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Contribution of crosstalk of mesothelial and tumoral epithelial cells in pleural metastasis of lung cancer

GSE242951 Homo sapiens Expression profiling by high throughput sequencing 12 samples 2024/06/26 GPL24676
Summary
Tumor metastasis commonly affects pleura in advanced lung cancer and is related to poor prognosis, but without systematic investigation on different cell types and their crosstalk at single cell resolution. Here, by integrating 180785 single cells from lung cancer and control samples, the most distinctive transcriptome profiles between tumor and control were revealed in mesothelial cells, which is the predominate cell type of pleura. Four subtypes were divided, including one predominately identified in malignant pleural effusion which was characterized by enriched cancer related pathways (e.g., cell migration) along evolutionary trajectory from normal mesothelial cells. Cancer-associated mesothelial cells exhibited varied interactions with different subtypes of malignant epithelial cells, and multiple ligands/receptors exhibited significant correlation with poor prognosis. Experimentally, mesothelial cells can increase the migration ability of lung cancer cells through co-culturing assay, and EGFR was the only affected gene in cancer cells that exhibited interaction with mesothelial cells and was associated with poor prognosis. Using EGFR antagonist cetuximab prevented the increased invasiveness of lung cancer cells induced by mesothelial cells. Moreover, EPGN-EGFR interaction was supported through spatial distribution analysis, revealing the significant proximity between EPGN+ mesothelial cells and EGFR+ epithelial cells. Our findings highlighted the important role of mesothelial cells and their interactions with cancer cells in pleural metastasis of lung cancer, which may facilitate cancer progression.
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NCBI GEO page ↗ Paper (PMID 38854934) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
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