3D Scleroderma Tissue Model Reveals Importance of Growth Factor Cross-Talk

Objectives: Systemic sclerosis (SSc) is a rare autoimmune disease characterized by skin, oral cavity and internal organ fibrosis. SSc has the highest mortality rate of all autoimmune diseases and currently, no specific FDA-approved drugs exist for its treatment. Study of SSc in two-dimensional (2D) monolayer cultures has been limited because 2D cultures do not fully represent 3D skin tissue architecture and function. To address this shortcoming, we have created an in vivo-like 3D tissue model of human skin incorporating multiple SSc patient-derived cell types, including fibroblasts, keratinocytes, and monocytes. This 3D tissue more adequately captures the microenvironment, tissue architecture, and cellular crosstalk seen in SSc patients. Here we examine how levels of known SSc biomarkers correlate to heterogeneous clinical phenotypes using these 3D tissues. This work will help demonstrate how these tissues can be used as a platform for screening new drugs to treat SSc.
Methods: 3D skin-like tissues were constructed using fibroblasts, keratinocytes, blood-derived monocytes, and plasma derived from SSc patients. We used Luminex and ELISA assays to measure levels of clinically-relevant soluble factors as SSc biomarkers in tissues and compared them to levels in tissues constructed from control patients.
Results: We detected differential levels of G-CSF, CCL22, IL-6, Il-7, and VEGF (p≤0.001), CCL3/MIP-1a and CCL4/MIP-1b (p≤0.01), and GM-CSF (p≤0.05) when tissues created from SSc-derived cells were compared to control tissues (N=6). ELISA assays will be performed to establish the presence of additional biomarkers important in scleroderma pathogenesis and their relevance to clinical phenotype of patients.
Conclusions: The differential expression of soluble biomarkers supports the development of 3D tissues that mimic SSc. Our 3D tissue model provides greater cellular complexity that better replicates cross-talk between fibroblasts and macrophages seen in SSc in vivo. This new SSc model offers new and more predictive ways to test drug responses to potential treatments.