Chapter 16 Establishment of In Vivo Ovarian Cancer Mouse Models Using Intraperitoneal Tumor Cell Injection Sonam Mittal, Prachi Gupta, Pradeep Chaluvally-Raghavan, and Sunila Pradeep Abstract Mouse models—xenograft models, syngeneic models (directly implanted or chemically or virally induced), and genetically engineered mice (including transgenic and knockout methods) are invaluable for preclinical studies of ovarian cancer as they recapitulate the structures and microenvironments of tumors, which in vitro studies are unable to accomplish. This chapter describes the methodology and approaches for generating various murine models currently employed in ovarian cancer research. It covers the implantation of cells from ovarian cancer cell lines into mice by intraperitoneal injection. Key words Ovarian cancer, In vivo models, Xenograft models, Syngeneic models 1 Introduction Ovarian cancer (OC) is the leading cause of cancer-related mortal- ity among women across the globe, and it accounts for more death than any other gynecologic malignancy. Despite various patient management strategies, the overall survival rate remains 30–40% [1]. Ovarian cancer diagnosed in late stages is difficult to treat by surgical debulking, and its metastasis to other organs in the perito- neal cavity makes chemotherapeutic treatment with platinum (cis- platin or carboplatin) and taxane (paclitaxel or docetaxel) challenging [2, 3]. It is also a complex and heterogeneous disease with at least five different histotypes: clear cell, endometrioid, mucinous, low-grade serous, and high-grade serous ovarian cancer (HGSOC). The multiple histological subtypes are characterized by different phenotypes, cells of origin, and distinct genetic and geno- mic alterations that may give rise to different forms of the disease [4–6]. Pamela K. Kreeger (ed.), Ovarian Cancer: Methods and Protocols, Methods in Molecular Biology, vol. 2424, https://doi.org/10.1007/978-1-0716-1956-8_16, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022 247