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

Abstract

Copyright © author/funder 2022. 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-α and IFN-γ Response, TNF-α 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.