 83 (03) :359-364
[10]   CircInteractome: A web tool for exploring circular RNAs and their interacting proteins and microRNAs [J].
Dudekulay, Dawood B. ;
Panda, Amaresh C. ;
Grammatikakis, Ioannis ;
De, Supriyo ;
Abdelmohsen, Kotb ;
Gorospe, Myriam .
RNA BIOLOGY, 2016, 13 (01) :34-42