PURPOSE: High programmed death-ligand 1 (PD-L1) expression is associated with unfavorable clinical outcomes in epidermal growth factor receptor (EGFR)-mutated lung adenocarcinomas (LUAD) patients treated with tyrosine kinase inhibitors (TKIs) or anti-PD-1/PD-L1 therapy, yet the underlying mechanisms are less explored. METHODS: Bulk RNA sequencing (RNA-seq) datasets were analyzed to investigate intertumoral transcriptional variations linked to PD-L1 expression. Immunohistochemistry (IHC) was utilized to quantify PD-L1 expression on tumor cells. Digital spatial profiling (DSP) was performed on 23 EGFR-mutated LUAD tissue samples to characterize transcriptomic differences in tumor cell (TC), immune cell (IM), and macrophage (MA) compartments between PD-L1 high and low groups. Furthermore, a publicly available DSP dataset was analyzed and IHC was conducted for validation. RESULTS: Analysis of RNA-seq datasets identified differentially expressed genes, signaling pathways, and immune profiles associated with PD-L1 expression. Compared to low PD-L1 tumors, high PD-L1 tumors exhibited increased infiltration of T regulatory cells (Tregs) and enhanced immunosuppressive signatures. DSP analysis revealed compartment-specific molecular disparities: TC segment in high PD-L1 tumors showed upregulated signatures of cell proliferation, invasion, and metastasis. IM segment displayed increased infiltration of immunosuppressive cells, including Tregs and myeloid-derived suppressor cells and upregulated expression of inhibitory immunomodulators CD276, HAVCR2, and LGALS9C. CONCLUSION: Combining bulk and spatial RNA-seq, this study characterized the molecular and immunological hallmarks of EGFR-mutated LUAD in the context of PD-L1 expression, providing new insights into the development of tailored therapeutic strategies for EGFR-mutated LUAD with high PD-L1 expression.
Spatially resolved whole-transcriptomic profiling of EGFR-mutated lung adenocarcinomas stratified by PD-L1 expression.
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作者:Yu Chenxi, Shi Chenxi, Zhou Hao, Li Na, Ma Ruyi, Liu SongBai, Tang Zaixiang, Zhang Xianling, Lei Zhe, Qin Hualong
| 期刊: | Cellular Oncology | 影响因子: | 4.800 |
| 时间: | 2025 | 起止号: | 2025 Dec 22; 49(1):2 |
| doi: | 10.1007/s13402-025-01143-9 | ||
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