Multimodal single-cell and spatial analyses reveal a distinct immune ecosystem in pediatric classic Hodgkin lymphoma Free

Classic Hodgkin lymphoma (CHL) is unique among most malignancies as the malignant Hodgkin and Reed–Sternberg (HRS) cells (0.1-5%) are vastly outnumbered by a heterogeneous population of reactive, non-neoplastic cells within the tumor-microenvironment (TME). CHL exhibits a bimodal age distribution, with peaks in adolescents and young adults (AYAs) aged 15-39 years and older adults (over 50 years). Although a previous bulk gene expression-based study (Johnston et al., Blood 2022) suggested differences in the TME transcriptional profiles between pediatric CHL and adult CHL, the study did not take into account for key factors such as cellular interactions, specific expression features of HRS cells, or the spatial architecture of the TME. A deeper understanding of the age-related TME ecosystem is essential for advancing our knowledge of the unique pathogenesis of pediatric CHL and for developing biomarker-driven targeted therapies. In this study, we aim to elucidate distinct TME ecosystems in pediatric CHL by applying single-cell and spatial technology.

We performed single-nuclei RNA sequencing (snRNA-seq) on formalin-fixed, paraffin-embedded (FFPE) tissue samples from a total of 27 patients, including 11 adult (19-39 years) and 8 pediatric HL patients (10-16 years) with Epstein-Barr virus (EBV)-negative nodular sclerosis HL, as well as 4 adult and 4 pediatric reactive lymph nodes (RLN) serving as normal controls. We merged the expression data from all cells and used the louvain clustering algorithm to identify major cell types and functional cellular subsets and defined each immune cell population based on marker expression. We also performed spatial transcriptomics using the CosMx™ Spatial Molecular Imager with the human 6K discovery panel, applied to tissue microarray (TMA) from 75 pediatric CHL patients (3-18 years) enrolled in the Children's Oncology Group (COG) AHOD0031 trial. We utilized transcriptomic signatures of cell types identified by snRNA-seq to annotate major cell types in CosMx data by a label transfer approach. For each cell type in the TME, we calculated a ‘spatial score’ (Aoki et al., J Clin Oncol 2024), spatial cell enrichment score of a given cell type as the distance to the five nearest neighbor cells, capped at the spatial interaction range (50µm).

We analyzed 119,335 cell transcriptomes after quality control filtering in the snRNA-seq data. Unsupervised clustering revealed 20 phenotypically distinct clusters. When comparing age-related distributions of immune cell phenotypes, CD8⁺ T cells, NK cells, naïve T cells, CD4⁺ T cells and B cells were significantly more predominant in pediatric CHL compared to adult CHL (p < 0.001). In contrast, myeloid cells including monocytes, macrophages, and dendritic cells, were more enriched in adult CHL than in pediatric CHL (p < 0.001). In particular, we identified a subcluster, myeloid-C2, characterized by high CXCL13and CD68expression, which represent the most distinct population in adult CHL.

Among the immune populations enriched in the TME of pediatric CHL, we further investigated the CD8⁺ T cell subsets, as the role of CD8⁺ T cells in CHL remains incompletely understood. We first performed differential gene expression analysis between cells from pediatric and adult CHL samples within the CD8⁺ T cell cluster, identifying CCL5 as the one of the most up-regulated genes in pediatric CHL. We further identified a pediatric HL enriched subcluster, CD8-C2, characterized by high CCL5 and LAG3 expression. The CD8-C2 cluster exhibited high expression of cytotoxicity, IFN response, and exhaustion signatures. Notably, the cell-to-cell communication tool, Cell-Chat, revealed a significant interaction between the CCL5⁺ (CD8-C2) and CCR4(HRS cells) axis (p<0.001). CCR4⁺ HRS cells were significantly more enriched in pediatric CHL compared to adult CHL (p < 0.001).

To validate these findings, we analyzed CosMx data comprising 557,742 cells. By calculating a spatial score, we confirmed that CCR4⁺ HRS cells were significantly more proximal to CCL5⁺ CD8⁺T (CD8-C2) cells (p=0.02), but not to CCL5^- CD8⁺T cells.

Multimodal transcriptional and spatial profiling reveals a distinct TME in pediatric CHL. We identified the interaction of CCR4⁺ HRS cells with ligand-expressing CCL5⁺ CD8⁺ T cells as a prominent crosstalk axis in pediatric CHL, with potential Iimplications for novel therapeutic approaches.