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 gene and by mast cells via the gene. PGD2 signaling was shown to primarily be received by the PGD2 receptor () on NK/T cells and transported by the transporter on endothelial cells. NK/T cells, which are prominent cytotoxic populations, as a PGD2 autocrine signaling axis, are involved in PGD2 autocrine signaling, while KLRC2+ NK, DNAJB1+ NK cells and CD8+ MAIT cells participate in PGD2 paracrine signaling. PGD2 may also assist lactate efflux via on endothelial cells. The clinical relevance of the PGD2 signaling axis was validated across multiple bulk RNA datasets, showing that it is associated with the infiltration of above immune cells such as DNAJB1+ NK cells, and linked to better prognosis in LUAD. Furthermore, we found that a risk model developed based on this signaling axis could predict responses to immune therapy in hot and cold tumors, suggesting potential drugs that may benefit low-risk patients. These findings were further supported by RT-qPCR and immunofluorescence data, which confirmed the downregulation of PTGDS and PTGDR in LUAD tumor tissues compared to normal tissues.

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.