Yeo, Kok Siong

Abstract Neuroblastoma (NB) accounts for 10% of pediatric cancer-related deaths. High-risk NB is frequently metastatic at diagnosis and has a poor 5-year survival rate (<50%) despite aggressive treatment. GD2, a disialoganglioside glycolipid that is expressed in nearly all NBs, has been validated as a promising immunotherapy target. Although GD2-CAR-T cells have been clinically evaluated, their efficacy has been limited by poor tumor infiltration and the immunosuppressive tumor microenvironment (TME), highlighting the need for alternative immune-based strategies. With inherent capacity of macrophages to infiltrate tumors, phagocytose cancer cells, and modulate TME, they represent a promising alternative strategy for immunotherapy in NB. In this study, we developed and evaluated GD2-CAR-macrophages (GD2-CAR-Ms) as a novel therapeutic approach for NB. GD2-specific CAR constructs were designed, validated, and introduced into multiple human and murine monocyte/macrophage cell lines via lentiviral transduction. Fluorescent microscopy and flow cytometry confirmed a significant enhancement in the phagocytosis of GD2-high NB cells by GD2-CAR-Ms containing Hu3F8 single-chain variable fragment (scFv). A strong positive correlation was observed between GD2 expression levels on the target cells and phagocytosis efficiency of GD2-CAR-Ms, indicating that the phagocytic activity of GD2-CAR-Ms is antigen-specific. Anti-tumor efficacy was further evaluated in vivo using an immunocompetent Mycn-expressing NB non-genetically engineered mouse model (MYCN-NGEMM). Mice treated with GD2-CAR-Ms exhibited significantly reduced tumor burden and prolonged survival compared to control groups. Notably, treatment of mice bearing GD2-high tumors resulted in markedly improved survival, including one complete remission among ten treated animals, underscoring the therapeutic potential of GD2-targeted macrophage therapy. Histological analysis showed increased deposition of connective tissues and decreased tumor cells density, suggesting TME remodeling. Furthermore, immunohistochemistry reveals increased immune cell infiltration, particularly of macrophages, neutrophils and T cells, indicating a favorable shift in the immune TME from “cold” to “hot” following GD2-CAR-M treatment. Additionally, inhibition of tumor growth was also observed in our zebrafish NB model after GD2-CAR-Ms treatment, further supporting their therapeutic potential. Together, our findings demonstrate that GD2-CAR-Ms exhibit potent antitumor activity and reshape the tumor immune microenvironment, supporting their translational potential as a therapeutic strategy for high-risk NB. Citation Format: Ke-En Tan, Kok Siong Yeo, Cheng Zhang, Caleb Baker, Shyang Hong Tan, Alexis M. Sosic, Yat-Yuen Lim, Choong-Yong Ung, Cristina Correia, Stephanie F. Polites, Yi Lin, William A. Weiss, Hu Li, Shizhen Zhu. Engineering macrophages as a novel therapeutic approach for high-risk neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7810.

Abstract Neuroblastoma (NB) accounts for approximately 10% of pediatric cancer-related deaths. High-risk NB is often metastatic at diagnosis with a poor 5-year survival rate (<50%) despite intensive multimodal therapy. GD2, a disialoganglioside glycolipid expressed in nearly all NBs, is a well-validated immunotherapy target. Although GD2-CAR-T cells have been clinically evaluated, their efficacy remains limited due to poor tumor infiltration and the immunosuppressive tumor microenvironment (TME), underscoring the need for alternative immune-based approaches. Given the inherent capacity of macrophages to infiltrate solid tumors, phagocytose cancer cells, and modulate the TME, we engineered the GD2-CAR macrophage (GD2-CAR-M) as a novel therapeutic platform for NB. GD2-specific CAR constructs containing the Hu3F8 single-chain variable fragment (scFv) were designed, validated, and introduced into multiple human and murine monocyte/macrophage cell lines via lentiviral transduction. Fluorescence microscopy and flow cytometry demonstrated a significant enhancement in the phagocytosis of GD2-high NB cells and the phagocytic efficiency correlating positively with GD2 expression levels, suggesting antigen-specific phagocytosis by GD2-CAR-M. Our further in vivo studies using an immunocompetent MYCN-driven NB non-genetically engineered mouse model (MYCN-NGEMM) showed that treatment with GD2-CAR-M markedly reduced tumor burden and prolonged survival compared with controls. Notably, mice bearing GD2-high-tumors exhibited significantly improved survival, including one complete remission among ten treated animals. Histological analyses revealed increased connective tissue deposition and decreased tumor cell density, suggesting TME remodeling. Single-cell RNA sequencing and immunohistochemistry further demonstrated enhanced infiltration of macrophages, neutrophils, and T cells, indicating a shift from a “cold” to a “hot” immune TME following GD2-CAR-M treatment. Consistent antitumor effects were also observed in our dbh-MYCN transgenic zebrafish with spontaneous development of NB following GD2-CAR-M administration. Taken together, GD2-CAR-M exhibits potent antigen-specific antitumor activity and promotes favorable TME remodeling in NB models. These findings highlight GD2-CAR-M as a promising translational immunotherapy strategy for high-risk NB. Citation Format: Shizhen (Jane) Zhu, Ke-En Tan, Kok Siong Yeo, Cheng Zhang, Caleb T. Baker, Alexis M. Sosic, Eddie Lim . Yat Yuen, Choong Yong Ung, Stephanie F. Polites, Yi Lin, William A. Weiss, Hu Li. Harnessing GD2-CAR macrophages to target high-risk neuroblastoma [abstract]. In: Proceedings of the AACR Immuno-Oncology Conference (AACR IO): Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2026 Feb 18-21; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2026;14(2 Suppl):Abstract nr B005.

ABSTRACT Symmetry refers to properties that remain invariant upon mathematical transformations. The principles of symmetry have guided numerous important discoveries in physics and chemistry but not in biology and medicine. Here, we aim to explore the presence of symmetry relationships at the gene expression level as a mean to distinguish between healthy and disease states. We deployed Learning-Based Invariant Feature Engineering - LIFE, a hybrid machine learning approach implemented with two symmetric invariant feature functions (IFFs) to identify Invariant Feature Genes (IFGs), which are gene pairs whose IFF single-value outputs remain invariant across individual samples in a given biological phenotype. Our multiclass classification results across the transcriptomes of 25 normal organs, 25 cancer types, and blood samples obtained from 4 different types of neurodegenerative diseases revealed the presence of unique phenotype-specific IFGs. We constructed networks using these IFGs (IF-Nets) and intriguingly, we demonstrated that the hubs could serve as information encoders, capable of reconstructing sample-wise expression values in relation to their counterpart genes. More importantly, we found that hubs of cancer IF-Nets were enriched with both approved and clinical trial drugs, highlighting “symmetry breaking” as a novel approach for treating diseases.

Spatially resolved sequencing technologies help us dissect how cells are organized in space. Several available computational approaches focus on the identification of spatially variable genes (SVGs), genes whose expression patterns vary in space. The detection of SVGs is analogous to the identification of differentially expressed genes and permits us to understand how genes and associated molecular processes are spatially distributed within cellular niches. However, the expression activities of SVGs fail to encode all information inherent in the spatial distribution of cells. Here, we devised a deep learning model, Spatially Informed Artificial Intelligence (SPIN-AI), to identify spatially predictive genes (SPGs), whose expression can predict how cells are organized in space. We used SPIN-AI on spatial transcriptomic data from squamous cell carcinoma (SCC) as a proof of concept. Our results demonstrate that SPGs not only recapitulate the biology of SCC but also identify genes distinct from SVGs. Moreover, we found a substantial number of ribosomal genes that were SPGs but not SVGs. Since SPGs possess the capability to predict spatial cellular organization, we reason that SPGs capture more biologically relevant information for a given cellular niche than SVGs. Thus, SPIN-AI has broad applications for detecting SPGs and uncovering which biological processes play important roles in governing cellular organization.

For nearly a decade, researchers in the field of pediatric oncology have been using zebrafish as a model for understanding the contributions of genetic alternations to the pathogenesis of neuroblastoma (NB), and exploring the molecular and cellular mechanisms that underlie neuroblastoma initiation and metastasis. In this review, we will enumerate and illustrate the key advantages of using the zebrafish model in NB research, which allows researchers to: monitor tumor development in real-time; robustly manipulate gene expression (either transiently or stably); rapidly evaluate the cooperative interactions of multiple genetic alterations to disease pathogenesis; and provide a highly efficient and low-cost methodology to screen for effective pharmaceutical interventions (both alone and in combination with one another). This review will then list some of the common challenges of using the zebrafish model and provide strategies for overcoming these difficulties. We have also included visual diagram and figures to illustrate the workflow of cancer model development in zebrafish and provide a summary comparison of commonly used animal models in cancer research, as well as key findings of cooperative contributions between MYCN and diverse singling pathways in NB pathogenesis.

Abstract One of the greatest barriers to curative treatment of neuroblastoma is its frequent metastatic outgrowth prior to diagnosis, especially in cases driven by amplification of the MYCN oncogene. However, only a limited number of regulatory proteins that contribute to this complex MYCN-mediated process have been elucidated. Here we show that the growth arrest-specific 7 (GAS7) gene, located at chromosome band 17p13.1, is preferentially deleted in high-risk MYCN-driven neuroblastoma. GAS7 expression was also suppressed in MYCN-amplified neuroblastoma lacking 17p deletion. GAS7 deficiency led to accelerated metastasis in both zebrafish and mammalian models of neuroblastoma with overexpression or amplification of MYCN. Analysis of expression profiles and the ultrastructure of zebrafish neuroblastoma tumors with MYCN overexpression identified that GAS7 deficiency led to (i) downregulation of genes involved in cell–cell interaction, (ii) loss of contact among tumor cells as critical determinants of accelerated metastasis, and (iii) increased levels of MYCN protein. These results provide the first genetic evidence that GAS7 depletion is a critical early step in the cascade of events culminating in neuroblastoma metastasis in the context of MYCN overexpression. Significance: Heterozygous deletion or MYCN-mediated repression of GAS7 in neuroblastoma releases an important brake on tumor cell dispersion and migration to distant sites, providing a novel mechanism underlying tumor metastasis in MYCN-driven neuroblastoma. See related commentary by Menard, p. 2815