Yang F, Zhou YL. Identification of a four-miRNA signature predicts the prognosis of papillary thyroid cancer. World J Clin Cases 2023; 11(1): 92-103 [PMID: 36687184 DOI: 10.12998/wjcc.v11.i1.92]
Corresponding Author of This Article
Yi-Li Zhou, MD, PhD, Doctor, Department of Thyroid Surgery, The First Affiliated Hospital of Wenzhou Medical University, South of Bai-Xiang Street, Ou-Hai District, Wenzhou 325000, Zhejiang Province, China. yilistar@163.com
Research Domain of This Article
Oncology
Article-Type of This Article
Clinical and Translational Research
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Clin Cases. Jan 6, 2023; 11(1): 92-103 Published online Jan 6, 2023. doi: 10.12998/wjcc.v11.i1.92
Identification of a four-miRNA signature predicts the prognosis of papillary thyroid cancer
Fan Yang, Yi-Li Zhou
Fan Yang, Yi-Li Zhou, Department of Thyroid Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang Province, China
Author contributions: Yang F and Zhou YL designed the research study, performed the research, and wrote the manuscript; all authors have read and approved the final manuscript.
Supported bythe Foundation of Wenzhou Municipal Science and Technology Bureau, No. Y20190209 and No. Y2020739; and the Hospital Research Incubation Program, No. FHY2019075.
Institutional review board statement: The study was reviewed and approved by Ethics Committee of The First Affiliated Hospital of Wenzhou Medical University (Approval No. 2022-69).
Informed consent statement: Patients were not required to give informed consent to the study because this study is a bioinformatics analysis and the required patient information was downloaded from the TCGA database.
Conflict-of-interest statement: All other authors have nothing to disclose.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yi-Li Zhou, MD, PhD, Doctor, Department of Thyroid Surgery, The First Affiliated Hospital of Wenzhou Medical University, South of Bai-Xiang Street, Ou-Hai District, Wenzhou 325000, Zhejiang Province, China. yilistar@163.com
Received: September 28, 2022 Peer-review started: September 28, 2022 First decision: November 4, 2022 Revised: November 10, 2022 Accepted: December 21, 2022 Article in press: December 21, 2022 Published online: January 6, 2023 Processing time: 98 Days and 14.5 Hours
ARTICLE HIGHLIGHTS
Research background
Papillary thyroid cancer is a highly heterogeneous disease and therefore molecular markers need to be established to predict its prognosis.
Research motivation
The present study aims to explore novel markers consisting of microRNA (miRNA)-associated signatures for papillary thyroid cancer (PTC) prognostication.
Research objectives
To establish a practical tool has satisfying potential in stratifying PTC patients and individualized therapy to avoid overtreatment or inadequate treatment.
Research methods
In this study, a panel of four miRNAs is generated as a prognostic signature, which is then tested in PTC patients.
Research results
The panel of four miRNAs could reliably distinguished PTC patients from high and low risk with a significant difference in the overall survival.
Research conclusions
More intensive treatment and closer follow-ups for high-risk PTC patients are recommended.
Research perspectives
Our prognostic signature contributed to individualized therapy to avoid overtreatment or inadequate treatment.
