Class distinction between follicular adenomas and follicular carcinomas of the thyroid gland on the basis of their signature expression

BACKGROUND Nodules of the thyroid gland are observed frequently in patients who undergo ultrasound studies. The majority of these nodules are benign, corresponding to goiters or adenomas, and only a small fraction corresponds to carcinomas. Among thyroid tumors, the diagnosis of follicular adenocarc...

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Bibliographic Details
Published in:Cancer 2006-05, Vol.106 (9), p.1891-1900
Main Authors: Stolf, Beatriz S., Santos, Mariana M. S., Simao, Daniel F., Diaz, Juan P., Cristo, Elier B., Hirata, Roberto, Curado, Maria P., Neves, Eduardo J., Kowalski, Luiz P., Carvalho, Alex F.
Format: Article
Language:English
Subjects:
Adenocarcinoma, Follicular - classification
Adenocarcinoma, Follicular - genetics
adenoma
Adenoma - classification
Adenoma - genetics
Biological and medical sciences
Endocrinopathies
follicular carcinoma
Gene Expression Profiling
Humans
Malignant tumors
Medical sciences
molecular classifiers
thyroid
Thyroid Neoplasms - classification
Thyroid Neoplasms - genetics
Thyroid. Thyroid axis (diseases)
Tumors
ultrasound
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Summary:BACKGROUND Nodules of the thyroid gland are observed frequently in patients who undergo ultrasound studies. The majority of these nodules are benign, corresponding to goiters or adenomas, and only a small fraction corresponds to carcinomas. Among thyroid tumors, the diagnosis of follicular adenocarcinomas by preoperative fine‐needle aspiration biopsy is a major challenge, because it requires inspection of the entire capsule to differentiate it from adenoma. Consequently, large numbers of patients undergo unnecessary thyroidectomy. METHODS Using data from gene expression analysis, the authors applied Fisher linear discriminant analysis and searched for expression signatures of individual samples of adenomas and follicular carcinomas that could be used as molecular classifiers for the precise classification of malignant and nonmalignant lesions. RESULTS Fourteen trios of genes were described that fulfilled the criteria for the correct classification of 100% of samples. The robustness of these trios was verified by using leave‐1‐out cross‐validation and bootstrap analyses. The results demonstrated that, by combining trios, better classifiers could be generated that correctly classified >92% of samples. CONCLUSIONS The strategy of classifiers based on individual signatures was a useful strategy for distinguishing between samples with very similar expression profiles. Cancer 2006. © 2006 American Cancer Society. The authors used data from gene expression analysis to search for expression signatures of individual samples of adenomas and follicular carcinomas that could be used as molecular classifiers for the precise classification of malignant and nonmalignant lesions. The results indicated that these classifiers may have value as diagnostic tools in fine‐needle aspiration biopsy samples and, ultimately, may help to reduce the numbers of patients who undergo unnecessary thyroidectomy.
ISSN:0008-543X
1097-0142
DOI:10.1002/cncr.21826