Diagnosis of suspicious thyroid nodules using four protein biomarkers.

PURPOSE

Fine-needle aspiration (FNA) cytology, a standard method for thyroid nodule diagnosis, cannot distinguish between benign follicular thyroid adenoma (FTA) and malignant follicular thyroid carcinoma (FTC). Previously, using expression profiling, we found that a combination of transcript expression levels from DDIT3, ARG2, C1orf24, and ITM1 distinguished between FTA and FTC. The goal of this study was to determine if antibody markers used alone or in combination could accurately distinguish between a wider variety of benign and malignant thyroid lesions in fixed sections and FNA samples.

EXPERIMENTAL DESIGN

Immunohistochemistry was done on 27 FTA, 25 FTC, and 75 other benign and malignant thyroid tissue sections using custom antibodies for chromosome 1 open reading frame 24 (C1orf24) and integral membrane protein 1 (ITM1) and commercial antibodies for DNA damage-inducible transcript 3 (DDIT3) and arginase II (ARG2). FNA samples were also tested using the same antibodies. RNA expression was measured by quantitative PCR in 33 thyroid lesions.

RESULTS

C1orf24 and ITM1 antibodies had an estimated sensitivity of 1.00 for distinguishing FTA from FTC. For the expanded analysis of all lesions studied, ITM1 had an estimated sensitivity of 1.00 for detecting malignancy. Because all four cancer biomarkers did well, producing overlapping confidence intervals, not one best marker was distinguished. Transcript levels also reliably predicted malignancy, but immunohistochemistry had a higher sensitivity. Malignant cells were easily detected in FNA samples using these markers.

CONCLUSIONS

We improved this diagnostic test by adding C1orf24 and ITM1 custom antibodies and showing use on a wider variety of thyroid pathology. We recommend that testing of all four cancer biomarkers now be advanced to larger trials. Use of one or more of these antibodies should improve diagnostic accuracy of suspicious thyroid nodules from both tissue sections and FNA samples.