1. Potential five‑mRNA signature model for the prediction of prognosis in patients with papillary thyroid carcinoma
- Author
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Lin‑Kun Zhong, Xiao‑Xiong Gan, Xing‑Yan Deng, Bo Xu, Qiong‑Yao Liu, Fei Shen, Wen‑Song Cai, Jian‑Hua Feng, Bing‑Xing Zheng, and Jian‑Hang Miao
- Subjects
0301 basic medicine ,Cancer Research ,Messenger RNA ,endocrine system diseases ,mRNAs ,Articles ,Enzyme inhibitor activity ,Biology ,Thyroid carcinoma ,03 medical and health sciences ,030104 developmental biology ,0302 clinical medicine ,Oncology ,030220 oncology & carcinogenesis ,Gene expression ,papillary thyroid carcinoma ,Cancer research ,prognosis ,Calcium ion binding ,Glutathione transferase activity ,KEGG ,Gene - Abstract
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
- Published
- 2020