Dataset Information

Molecular characterization of papillary thyroid carcinoma: a potential three-lncRNA prognostic signature.

ABSTRACT: Purpose:Papillary thyroid carcinoma (PTC), the most frequent type of malignant thyroid tumor, lacks novel and reliable biomarkers of patients' prognosis. In the current study, we mined The Cancer Genome Atlas (TCGA) to develop lncRNA signature of PTC. Patients and methods:The intersection of PTC lncRNAs was obtained from the TCGA database using integrative computational method. By the univariate and multivariate Cox analysis, key lncRNAs were identified to construct the prognostic model. Then, all patients were divided into the high-risk group and low-risk group to perform the Kaplan-Meier (K-M) survival curves and time-dependent receiver operating characteristic (ROC) curve, estimating the prognostic power of the prognostic model. Functional enrichment analysis was also performed. Finally, we verified the results of the TCGA analysis by the Gene Expression Omnibus (GEO) databases and quantitative real-time PCR (qRT-PCR). Results:After the comprehensive analysis, a three-lncRNA signature (PRSS3P2, KRTAP5-AS1 and PWAR5) was obtained. Interestingly, patients with low-risk scores tended to gain obviously longer survival time, and the area under the time-dependent ROC curve was 0.739. Furthermore, gene ontology (GO) and pathway analysis revealed the tumorigenic and prognostic function of the three lncRNAs. We also found three potential transcription factors to help understand the mechanisms of the PTC-specific lncRNAs. Finally, the GEO databases and qRT-PCR validation were consistent with our TCGA bioinformatics results. Conclusion:We built a three-lncRNA signature by mining the TCGA database, which could effectively predict the prognosis of PTC.

SUBMITTER: You X

PROVIDER: S-EPMC6183593 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Molecular characterization of papillary thyroid carcinoma: a potential three-lncRNA prognostic signature.

You Xin X Yang Sheng S Sui Jing J Wu Wenjuan W Liu Tong T Xu Siyi S Cheng Yanping Y Kong Xiaoling X Liang Geyu G Yao Yongzhong Y

Cancer management and research 20181008

<h4>Purpose</h4>Papillary thyroid carcinoma (PTC), the most frequent type of malignant thyroid tumor, lacks novel and reliable biomarkers of patients' prognosis. In the current study, we mined The Cancer Genome Atlas (TCGA) to develop lncRNA signature of PTC.<h4>Patients and methods</h4>The intersection of PTC lncRNAs was obtained from the TCGA database using integrative computational method. By the univariate and multivariate Cox analysis, key lncRNAs were identified to construct the prognostic ...[more]

PMID: 30349364

Similar Datasets

Project description:Although the mortality rate of papillary thyroid carcinoma (PTC) is relatively low, the recurrence rates of PTC remain high. The high recurrence rates are related to the difficulties in treatment. Gene expression profiles has provided novel insights into potential therapeutic targets and molecular biomarkers of PTC. The aim of the present study was to identify mRNA signatures which may categorize PTCs into high-and low-risk subgroups and aid with the predictions for prognoses. The mRNA expression profiles of PTC and normal thyroid tissue samples were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs were identified using the 'EdgeR' software package. Gene signatures associated with the overall survival of PTC were selected, and enrichment analysis was performed to explore the biological pathways and functions of the prognostic mRNAs using the Database for Visualization, Annotation and Integration Discovery. A signature model was established to investigate a specific and robust risk stratification for PTC. A total of 1,085 differentially expressed mRNAs were identified between the PTC and normal thyroid tissue samples. Among them, 361 mRNAs were associated with overall survival (P<0.05). A 5-mRNA prognostic signature for PTC (ADRA1B, RIPPLY3, PCOLCE, TEKT1 and SALL3) was identified to classify the patients into high-and low-risk subgroups. These prognostic mRNAs were enriched in Gene Ontology terms such as 'calcium ion binding', 'enzyme inhibitor activity', 'carbohydrate binding', 'transcriptional activator activity', 'RNA polymerase II core promoter proximal region sequence-specific binding' and 'glutathione transferase activity', and Kyoto Encyclopedia of Genes and Genomes signaling pathways such as 'pertussis', 'ascorbate and aldarate metabolism', 'systemic lupus erythematosus', 'drug metabolism-cytochrome P450 and 'complement and coagulation cascades'. The 5-mRNA signature model may be useful during consultations with patients with PTC to improve the prediction of their prognosis. In addition, the prognostic signature identified in the present study may reveal novel therapeutic targets for patients with PTC.

Dataset Information

Molecular characterization of papillary thyroid carcinoma: a potential three-lncRNA prognostic signature.

Publications

Molecular characterization of papillary thyroid carcinoma: a potential three-lncRNA prognostic signature.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets