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Journal of Experimental & Clinical Cancer Research
Published in: Journal of Experimental & Clinical Cancer Research 1/2016

Open Access 01-12-2016 | Research

A panel of four genes accurately differentiates benign from malignant thyroid nodules

Authors: Qing-Xuan Wang, En-Dong Chen, Ye-Feng Cai, Quan Li, Yi-Xiang Jin, Wen-Xu Jin, Ying-Hao Wang, Zhou-Ci Zheng, Lu Xue, Ou-Chen Wang, Xiao-Hua Zhang

Published in: Journal of Experimental & Clinical Cancer Research | Issue 1/2016

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Abstract

Background

Clinicians are confronted with an increasing number of patients with thyroid nodules. Reliable preoperative diagnosis of thyroid nodules remains a challenge because of inconclusive cytological examination of fine-needle aspiration biopsies. Although molecular analysis of thyroid tissue has shown promise as a diagnostic tool in recent years, it has not been successfully applied in routine clinical use, particularly in Chinese patients.

Methods

Whole-transcriptome sequencing of 19 primary papillary thyroid cancer (PTC) samples and matched adjacent normal thyroid tissue (NT) samples were performed. Bioinformatics analysis was carried out to identify candidate diagnostic genes. Then, RT-qPCR was performed to evaluate these candidate genes, and four genes were finally selected. Based on these four genes, diagnostic algorithm was developed (training set: 100 thyroid cancer (TC) and 65 benign thyroid lesions (BTL)) and validated (independent set: 123 TC and 81 BTL) using the support vector machine (SVM) approach.

Results

We discovered four genes, namely fibronectin 1 (FN1), gamma-aminobutyric acid type A receptor beta 2 subunit (GABRB2), neuronal guanine nucleotide exchange factor (NGEF) and high-mobility group AT-hook 2 (HMGA2). A SVM model with these four genes performed with 97.0 % sensitivity, 93.8 % specificity, 96.0 % positive predictive value (PPV), and 95.3 % negative predictive value (NPV) in training set. For additional independent validation, it also showed good performance (92.7 % sensitivity, 90.1 % specificity, 93.4 % PPV, and 89.0 % NPV).

Conclusions

Our diagnostic panel can accurately distinguish benign from malignant thyroid nodules using a simple and affordable method, which may have daily clinical application in the near future.
Appendix
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Metadata
Title
A panel of four genes accurately differentiates benign from malignant thyroid nodules
Authors
Qing-Xuan Wang
En-Dong Chen
Ye-Feng Cai
Quan Li
Yi-Xiang Jin
Wen-Xu Jin
Ying-Hao Wang
Zhou-Ci Zheng
Lu Xue
Ou-Chen Wang
Xiao-Hua Zhang
Publication date
01-12-2016
Publisher
BioMed Central
Published in
Journal of Experimental & Clinical Cancer Research / Issue 1/2016
Electronic ISSN: 1756-9966
DOI
https://doi.org/10.1186/s13046-016-0447-3

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