Clinical and Translational Research
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
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 by the 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
Abstract
BACKGROUND

In recently diagnosed patients with thyroid cancer, papillary thyroid cancer (PTC), as the most common histological subtype, accounts for 90% of all cases. Although PTC is known as a relatively adolescent malignant disease, there still is a high possibility of recurrence in PTC patients with a poor prognosis. Therefore, new biomarkers are necessary to guide more effective stratification of PTC patients and personalize therapy to avoid overtreatment or inadequate treatment. Accumulating evidence demonstrates that microRNAs (miRNAs) have broad application prospects as diagnostic biomarkers in cancer.

AIM

To explore novel markers consisting of miRNA-associated signatures for PTC prognostication.

METHODS

We obtained and analyzed the data of 497 PTC patients from The Cancer Genome Atlas. The patients were randomly assigned to either a training or testing cohort.

RESULTS

We discovered 237 differentially expressed miRNAs in tumorous thyroid tissues compared with normal tissues, which contained 172 up-regulated and 65 down-regulated miRNAs. The evaluation of differently expressed miRNAs was conducted using our risk score model. We then successfully generated a four-miRNA potential prognostic signature [risk score = (-0.001 × hsa-miR-181a-2-3p) + (0.003 × hsa-miR-138-5p) + (-0.018 × hsa-miR-424-3p) + (0.284 × hsa-miR-612)], which reliably distinguished patients from high and low risk with a significant difference in the overall survival (P < 0.01) and was effective in predicting the five-year disease survival rate with the area under the receiver operating characteristic curve of 0.937 and 0.812 in the training and testing cohorts, respectively. Additionally, there was a trend indicated that high-risk patients had shorter relapse-free survival, although statistical significance was not reached (P = 0.082) in our sequencing cohort.

CONCLUSION

Our results indicated a four-miRNA signature that has a robust predictive effect on the prognosis of PTC. Accordingly, we would recommend more radical therapy and closer follow-ups for high-risk groups.

Keywords: Papillary thyroid cancer; microRNA; Prognosis; Signature

Core Tip: Thyroid cancer is the most prevalent endocrine malignancy in the world, and its incidence is rapidly rising. In this paper, an efficient and accurate prognostic prediction model for thyroid cancer was constructed, which is valuable for future clinical studies.