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Yan Y.,Neurosurgery Research Institution of Shanghai | Xu T.,Neurosurgery Research Institution of Shanghai | Chen J.,Neurosurgery Research Institution of Shanghai | Hu G.,Neurosurgery Research Institution of Shanghai | Lu Y.,Neurosurgery Research Institution of Shanghai
Journal of Clinical Neuroscience | Year: 2011

Intraspinal Ewing's sarcoma (ES) and primitive neuroectodermal tumors (PNET) are very rare, and the characteristics and prognoses of the disease remain unclear. We present an illustrative patient with an intradural, extramedullary PNET arising within the cervical spinal canal, with clinical and radiological manifestations of leptomeningeal spread, and review the reports of a further 77 patients with intraspinal ES/PNET. Cox regression analyses showed that tumor location (extradural, intradural) (p = 0.002, RR = 4.217, 95% confidence interval [CI] 1.668-10.664) and spinal segment location (cervical, thoracic, lumbar, or sacral) (p = 0.017, RR = 2.040, 95% CI 1.133-3.673) were independent factors in the prognosis of intraspinal ES/PNET. We concluded that a peripheral PNET may originate within the spinal canal and exhibit leptomeningeal spread similar to that seen in central PNET, and that a patient with an intradural ES/PNET high in the spinal canal is more likely to have a poor prognosis. © 2010 Published by Elsevier Ltd.


Yan Y.,Neurosurgery Research Institution of Shanghai | Zhang L.,Neurosurgery Research Institution of Shanghai | Xu T.,Neurosurgery Research Institution of Shanghai | Zhou J.,101st Hospital of PLA | And 7 more authors.
PLoS ONE | Year: 2013

Objectives: To study the expression pattern and prognostic significance of SAMSN1 in glioma. Methods: Affymetrix and Arrystar gene microarray data in the setting of glioma was analyzed to preliminarily study the expression pattern of SAMSN1 in glioma tissues, and Hieratical clustering of gene microarray data was performed to filter out genes that have prognostic value in malignant glioma. Survival analysis by Kaplan-Meier estimates stratified by SAMSN1 expression was then made based on the data of more than 500 GBM cases provided by The Cancer Genome Atlas (TCGA) project. At last, we detected the expression of SAMSN1 in large numbers of glioma and normal brain tissue samples using Tissue Microarray (TMA). Survival analysis by Kaplan-Meier estimates in each grade of glioma was stratified by SAMSN1 expression. Multivariate survival analysis was made by Cox proportional hazards regression models in corresponding groups of glioma. Results: With the expression data of SAMSN1 and 68 other genes, high-grade glioma could be classified into two groups with clearly different prognoses. Gene and large sample tissue microarrays showed high expression of SAMSN1 in glioma particularly in GBM. Survival analysis based on the TCGA GBM data matrix and TMA multi-grade glioma dataset found that SAMSN1 expression was closely related to the prognosis of GBM, either PFS or OS (P<0.05). Multivariate survival analysis with Cox proportional hazards regression models confirmed that high expression of SAMSN1 was a strong risk factor for PFS and OS of GBM patients. Conclusion: SAMSN1 is over-expressed in glioma as compared with that found in normal brains, especially in GBM. High expression of SAMSN1 is a significant risk factor for the progression free and overall survival of GBM. © 2013 Yan et al.

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