scholarly journals Exploration of the Potential Biomarkers of Papillary Thyroid Cancer (PTC) Based on RT2 Profiler PCR Arrays and Bioinformatics Analysis

2020 ◽  
Vol Volume 12 ◽  
pp. 9235-9246
Author(s):  
Ying Peng ◽  
Han-Wen Zhang ◽  
Wei-Han Cao ◽  
Ying Mao ◽  
Ruo-Chuan Cheng
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Bioinformatics Analysis ◽  
Papillary Thyroid ◽  
Potential Biomarkers

scholarly journals Comprehensive transcriptomic analysis of Papillary Thyroid Cancer: potential biomarkers associated with tumor progression

2019 ◽  
Author(s):  
Nazanin Hosseinkhan ◽  
Maryam Honardoost ◽  
Kevin Blighe ◽  
C.B. Tara Moore ◽  
Mohammad Ebrahim Khamseh
Keyword(s):  
Thyroid Cancer ◽  
Tumor Progression ◽  
Papillary Thyroid Cancer ◽  
Transcriptomic Analysis ◽  
Papillary Thyroid ◽  
Potential Biomarkers

Abstract The authors have withdrawn this preprint from Research Square

scholarly journals Identification of Hub lncRNAs Along With lncRNA-miRNA-mRNA Network for Effective Diagnosis and Prognosis of Papillary Thyroid Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Haiyan Li ◽  
Feng Liu ◽  
Xiaoyang Wang ◽  
Menglong Li ◽  
Zhihui Li ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Prognostic Indicators ◽  
Validation Dataset ◽  
Papillary Thyroid ◽  
Cerna Network ◽  
Diagnosis And Prognosis ◽  
Potential Biomarkers

Long noncoding RNAs (lncRNAs) play important roles in tumorigenesis and progression of different cancers and they have been potential biomarkers for cancer diagnosis and prognosis. As the most common endocrine malignancy, precise diagnosis and prognosis of papillary thyroid cancer (PTC) is of great clinical significance. Here, we aim to identify new hub lncRNAs for marking PTC and constructed prognostics signatures based on lncRNA- miRNA-mRNA competing endogenous RNAs (ceRNA) network to predict overall survival (OS) and disease-free survival (DFS) respectively. Five reliable hub lncRNAs were identified by integrating differential genes of four Gene Expression Omnibus (GEO) gene chips using the RobustRankAggreg (RRA) method. Based on differential analyses and interaction prediction, a lncRNA-mRNA co-expression network and a lncRNA-miRNA-mRNA ceRNA network were established. Then a comprehensive function characterization of the five hub lncRNAs was performed, including validation dataset testing, receiver operating characteristic (ROC) curve analysis, and functional analysis on two networks. All results suggest that these five hub lncRNAs could be potential biomarkers for marking PTC. The ceRNA network was used to identify RNAs which were associated with PTC prognosis. Two prognostic signatures were developed using univariate and step-wise multivariate Cox regression analyses and both of them were independent prognostic indicators for PTC OS and DFS. Tumor microenvironment difference analysis between high and low-risk patients showed that dendritic cells activated and macrophages M0 may be a possible target for immunotherapy of PTC. In addition, disclosing the potential drugs that may reverse the expression of hub genes may improve the prognosis of patients with PTC. Here, connectivity map (CMap) analysis indicates that three bioactive chemicals (pioglitazone, benserazide, and SB-203580) are promising therapeutic agents for PTC. So, the paper presents a comprehensive study on diagnosis, prognosis, and potential drug screening for PTC based on the five hub lncRNAs identified by us.

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