Spatial transcriptomic analysis delineates epithelial and mesenchymal subpopulations and transition stages in childhood ependymoma

BACKGROUND

The diverse cellular constituents of childhood brain tumor ependymoma, recently revealed by single cell RNA-sequencing, may underly therapeutic resistance. Here we use spatial transcriptomics to further advance our understanding of the tumor microenvironment, mapping cellular subpopulations to the tumor architecture of ependymoma posterior fossa subgroup A (PFA), the commonest and most deadly childhood ependymoma variant.

METHODS

Spatial transcriptomics data from intact PFA sections was deconvoluted to resolve the histological arrangement of neoplastic and non-neoplastic cell types. Key findings were validated using immunohistochemistry, in vitro functional assays and outcome analysis in clinically-annotated PFA bulk transcriptomic data.

RESULTS

PFA are comprised of epithelial and mesenchymal histological zones containing a diversity of cellular states, each zone including co-existing and spatially distinct undifferentiated progenitor-like cells; a quiescent mesenchymal zone population, and a second highly mitotic progenitor population that is restricted to hypercellular epithelial zones and that is more abundant in progressive tumors. We show that myeloid cell interaction is the leading cause of mesenchymal transition in PFA, occurring in zones spatially distinct from hypoxia-induced mesenchymal transition, and these distinct EMT-initiating processes were replicated using in vitro models of PFA.

CONCLUSIONS

These insights demonstrate the utility of spatial transcriptomics to advance our understanding of ependymoma biology, revealing a clearer picture of the cellular constituents of PFA, their interactions and influence on tumor progression.

Transcription factor-nucleosome dynamics from plasma cfDNA identifies ER-driven states in breast cancer

Genome-wide binding profiles of estrogen receptor (ER) and FOXA1 reflect cancer state in ER+ breast cancer. However, routine profiling of tumor transcription factor (TF) binding is impractical in the clinic. Here, we show that plasma cell-free DNA (cfDNA) contains high-resolution ER and FOXA1 tumor binding profiles for breast cancer. Enrichment of TF footprints in plasma reflects the binding strength of the TF in originating tissue. We defined pure in vivo tumor TF signatures in plasma using ER+ breast cancer xenografts, which can distinguish xenografts with distinct ER states. Furthermore, state-specific ER-binding signatures can partition human breast tumors into groups with significantly different ER expression and mortality. Last, TF footprints in human plasma samples can identify the presence of ER+ breast cancer. Thus, plasma TF footprints enable minimally invasive mapping of the regulatory landscape of breast cancer in humans and open vast possibilities for clinical applications across multiple tumor types.