Direct imaging and automatic analysis in tumor-on-chip reveal cooperative antitumoral activity of immune cells and oncolytic vaccinia virus

Abstract

Organ-on-chip and tumor-on-chip microfluidic cell cultures represent a fast-growing research field for modelling organ functions and diseases, for drug development, and for promising applications in personalized medicine. Still, one of the bottlenecks of this technology is the analysis of the huge amount of bio-images acquired in these dynamic 3D microenvironments, a task that we propose to achieve by exploiting the interdisciplinary contributions of computer science and electronic engineering. In this work, we apply this strategy to the study of oncolytic vaccinia virus (OVV), an emerging agent in cancer immunotherapy. Infection and killing of cancer cells by OVV were recapitulated and directly imaged in tumor-on-chip. By developing and applying appropriate image analysis strategies and advanced automatic algorithms, we uncovered synergistic cooperation of OVV and immune cells to kill cancer cells. Moreover, we observed that the kinetics of immune cells were modified in presence of OVV and that these immune modulations varied during the course of infection. A correlation between cancer cell infection and cancer-immune interaction time was pointed out, strongly supporting a cause-effect relationship between infection of cancer cells and their recognition by the immune cells. These results shed new light on the mode of action of OVV, and suggest new clinical avenues for immunotherapy developments.

Keywords: Cancer immunotherapy; Live imaging; Machine learning; Oncolytic vaccinia virus; Tumor-on-chip.