1 Welcome - Still Under construction

Pak Hin Yu1 🌵, Brian Davis2 🌵, Forough Abbasi1 🌵, Stephanie Chen2 , Robbin Nameki1, Ronny Drapkin3 , Kelly Bolton4 , Jasmine Plummer2 , Rosario I. Corona1, Simon A. Gayther1 2 🌞, Kate LawLnson1 2 🌞

1 Women’s Cancer Research Program at the Samuel Oschin Comprehensive Cancer Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA 2 Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, CA, USA 3 Ovarian Cancer Research Center, Department of Obstetrics and Gynecology, University of Pennsylvania Perelman School of Medicine, PA, USA 4. Department of Medicine,Washington University in St Louis , St Louis, MO

🌵 These authors contributed equally to this work. 🌞 These authors jointly supervised this work: Simon A. Gayther, Kate Lawrenson. email: ;

1.1 Abstract

Epithelial ovarian cancer is the most lethal gynecologic malignancy with an expected 13,770 deaths in the US in 2021. Clear cell ovarian cancer (CCOC) is a rare aggressive subtype of epithelial ovarian cancer that is known to be more chemoresistance and displays poorer prognosis compared to other subtypes. Despite its distinctive clinical and molecular characteristics, there is no specific treatment for CCOC. There is an unmet need to identify which CCOC models most faithfully capture the features of human disease to enable the development of novel therapeutics based on the specific molecular features of a patients tumor (‘personalized medicine’).

Three-dimensional (3D) cultures provided a more physiological relevant cancer model than a traditional two-dimensional (2D) monolayer cell cultures, as they more closely mimic the histological, biological, and molecular features of primary tumors. We therefore characterized sixteen cancer cell lines reportedly derived from CCOC in 2D and 3D cell culture by subjecting each to ‘multi-omic’ profiling comprising somatic genome sequencing to catalog somatic coding mutations, RNA-sequencing to profile gene expression, immunoprecipitation-sequencing (ChIP-seq) for active chromatin associated with acetylated histone 3 (H3K27ac), and reverse phase protein arrays (RPPAs) to profile protein abundance and activation state of key cancer pathways respectively. Consensus clustering stratified CCOC into two groups, explained in part by PI3K pathway mutations. Comparing the ‘multi-omic’ profiles among the cell lines, we observed molecular heterogeneity driven by both the cell line and culture conditions. Protein expression and post-translational modification better stratified 2D and 3D cultured cells compared to gene expression. 3D culture was associated with altered regulation of pathways involved in cell proliferation, and also cellular metabolism and responses to stress. Our results prioritize some less widely used models as faithful models of human CCOC (JHOC5, RMG-II) and concur with previous reports questioning the validity of ES-2 as a model of this disease. Currently, fewer than 5% of drugs with promising in vitro results translate into novel therapeutics for patients. We expect this comprehensive multi-omic profiling of 3D CCOC models will pave the way for the development of new therapies for this aggressive malignancy