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Polysialic Acid Neural Cell Adhesion Molecule (PSA-NCAM) is an adverse prognosis factor in glioblastoma, and regulates olig2 expression in glioma cell lines
BACKGROUND: Glioblastoma multiforme (GBM) is the most aggressive and frequent brain tumor, albeit without cure. Although patient survival is limited to one year on average, significant variability in outcome is observed. The assessment of biomarkers is needed to gain better knowledge of this type of...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2854115/ https://www.ncbi.nlm.nih.gov/pubmed/20219118 http://dx.doi.org/10.1186/1471-2407-10-91 |
Sumario: | BACKGROUND: Glioblastoma multiforme (GBM) is the most aggressive and frequent brain tumor, albeit without cure. Although patient survival is limited to one year on average, significant variability in outcome is observed. The assessment of biomarkers is needed to gain better knowledge of this type of tumor, help prognosis, design and evaluate therapies. The neurodevelopmental polysialic acid neural cell adhesion molecule (PSA-NCAM) protein is overexpressed in various cancers. Here, we studied its expression in GBM and evaluated its prognosis value for overall survival (OS) and disease free survival (DFS). METHODS: We set up a specific and sensitive enzyme linked immunosorbent assay (ELISA) test for PSA-NCAM quantification, which correlated well with PSA-NCAM semi quantitative analysis by immunohistochemistry, and thus provides an accurate quantitative measurement of PSA-NCAM content for the 56 GBM biopsies analyzed. For statistics, the Spearman correlation coefficient was used to evaluate the consistency between the immunohistochemistry and ELISA data. Patients' survival was estimated by using the Kaplan-Meier method, and curves were compared using the log-rank test. On multivariate analysis, the effect of potential risk factors on the DFS and OS were evaluated using the cox regression proportional hazard models. The threshold for statistical significance was p = 0.05. RESULTS: We showed that PSA-NCAM was expressed by approximately two thirds of the GBM at variable levels. On univariate analysis, PSA-NCAM content was an adverse prognosis factor for both OS (p = 0.04) and DFS (p = 0.0017). On multivariate analysis, PSA-NCAM expression was an independent negative predictor of OS (p = 0.046) and DFS (p = 0.007). Furthermore, in glioma cell lines, PSA-NCAM level expression was correlated to the one of olig2, a transcription factor required for gliomagenesis. CONCLUSION: PSA-NCAM represents a valuable biomarker for the prognosis of GBM patients. |
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