title: Expression profiling of difficult-to-diagnose thyroid histologic subtypes shows distinct expression profiles and identify candidate diagnostic microRNAs.
abstract: BACKGROUND
  The incidence of thyroid cancer is increasing worldwide. The findings of up to 30% of thyroid fine-needle aspiration biopsies (FNAB) are inconclusive, primarily as a result of several thyroid histologic subtypes with overlapping cytologic features. MicroRNAs (miRNAs) are small noncoding RNAs and have been implicated in carcinogenesis. We hypothesized that there are miRNAs that are differentially expressed between benign and malignant thyroid tumors that are difficult to distinguish by FNAB.
  
  
  METHODS
  The expression of 1263 human miRNAs was profiled in 47 tumor samples representing difficult to diagnose histologic subtypes of thyroid neoplasm (21 benign, 26 malignant). Differentially expressed miRNAs were validated by quantitative real-time reverse transcriptase-polymerase chain reaction. The area under the receiver operating characteristic curve (AUC) was used to determine the diagnostic accuracy of differentially expressed miRNAs.
  
  
  RESULTS
  Supervised hierarchical cluster analysis demonstrated grouping of 2 histologies (papillary and follicular thyroid carcinoma). A total of 34 miRNAs were differentially expressed in malignant compared to benign thyroid neoplasms (P<0.05). A total of 25 of the 34 nonproprietary miRNAs were selected for validation, and 15 of the 25 miRNAs were differentially expressed between benign and malignant samples with P-value<0.05. Seven miRNAs had AUC values of >0.7. miR-7 and miR-126 had the highest diagnostic accuracy with AUCs values of 0.81 and 0.77, respectively.
  
  
  CONCLUSIONS
  To our knowledge, this is the first study to evaluate the diagnostic accuracy of miRNAs in thyroid histologies that are difficult to distinguish as benign or malignant by FNAB. miR-126 and miR-7 had high diagnostic accuracy and could be helpful adjuncts to thyroid FNAB.
authors.affiliation: Endocrine Oncology Section, Surgery Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
authors.forename: Mio
authors.initials: M
authors.lastname: Kitano
authors.forename: Reza
authors.initials: R
authors.lastname: Rahbari
authors.forename: Erin E
authors.initials: EE
authors.lastname: Patterson
authors.forename: Yin
authors.initials: Y
authors.lastname: Xiong
authors.forename: Nijaguna B
authors.initials: NB
authors.lastname: Prasad
authors.forename: Yongchun
authors.initials: Y
authors.lastname: Wang
authors.forename: Martha A
authors.initials: MA
authors.lastname: Zeiger
authors.forename: Electron
authors.initials: E
authors.lastname: Kebebew
mesh_terms: D018263:Adenocarcinoma, Follicular / Q000175:diagnosis / Q000235:genetics*; D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000235:genetics*; D044963:Biopsy, Fine-Needle; D020869:Gene Expression Profiling; D006801:Humans; D035683:MicroRNAs / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D012372:ROC Curve; D060888:Real-Time Polymerase Chain Reaction; D013964:Thyroid Neoplasms / Q000145:classification* / Q000175:diagnosis / Q000235:genetics*
chemical_list: D014408:Biomarkers, Tumor; D035683:MicroRNAs