Histology-based expression profiling yields novel prognostic markers in human glioblastoma

Shumin Dong, Catherine L. Nutt, Rebecca A. Betensky, Anat O. Stemmer-Rachamimov, Nicholas C. Denko, Keith L. Ligon, David H. Rowitch, David N. Louis

Research output: Contribution to journalArticlepeer-review


Although the prognosis for patients with glioblastoma is poor, survival is variable, with some patients surviving longer than others. For this reason, there has been longstanding interest in the identification of prognostic markers for glioblastoma. We hypothesized that specific histologic features known to correlate with malignancy most likely express molecules that are directly related to the aggressive behavior of these tumors. We further hypothesized that such molecules could be used as biomarkers to predict behavior in a manner that might add prognostic power to sole histologic observation of the feature. We reasoned that perinecrotic tumor cell palisading, which denotes the most aggressive forms of malignant gliomas, would be a striking histologic feature on which to test this hypothesis. We therefore used laser capture microdissection and oligonucleotide arrays to detect molecules differentially expressed in perinecrotic palisades. A set of RNAs (including POFUT2, PTDSR, PLOD2, ATF5, and HK2) that were differentially expressed in 3 initially studied, microdissected glioblastomas also provided prognostic information in an independent set of 28 glioblastomas that did not all have perinecrotic palisades. On validation in a second, larger independent series, this approach could be applied to other human glioma types to derive tissue biomarkers that could offer ancillary prognostic and predictive information alongside standard histopathologic examination.

Original languageEnglish (US)
Pages (from-to)948-955
Number of pages8
JournalJournal of Neuropathology and Experimental Neurology
Issue number11
StatePublished - Nov 2005


  • Glioblastoma
  • Glioma
  • Hypoxia
  • Necrosis
  • Prognosis

ASJC Scopus subject areas

  • General Medicine


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