Affiliations: Department of Otolaryngology-Head and Neck Surgery, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea
Correspondence:
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Corresponding author: Dong Jin Lee, 1 Singil-ro Yeongdeungpo-gu, Seoul 150-950, Korea. Tel.: +82 2 829 5217; Fax: +82 2 842 5217; E-mail: [email protected].
Abstract: BACKGROUND: Cervical lymph node metastases (LNM) in papillary thyroid carcinomas (PTCs) are common and develop in approximately 30–80% of PTCs. The presence of cervical LNM significantly increases the rate of locoregional recurrence in PTCs. OBJECTIVE: To search for predictive gene signatures for nodal metastasis in PTCs. METHODS: We used unsupervised clustering with unbiased manner to compare molecular profiles between PTCs with nodal metastasis and PTCs without nodal metastasis using mRNA-seq of TCGA data. Using gene ontology (GO) and logistic regression test, we generated 12-predictive genes for nodal metastasis in PTCs. RESULTS: Unsupervised clustering of mRNA-seq (training set, N = 158) revealed that PTCs with nodal metastasis showed different gene expression patterns compared to PTCs without nodal metastasis. We generated 12 predictive genes and these gene signatures showed consistency for predicting nodal metastasis when we applied them to a validation set (N = 80). Based on multivariate analysis, these 12 predictive gene signatures showed more significant odds ratio compared to other variables. CONCLUSIONS: These 12 gene signatures could be used to predict the chance of nodal metastasis in PTCs in preoperative evaluation using fine needle aspiration biopsy (FNAB) so that appropriate plan such as central neck dissection could be made.
