Integrating single-cell and spatial transcriptomic analysis to unveil heterogeneity in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) presents significant challenges due to its heterogeneity and late-stage diagnoses. Using single-cell and spatial transcriptomics to elucidate the complex landscape of HGSOC to understand its underlying mechanism. Our analysis reveals significant inter- and intra-tumoral diversity, manifested through distinct cellular subpopulations and varied microenvironmental niches. Notably, our findings highlight a widespread immunosuppressive environment, marked by complex networks of cell-cell interactions, particularly evident in areas of elevated tumor cell density within metastatic samples. We identify the exclusive presence of COL14A1+ neoplastic cells in metastatic specimens, alongside a strong correlation between CD8A+ NKT cells and poor prognosis, and elevated CHODL expression in HGSOC metastasis tissues. Furthermore, knockdown experiments targeting CHODL demonstrate its role in reducing migration and invasion abilities in HGSOC cells. A pivotal discovery of our study is the delineation of specific cellular signatures correlated with adverse outcomes, notably a subset of CHODL+ neoplastic cells characterized by a distinct metabolic phenotype with a predilection for lipid metabolism. The therapeutic targeting of this metabolic pathway with existing inhibitors appears promising in curbing tumor proliferation. These findings enhance our understanding of HGSOC heterogeneity and reveal potential therapeutic targets, promising more effective management strategies for this aggressive cancer subtype.