Next Article in Journal
Deciphering Structural Photophysics of Fluorescent Proteins by Kinetic Crystallography
Next Article in Special Issue
Differentiated Thyroid Cancer—Treatment: State of the Art
Previous Article in Journal
Micro-RNAs as Potential Predictors of Response to Breast Cancer Systemic Therapy: Future Clinical Implications
Previous Article in Special Issue
Impact of Gravity on Thyroid Cells
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Int. J. Mol. Sci. 2017, 18(6), 1184; doi:10.3390/ijms18061184

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

1
Department of Nuclear Medicine and Endocrine Oncology, Maria Sklodowska-Curie Institute—Oncology Center, Gliwice Branch, Wybrzeze Armii Krajowej 15, 44-101 Gliwice, Poland
2
Laboratory of Molecular Neurobiology, Neurobiology Center, Nencki Institute of Experimental Biology, Pasteura 3, 02-093 Warsaw, Poland
3
Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 2A, 44-100 Gliwice, Poland
4
The Oncologic and Reconstructive Surgery Clinic, Maria Sklodowska-Curie Institute—Oncology Center, Gliwice Branch, Wybrzeze Armii Krajowej 15, 44-101 Gliwice, Poland
5
Department of Oncology & Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
6
Department of General, Visceral, and Transplantation Surgery, University Medical Center of the Johannes Gutenberg University, D55099 Mainz, Germany
7
Department of Clinical Science, University of Bergen, 5020 Bergen, Norway
8
Genomic Medicine, Department of General, Transplant, and Liver Surgery, Medical University of Warsaw, Zwirki i Wigury 61, 02-093 Warsaw, Poland
9
Tumor Pathology Department, Maria Sklodowska-Curie Institute—Oncology Center, Gliwice Branch, Wybrzeze Armii Krajowej 15, 44-101 Gliwice, Poland
10
Department of Pathology, Martin Luther University Halle-Wittenberg, 06108 Halle (Saale), Germany
11
III Department of Radiotherapy and Chemotherapy, Maria Sklodowska-Curie Institute—Oncology Center, Gliwice Branch, Wybrzeze Armii Krajowej 15, 44-101 Gliwice, Poland
12
Division of Endocrinology, Departments of Medicine, Pathology, Biochemistry & Molecular Biology, and Oncology, and Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta T2N 4N1, Canada
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Daniela Gabriele Grimm
Received: 3 April 2017 / Revised: 26 May 2017 / Accepted: 28 May 2017 / Published: 2 June 2017
(This article belongs to the Special Issue Current Knowledge in Thyroid Cancer—From Bench to Bedside)
View Full-Text   |   Download PDF [2372 KB, uploaded 5 June 2017]   |  

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. View Full-Text
Keywords: follicular thyroid adenoma; follicular thyroid cancer; gene expression; microarray; meta-analysis follicular thyroid adenoma; follicular thyroid cancer; gene expression; microarray; meta-analysis
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Wojtas, B.; Pfeifer, A.; Oczko-Wojciechowska, M.; Krajewska, J.; Czarniecka, A.; Kukulska, A.; Eszlinger, M.; Musholt, T.; Stokowy, T.; Swierniak, M.; Stobiecka, E.; Chmielik, E.; Rusinek, D.; Tyszkiewicz, T.; Halczok, M.; Hauptmann, S.; Lange, D.; Jarzab, M.; Paschke, R.; Jarzab, B. Gene Expression (mRNA) Markers for Differentiating between Malignant and Benign Follicular Thyroid Tumours. Int. J. Mol. Sci. 2017, 18, 1184.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Int. J. Mol. Sci. EISSN 1422-0067 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top