Spatial transcriptomics in cancer
Revealing distinct tumor core and edge architectures that predict survival and therapy response
We performed an integrative single-cell and spatial transcriptomic analysis on HPV-negative oral squamous cell carcinoma (OSCC) to comprehensively characterize malignant cells in tumor core (TC) and leading edge (LE) transcriptional architectures. The TC and LE are characterized by unique transcriptional profiles, neighboring cellular compositions, and ligand-receptor interactions.
Key Findings
- The gene expression profile associated with the LE is conserved across different cancers while the TC is tissue specific
- LE gene signature is associated with worse clinical outcomes; TC gene signature is associated with improved prognosis across multiple cancer types
- Identified spatially-regulated patterns of cell development in OSCC that are predictably associated with drug response
- Developed machine learning models to identify conserved TC and LE signatures across 17 cancer types
Interactive Atlases
We provide interactive spatial atlases for exploring the data: Spatial Atlas and Dynamo Atlas.
Collaborators
This work was conducted with researchers from the University of Calgary, University of Toronto, and University of Oxford, in collaboration with Pinaki Bose's lab. The study involved spatial transcriptomic profiling of 12 OSCC samples from 10 patients.
Publications
Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response · Nature Communications 2023
ASCO 2022 Abstract · Journal of Clinical Oncology 2022
Press
Featured in The Scientist.