Integrating highly multiplexed immunofluorescence with label-free 2D hyperspectral chemical imaging to interrogate the colorectal cancer tumor-invasive front

Project Summary/Abstract Colorectal cancer (CRC) is the second most common cause of cancer-related death in the United States. Despite advances in both diagnostic and therapy, a large inter-individual variability in therapy response and diagnostic accuracy can be observed. The optimization of medical imaging agents in CRC is a critical component for

improving our technical capabilities relating to early diagnostics, complete labeling of tumor-positive tissue for surgical resection, surveillance, and precision therapy. One major requirement for improving the clinical performance of therapeutics and medical imaging agents is the characterization of structural and functional

chemistries in cancerous tissue that are either different from or absent in normal tissue. This is especially important in regions that may not be sufficiently labeled by existing imaging agents with a clinically acceptable and implementable signal-to-background ratio. In these cases, curative surgical intervention achieves mixed

success in the CRC patient population due to the technical inability to label accurately and precisely tumor- positive tissues. Moreover, these differences may potentially explain the clinically observed variation in patient therapy response and disease aggressiveness. To develop a computational workflow that integrates CODEX imaging with high-dimensional hyperspectral

chemical mapping and test my hypothesis, my experimental structure is divided into two main components. (1) I will perform preliminary non-destructive, label-free spatiochemical imaging on normal and CRC patient biopsies to identify differences in the functional heterogenous chemistries. (2) I will perform spatial omic identification of

CRC related tissue architectures using CODEX for integration with the high-dimensional label-free 2D infrared spectral maps. The innovation of this research is the development of the computational workflow and framework that integrates highly multiplexed CODEX with high-dimensional label-free 2D hyperspectral chemical imaging. This approach

can lead an alternative representation of physicochemical tissue properties for the characterization and identification of spatiochemistries relevant to CRC and its tumor-invasive front. Long-term, this can be used in the future to guide the development and optimization of cancer imaging agents to improve patient overall

outcomes.