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Prognostic value of a two‐microRNA signature for papillary thyroid cancer and a bioinformatic analysis of their possible functions
Author(s) -
Liu Tong,
You Xin,
Sui Jing,
Shen Bo,
Zhang Yan,
Zhang XiaoMei,
Yang Sheng,
Yao YongZhong,
Yang Fei,
Yin LiHong,
Pu YuePu,
Liang GeYu
Publication year - 2019
Publication title -
journal of cellular biochemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.028
H-Index - 165
eISSN - 1097-4644
pISSN - 0730-2312
DOI - 10.1002/jcb.27993
Subject(s) - microrna , computational biology , biology , thyroid cancer , papillary thyroid cancer , microarray , proportional hazards model , bioinformatics , univariate , oncology , gene , cancer , medicine , multivariate statistics , gene expression , genetics , computer science , machine learning
Background Recent scientific evidence has suggested that microRNAs (miRNAs) play an important role in papillary thyroid cancer (PTC). In the current study, we aim to identify a miRNA‐related signature as the sensitive and novel prognostic biomarkers. Methods We performed a comprehensive analysis of the data downloaded from the Cancer Genome Atlas (TCGA) database. The association between survival outcome and miRNA was assessed by the univariate and multivariate Cox proportional hazards model. The risk score model was built to evaluate the predicting value of miRNA signature. The potential biofunctions and transcription factors of target miRNAs were investigated through bioinformatic analysis. The result was verified by the quantitative real‐time polymerase chain reaction (qRT‐PCR) in 32 pairs of PTC and adjacent nontumor tissues. In addition, the results were verified by other cohorts from gene expression omnibus (GEO) as detected by microarrays. Results A total of 1030 miRNAs were identified from the TCGA database. Thirty‐six key intersection miRNAs were obtained. The associations between clinical features and key miRNAs were evaluated. Eventually, a two‐miRNA signature (hsa‐miR‐181a‐2‐3p and hsa‐miR‐138‐1‐3p) was identified. The power of the miRNA prognostic signature was effective. In total, we identified 202 genes that were associated with 2 miRNAs above, and the top 10 enriched transcript factors that highly related with the target miRNAs were explored. The qRT‐PCR and GEO data validation were consistent with bioinformatics results. Conclusions A tumor‐specific miRNA signature was identified, and the joint prognostic power was evaluated, which may be potential biomarkers for prognosis of PTC. Impact : The two‐miRNA signature could become the potential prognostic indicator of PTC in the future.