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Integrative precision oncology in neuroblastoma: multi-omics biomarkers, molecular targets, and immunotherapeutic strategies

Jul 2026 · Frontiers in Oncology · Vol 16 · 1 citation · 50 references
Medicine

TL;DR

Current evidence for molecular and cellular mechanisms underlying neuroblastoma initiation, progression, and therapeutic resistance is examined, with a focus on MYCN amplification, ALK pathway dysregulation, chromosomal instability, telomere maintenance mechanisms, epigenetic remodeling, and neural crest developmental biology.

Abstract

Neuroblastoma is the most frequent extracranial solid tumor of young children and demonstrates a wide range of biological behavior, from spontaneous regression to highly aggressive metastatic disease. Recent advances in genomics, epigenetics, tumor microenvironment biology, and multi-omics technologies have greatly enhanced understanding of neuroblastoma pathogenesis and enabled the development of precision diagnostic and prognostic approaches. This review examines current evidence for molecular and cellular mechanisms underlying neuroblastoma initiation, progression, and therapeutic resistance, with a focus on MYCN amplification, ALK pathway dysregulation, chromosomal instability, telomere maintenance mechanisms, epigenetic remodeling, and neural crest developmental biology. This review primarily emphasizes that these characteristics should be interpreted within a unified developmental framework. In this context, age serves more as an indicator of the differentiation status of the sympathoadrenal progenitor pool rather than merely a timeline for the accumulation of somatic mutations. This viewpoint connects the epigenetic, genetic, and clinical aspects of the disease, providing insight into its distinctive range of behaviors, from spontaneous regression in infants to fatal progression in older children. The promising role of integrative diagnostic platforms — such as genomic profiling, liquid biopsy, radiomics, metabolomics, single-cell sequencing, and artificial intelligence-aided imaging approaches — in early detection and disease characterization is explored in detail. The evaluation of both existing and emerging prognostic models involves a critical analysis of molecular biomarkers, tumor microenvironment signatures, circulating tumor DNA, immune profiling, and machine-learning-based stratification systems. Additionally, the translational potential of systems biology approaches is examined, along with future directions for integrating multi-omics data into clinically relevant precision oncology frameworks. Integrative approaches are collectively reshaping neuroblastoma research by connecting molecular pathogenesis with advanced diagnostic and prognostic tools. These developments are expected to facilitate enhanced risk-adapted therapeutic strategies, personalized medicine, and ultimately, improved survival rates in children with neuroblastoma.

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