YKL-40 is a differential diagnostic marker for histologic subtypes of high-grade gliomas.
PURPOSE AND EXPERIMENTAL DESIGN: In modern neuro-oncology, no variable affects therapeutic decisions and prognostic estimation more than tumor classification. We showed recently that class prediction models, based on gene expression profiles, classify diagnostically challenging malignant gliomas in a manner that better correlates with clinical outcome than standard pathology. In the present study, we used immunohistochemistry to investigate YKL-40 protein expression in independent sets of glioblastomas and anaplastic oligodendrogliomas to determine whether this single marker can aid classification of these high-grade gliomas. RESULTS AND CONCLUSIONS: Glioblastomas show strikingly more YKL-40 expression than anaplastic oligodendrogliomas. Only 2 of 37 glioblastomas showed completely negative YKL-40 staining in both tumor cells and extracellular matrix, whereas 18 of 29 anaplastic oligodendrogliomas were completely negative in non-microgemistocytic tumor cells and extracellular matrix. Tumor cell staining intensity was also markedly different: 84% of glioblastomas showed strong staining intensities of 2+ or 3+ whereas 76% of anaplastic oligodendrogliomas either did not stain or stained at only 1+. YKL-40 staining provided a better class distinction of glioblastoma versus anaplastic oligodendroglioma than glial fibrillary acidic protein, the current standard immunohistochemical marker used to distinguish diagnostically challenging gliomas. Moreover, a combination of YKL-40 and glial fibrillary acidic protein immunohistochemistry afforded even greater diagnostic accuracy in anaplastic oligodendrogliomas.[1]References
- YKL-40 is a differential diagnostic marker for histologic subtypes of high-grade gliomas. Nutt, C.L., Betensky, R.A., Brower, M.A., Batchelor, T.T., Louis, D.N., Stemmer-Rachamimov, A.O. Clin. Cancer Res. (2005) [Pubmed]
Annotations and hyperlinks in this abstract are from individual authors of WikiGenes or automatically generated by the WikiGenes Data Mining Engine. The abstract is from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.About WikiGenesOpen Access LicencePrivacy PolicyTerms of Useapsburg