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Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
Published on: January 9, 2019
Diagnostic markers for glioblastoma
C S Jung1, A W Unterberg, C Hartmann
1Department of Neurosurgery, Institute of Pathology, Ruprecht-Karls-University Heidelberg and Clinical Cooperation Unit Neuropathology, German Cancer Research Center, Germany. carla.jung@med.uni-heidelberg.de
Histology and Histopathology
|August 27, 2011
Summary
Glioblastoma (GBM) remains a deadly brain cancer despite advances. This review highlights recent progress in diagnostic markers for GBM, improving patient identification and treatment strategies.
Area of Science:
- Neuro-oncology
- Molecular diagnostics
- Biomarker research
Background:
- Glioblastoma (GBM) is the most aggressive primary brain tumor with a dismal prognosis.
- Despite multimodal treatment (surgery, radiation, chemotherapy), patient outcomes remain poor.
- Advances in understanding GBM genomics and proteomics have spurred biomarker discovery.
Purpose of the Study:
- To review current concepts and recent developments in diagnostic markers for Glioblastoma.
- To focus on biomarkers measurable in cerebrospinal fluid (CSF), serum, and tumor tissue.
- To provide an overview of diagnostic, prognostic, predictive, and pharmakodynamic markers.
Main Methods:
- Literature review of recent advancements in Glioblastoma biomarker research.
- Compilation of established and emerging diagnostic markers.
- Focus on markers analyzed in clinical samples (CSF, serum) and tumor tissue.
Main Results:
- Significant progress has been made in identifying various biomarkers for GBM.
- Genomic and proteomic insights are crucial for biomarker development.
- Multi-platform biomarker analysis (CSF, serum, tissue) is essential for comprehensive assessment.
Conclusions:
- Improved diagnostic markers are critical for better Glioblastoma patient management.
- Continued research into novel biomarkers holds promise for enhancing early detection and treatment.
- The integration of diverse biomarker data may lead to more personalized therapeutic strategies.
