Fu Zhao ^1* Xiaojing Jiang ² Yumeng Li ¹ Tian Jiao Huang ³ Xiahou Zhikai ^4* Wenyang Nie ^1* Qian Li ^5*

• ¹ Shandong University of Traditional Chinese Medicine, Jinan, China
• ² Affiliated Hospital of Shandong Academy of Traditional Chinese Medicine, Jinan, Shandong Province, China
• ³ The First School of Clinical Medicine, Heilongjiang University of Traditional Chinese Medicine, Harbin, Jilin Province, China
• ⁴ China Institute of Sport and Health Science, Beijing Sport University, Beijing, China
• ⁵ Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, China

Abstract: Background: High-grade serous ovarian cancer (HGSOC) is a complex and aggressive form of ovarian cancer, often associated with poor outcomes due to metastasis and treatment resistance. Using single-cell RNA sequencing (scRNA-seq), we explored the cellular heterogeneity within HGSOC, focusing on tumor cell subtypes and their interactions within the tumor microenvironment (TME). Methods: Data from scRNA-seq were sourced from the GEO database. We performed geneontology and gene set enrichment analyses to identify differentially expressed genes. The inferCNV method was employed to detect tumor epithelial cells. Utilizing Monocle, Cytotrace, and Slingshot, we inferred subtype differentiation trajectories. Cellular interactions were predicted with CellChat, and pySCENIC analyzed transcription factor (TF) networks in tumor cell subtypes. OVCAR3 and OVCAR8 cell lines validated our findings through functional experiments. A risk scoring model was developed to evaluate clinical characteristics and predict prognosis, immune responses, and drug sensitivity. Results: The study investigates the heterogeneity of HGSOC using scRNA-seq, focusing on tumor cell subtypes and their interactions within the TME. The C2 IGF2+ tumor cell subtype is identified as a key player in HGSOC, associated with poorer prognosis and high chromosomal copy number variations (CNVs). Metabolic reprogramming, particularly in pathways like glycolysis and oxidative phosphorylation, is noted in the C2 subtype. The study also uncovers significant cell-cell communication, especially between C2 IGF2+ tumor cells and fibroblasts, potentially influencing tumor progression. The MDK-NCL signaling pathway is highlighted as a critical mediator in these interactions. The transcription factor PRRX1, highly expressed in the C2 subtype, is identified as a potential therapeutic target. In vitro experiments confirm the role of PRRX1 in tumor cell behavior. A prognostic model based on the C2 subtype's marker genes is developed, showing potential for personalized treatment strategies. Conclusion: By examining the cellular heterogeneity of the unique C2 IGF2+ tumor cell subtype within the HGSOC TME, we revealed its complex interaction with disease progression. This finding offered a novel perspective for diagnosing and treating HGSOC. Keywords：High-grade serous ovarian cancer, Prognostic Model, Immunotherapy, Molecular mechanisms, Tumor microenvironment, Multi-omics.