Abstract 4505: Differential protein expression in platelets collected from glioma patients and healthy controls: A comparative study

Abstract Background: Glioblastoma (GBM) is the most aggressive type of primary brain tumor in adults. Standard treatment fosters event free survival for approximately 7 months and extends overall survival to only 15 months. Due to the risk of biopsy complications, the verification of the tumor is not always possible. Therefore, in many cases the treatment is based on MRI findings and exclusion of other malignancies. A confirmative liquid biopsy would provide additional and useful support for clinical decision making and patient counselling. To date no liquid biopsy for GBM is available. Platelets interact with tumor cells in multiple ways, including direct contact, release of cytokines, and uptake of tumor-derived extracellular vesicles. These interactions cause modifications in platelet RNA and protein profiles, yielding tumor educated platelets that reflect specific tumor characteristics. Our study aimed to use proteomic analysis to identify differential protein expression in platelets collected from glioma patients compared to healthy controls, identifying potential biomarkers for glioma diagnosis and therapeutic monitoring Methods: Platelet samples were collected from 14 glioma patients and 14 matching healthy controls. Platelets were isolated using differential centrifugation to minimize contamination with other blood components. Protein extraction and quantification were performed, followed by analysis using mass spectrometry-based proteomics. Protein identification and quantification were conducted with Label-Free Quantification techniques, and differentially expressed proteins were statistically validated. Bioinformatic tools were employed to analyze pathways and functional annotations related to identified proteins. Results: In total 3444 proteins were identified and quantified. Of these, 463 proteins were differentially expressed between platelets in glioma patients and healthy controls. Reactome Pathway, gene ontology enrichment and protein protein interactions analyses revealed proteins associated with pathways linked to Vesicle-mediated transport, Apoptosis, Metabolism of Lipids, Cell Cycle Checkpoints, Glutathione synthesis/recycling, Platelet Activation and Signal transduction. Conclusion: The study identifies a distinct proteomic profile in platelets from glioma patients compared to healthy individuals, suggesting that platelets in glioma may harbor unique proteins characteristics related to tumor biology. These findings support the potential of platelets as a source of biomarkers for glioma detection, confirmation of diagnosis and monitoring. Future studies with larger cohorts are warranted to validate these proteins as diagnostic markers and explore their mechanistic roles in glioma progression. Citation Format: Vibecke Markhus, Katarina Fritz-Wallace, Olav Mjaavatten, Einar Kleboe Kristoffersen, Rupavathana Mahesparan, Hrvoje Miletic, Frode Selheim, Dorota Goplen. Differential protein expression in platelets collected from glioma patients and healthy controls: A comparative study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4505.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-4505
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 4505: Differential protein expression in platelets collected from glioma patients and healthy controls: A comparative study

Vibecke Markhus, Olav Mjaavatten, Rupavathana Mahesparan, Hrvoje Miletić et al.
Cancer Research
Inflammatory Biomarkers in Disease Prognosis
article

Abstract 4505: Differential protein expression in platelets collected from glioma patients and healthy controls: A comparative study

Vibecke Markhus, Olav Mjaavatten, Rupavathana Mahesparan, Hrvoje Miletić, Frode Selheim, Dorota Goplen, Katarina Fritz‐Wallace, E. K. Kristoffersen
article en

Abstract

Abstract Background: Glioblastoma (GBM) is the most aggressive type of primary brain tumor in adults. Standard treatment fosters event free survival for approximately 7 months and extends overall survival to only 15 months. Due to the risk of biopsy complications, the verification of the tumor is not always possible. Therefore, in many cases the treatment is based on MRI findings and exclusion of other malignancies. A confirmative liquid biopsy would provide additional and useful support for clinical decision making and patient counselling. To date no liquid biopsy for GBM is available. Platelets interact with tumor cells in multiple ways, including direct contact, release of cytokines, and uptake of tumor-derived extracellular vesicles. These interactions cause modifications in platelet RNA and protein profiles, yielding tumor educated platelets that reflect specific tumor characteristics. Our study aimed to use proteomic analysis to identify differential protein expression in platelets collected from glioma patients compared to healthy controls, identifying potential biomarkers for glioma diagnosis and therapeutic monitoring Methods: Platelet samples were collected from 14 glioma patients and 14 matching healthy controls. Platelets were isolated using differential centrifugation to minimize contamination with other blood components. Protein extraction and quantification were performed, followed by analysis using mass spectrometry-based proteomics. Protein identification and quantification were conducted with Label-Free Quantification techniques, and differentially expressed proteins were statistically validated. Bioinformatic tools were employed to analyze pathways and functional annotations related to identified proteins. Results: In total 3444 proteins were identified and quantified. Of these, 463 proteins were differentially expressed between platelets in glioma patients and healthy controls. Reactome Pathway, gene ontology enrichment and protein protein interactions analyses revealed proteins associated with pathways linked to Vesicle-mediated transport, Apoptosis, Metabolism of Lipids, Cell Cycle Checkpoints, Glutathione synthesis/recycling, Platelet Activation and Signal transduction. Conclusion: The study identifies a distinct proteomic profile in platelets from glioma patients compared to healthy individuals, suggesting that platelets in glioma may harbor unique proteins characteristics related to tumor biology. These findings support the potential of platelets as a source of biomarkers for glioma detection, confirmation of diagnosis and monitoring. Future studies with larger cohorts are warranted to validate these proteins as diagnostic markers and explore their mechanistic roles in glioma progression. Citation Format: Vibecke Markhus, Katarina Fritz-Wallace, Olav Mjaavatten, Einar Kleboe Kristoffersen, Rupavathana Mahesparan, Hrvoje Miletic, Frode Selheim, Dorota Goplen. Differential protein expression in platelets collected from glioma patients and healthy controls: A comparative study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4505.

Cancer ResearchVol. 85(8_Supplement_1)
Haukeland University Hospital (NO), University of Bergen (NO)
Openalex Percentile: Top 88%
Inflammatory Biomarkers in Disease Prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.