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Integrative precision oncology in neuroblastoma: multi-omics biomarkers, molecular targets, and immunotherapeutic
Amitabh Singh1, Neha Goel1, Sumit Mehndiratta1
1Department of Pediatrics, Division of Pediatric Oncology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.
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.
Insights
Neuroblastoma research integrates multi-omics data, developmental biology, and advanced diagnostics to understand its varied behaviors. This approach aims for improved precision medicine and survival rates in children with this common childhood cancer.
Area of Science:
- Pediatric Oncology
- Developmental Biology
- Genomics
Background:
- Neuroblastoma is a frequent pediatric extracranial solid tumor with diverse clinical behaviors.
- Recent advances in multi-omics and tumor microenvironment biology have improved understanding of neuroblastoma.
- Existing knowledge requires a unified developmental framework to interpret disease characteristics.
Purpose of the Study:
- To review molecular and cellular mechanisms of neuroblastoma initiation, progression, and resistance.
- To emphasize a unified developmental framework for understanding neuroblastoma's varied behaviors.
- To explore integrative diagnostic and prognostic platforms for precision oncology.
Main Methods:
- Review of current evidence on molecular mechanisms (e.g., MYCN amplification, ALK dysregulation, epigenetics).
- Analysis of developmental biology, particularly neural crest origins.
- Evaluation of integrative diagnostic tools (genomics, liquid biopsy, AI imaging) and prognostic models (biomarkers, immune profiling, machine learning).
Main Results:
- Neuroblastoma's behavior is linked to the differentiation status of sympathoadrenal progenitors, not just mutation accumulation.
- Integrative diagnostic platforms show promise for early detection and characterization.
- Emerging prognostic models incorporate molecular, microenvironment, and machine learning approaches.
Conclusions:
- A unified developmental framework connects epigenetic, genetic, and clinical aspects of neuroblastoma.
- Integrative approaches are reshaping research, linking pathogenesis to diagnostics and prognostics.
- These developments are expected to enhance risk-adapted therapies, personalized medicine, and survival rates for neuroblastoma patients.
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