Periodic Reporting for period 3 - BRAIN-MATCH (Matching CNS Lineage Maps with Molecular Brain Tumor Portraits for Translational Exploitation)
Okres sprawozdawczy: 2022-05-01 do 2023-10-31
• improvement of our understanding of the tumor “cell of origin” by investigating tumor and normal brain development at single cell resolution
• identification of the transcriptional regulation shared between tumors and it’s lineage of origin, in addition to identifying genes that distinguishes former from the later
• identification of newer therapeutic targets that could be cell surface-based proteins involved in cell-cell communication, signaling or intracellular regulatory protein that could be targeted by known or putative drugs
• atlasing the hindbrain (cerebellum and lower brainstem) since these are common locations of childhood brain tumors
1) We have generated and fully annotated a single cell RNA sequencing atlas of the human cerebellum covering its development from the early neurogenesis to adult.
2) We compared the cerebellar tumors to the above generated normal developing cerebellum atlas in order to identify most similar cerebellar cell population associated with specific tumor types. We focused on medulloblastoma, posterior fossa ependymoma, pilocytic astrocytoma and radiation induced glioma (possible relapse tumor type after medulloblatoma treatment) and identified specific cell populations (lineage of origin) that match most to
each of these tumor types.
3) We distinguished tumor-specific genes in association with the cells of origin as well as the unique tumor that could be potentially used in improved therapeutic approaches.
4) We generated a single nucleus RNA sequencing atlas of the human lower brainstem (pons and medulla) covering its development from the early neurogenesis to adult. We have data for 250,00 cells and the analysis is ongoing.
5) We established a single nucleus ATAC sequencing atlas of the mouse cerebellum development (90,000 cells, published) and the human cerebellum development (110,000 cells, analysis ongoing).
We are also developing a single cell methylome protocol. This would allow the comparison of the cell type-specific methylation profiles from normal development to the tumour types (classified by methylation profiles).
We expect these state-of-the-art methods to complement the snRNA-seq atlases (this is what was proposed) that altogether would allow more precise mapping of the tumour classes/types.