Differential gene expression profiling of aggressive and nonaggressive follicular carcinomas.

The classification of follicular thyroid neoplasms requires surgical resection for histologic evaluation of malignancy. Because variable clinical behavior exists, genomic expression profiling may lead to the identification of novel markers that facilitate better biologic classification. We performed for the first time gene expression analysis on clinically aggressive and nonaggressive follicular carcinomas (FCs) from patients for whom long-term follow-up data were available. We examined matched fresh-frozen tissue from 15 histopathologically diagnosed follicular carcinomas (7 patients with documented distant metastasis and/or death from disease and 8 patients without recurrence). For categorical comparison, we analyzed 4 follicular adenomas (FAs). The biologic control comprised 11 normal thyroid tissue specimens. High-quality RNA was extracted from the tissues, labeled, and hybridized to an Affymetrix (Santa Clara, CA) oligonucleotide microarray (HG-U133A). With the exceptions of 1 follicular adenoma and 1 follicular carcinoma, unsupervised hierarchical cluster analysis revealed 2 distinct groups--one containing normal thyroid tissue and follicular adenomas and another containing follicular carcinomas. We identified 421 genes that were differentially expressed between histologically normal thyroid tissues and all follicular neoplasms (P < 0.01; fold-change >2), 94 genes that distinguished follicular carcinomas from follicular adenomas (including PBP and CKS2), and 4 genes that distinguished aggressive follicular carcinomas from nonaggressive follicular carcinomas (NID2, TM7SF2, TRIM2, and GLTSCR2). Comparative genomic groupings identified differentially expressed genes that may lead to better classification of follicular thyroid neoplasms. Such genes may be used in future prospective validation studies to establish clinically useful and complementary diagnostic markers.

Duke Scholars

Author Danielle Elliott Range Pathology