Use of long non-coding RNAs for the molecular diagnosis of papillary thyroid cancer

Daham Kim, Juyeon Yu, Jiwon Kim, Yoon A. Hwang, Jin Kyong Kim, Cheol Ryong Ku, Jung Hyun Yoon, Jin Young Kwak, Kee Hyun Nam, Eun Jig Lee

Research output: Contribution to journalArticlepeer-review


Objective: Improved molecular testing for common somatic mutations and the identification of mRNA and microRNA expression classifiers are promising approaches for the diagnosis of thyroid nodules. However, there is a need to improve the diagnostic accuracy of such tests for identifying thyroid cancer. Recent findings have revealed a crucial role of long non-coding RNAs (lncRNAs) in gene modulation. Thus, we aimed to evaluate the diagnostic value of selected lncRNAs from The Atlas of Noncoding RNAs in Cancer (TANRIC) thyroid cancer dataset. Methods: LncRNAs in TANRIC thyroid cancer dataset that have significantly increased or decreased expression in papillary thyroid cancer (PTC) tissues were selected as candidates for PTC diagnosis. Surgical specimens from patients who underwent thyroidectomy were used to determine the separation capability of candidate lncRNAs between malignant and benign nodules. Fine needle aspiration samples were obtained and screened for candidate lncRNAs to verify their diagnostic value. Results: LRRC52-AS1, LINC02471, LINC02082, UNC5B-AS1, LINC02408, MPPED2-AS1, LNCNEF, LOC642484, ATP6V0E2-AS1, and LOC100129129 were selected as the candidate lncRNAs. LRRC52-AS1, LINC02082, UNC5B-AS1, MPPED2-AS1, LNCNEF, and LOC100129129 expression levels were significantly increased or decreased in malignant nodules compared to those in benign nodules and paired normal thyroid tissues. The combination of LRRC52-AS1, LINC02082, and UNC5B-AS1 showed favorable results for the diagnosis of PTC from fine needle aspirates, with 88.9% sensitivity and 100.0% specificity. Conclusions: LncRNA expression analysis is a promising approach for advancing the molecular diagnosis of PTC. Further studies are needed to identify lncRNAs of additional diagnostic value.

Original languageEnglish
Article number924409
JournalFrontiers in Oncology
Publication statusPublished - 2022 Sept 5

Bibliographical note

Publisher Copyright:
Copyright © 2022 Kim, Yu, Kim, Hwang, Kim, Ku, Yoon, Kwak, Nam and Lee.

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research


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