A Meta-analysis of 2D vs. 3D Ovarian Cancer Cellular Models

Three-dimensional (3D) cancer models are revolutionizing research, allowing for the recapitulation of in vivo like response through the use of an in vitro system, more complex and physiologically relevant than traditional mono-layer culture. Cancers such as ovarian (OvCa), are prone to developing resistance and are often lethal, and stand to benefit greatly from the enhanced modelling emulated by 3D culture. However current models often fall short of predicted response where reproducibility is limited owing to the lack of standardized methodology and established protocols. This meta-analysis aims to assess the current scope of 3D OvCa models and the differences in genetic profile presented by a vast array of 3D cultures. A meta-analysis of the literature (Pubmed.gov) spanning 2012 - 2022, was used to identify studies with comparable monolayer (2D) counterparts in addition to RNA sequencing and microarray data. From the data 19 cell lines were found to show differential regulation in their gene expression profiles depending on the bio-scaffold (i.e. agarose, collagen or Matrigel) compared to 2D cell cultures. Top genes differentially expressed 2D vs. 3D include C3, CXCL1, 2 and 8, IL1B, SLP1, FN1, IL6, DDIT4, PI3, LAMC2, CCL20, MMP1, IFI27, CFB, and ANGPTL4. Top Enriched Gene sets for 2D vs. 3D include IFN- and IFN-{gamma} Response, TNF- signalling, IL-6-JAK-STAT3 signalling, angiogenesis, hedgehog signalling, apoptosis, epithelial mesenchymal transition, hypoxia, and inflammatory response. Our transversal comparison of numerous scaffolds allowed us to highlight the variability that can be induced by these scaffolds in the transcriptional landscape as well as identifying key genes and biological processes that are hallmarks of cancer cells grown in 3D cultures. Future studies are needed to identify which is the most appropriate in vitro/preclinical model to study tumour microenvironment. SummaryOvarian cancer is one of the most lethal forms of female cancers. Cell culture is often the go to model to study the molecular processes of cancer. However, this is an oversimplification of the reality. 3D tissue culture has been developed to address the cell culture limitations and to provide a more realistic model of the system studied. Cells grown in 3D represent better the human tumour microenvironment. This meta-analysis is exploring the use of 3D tissue culture as a model of ovarian cancer. Our analysis shows that ovarian cancer cells grown in 3D exhibit enhanced regulation in processes pertinent to tumour development and progression. We identify a panel of genes associated with specific 3D growth conditions that could be used as conditional markers. Finally, we present an overview of the state-of-art of 3D culture with an extensive profile of the genes and pathways enhanced in ovarian cancer models.