Four tumor micro-environmental niches explain a continuum of inter-patient variation in the macroscopic cellular composition of breast tumors.
El Marrahi, A.; Lipreri, F.; Alber, D.; Hausser, J.
Show abstract
The tumor microenvironment is a complex, self-organising tissue whose architecture determines prognostic and response to therapy. There is significant variation in the cellular and spatial architecture of the tumor-microenvironment within and across patients. Are there rules that constrain the architecture of the tumor-microenvironment? To find out, we develop a quantitative framework of tumor architecture inspired by ideas from satellite imaging, which we apply on deep single-cell profiling and multiplex imaging data in breast tumors. Data analysis shows that inter-patient variation in the macroscopic cellular composition of tumors is structured as a continuum explained by four tumor niches: cancer, inflammatory, tertiary lymphoid structure and fibrotic/necrotic. These niches have their origin in tumor micro-architecture and are shared across patients and tumor subtypes. Niche prevalence depends strongly on the patient, which constraints and explains inter-patient variation. The present framework will facilitate interpreting inter-patient variation in terms of a tractable number of micro-environmental niches which serve as organizational entities at the meso-scale to bridge the micro- and macro-scales of tumor architecture.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Automated assignment of cell identity from single-cell multiplexed imaging and proteomic data 97%
- Deciphering tumor ecosystems at super-resolution from spatial transcriptomics with TESLA 96%
- Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces 95%
Similar papers in this journal
Similar papers in this journal
- Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST 95%
- Learning tissue representation by identification of persistent local patterns in spatial omics data 95%
- MorphLink: Bridging Cell Morphological Behaviors and Molecular Dynamics in Multi-modal Spatial Omics 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.