Perspectives for improved and more accurate classification of thyroid epithelial tumors.
BACKGROUND
Histologic examination of thyroid nodules is the current standard to distinguish benign from malignant thyroid epithelial tumors and to classify histologic subtypes. This review analyzes the problems in histological differential diagnosis as well as contradictions between histology and molecular data and describes possibilities to combine histology with molecular data in an effort to more accurately classify thyroid epithelial tumors.


METHODS
Published literature, addressing the current recommendations for thyroid tumor classification, as well as literature on the application of histology and molecular studies on the etiology of thyroid tumors is analyzed.


RESULTS
The current histologic criteria to classify thyroid tumors, especially follicular-patterned tumors, are hampered by considerable interobserver variability. The detection of somatic mutations via genotyping and the definition of potentially informative gene expression signatures by microarray analyses, which can distinguish cancer subtypes as well as low- and high-risk cohorts, have recently demonstrated significant diagnostic potential. Moreover, in a routine diagnostic setting, micro-RNA profiling appears most promising due to their relative stability and the high accuracy of their expression profiles.


CONCLUSIONS
It is very likely that molecular definitions of thyroid tumors mentioned in the current World Health Organization classification will be further developed, leading to future progress in defining thyroid tumor types by an integrated histologic and molecular approach. These integrated classifications need to be evaluated for their specific impact on thyroid tumor diagnosis and prognosis.
Eszlinger
Markus
M
Third Medical Department, University of Leipzig, D-04103 Leipzig, Germany.
Krohn
Knut
K
Hauptmann
Steffen
S
Dralle
Henning
H
Giordano
Thomas J
TJ
Paschke
Ralf
R
D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D035683:MicroRNAs / Q000235:genetics; D008954:Models, Biological; D025202:Molecular Diagnostic Techniques; D009367:Neoplasm Staging / Q000379:methods* / Q000639:trends; D009375:Neoplasms, Glandular and Epithelial / Q000145:classification* / Q000175:diagnosis / Q000235:genetics / Q000473:pathology*; D040901:Proteomics / Q000379:methods / Q000639:trends; D013964:Thyroid Neoplasms / Q000145:classification* / Q000175:diagnosis / Q000235:genetics / Q000473:pathology*
D035683:MicroRNAs