Chuanyu Wang1,Chung-Hui Huang1,Pengyu Chen1
Auburn university1
Chuanyu Wang1,Chung-Hui Huang1,Pengyu Chen1
Auburn university1
Cellular communication is an essential process to maintain cellular bio-function. Communication between cancer cells and immune cells has been investigated for decades. One of immune checkpoint cancer therapies is developed after fully understanding the communication between programmed death ligand 1 (PD-L1) from cancer cells and programmed death 1 (PD-1) on T cells. Cancer cells can remotely deactivate T cells by secreting soluble PD-L1 proteins and secreting extracellular vesicles (EVs) with exosomal PD-L1. Commercial immunoassays, such as enzyme-linked immunosorbent assay (ELISA), have been utilized to measure concentrations of PD-L1, IL-2, and IFN-γ for the demonstration of cellular interaction between cancer cells and T cells. However, commercial immunoassays cannot detect a diffusion path of proteins. A diffusion map of proteins is also significant information to understand how cells secrete proteins. Here, a specially designed on-chip device consists of cell isolation chambers and a gold nanosphere-based nanoplasmonic digital immunoassay, rendering <i>in situ </i>remote cell communication to visualize a diffusion map and quantify a concentration of proteins. A machine-learning-based image process method was utilized to generate a signal map translating a PD-L1- exosome-mediated communication between breast cancer cells and T cells. This developed platform provides new methods for visualizing cell-cell remote communication that has high potential as a characterization method for monitoring cellular progression.