Literature DB >> 14606584

Glycosphingolipid component profiles or human gliomas--correlation to survival time and histopathological malignancy grading.

R Becker1, J Rohlfs, R Jennemann, H Wiegandt, H D Mennel, B L Bauer.   

Abstract

BACKGROUND: Glycosphingolipids (GSL) are expressed on the surface of neuroectodermal cells. The correlation of a variety of distinct GSL with different primary brain tumors has been demonstrated. Three distinct GSL-component profiles (GSL-types I, II and III) of human gliomas have been defined by our group. The purpose of this study was to evaluate the correlation of the established GSL-types I-III with survival time and histopathological malignancy grading in 40 human gliomas.
METHODS: Neutral and acidic GSL-component patterns, histopathological malignancy grade and survival time, and a number of other relevant variables were examined. Kaplan-Meier survival curves were analyzed with the log rank test.
RESULTS: GSL-type I was expressed in 18 tumors (17 Glioblastoma multiforme (GBM) and 1 anaplastic astrocytoma (AA)). GSL-type II was expressed in 11 tumors (7 GBM, 3 AA, 1 low grade astrocytoma (LGA)). 10 patients presented with GSL-type III (3 GBM, 4 AA, 3 LGA). Kaplan Meier survival curves of GSL-types I-III differed significantly (p = 0.0231, log-rank-test). However, survival time correlated better to the WHO grades. Within a given malignancy grade, GSL-types gave additional informations about the proliferative properties.
CONCLUSIONS: This is the first report of a correlation between survival time and human glioma neutral and acidic GSL-components. The results are in agreement with observations of other investigators. The analysis of GSL-type expression might give useful additional information about proliferative properties of human gliomas in a given malignancy grade. In particular, the early prediction of outcomes in anaplastic or low grade gliomas might be possible.

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Year:  2000        PMID: 14606584

Source DB:  PubMed          Journal:  Clin Neuropathol        ISSN: 0722-5091            Impact factor:   1.368


  1 in total

1.  Integrating diverse genomic data using gene sets.

Authors:  Svitlana Tyekucheva; Luigi Marchionni; Rachel Karchin; Giovanni Parmigiani
Journal:  Genome Biol       Date:  2011-10-21       Impact factor: 13.583

  1 in total

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