Integrated multi-omics analysis reveals the immunotherapeutic significance of tumor cells with high FN1 expression in ovarian cancer.

BACKGROUND: Ovarian cancer is a highly lethal gynecological malignancy characterized by significant heterogeneity and immunosuppressive tumor microenvironments, contributing to poor prognosis and therapeutic resistance. This study investigates the immunological and prognostic significance of FN1-expressing tumor cells using integrated multi-omics approaches. METHODS: The study used GEO database data processed with Seurat and Harmony R. Each cluster had marker genes and cells were tested for preference. Cell stemness was measured using AUCell and CytoTRACE. The gene regulatory network was analyzed using pySCENIC. Molecular signaling exchange study was done with CellChat. And immune infiltration as well as prognostic stratification was performed using bulk analysis. Finally, the identified FN1 targets were validated in conjunction with the spatial transcriptome as well as experimentally. RESULTS: The study highlighted FN1 expression as a key factor in ovarian cancer prognosis and immune resistance. High FN1 tumor cells were linked to poor survival. FN1 knockdown inhibited tumor growth by reducing tumor cells aggregation, invasion, and migration. Our findings suggested that FN1+ tumor cells contributed to immunotherapy resistance, making FN1 a potential biomarker and therapeutic target for improving treatment outcomes in ovarian cancer. CONCLUSION: A prognostic model created based on FN1 tumor cells provided a new idea for clinical staging of ovarian cancer patients. Meanwhile, this study provided new insights into the heterogeneity of tumor cells and suggested a potential therapeutic target, FN1, which could be helpful for precise immunotherapy of ovarian cancer.