3D modeling of normal skin and cutaneous squamous cell carcinoma. A comparative study in 2D cultures, spheroids, and 3D bioprinted systems.

Abstract

The current cancer research and drug testing are primarily based on 2D cell cultures and animal models. However, these methods have limitations and yield distinct drug response patterns. This study addressed this gap by developing an innovativein vitrohuman three-dimensional (3D) normal skin model and a multicellular model of human cutaneous squamous cell carcinoma (cSCC) using 3D bioprinting technology. Comparative analyzes were performed between bioprinted 3D-cSCC model, consisting of HaCaT keratinocytes, primary normal human dermal fibroblasts and A431 cancer cells (tricellular), bioprinted 3D-A431 model composed of A431 cancer cells only (monocellular), A431 cancer cell spheroids, and conventional 2D models. The models were structurally characterized by light microscopy, immunofluorescence (LIVE/DEAD assay, confocal microscopy) and immunohistochemistry (hematoxylin/eosin, p63, vimentin, Ki67, epidermal growth factor receptor stainings). The spatial arrangement of the 3D models was analyzed using the ARIVIS scientific image analysis platform. All models were also functionally assessed by cetuximab (CTX) response testing with the MTS assay. 3D-cSCC models were maintained for up to 16 weeks. Morphological and histological examinations confirmed the presence of skin-like layers in the bioprinted 3D models of normal skin, and the intricate and diverse features of the bioprinted skin cancer model, replicating the criticalin vivocharacteristics. In both mono- and tricellular bioprinted tumor constructs, there was a gradual formation and continuous growth of spheroid-like clusters of cancer cells, significantly influencing the morphology of the models. Cancer cells in the 3D bioprinted constructs showed reduced sensitivity to CTX compared to spheroids and 2D cultures. This study underscores the potential of 3D multicellular models in elucidating drug responses and gaining a better understanding the intricate interplay of cellular components within the tumor microenvironment. Developing the multicellular 3D tumor model paves the way for new research critical to advancing fundamental cancer research and future clinical applications, particularly drug response testing.