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. 2016 Jul 19;7(29):45776-45788.
doi: 10.18632/oncotarget.10166.

Identification of CHEK1, SLC26A4, c-KIT, TPO and TG as new biomarkers for human follicular thyroid carcinoma

Anne-Marie Makhlouf  1 , Zhanna Chitikova  1 , Marc Pusztaszeri  2 , Margaret Berczy  2 , Celine Delucinge-Vivier  3 , Frederic Triponez  4 , Patrick Meyer  5 , Jacques Philippe  1   5 , Charna Dibner  1   5
Affiliations

Identification of CHEK1, SLC26A4, c-KIT, TPO and TG as new biomarkers for human follicular thyroid carcinoma

Anne-Marie Makhlouf et al. Oncotarget. .

Abstract

The search for preoperative biomarkers for thyroid malignancies, in particular for follicular thyroid carcinoma (FTC) diagnostics, is of utmost clinical importance. We thus aimed at screening for potential biomarker candidates for FTC. To evaluate dynamic alterations in molecular patterns as a function of thyroid malignancy progression, a comparative analysis was conducted in clinically distinct subgroups of FTC and poorly differentiated thyroid carcinoma (PDTC) nodules. NanoString analysis of FFPE samples was performed in 22 follicular adenomas, 56 FTC and 25 PDTC nodules, including oncocytic and non-oncocytic subgroups. The expression levels of CHEK1, c-KIT, SLC26A4, TG and TPO were significantly altered in all types of thyroid carcinomas. Based on collective changes of these biomarkers which correlating among each other, a predictive score has been established, allowing for discrimination between benign and FTC samples with high sensitivity and specificity. Additional transcripts related to thyroid function, cell cycle, circadian clock, and apoptosis regulation were altered in the more aggressive oncocytic subgroups only, with expression levels correlating with disease progression. Distinct molecular patterns were observed for oncocytic and non-oncocytic FTCs and PDTCs. A predictive score correlation coefficient based on collective alterations of identified here biomarkers might help to improve the preoperative diagnosis of FTC nodules.

Keywords: NanoString analysis; diagnostic biomarkers; follicular thyroid carcinoma; poorly differentiated thyroid carcinoma.

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Conflict of interest statement

The authors declare that there is no duality of interest associated with this manuscript.

Figures

Figure 1
Figure 1. Scatter plot of the gene expression-based predictive score correlated with FTC aggressiveness
The gene expression-based score for benign and FTC samples was calculated based on joint expression levels of CHEK1, c-KIT, SLC26A4, TG and TPO transcripts. Thus obtained score values were plotted for three clusters: benign, non-oncocytic FTC and oncocytic FTC, and allowed for a clear distinction between these groups.
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