Biological and prognostic insights into the prostaglandin D2 signaling axis in lung adenocarcinoma.

Background: Tumor metabolism reprogramming is a hallmark of cancer, but metabolite-mediated intercellular communication remains poorly understood. To address this gap, we estimated and explored communication events exploring based on single-cell RNA data, to explore the metabolic landscape of tumor microenvironment (TME) in lung adenocarcinoma (LUAD) and identify novel metabolite signaling axis. Methods: The scRNA-seq dataset was subjected to dimensionality reduction using the Seurat package. Cell annotation was manually performed using typical markers from Cell Marker 2.0 and previous studies. Single-cell metabolite abundance and communication events were inferred using MEBOCOST. The TCGA-LUAD datasets was used to estimate and analyze immune cell infiltration levels and tumor hot score using the ESTIMATE and ssGSEA algorithms. Additionally, survival analysis was conducted on genes within relative signaling axis. All analysis above in TCGA-LUAD dataset was validated by two Gene Expression Omnibus (GEO) datasets. The expression patterns of PTGDR and PTGDS were validated by RT-qPCR and fluorescence in situ hybridisation. Results: Five landmark metabolites across cell types were identified as prostaglandin D2 (PGD2), D-Mannose, Choline, L-Cysteine, and Cholesterol of TME in LUAD. Prostaglandin D2 (PGD2) emerged as a key player, primarily produced by fibroblasts and plasmacytoid dendritic cells (pDCs) by via the Conclusion: Collectively, these results suggest that PGD2 and its signaling axis play a significant role in tumor-suppressive and anti-inflammatory effects in LUAD, with potential applications in prognosis management and therapy decision-making.