Spatially organized multicellular immune hubs in human colorectal cancer
By K. Pelka, Matan Hofree, Jonathan H. Chen, Siranush Sarkizova, Joshua D. Pirl, Vjola Jorgji, Alborz Bejnood, Danielle Dionne, William Ge, Katherine H Xu and 62 more. Cell, 2021
691 citations recorded by the source corpus.
SUMMARY Immune responses to cancer are highly variable, with mismatch repair-deficient (MMRd) tumors exhibiting more anti-tumor immunity than mismatch repair-proficient (MMRp) tumors. To understand the rules governing these varied responses, we transcriptionally profiled 371,223 cells from colorectal tumors and adjacent normal tissues of 28 MMRp and 34 MMRd patients. Analysis of 88 cell subsets and their 204 associated gene expression programs revealed extensive transcriptional and spatial remodeling across tumors. To discover hubs of interacting malignant and immune cells, we identified expression programs in different cell types that co-varied across patient tumors and used spatial profiling to localize coordinated programs.We discovered a myeloid cell-attracting hub at the tumor-luminal interface associated with tissue damage, and an MMRd-enriched immune hub within the tumor, with activated T cells together with malignant and myeloid cells expressing T-cell-attracting chemokines. By identifying interacting cellular programs, we thus reveal the logic underlying spatially organized immune-malignant cell networks.
Subfields: Immunology, Molecular Biology, Oncology
View Paper: https://www.semanticscholar.org/paper/ff3fc93d99090d693e408354d6819f267a547c02
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In Immunology
In Molecular Biology
- Fabian J Theis
- Aviv Regev
- Giovanni Palla
- David S. Fischer
- Malte D. Luecken
- Rahul Satija
- Nir Yosef
- F. Alexander Wolf
Citations in the corpus
- Spatial components of molecular tissue biology (2022, positive): “Inference of cell–cell communication (a functional feature) from molecular profiling data has been addressed by statistical association methods that typically relate cell types to each other via previous knowledge annotation 27–30 , or by covariation patterns across samples 26,31 .”