“Cancer in MIVO®”: a 3D fluid-dynamic model for recapitulating the tumor microenvironment

The tumor microenvironment (TME) comprises of various cellular components (e. g. cancer cells, cancer-associated fibroblasts (CAFs), endothelial and immune cells), signaling molecules (e. g. cytokines, chemokines, and growth factors), extracellular matrix components (e. g. collagen, elastin, and laminins), and biomechanical factors (e.g. stiffness and shear pressure). A deeper understanding of the TME has led to new therapeutic strategies, such as targeting CAFs1 and tumor-infiltrated immune cells2. Moreover, the TME plays a crucial role in therapy resistance3, making its integration into preclinical models essential for studying mechanisms of therapy resistance and testing next generation targeted therapies. The multi-in vitro-organ (MIVO®) platform is a dynamic 3D cell culture platform, incorporating both the cellular and extracellular components of tumor tissue—cancer cells and fibroblasts embedded in a biomimetic matrix—while also replicating the physiological shear forces exerted by blood flow on a solid tumor. This versatile model has been shown to effectively recapitulate the TME, enabling the study of immune-infiltration4, predicting drug efficacy comparable to in vivo condition5, and testing novel therapeutic strategies, such as magnetic nanomedicine approaches6. In an on-going study, we aim to extend our investigation into the tumor-stroma interactions. Specifically, fibroblasts, a main cell type of the stroma (HDF), are cocultured with cancer cells (e.g. esophageal adenocarcinoma cells OE-19 or breast cancer cells MDA-MB-231) within a tissue-mimicking matrix under physiological fluiddynamic conditions in MIVO®. By optimizing the key conditions for this system, including the fibroblast-to-cancer cell ratio (e.g. 1:1, 1:10, and 10:1) and different types of 3D matrices (collagen, alginate, and GelMA), we may induce CAF phenotype in fibroblasts, as indicated by increased expression of αSMA, typically observed in vivo. This improved model will enable us to gain in-depth insights into the interactions taking place within the tumor milieu, e.g. exploring the signaling pathways that activate cancer-associated fibroblasts (CAFs), their role in remodeling the extracellular matrix, their contribution to epithelial-to-mesenchymal transition (EMT) and therapy resistance in cancer cells, and the testing of drugs that target these pathways. References 1. Glabman RA, Choyke PL, Sato N. Cancer-Associated Fibroblasts: Tumorigenicity and Targeting for Cancer Therapy. Cancers (Basel). 2022;14(16):3906. doi:10.3390/cancers14163906 2. Gun SY, Lee SWL, Sieow JL, Wong SC. Targeting immune cells for cancer therapy. Redox Biology. 2019;25:101174. doi:10.1016/j.redox.2019.101174 3. Garcia GG, Schmidt CJ, Hajal C. The tumor microenvironment in therapy resistance. Front Lab Chip Technol. 2024;3. doi:10.3389/frlct.2024.1420233 4. Marzagalli M, Pelizzoni G, Fedi A, et al. A multi-organ-on-chip to recapitulate the infiltration and the cytotoxic activity of circulating NK cells in 3D matrix-based tumor model. Front Bioeng Biotechnol. 2022;10. doi:10.3389/fbioe.2022.945149 5. Marrella A, Varani G, Aiello M, et al. 3D fluid-dynamic ovarian cancer model resembling systemic drug administration for efficacy assay. ALTEX - Alternatives to animal experimentation. 2021;38(1):82-94. doi:10.14573/altex.2003131 6. Behr J, Carnell LR, Stein R, et al. In Vitro Setup for Determination of Nanoparticle- Mediated Magnetic Cell and Drug Accumulation in Tumor Spheroids under Flow Conditions. Cancers. 2022;14(23):5978. doi:10.3390/cancers14235978