# Factors Influencing Immunotherapy Response in Neuroblastoma: From Tumor Microenvironment to Combination Strategies

## TL;DR

This review explores why some children with neuroblastoma respond poorly to immunotherapy, highlighting factors like the tumor environment and genetic traits to guide better treatment strategies.

## Contribution

The paper introduces a multidimensional framework for predicting immunotherapy response and proposes mechanism-driven combination strategies for neuroblastoma.

## Key findings

- Therapy-driven lineage plasticity and immunosuppressive tumor microenvironment features drive resistance and relapse.
- A biomarker framework incorporating MES scores, TAM abundance, and ctDNA monitoring can identify non-responders and track resistance.
- Combination strategies like TME remodeling and dual-targeting CAR designs offer precision intervention opportunities.

## Abstract

What are the main findings?
This review systematically deconstructs the multifaceted determinants of immunotherapy response in neuroblastoma into four interconnected domains—tumor microenvironment (TME), tumor cell-intrinsic properties, host genetic background, and treatment-induced adaptive resistance—revealing that therapeutic outcome is governed by a dynamic ecosystem rather than any single factor.We synthesize emerging evidence from single-cell and spatial multi-omics studies demonstrating that therapy-driven adrenergic-to-mesenchymal (ADR-MES) lineage plasticity, coupled with spatiotemporal remodeling of an immunosuppressive TME (SPP1+ TAMs, TANs, CAF-mediated physical barriers, TIGIT/NECTIN2 checkpoint axis), constitutes the core mechanistic architecture underlying primary resistance and relapse.

This review systematically deconstructs the multifaceted determinants of immunotherapy response in neuroblastoma into four interconnected domains—tumor microenvironment (TME), tumor cell-intrinsic properties, host genetic background, and treatment-induced adaptive resistance—revealing that therapeutic outcome is governed by a dynamic ecosystem rather than any single factor.

We synthesize emerging evidence from single-cell and spatial multi-omics studies demonstrating that therapy-driven adrenergic-to-mesenchymal (ADR-MES) lineage plasticity, coupled with spatiotemporal remodeling of an immunosuppressive TME (SPP1+ TAMs, TANs, CAF-mediated physical barriers, TIGIT/NECTIN2 checkpoint axis), constitutes the core mechanistic architecture underlying primary resistance and relapse.

What are the implications of the main findings?
By framing neuroblastoma as a continuously evolving ecosystem under therapeutic pressure, this work provides a rational roadmap for next-generation combination strategies—including epigenetically re-sensitizing MES-state cells, temporally sequenced TME remodeling prior to immunotherapy, and dual-targeting CAR designs—moving beyond empirical one-size-fits-all approaches toward mechanism-guided precision intervention.The integrated multidimensional biomarker framework proposed herein (incorporating MES signature scores, TAM subset abundance, FcγRIIIa genotyping, and ctDNA-based dynamic monitoring) offers a clinically actionable strategy for early identification of non-responders, real-time detection of emerging resistance, and patient stratification in future trial designs.

By framing neuroblastoma as a continuously evolving ecosystem under therapeutic pressure, this work provides a rational roadmap for next-generation combination strategies—including epigenetically re-sensitizing MES-state cells, temporally sequenced TME remodeling prior to immunotherapy, and dual-targeting CAR designs—moving beyond empirical one-size-fits-all approaches toward mechanism-guided precision intervention.

The integrated multidimensional biomarker framework proposed herein (incorporating MES signature scores, TAM subset abundance, FcγRIIIa genotyping, and ctDNA-based dynamic monitoring) offers a clinically actionable strategy for early identification of non-responders, real-time detection of emerging resistance, and patient stratification in future trial designs.

Neuroblastoma is the most common extracranial solid tumor in children, and the prognosis for high-risk patients remains dismal. Immunotherapies, represented by anti-GD2 monoclonal antibodies and chimeric antigen receptor T cells (CAR-T), have significantly improved the survival of high-risk neuroblastoma patients and become part of standard therapy. However, their efficacy exhibits significant inter-individual heterogeneity, with some patients showing primary resistance or secondary relapse. This review aims to analyze the multi-faceted factors influencing the response to immunotherapy in neuroblastoma, including: (1) the inherent immunosuppressive properties of the tumor microenvironment, such as infiltration of myeloid-derived suppressor cells and tumor-associated macrophages, as well as checkpoint molecules and metabolic barriers; (2) tumor cell-intrinsic characteristics, such as low tumor mutational burden, MYCN amplification-associated downregulation of MHC-I, and heterogeneity of GD2 antigen expression; (3) host factors, such as systemic immune status and Fc receptor polymorphisms; and (4) treatment-related factors, such as combination strategies and the development of novel immunotherapeutic products. A deep understanding of these interrelated factors is crucial for developing predictive biomarkers, designing novel combination strategies and next-generation immunotherapies, and ultimately achieving precise immunotherapy for neuroblastoma.