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Michael Xu

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Open access Sep 2026

A CCL4-enriched NK-cell transcriptional state is associated with inflammatory and myeloid-stromal programs in colorectal cancer liver metastasis

Colorectal cancer liver metastasis (CRLM) develops within a liver-specific immune and stromal microenvironment, yet the natural killer (NK)-cell adaptations associated with this metastatic niche remain incompletely defined. We integrated human single-cell RNA sequencing, an exploratory murine cross-species comparison, spatial transcriptomics, bulk transcriptomic cohorts, donor-level pseudobulk analyses, cell-cell communication, pseudotime and in silico perturbation analyses, together with multiplex immunofluorescence, conditioned-medium assays, ELISA and immunoblotting. Across 73,486 cells from six anatomical sites, NK cells showed lower relative representation within the recovered T/NK compartment in primary tumors and liver metastases, while the residual compartment showed inflammatory remodeling. NK-cell reclustering identified CD56-associated and CD16-associated CCL4 source clusters that were analyzed jointly as a CCL4-enriched NK-cell transcriptional state characterized by NF-κB, TNF, MAPK and JAK-STAT programs. In paired GSE164522 samples from 10 patients, this state was independently recovered, with nominally higher CCL4-associated signal in liver metastases than in primary tumors that did not remain significant after Benjamini-Hochberg correction. Spatial and communication analyses associated the state with SPP1-positive macrophage and stromal programs without establishing causality. Tissue imaging, conditioned-medium assays, ELISA and immunoblotting provided complementary marker-level and model-system support for CCL4-associated inflammatory activity and NF-κB pathway responsiveness. CRLM is associated with altered NK-cell representation among recovered cells and a reproducible CCL4-enriched inflammatory NK-cell transcriptional state. Its association with inflammatory and myeloid-stromal programs across independent, spatial and model-system analyses provides a focused framework for future lineage-restricted and in vivo studies.

Li-Hong Lin, Michael Xu, Xiao-Chun Gu et al. · 0 citations

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