Advances in multi-omics research on neuroblastoma

Area of Science:

• Pediatric Oncology
• Molecular Diagnostics
• Computational Biology

Background:

• Neuroblastoma, a common childhood extracranial solid tumor, presents diagnostic and therapeutic challenges due to heterogeneity.
• Understanding its complex genetic background and identifying molecular subtypes are crucial for effective treatment.

Purpose of the Study:

• To review the roles of transcriptomics, radiomics, and digital pathology in neuroblastoma diagnosis and treatment.
• To emphasize the benefits of multi-omics integration for personalized medicine.

Main Methods:

• Transcriptomics (gene expression profiling, single-cell sequencing) to analyze molecular subtypes and drug resistance.
• Radiomics (MRI, PET-CT, CT) for non-invasive prediction of MYCN amplification, metastasis risk, and prognosis.
• Artificial intelligence (AI) in digital pathology for cellular diversity and immune microenvironment analysis.

Main Results:

• Transcriptomics aids in identifying tumor subtypes and drug resistance mechanisms.
• Radiomics enables non-invasive assessment of tumor characteristics and prognostic stratification.
• AI in pathology enhances diagnostic accuracy and mutation prediction.
• Multi-omics integration provides more precise classification and personalized treatment plans.

Conclusions:

• Transcriptomics, radiomics, and AI-powered pathology significantly enhance neuroblastoma diagnostic precision.
• Multi-omics fusion strategies are key to optimizing treatment decisions and developing personalized therapies for neuroblastoma.