MiR-9 and miR-21 as prognostic biomarkers for recurrence in papillary thyroid cancer

2015 ◽  
Vol 32 (6) ◽  
pp. 521-530 ◽  
Author(s):  
Adriana Sondermann ◽  
Flavia Maziero Andreghetto ◽  
Ana Carolina Bernardini Moulatlet ◽  
Elivane da Silva Victor ◽  
Marilia Germanos de Castro ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Prognostic Biomarkers ◽  
Papillary Thyroid

scholarly journals Comprehensive Analysis of Prognostic Alternative Splicing Signature Reveals Recurrence Predictor for Papillary Thyroid Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Mian Liu ◽  
Rooh Afza Khushbu ◽  
Pei Chen ◽  
Hui-Yu Hu ◽  
Neng Tang ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Alternative Splicing ◽  
Papillary Thyroid Cancer ◽  
Molecular Mechanisms ◽  
Prediction Models ◽  
Cox Regression ◽  
Prognostic Biomarkers ◽  
Papillary Thyroid ◽  
Network Diagram ◽  
Prognostic Prediction

BackgroundAlternative splicing (AS) plays a key role in the diversity of proteins and is closely associated with tumorigenicity. The aim of this study was to systemically analyze RNA alternative splicing (AS) and identify its prognostic value for papillary thyroid cancer (PTC).MethodsAS percent-splice-in (PSI) data of 430 patients with PTC were downloaded from the TCGA SpliceSeq database. We successfully identified recurrence-free survival (RFS)-associated AS events through univariate Cox regression, LASSO regression and multivariate regression and then constructed different types of prognostic prediction models. Gene function enrichment analysis revealed the relevant signaling pathways involved in RFS-related AS events. Simultaneously, a regulatory network diagram of AS and splicing factors (SFs) was established.ResultsWe identified 1397 RFS-related AS events which could be used as the potential prognostic biomarkers for PTC. Based on these RFS-related AS events, we constructed a ten-AS event prognostic prediction signature that could distinguish high-and low-risk patients and was highly capable of predicting PTC patient prognosis. ROC curve analysis revealed the excellent predictive ability of the ten-AS events model, with an area under the curve (AUC) value of 0.889; the highest prediction intensity for one-year RFS was 0.923, indicating that the model could be used as a prognostic biomarker for PTC. In addition, the nomogram constructed by the risk score of the ten-AS model also showed high predictive efficiency for the prognosis of PTC patients. Finally, the constructed SF-AS network diagram revealed the regulatory role of SFs in PTC.ConclusionThrough the limited analysis, AS events could be regarded as reliable prognostic biomarkers for PTC. The splicing correlation network also provided new insight into the potential molecular mechanisms of PTC.

Abstract #1086: Patient Experience with Severe Low Energy Following Total Thyroidectomy for Papillary Thyroid Cancer

2017 ◽  
Vol 23 ◽  
pp. 258
Author(s):  
Elizabeth Wendt ◽  
Maria Bates ◽  
Reese Randle ◽  
Jason Orne ◽  
Cameron Macdonald ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Total Thyroidectomy ◽  
Papillary Thyroid Cancer ◽  
Patient Experience ◽  
Low Energy ◽  
Papillary Thyroid

Examination of CYP24A1 and ‘three-genes' (SFN, MRC2, HMGA2) expressions in different pathological subgroups of human papillary thyroid cancer

2013 ◽  
Author(s):  
Bernadett Balla ◽  
Janos Kosa ◽  
Balint Tobias ◽  
Istvan Takacs ◽  
Zsolt Nagy ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Papillary Thyroid

In papillary thyroid cancer TERT promoter mutations have a worst impact on outcome than BRAF mutations

2015 ◽  
Author(s):  
Marina Muzza ◽  
Carla Colombo ◽  
Maria Carla Proverbio ◽  
Stefania Rossi ◽  
Delfina Tosi ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Papillary Thyroid ◽  
Braf Mutations ◽  
Tert Promoter ◽  
Tert Promoter Mutations ◽  
Promoter Mutations
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