Heparan Sulfate Biosynthetic System Is Inhibited in Human Glioma Due to EXT1/2 and HS6ST1/2 Down-Regulation.

Heparan sulfate (HS) is an important component of the extracellular matrix and cell surface, which plays a key role in cell-cell and cell-matrix interactions. Functional activity of HS directly depends on its structure, which determined by a complex system of HS biosynthetic enzymes. During malignant transformation, the system can undergo significant changes, but for glioma, HS biosynthesis has not been studied in detail. In this study, we performed a comparative analysis of the HS biosynthetic system in human gliomas of different grades. RT-PCR analysis showed that the overall transcriptional activity of the main HS biosynthesis-involved genes (EXT1, EXT2, NDST1, NDST2, GLCE, HS2ST1, HS3ST1, HS3ST2, HS6ST1, HS6ST2, SULF1, SULF2, HPSE) was decreased by 1.5-2-fold in Grade II-III glioma (p < 0.01) and by 3-fold in Grade IV glioma (glioblastoma multiforme, GBM) (p < 0.05), as compared with the para-tumourous tissue. The inhibition was mainly due to the elongation (a decrease in EXT1/2 expression by 3-4-fold) and 6-O-sulfation steps (a decrease in 6OST1/2 expression by 2-5-fold) of the HS biosynthesis. Heparanase (HPSE) expression was identified in 50% of GBM tumours by immunostaining, and was characterised by a high intratumoural heterogeneity of the presence of the HPSE protein. The detected disorganisation of the HS biosynthetic system in gliomas might be a potential molecular mechanism for the changes of HS structure and content in tumour microenvironments, contributing to the invasion of glioma cells and the development of the disease.

Prognostic relevance of NG2/CSPG4, CD44 and Ki-67 in patients with glioblastoma.

Neuron-glial antigen 2 (NG2, also known as CSPG4) and hyaluronic acid receptor CD44 are chondroitin sulphate proteoglycans actively involved in brain development and its malignant transformation. Here, we aimed to compare prognostic significances of NG2, CD44 and Ki-67 expression in glioblastoma multiforme patients. Totally, 45 tissue samples and 83 paraffin-embedded tissues for 75 patients were analysed. The prognostic values of the genes were analysed using Kaplan-Meier survival curves. Grade III gliomas showed 2-fold difference in NG2 expression between anaplastic astrocytoma and oligoastrocytoma (10.1 ± 3.5 and 25.5 ± 14.5, respectively). For grade IV gliomas, upregulated NG2 expression (21.0 ± 6.8) was associated with poor glioblastoma multiforme prognosis (overall survival < 12 months) compared with glioblastoma multiforme patients with good prognosis (4.4 ± 3.2; overall survival > 12 months). Multivariate survival analysis using Cox proportional hazards model confirmed that high NG2 expression was associated with low survival of the patients (hazard ratio: 3.43; 95% confidence interval: 1.18-9.93; p = 0.02), whereas age (hazard ratio: 1.02; 95% confidence interval: 0.96-1.09; p = 0.42), tumour resection (hazard ratio: 1.03; 95% confidence interval: 0.98-1.08; p = 0.25) and sex (hazard ratio: 0.62; 95% confidence interval: 0.21-1.86; p = 0.40) did not show significant association with prognosis. Although the positive correlation was shown for NG2 and CD44 expression in the glioblastomas (Pearson coefficient = 0.954), Kaplan-Meier and multivariate survival analyses did not revealed a significant association of the increased CD44 expression (hazard ratio: 2.18; 95% confidence interval: 0.50-9.43; p = 0.30) or high Ki-67 proliferation index (hazard ratio: 1.10; 95% confidence interval: 1.02-1.20; p = 0.02) with the disease prognosis. The results suggest that upregulation of NG2/CSPG4 rather than changes in CD44 or Ki-67 expression is associated with low overall survival in glioblastoma multiforme patients, supporting NG2/CSPG4 as a potential prognostic marker in glioblastoma.

New Software for Preoperative Diagnostics of Meningeal Tumor Histologic Types.

OBJECTIVE: Meningeal tumors are neoplasms with different histologic manifestations of both benign and malignant types that determine the prognosis of tumor recurrence and its consistency. The risk of surgical treatment depends on the location, size, and consistency of the tumor. Magnetic resonance imaging (MRI) sequences can be used to identify the features of tumors, but these MRI characteristics are not well understood. The present study describes an advanced mathematical algorithm to analyze MRI data and distinguish histologic types of meningeal tumors before surgery. METHODS: Forty-eight patients underwent surgical removal of meningeal brain tumor. All patients had preoperative MRI with a 1.5-T scanner. One radiologist and 2 neurosurgeons evaluated MRI histogram peaks of the whole tumor volume using the advanced computer algorithm. RESULTS: Three specialists received the following mean value of histogram peaks: 15.99 ± 0.23 (± standard error of the mean [SEM]) for meningoteliomatous meningiomas; 21.24 ± 0.3 (±SEM) for fibroplastic meningiomas; 19.0 ± 0.28 (±SEM) for transitional meningiomas; 10.7 ± 0.27 (±SEM) for anatypical, anaplastic meningiomas, 11.03 ± 0.51 (±SEM) for primary intracranial fibrosarcomas and 25.72 ± 0.29 (±SEM) for meningeal hemangiopericytomas. A one-way analysis of variance test proved the difference between group means: F = 70.138, P < 0.01. The Tukey test and the Games-Howell test indicated that the difference between the tumor groups was significant. Mean deviation in agreement index between specialists was 0.98 ± 0.007 (±SEM). CONCLUSIONS: The advanced algorithm proved high specificity, sensitivity, and interoperator repeatability.