title: Evaluation of gene expression profiles in thyroid nodule biopsy material to diagnose thyroid cancer.
abstract: BACKGROUND
  Detection of thyroid cancer among benign nodules on fine-needle aspiration biopsies (FNAB), which presently relies on cytological examination, is expected to be improved by new diagnostic tests set up from genomic data.
  
  
  OBJECTIVE
  The aim of the study was to use a set of genes discriminating benign from malignant tumors, on the basis of their expression levels, to build tumor classifiers and evaluate their capacity to predict malignancy on FNAB.
  
  
  METHODS
  We analyzed the level of expression of 200 potentially informative genes in 56 thyroid tissue samples (benign or malignant tumors and paired normal tissue) using nylon macroarrays. Gene expression data were subjected to a weighted voting algorithm to generate tumor classifiers. The performances of the classifiers were evaluated on a series of 26 sham FNAB, i.e. FNAB carried out on thyroid nodules after surgical resection.
  
  
  RESULTS
  A series of 19 genes with a similar expression in follicular adenomas and normal tissue and discriminating follicular adenomas+normal tissue from the following: 1) follicular thyroid carcinomas (FTCs), 2) papillary thyroid carcinomas (PTCs), or 3) both FTCs and PTCs. These were used to generate four classifiers, the FTCs, PTCs, common (FTC+PTCs), and global classifiers. In 23 of the 26 sham FNAB, the four classifiers yielded a diagnosis in agreement with the diagnosis of the pathologist used as reference; in the three other cases, the correct diagnosis was given by three of four classifiers.
  
  
  CONCLUSIONS
  We developed a procedure of molecular diagnosis of benign vs. malignant tumors applicable to the material collected by FNAB. The molecular test complied with a preclinical validation stage; it must be now evaluated on ultrasound-guided FNAB in a large-scale prospective study.
authors.affiliation: Institut National de la Santé et de la Recherche Médicale, Unité Mixte de Recherche 664, Université Lyon 1, Lyon, France.
authors.forename: Stéphanie
authors.initials: S
authors.lastname: Durand
authors.forename: Carole
authors.initials: C
authors.lastname: Ferraro-Peyret
authors.forename: Samia
authors.initials: S
authors.lastname: Selmi-Ruby
authors.forename: Christian
authors.initials: C
authors.lastname: Paulin
authors.forename: Michelle
authors.initials: M
authors.lastname: El Atifi
authors.forename: François
authors.initials: F
authors.lastname: Berger
authors.forename: Nicole
authors.initials: N
authors.lastname: Berger-Dutrieux
authors.forename: Myriam
authors.initials: M
authors.lastname: Decaussin
authors.forename: Jean-Louis
authors.initials: JL
authors.lastname: Peix
authors.forename: Claire
authors.initials: C
authors.lastname: Bournaud
authors.forename: Jacques
authors.initials: J
authors.lastname: Orgiazzi
authors.forename: Françoise
authors.initials: F
authors.lastname: Borson-Chazot
authors.forename: Bernard
authors.initials: B
authors.lastname: Rousset
mesh_terms: D000328:Adult; D001707:Biopsy, Needle; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D020133:Reverse Transcriptase Polymerase Chain Reaction; D013964:Thyroid Neoplasms / Q000175:diagnosis*; D016606:Thyroid Nodule / Q000378:metabolism* / Q000473:pathology