Uncovering key regulatory pathways and prognostic biomarkers in the tumor microenvironment of high-grade serous ovarian cancer through single-cell RNA sequencing and experimental validation.

BACKGROUND

High-grade serous ovarian cancer (HGSOC) is a leading cause of cancer-related deaths among women globally. This study aims to identify novel regulatory targets and signaling pathways that modulate the tumor microenvironment (TME) in HGSOC, focusing on the pleiotrophin (PTN) signaling pathway and syndecan 4 (SDC4) expression as potential biomarkers for prognosis.

METHODS

Bioinformatics analysis was conducted on single-cell RNA sequencing (scRNA-seq) data (GSE146026) of HGSOC to investigate the TME. The data were subjected to unsupervised clustering to classify cell types within the TME, revealing eight distinct clusters representing various cell types. Cell-cell interactions were analyzed using the CellChat tool. Additionally, TCGA datasets were used to validate the expression of SDC4 and its association with clinical outcomes. The functional enrichment of differentially expressed genes (DEGs) between high and low SDC4 expression groups was performed to uncover associated pathways. Experimental validation was carried out using quantitative real-time PCR (qRT-PCR) and Western blotting on ovarian cancer cell lines (OVCAR3 and SKOV3).

RESULTS

The unsupervised clustering analysis revealed eight major cell types: macrophages, fibroblasts, ovarian cancer cells, B cells, T cells, dendritic cells, and erythrocytes. CellChat analysis highlighted significant interactions between these cell types, suggesting a complex TME. Further exploration identified PTN signaling as a key regulator within the HGSOC TME. Validation using TCGA datasets revealed upregulation of SDC4 in ovarian cancer tissues, with high SDC4 expression correlating with shorter overall survival. DEGs between high and low SDC4 expression groups were linked to the PI3K-Akt and MAPK signaling pathways, cell junction organization, and focal adhesion. qRT-PCR validation confirmed a significant upregulation of SDC4 in OVCAR3 and SKOV3 ovarian cancer cell lines, with expression levels 3.8- to 4.2-fold higher than control cells (<0.01), supporting the computational predictions.

CONCLUSION

This study highlights the PTN signaling pathway as a potential therapeutic target in HGSOC and identifies SDC4 as a prognostic biomarker for poor patient outcomes. Our findings offer new insights into the molecular mechanisms governing the TME of HGSOC, although further investigation is needed to fully elucidate the functional role of SDC4 in ovarian cancer progression.