ExoBCD

ExoBCD catalogs and integrates exosomal molecular data for breast cancer to enable discovery and validation of exosomal biomarkers for diagnosis, prognosis, and precision oncology research.

Key Features:

• High-throughput data integration: Integrates four high-throughput datasets yielding approximately 20,900 annotation entries.
• Annotation aggregation: Aggregates annotations from 25 external databases to enrich molecular and clinical metadata.
• TCGA transcriptome validation: Performs transcriptome validation across 1,191 TCGA cases.
• Literature mining: Includes manual mining of 950 studies to curate evidence for exosomal molecules.
• Exosomal molecule catalog: Catalogs 306 exosomal molecules comprising 121 mRNAs, 172 miRNAs, and 13 lncRNAs, including 49 potential biomarkers and 257 biologically interesting molecules.
• Molecular and clinical annotations: Provides molecular characteristics, experimental biology, gene expression patterns, overall survival rates, functional evidence, tumor stage information, and clinical application annotations.
• Biomarker identification paradigm: Uses a data-driven and literature-based approach that identified 36 promising molecules, highlighting IGF1R and FRS2 as top prognostic candidates.

Scientific Applications:

• Exosomal biomarker discovery: Identification and prioritization of exosomal biomarkers for breast cancer diagnosis and prognosis.
• Prognostic biomarker prioritization: Prioritizes prognostic candidates such as IGF1R and FRS2 for further validation.
• Molecular mechanism exploration: Enables study of exosome-related molecular mechanisms in breast cancer using integrated molecular and clinical data.
• Precision oncology research: Supports discovery of clinically relevant exosomal biomarkers for application in precision oncology.

Methodology:

Integration of four high-throughput datasets; aggregation of ~20,900 annotation entries from 25 external databases; transcriptome validation across 1,191 TCGA cases; manual mining of 950 studies; cataloging and categorization of 306 exosomal molecules into mRNAs, miRNAs, and lncRNAs; and a data-driven plus literature-based selection that identified 36 promising molecules.