A Three-Dimensional Bioprinted Skin Melanoma Model for High-Throughput Drug Screening

Abstract

Melanoma is the deadliest form of skin cancer, and despite major advances in immunotherapy and targeted therapies, most patients with advanced disease eventually develop treatment resistance. The lack of physiologically relevant, scalable preclinical models that recapitulate the tumor microenvironment (TME) remains a major barrier to identifying more effective therapies. Here, we present a novel high-throughput screening platform based on a bioprinted, full-thickness human melanoma skin model that combines the biological complexity of native skin with the scalability required for drug discovery. The 3D tissue construct comprises a dermal region containing primary human dermal fibroblasts, melanoma tumor-like cell clusters localized at the dermal-epidermal interface, and an overlying differentiated epidermis composed of primary human keratinocytes cultured at the air-liquid interface, thereby recapitulating key structural and cellular features of the melanoma TME. To enable multiplexed, high-content analysis, melanoma cells and fibroblasts were engineered to express red and green fluorescent proteins, respectively, allowing automated confocal imaging to simultaneously quantify tumor growth and stromal viability. This dual-readout strategy provides an intrinsic counterscreen to distinguish melanoma-selective compounds from nonspecific cytotoxic agents. The assay was implemented in a 96-well bioprinted format compatible with high-throughput screening of compound libraries across multiple concentrations. Using this platform, we identified compounds that selectively reduced melanoma cell viability while sparing surrounding stromal cells, demonstrating the value of incorporating the TME into primary drug screens. By integrating bioprinting, human tissue engineering, and automated high-content imaging into a scalable workflow, this platform provides a robust and clinically relevant approach for melanoma therapeutic discovery and has the potential to improve the translation of preclinical findings into effective treatments for advanced melanoma.