Modeling melanoma in reconstructed human skin

With increasing pressure from the European Union to replace, reduce, and refine animal experiments, there is a critical need for models that reliably mimic human diseases in a physiological setting. While three-dimensional (3D) in vitro models of melanoma help researchers understand disease progression and test therapies, they have not fully captured the complexity of in vivo tumors. This thesis aims to create a melanoma-reconstructed human skin (Mel-RhS) model that emulates key aspects of melanoma progression. Chapter 2 explores the current progress in developing 3D melanoma models, both in vitro and in vivo. It examines their applications, limitations, and the necessary advances for seamless translation from bench to bedside. Chapter 3 outlines the initial efforts to establish a Mel-RhS to mimic melanoma cell behavior and immune modulation in vitro. Given the complexity of melanoma, it is crucial to study the varied stages of disease progression, from melanoma in situ to metastatic melanoma, in their representative models. Chapter 4 expands the previously developed Mel-RhS by modeling different stages of tumor progression using various melanoma cell lines. While tumor features could be replicated to a certain extent, the in vivo tumor microenvironment is much more complex, involving dynamic interactions between tumor cells and various cell types, e.g. immune cells. Efforts have been made to include dendritic cells in Mel-RhS. However, integrating an immune component into Mel-RhS remains challenging and more research is needed to assess the survival of different immune cell types in the 3D microenvironment and their ability to orchestrate anti-tumor responses. Among immune subsets, γδ-T cells are of particular interest due to their rapid recognition of ligands independent of human leukocyte antigen (HLA) molecules and their robust killing activity in different tumors. Various γδ-T cell-based therapeutic strategies are currently under evaluation in clinical trials. Therefore, chapter 5 explores the potential of Mel-RhS as a preclinical tool for testing Vγ9Vδ2-T cell-based melanoma therapies, with Vγ9Vδ2-T cells being the major subset of γδ-T cells in peripheral blood. Despite the benefits of including diverse immune cell types in the tumor milieu, a major limitation of Mel-RhS is its inability to replicate the metastatic cascade (i.e. Mel-RhS are typically cultured under static conditions), wherein melanoma cells disseminate to other skin locations or distant tissues via the lymphatic system or the bloodstream. To address this, organ-on-chip (OoC) platforms have been developed to provide the physical and mechanical cues occurring in the skin vasculature. However, before modeling melanoma and its metastatic cascade, chapter 6 first aims to first establish a skin-on-chip (SoC) model to initially validate the use of a microfluidic system in a proof-of-concept toxicology study. This model incorporates an endothelial layer to mimic blood vasculature and a myeloid cell component to emulate immune cell responses to external stimuli. Investigating the microenvironment in in vitro models over an extended period has traditionally faced limitations due to the need for disruptive harvesting of tissue cultures for analysis. To overcome this, non-invasive real-time detection and monitoring techniques have been implemented. One such technique, line-field confocal optical coherence tomography (LC-OCT), allows for the non-invasive generation of real-time section images at a cellular level of in vivo skin and holds significant promise for early diagnosis and therapeutic monitoring of skin conditions and diseases, including melanoma. New technologies have also emerged for continuous non-destructive extraction of interstitial fluid and in situ biomarker mapping. Chapter 7 focuses on applying these technologies for local imaging and in situ sampling of the microenvironment of living RhS and Mel-RhS, further advancing real-time examination of processes in healthy and diseased in vitro skin models. Chapter 8 discusses the key findings of each chapter.