bioRxivBioinformaticsPreprint
Deconvoluting single-cell transcriptomics reveals cellular programs regulated by cell-cell communication in colorectal cancer
Han ZhangiD, Binfeng LuiD, Aodong Qiu, Gregory F. CooperiD, Anwaar SaeediD, John William PaisleyiD, Xinghua LuiD, Lujia CheniD
Abstract
Cells within a tissue microenvironment communicate through intricate cell-cell communication (CCC) networks. In this meta-analysis of eight single-cell cohorts encompassing 153 patients and 279 samples, we advance the understanding of CCC networks in colorectal cancers through a novel analytical framework. Employing hierarchical topic modeling, we identify gene expression modules (GEMs) that mirror single-cell signaling states, crucial for deciphering the complexity of intercellular interactions. By applying causal discovery methods, we systematically uncover GEMs likely regulated by ligand-receptor signaling and cross-cell-type communication. This analysis reveals cross-cell-type CCC programs, marked by highly correlated GEMs across various cell types, shedding light on the intricate CCC networks within the tumor microenvironment. Spatial transcriptomics further validate these findings by demonstrating the co-localization of GEMs within CCC programs in distinct spatial domains, emphasizing the spatial dynamics of tumor intercellular communication. Our interactive website (http://44.192.10.166:3838/) and analytical framework equip researchers with powerful tools to explore these complex mechanisms, potentially uncovering novel drug targets and refining strategies for precision immunotherapies. This comprehensive study not only presents a detailed catalog of CCC networks driven by ligand-receptor interactions in colorectal cancer but also highlights the significance of integrating multi-sample and patient data to unravel the molecular underpinnings of cancer communication pathways.
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 1
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