Modeling tumor-immune interactions using hybrid spheroids and microfluidic platforms for studying tumor-associated macrophage polarization in melanoma

Abstract

Tumor-associated macrophages (TAMs), as key components of tumor microenvironment (TME), exhibit phenotypic plasticity in response to environmental cues, causing polarization into either pro-inflammatory M1 phenotypes or immunosuppressive M2 phenotypes. Although TAM has been widely studied for its crucial involvement in the initiation, progression, metastasis, and immune regulation of cancer cells, there have been limited attempts to understand how the metastatic potentials of cancer cells influence TAM polarization within TME. Here, we developed a miniaturized TME model using a 3D hybrid system composed of murine melanoma cells and macrophages, aiming to investigate interactions between cancer cells exhibiting various metastatic potentials and macrophages within TME. The increase in spheroid size within this model was associated with a reduction in cancer cell viability. Examining macrophage surface marker expression and cytokine secretion indicated the development of diverse TMEs influenced by both spheroid size and the metastatic potential of cancer cells. Furthermore, a high-throughput microfluidic platform equipped with trapping systems and hybrid spheroids was employed to simulate the tumor-immune system of complex TMEs and for comparative analysis with traditional 3D culture models. This study provides insight into TAM polarization in melanoma with different heterogeneities by modeling cancer-immune systems, which can be potentially employed for immune-oncology research, drug screening, and personalized therapy.

Statement of significance

This study presents the development of a 3D hybrid spheroid system designed to model tumor-immune interactions, providing a detailed analysis of how melanoma cell metastatic potential influences tumor-associated macrophage (TAM) polarization. By utilizing a microfluidic platform, we are able to replicate and investigate the complex tumor-immune system of the tumor microenvironments (TMEs) under continuous flow conditions. Our model holds significant potential for high-throughput drug screening and personalized medicine applications, offering a versatile tool for advancing cancer research and treatment strategies.