Modeling the Tumor Microenvironment of Ovarian Cancer: The Application of Self-Assembling Biomaterials.

Abstract

Simple SummaryThe tumor-surrounding niche comprises not only cancer cells but also stromal cells, signaling molecules, secreted factors and the extracellular matrix. This niche has a three-dimensional (3D) architecture and is implicated in tumor progression, metastasis and drug resistance. 3D cancer models have been increasingly attracting attention due to their potential to provide a more representative tumor niche compared to traditional two-dimensional (2D) models. Bioengineered 3D models contain multiple cell types and important molecules that interact with each other to resemble crucial features of tumor tissues, including the 3D architecture, mechanical properties, genetic profile and cell responses to therapeutics. These defined characteristics highlight the application of 3D models to study tumor biology, metastatic pathways and drug resistance.Ovarian cancer (OvCa) is one of the leading causes of gynecologic malignancies. Despite treatment with surgery and chemotherapy, OvCa disseminates and recurs frequently, reducing the survival rate for patients. There is an urgent need to develop more effective treatment options for women diagnosed with OvCa. The tumor microenvironment (TME) is a key driver of disease progression, metastasis and resistance to treatment. For this reason, 3D models have been designed to represent this specific niche and allow more realistic cell behaviors compared to conventional 2D approaches. In particular, self-assembling peptides represent a promising biomaterial platform to study tumor biology. They form nanofiber networks that resemble the architecture of the extracellular matrix and can be designed to display mechanical properties and biochemical motifs representative of the TME. In this review, we highlight the properties and benefits of emerging 3D platforms used to model the ovarian TME. We also outline the challenges associated with using these 3D systems and provide suggestions for future studies and developments. We conclude that our understanding of OvCa and advances in materials science will progress the engineering of novel 3D approaches, which will enable the development of more effective therapies.