Rick Ursem

Chordomas are ultra-rare cancers from the axial skeleton with limited treatment options. Chordomas can exhibit immunogenic features, and immune checkpoint blockade has demonstrated clinical activity in some patients, yet the determinants of these responses remain poorly understood. We aimed to elucidate the biological basis of immunogenicity in chordomas through spatial transcriptomic and metabolomic analyses. We applied GeoMx digital spatial profiling to 15 chordomas, analyzing tumor and stromal compartments separately and comparing inflamed and non-inflamed tumors. Consecutive tissue sections were examined using MALDI-mass spectrometry imaging (MSI) at 20 µm spatial resolution. Findings were further explored through immunohistochemistry analyses. To assess whether transcriptional activity in tumor cells was associated with interferon-γ (IFN-γ) signaling, we tested the effect of IFN-γ treatment on chordoma cell lines. Digital spatial profiling of inflamed and non-inflamed chordomas revealed striking differences in both the cancer cell and stromal compartments. Increased immune infiltration was strongly associated with elevated transcriptional activity in cancer cells. MALDI-MSI revealed distinct metabolic signatures and pronounced glycogen accumulation in inflamed chordomas. Nevertheless, IFN-γ stimulation of chordoma cell lines did not induce expression of TBXT (brachyury), the master transcriptional regulator of chordoma biology. Collectively, our findings reveal a strong association between the transcriptomic and metabolic activity in chordomas and their immunogenicity. However, the causal direction of this relationship remains to be determined. Nevertheless, these findings are highly relevant for patient stratification, particularly in the context of immunotherapeutic strategies.

The integration of spatial omics technologies can provide important insights into the biology of tissues. Here we combined mass spectrometry imaging-based metabolomics and imaging mass cytometry-based immunophenotyping on a single tissue section to reveal metabolic heterogeneity at single-cell resolution within tissues and its association with specific cell populations such as cancer cells or immune cells. This approach has the potential to greatly increase our understanding of tissue-level interplay between metabolic processes and their cellular components.

Integration of spatial omics technologies can provide important insights into the biology of tissues. We combined mass spectrometry imaging-based metabolomics and imaging mass cytometry-based immunophenotyping on the same single tissue section to reveal metabolic heterogeneity within tissues and its association with specific cell populations like cancer cells or immune cells. This approach has the potential to greatly increase our understanding of tissue-level interplay between metabolic processes and their cellular components.