Single-cell Transcriptomic Analysis Reveals an Immunosuppressive Network Between POSTN CAFs and ACKR1 ECs in TKI-resistant Lung Cancer

Background/aim: Tyrosine kinase inhibitor (TKI) therapy, a principal treatment for advanced non-small cell lung cancer (NSCLC), frequently encounters the development of drug resistance. The tumor microenvironment (TME) plays a critical role in the progression of NSCLC, yet the relationship between endothelial cells (ECs) and cancer-associated fibroblasts (CAFs) subpopulations in TKI treatment resistance remains largely unexplored.

Materials and methods: The BioProject database PRJNA591860 project was used to analyze scRNA-seq data including 49 advanced-stage NSCLC samples across three different time points: pre-targeted therapy (naïve), post-partial response (PR) to targeted therapy, and post-progressive disease (PD) stage. The data involved clustering stromal cells into multiple CAFs and ECs subpopulations. The abundance changes and functions of each cluster during TKI treatment were investigated by KEGG and GO analysis. Additionally, we identified specific transcription factors and metabolic pathways via DoRothEA and scMetabolism. Moreover, cell-cell communications between PD and PR stages were compared by CellChat.

Results: ECs and CAFs were clustered and annotated using 49 scRNA-seq samples. We identified seven ECs subpopulations, with OIT3 ECs showing enrichment in the PR phase with a drug-resistance phenotype, and ACKR1 ECs being prevalent in the PD phase with enhanced cell adhesion. Similarly, CAFs were clustered into 7 subpopulations. PLA2G2A CAFs were predominant in PR, whereas POSTN CAFs were prevalent in PD, characterized by an immunomodulatory phenotype and increased collagen secretion. CellChat analysis showed that ACKR1 ECs strongly interacted with macrophage through the CD39 pathway and POSTN CAFs secreted Tenascin-C (TNC) to promote the progression of epithelial cells, primarily malignant ones, in PD.

Conclusion: This study reveals that POSTN CAFs and ACKR1 ECs are associated with resistance to TKI treatment, based on single-cell sequencing.