Abstract
Abstract
Background
Hepatoblastoma exhibits variable therapeutic response that is not fully explained by current risk stratification. While prior studies have characterized tumor composition, the role of spatial organization in determining outcome, particularly in unresectable disease requiring transplantation under immunosuppression, remains unclear.
Methods
We integrated spatial transcriptomics using the 10x Genomics Visium platform (
n
= 11 tumors) with single-cell spatial molecular imaging using NanoString CosMx (
n
= 3 tumors) on post-chemotherapy explant specimens across clinically defined groups (relapse-prone unresectable, non-relapse unresectable, and resectable hepatoblastoma). Spatial deconvolution, module scoring, spatial co-localization, and cell-cell interaction analyses were used to define region-level transcriptional programs and their underlying cellular organization.
Results
We identified three spatial architectures associated with clinical outcome. Relapse-prone tumors exhibited a centralized, TME-dominated organization enriched for progenitor-like, cycling, and stress-responsive tumor cell states co-localized with SPP1+ TAMs and CAFs, with enrichment of hypoxia response, extracellular matrix remodeling, and Midkine (MDK-LRP1) signaling. Non-relapse tumors displayed a distributed architecture with compartmentalized tumor-immune interactions, increased immune engagement, and preserved epithelial differentiation, including inflammatory hepatocyte-like states. Resection samples showed reduced tumor cell state heterogeneity and more uniform TME-immune organization.
Conclusions
Integration of regional and single-cell spatial transcriptomics across two platforms reveals that the chemo-remodeled tumor architecture of hepatoblastoma encodes spatially organized tumor cell-TME interactions as central determinants of therapeutic response.
Translational Relevance
Current risk stratification in hepatoblastoma — principally based on staging and clinical features — does not reliably predict therapeutic response, particularly in unresectable disease. Our findings identify that spatial tumor-microenvironment (TME) organization is a key determinant of patient outcome. Specifically, our analysis reveals that disease relapse is driven by specialized macrophage-fibroblast signaling networks that promote an immune-cold, therapy-resistant niche. We define a spatially derived gene signature capturing this high-risk TME, which demonstrates strong prognostic value across independent cohorts, highlighting its potential utility as a biomarker for refined patient stratification. These results strongly suggest that incorporating spatial biomarkers into clinical assessment can improve the choice of therapy. Furthermore, the identification of Midkine (MDK) signaling and macrophage-stromal crosstalk as key components of relapse-associated architecture provides a direct rationale for targeting TME communication to combat therapeutic resistance. Together, this work supports a crucial shift from composition-based to spatially informed approaches for risk assessment and therapeutic targeting in hepatoblastoma.