This invention identifies the molecular features that make high-grade gliomas, a type of brain tumor, more aggressive. Using advanced data analysis tools, researchers processed and normalized microarray data to find proteins that are differently expressed in tumor cells. They used two methods, 2D-DIGE and iTRAQ, to identify significant changes in proteins related to cell cycle regulation, tumor invasion, oxidative stress, and cell death. The study found disruptions in key metabolic pathways, including glycolysis and the Krebs cycle. A total of 171 proteins were identified, impacting pathways like blood coagulation and antigen presentation. Analysis of cerebrospinal fluid (CSF) also showed proteins that change with glioma grades. Autoantibody screening in the CSF found potential biomarkers, such as SMC1A, PIP5K2B, and FGFR1OP, which were more responsive in grade III tumors. Proteins like lactate dehydrogenase A, thymosin beta-4, and alpha-1-antitrypsin were linked to tumor grades. These findings highlight potential biomarkers and therapeutic targets, improving the understanding of glioma biology and how these tumors become invasive.
Figure (1) Pathway analysis of significantly altered proteins identified in gliomas. Significantly altered proteins were subjected to pathway analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID) an online tool, and identified various metabolic pathways like glycolysis, Krebs cycle, electron transport chain, antigen processing and presentation pathways.
High-grade gliomas are highly aggressive brain tumors with poor prognosis and limited treatment options. Current diagnostics and treatments fail to precisely target the tumor's molecular drivers. There is an urgent need for specific biomarkers to distinguish between glioma grades and understand the mechanisms behind their invasiveness. This lack of precise molecular profiling hampers the development of effective, personalized therapies, making gliomas one of the deadliest brain cancers with high recurrence and low survival rates.
- Comprehensive Biomarker Panel: The solution includes a variety of biomarkers such as lactate dehydrogenase A chain, thymosin beta-4 like 3 protein, alpha-1- antitrypsin, and others, which have been identified to show distinct upregulation or downregulation trends specific to gliomas compared to healthy controls.
- Grade-Specific Detection: This solution uniquely detects gliomas and differentiates between grades, with specific markers like FR1OP, PI42B, SMRC2, SMC1A, and FA13A linked to grade III gliomas.
- Multiple Biospecimen Compatibility: The panel detects biomarkers in both tissue and cerebrospinal fluid (CSF) samples, enhancing its diagnostic utility.
- Autoantibody Screening: Including autoantibody biomarkers adds specificity, especially for detecting immune responses in grade III gliomas.
- In-Vitro Evaluation Method: The thorough in-vitro screening ensures high accuracy in detecting and distinguishing glioma grades.
The prototype for detecting gliomas is an integrated diagnostic kit designed for laboratory use. It includes a microarray-based system for pre-processing and analyzing tissue and cerebrospinal fluid (CSF) samples. Key components include a high-sensitivity ELISA plate reader for detecting specific protein biomarkers, such as lactate dehydrogenase A, thymosin beta-4, and alpha-1-antitrypsin. The kit utilizes autoantibody screening methods for proteins like FR1OP and SMC1A, with reagents and buffers prepared for in-vitro use. Inputs include a power supply (110-240V), reagents stored at 4°C, and CSF or tissue samples. The system dimensions are approximately 12x10x8 inches, making it compact for benchtop use. Performance metrics include high specificity and sensitivity in differentiating glioma grades, processing up to 96 samples per run with results available in 2-4 hours. The kit also includes software for data analysis, compatible with standard lab computers, requiring minimal training for use.
A validated panel of biomarkers for glioma grading has been developed and tested in clinical samples using proteomic and immunoassay techniques. A diagnostic kit prototype for lab use is described and demonstrates high specificity in distinguishing tumor grades. The technology is currently lab-validated and available for licensing.
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The technology offers significant benefits across multiple aspects of healthcare. It enables improved diagnosis through more accurate detection and grading of gliomas, which supports better treatment decisions and ultimately leads to improved patient outcomes. By identifying specific biomarkers, it facilitates personalized medicine, allowing for treatments tailored to individual patients. This not only enhances the effectiveness of therapies but also helps minimize side effects. Additionally, it increases healthcare efficiency by reducing the need for invasive procedures and repeated diagnostic tests, thereby conserving both time and resources. On a broader scale, the innovation contributes to a positive economic impact by lowering overall healthcare costs and boosting productivity through better health outcomes.
- Hospitals and Clinics: Utilized for early detection, tumor grading, prognostic assessment, and monitoring treatment efficacy in glioma patients.
- Diagnostic Laboratories: Offering specialized testing services for glioma biomarkers to support accurate diagnosis and personalized treatment plans.
- Biotech Companies: Developing innovative diagnostic tools and therapeutic interventions targeting specific glioma biomarkers.
- Pharmaceutical Companies: Developing targeted therapies and personalized treatments, enhancing drug development through biomarker-based patient stratification.
Geography of IP
Type of IP
201721012423
489473