BIOM-72. INTEGRATION OF ULTRASENSITIVE ELECTROLUMINESCENT IMMUNOASSAY AND CELL-FREE DNAMETHYLATION ANALYSIS FOR NON-INVASIVE MONITORING OF ADULT DIFFUSE GLIOMAS

Abstract Gliomas are highly aggressive brain tumors with nearly universal recurrence rate. Despite this, the ability to accurately predict and identify tumor recurrence relies solely on serial MRI imaging, which is marred by treatment effects such as radiation necrosis, and necessarily identifies progression retrospectively. It is believe that tumor undergo molecular changes upon tumor progression, however the resampling of tumors upon recurrence imposes significant risks. This highlights the need for novel non-invasive biomarkers capable of identifying tumor recurrence. Due to the low accuracies of individual biomarkers, we have proposed the use of an integrated, multi-platform approach to biomarker discovery. A cohort of 107 glioma plasma samples, including 30 pairs, underwent plasma proteomic analysis, consisting of a panel of serum proteins (FABP4, GFAP, NFL, Tau and MMP3,4 &7) quantified through ultrasensitive electrochemiluminescence multiplexed immunoassays, and plasma DNA methylation analysis, captured through cell-free methylated DNA immunoprecipitation and high-throughput sequencing. Unsupervised hierarchal clustering revealed robust separation of primary and recurrent tumors through plasma proteomics, associated with a distinct plasma methylation signature. NFL, Tau and MMP3 levels differed between primary and recurrent samples; pair-wise analysis revealed increased in NFL and Tau concentrations upon recurrence. Tau levels predicted outcome independent of WHO Grade and IDH status. A predictive generalized linear regression model created through the integration of the proteomic and methylation signatures allowed for the discrimination of primary and recurrent samples in 83% of cases. This work suggests that the combination of DNA methylation and plasma proteomics may improve the ability of these techniques for the serial monitoring of gliomas patients.

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Publication Details

Journal
Neuro-Oncology
Published
2024-11-01
DOI
https://doi.org/10.1093/neuonc/noae165.0144
Citations
1
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
0.23
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article

BIOM-72. INTEGRATION OF ULTRASENSITIVE ELECTROLUMINESCENT IMMUNOASSAY AND CELL-FREE DNAMETHYLATION ANALYSIS FOR NON-INVASIVE MONITORING OF ADULT DIFFUSE GLIOMAS

Ioannis Prassas, Andrew Ajisebutu, Miyo K. Chatanaka, Diamandis Eleftherios et al.
1 citations
Neuro-Oncology
Advanced biosensing and bioanalysis techniques
0.23
article

BIOM-72. INTEGRATION OF ULTRASENSITIVE ELECTROLUMINESCENT IMMUNOASSAY AND CELL-FREE DNAMETHYLATION ANALYSIS FOR NON-INVASIVE MONITORING OF ADULT DIFFUSE GLIOMAS

Ioannis Prassas, Andrew Ajisebutu, Miyo K. Chatanaka, Diamandis Eleftherios, Gelareh Mohammed Zadeh, Vikas Patil
article en
1 citations

Abstract

Abstract Gliomas are highly aggressive brain tumors with nearly universal recurrence rate. Despite this, the ability to accurately predict and identify tumor recurrence relies solely on serial MRI imaging, which is marred by treatment effects such as radiation necrosis, and necessarily identifies progression retrospectively. It is believe that tumor undergo molecular changes upon tumor progression, however the resampling of tumors upon recurrence imposes significant risks. This highlights the need for novel non-invasive biomarkers capable of identifying tumor recurrence. Due to the low accuracies of individual biomarkers, we have proposed the use of an integrated, multi-platform approach to biomarker discovery. A cohort of 107 glioma plasma samples, including 30 pairs, underwent plasma proteomic analysis, consisting of a panel of serum proteins (FABP4, GFAP, NFL, Tau and MMP3,4 &7) quantified through ultrasensitive electrochemiluminescence multiplexed immunoassays, and plasma DNA methylation analysis, captured through cell-free methylated DNA immunoprecipitation and high-throughput sequencing. Unsupervised hierarchal clustering revealed robust separation of primary and recurrent tumors through plasma proteomics, associated with a distinct plasma methylation signature. NFL, Tau and MMP3 levels differed between primary and recurrent samples; pair-wise analysis revealed increased in NFL and Tau concentrations upon recurrence. Tau levels predicted outcome independent of WHO Grade and IDH status. A predictive generalized linear regression model created through the integration of the proteomic and methylation signatures allowed for the discrimination of primary and recurrent samples in 83% of cases. This work suggests that the combination of DNA methylation and plasma proteomics may improve the ability of these techniques for the serial monitoring of gliomas patients.

Neuro-OncologyVol. 26(Supplement_8)
University Health Network (CA), University of Toronto (CA)
Peace, Justice and strong institutions
Openalex Percentile: Top 41%
Advanced biosensing and bioanalysis techniques
0.23
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