Gene Expression (mRNA) Markers for Differentiating between Malignant and Benign Follicular Thyroid Tumours

Bartosz Wojtas, Aleksandra Pfeifer, Malgorzata Oczko-Wojciechowska, Jolanta Krajewska, Agnieszka Czarniecka, Aleksandra Kukulska, Markus Eszlinger, Thomas Musholt, Tomasz Stokowy, Michal Swierniak, Ewa Stobiecka, Ewa Chmielik, Dagmara Rusinek, Tomasz Tyszkiewicz, Monika Halczok, Steffen Hauptmann, Dariusz Lange, Michal Jarzab, Ralf Paschke, Barbara Jarzab*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

20 Citations (Web of Science)

Abstract

Distinguishing between follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA) constitutes a long-standing diagnostic problem resulting in equivocal histopathological diagnoses. There is therefore a need for additional molecular markers. To identify molecular differences between FTC and FTA, we analyzed the gene expression microarray data of 52 follicular neoplasms. We also performed a meta-analysis involving 14 studies employing high throughput methods (365 follicular neoplasms analyzed). Based on these two analyses, we selected 18 genes differentially expressed between FTA and FTC. We validated them by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent set of 71 follicular neoplasms from formaldehyde-fixed paraffin embedded (FFPE) tissue material. We confirmed differential expression for 7 genes (CPQ, PLVAP, TFF3, ACVRL1, ZFYVE21, FAM189A2, and CLEC3B). Finally, we created a classifier that distinguished between FTC and FTA with an accuracy of 78%, sensitivity of 76%, and specificity of 80%, based on the expression of 4 genes (CPQ, PLVAP, TFF3, ACVRL1). In our study, we have demonstrated that meta-analysis is a valuable method for selecting possible molecular markers. Based on our results, we conclude that there might exist a plausible limit of gene classifier accuracy of approximately 80%, when follicular tumors are discriminated based on formalin-fixed postoperative material.

Original languageEnglish
Article number1184
Number of pages19
JournalInternational journal of molecular sciences
Volume18
Issue number6
DOIs
Publication statusPublished - Jun 2017

Keywords

  • follicular thyroid adenoma
  • follicular thyroid cancer
  • gene expression
  • microarray
  • meta-analysis
  • MOLECULAR MARKERS
  • FUSION ONCOGENE
  • CARCINOMAS
  • CLASSIFICATION
  • NEOPLASMS
  • ADENOMAS
  • NODULES
  • CANCER
  • MODEL
  • ASPIRATION

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