Neuroblastoma GD2 Expression and Computational Analysis of Aptamer-Based Bioaffinity Targeting

Area of Science:

• Oncology
• Biochemistry
• Bioinformatics

Background:

• Neuroblastoma (NB) is a high-mortality pediatric cancer originating from neural crest cells.
• High-risk NB patients often have minimal residual disease (MRD), leading to relapse despite treatment.
• Disialoganglioside (GD2) is a unique antigen expressed on NB tumor cells, making it a target for MRD detection.

Purpose of the Study:

• To discuss Neuroblastoma minimal residual disease (MRD) expression.
• To review analytical assays for disialoganglioside (GD2) detection and quantification.
• To explore computational approaches for GD2 characterization using genomic and imaging data.

Main Methods:

• Review of analytical assays for GD2 detection.
• Analysis of computational approaches for GD2 characterization.
• Integration of high-throughput image processing and genomic data.

Main Results:

• GD2 serves as a specific biomarker for subclinical NB MRD detection.
• Various assays enable GD2 quantification for treatment response assessment.
• Computational methods enhance GD2 characterization from complex datasets.

Conclusions:

• GD2 detection is crucial for identifying and managing NB MRD.
• Advanced analytical and computational methods improve GD2 characterization.
• Targeting GD2 offers potential for improved NB patient outcomes.