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Biology subjects

McNeil, R.

Publications and source records attributed to McNeil, R..

2 recordsLinked to original sources

Spatially resolved single-cell analysis uncovers protein kinase C-& expressing microglia with anti-tumor activity in glioblastoma

Glioblastoma (GBM) is a brain tumor that poses a formidable challenge to treatment options available. The tumor microenvironment (TME) in GBM is highly complex, marked by immunosuppression and cellular heterogeneity. Understanding the cellular interactions and their spatial organization within the TME is crucial for developing effective therapeutic strategies. In this study, we integrated single-cell RNA sequencing and spatial transcriptomics in a GBM mouse model to unravel the spatial landscape of the brain TME. We identified a previously unrecognized microglia subtype expressing protein kinase C{delta} (PKC{delta}) associated with potent anti-tumor functions. The presence of PKC{delta}-expressing microglia was confirmed in resected human GBM specimens. Elevating tumoral PKC{delta} expression using niacin or adeno-associated virus in mice enhanced the phagocytosis of GBM cells by microglia in culture and increased the lifespan of mice with intracranial GBM. These findings were corroborated in analyses of the TCGA GBM datasets where low PKC{delta} samples showed negative pathway enrichment for apoptosis, phagocytosis, and immune signaling pathways, as well as lower levels of immune cell infiltration overall. Our study underscores the importance of integrating spatial context to unravel the TME, resulting in the identification of previously unrecognized subsets of microglia with anti-tumor functions. These findings provide valuable insights for advancing innovative immunotherapeutic strategies in GBM.

immunology↗

Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response

We performed the first integrative single-cell and spatial transcriptomic analysis on HPV-negative oral squamous cell carcinoma (OSCC) to comprehensively characterize tumor core (TC) and leading edge (LE) transcriptional architectures. We show that the TC and LE are characterized by unique transcriptional profiles, cellular compositions, and ligand-receptor interactions. We demonstrate that LE regions are conserved across multiple cancers while TC states are more tissue specific. Additionally, we found our LE gene signature is associated with worse clinical outcomes while the TC gene signature is associated with improved prognosis across multiple cancer types. Finally, using an in silico modeling approach, we describe spatially-regulated patterns of cell development in OSCC that are predictably associated with drug response. Our work provides pan-cancer insights into TC and LE biologies, a platform for data exploration (http://www.pboselab.ca/spatial_OSCC/) and is foundational for developing novel targeted therapies.

cancer biology↗