bioRxivGenomicsPreprint
Multi-regional characterisation of renal cell carcinoma and microenvironment at single cell resolution
Ruoyan LiiD, John Robert FerdinandiD, Kevin W. LoudoniD, Georgina BowyeriD, Lira MamanovaiD, Joana Briosa NevesiD, Liam BoltiD, Eirini Sofia FasouliiD, Andrew R. J. LawsoniD, Matthew D. YoungiD, Yvette E. Hooks, Thomas R. W. OliveriD, Timothy M. ButleriD, James N. Armitage, Tev AhoiD, Antony C. P. Riddick, Vincent J. GnanapragasamiD, Sarah Joanne WelshiD, Kerstin B. MeyeriD, Anne Yvonne WarreniD, Maxine G B TraniD, Grant Duncan StewartiD, Sam BehjatiiD, Menna Ruth ClatworthyiD, Peter J. CampbelliD, , Thomas J. MitchelliD
- Citations
- 3
Abstract
Tumour behaviour is dependent on the oncogenic properties of cancer cells and their multicellular interactions. These dependencies were examined through 270,000 single cell transcriptomes and 100 micro-dissected whole exomes obtained from 12 patients with kidney tumours. Tissue was sampled from multiple regions of tumour core, tumour-normal interface, normal surrounding tissues, and peripheral blood. We found the principal spatial location of CD8+ T cell clonotypes largely defined exhaustion state, with clonotypic heterogeneity not explained by somatic intra-tumoural heterogeneity. De novo mutation calling from single cell RNA sequencing data allows us to lineagetrace and infer clonality of cells. We discovered six meta-programmes that distinguish tumour cell function. An epithelial-mesenchymal transition meta-programme, enriched at the tumour-normal interface appears modulated through macrophage expressed IL1B, potentially forming a therapeutic target. Single sentence summaryKidney cancer evolution, prognosis and therapy are revealed by a single cell multi-regional study of the microenvironment.
- organism: human
- assay: scRNA-seq
- assay: whole-exome sequencing
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
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