Advancing the molecular diagnosis of thyroid nodules: defining benign lesions by molecular profiling. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Thyroid nodules are common and most are benign. Previous data from our laboratory and others has suggested that gene profiling can accurately distinguish between benign and malignant thyroid nodules and provide new leads in the study of thyroid tumorigenesis. Current preoperative techniques do not permit distinction between neoplastic and hyperplastic follicular neoplasms. These studies were undertaken to determine whether benign follicular tumors could be subcategorized by molecular profiling. METHODS: Molecular profiles of 8 follicular adenomas and 8 hyperplastic nodules were analyzed by oligonucleotide microarray analysis. A list of 402 differentially expressed genes was produced based on a comparison of these two groups. Seven additional benign follicular lesions were then added to the analysis. A hierarchical clustering analysis was performed on all 23 samples, utilizing the gene list generated from the test set, to examine the groups for potential differences and the ability of the gene list to distinguish tumor types. RESULTS: Cluster analysis of all 23 samples produced two distinct groups, one containing the adenomas and one containing the hyperplastic lesions. The analysis was able to identify follicular adenomas with a sensitivity of 84.6% and a specificity of 100%. CONCLUSIONS: These data indicate that benign thyroid lesions can be separated into distinct groups through molecular profiling. Analysis of the gene list may help further the understanding of thyroid tumorigenesis. Expression profiling may ultimately allow us to distinguish potentially malignant from benign follicular nodules.

publication date

  • June 1, 2005

Research

keywords

  • Gene Expression Profiling
  • Thyroid Neoplasms
  • Thyroid Nodule

Identity

Scopus Document Identifier

  • 22244449660

PubMed ID

  • 16029122

Additional Document Info

volume

  • 15

issue

  • 6