Multiplexed multiscale imaging for cellular immunotherapies

Cellular immunotherapies are treatments in which a patient’s own immune cells are reprogramed to recognize and destroy tumor cells. These approaches utilize ex vivo engineering and expansion via synthetic receptors to target immune specificity toward tumor antigens, followed by reinfusion into the patient. This approach has been demonstrated as a potentially curative treatment for certain classes of hematopoietic malignancies and is being further developed to target other diseases including solid tumors. In these treatments, synthetic receptors drive the formation of an immune synapse, a specialized structure through which the immune cell secretes cytotoxic granules to destroy the tumor. Thus, developing and evaluating effective treatments depends on understanding how synthetic receptors organize within and regulate synapse formation. However, current flow cytometry-based and in vitro cytotoxicity assays, which are essential components of cellular immunotherapy research and development, do not provide a detailed view of synapse formation or structure. Although this can be accomplished by high-resolution microscopy, current implementations are limited in spatial resolution, in the number of molecules they can detect simultaneously, and in the throughput at which they can acquire data. To overcome these limitations, we will develop new fluorescent probes to simultaneously visualize many proteins at once in immune cells, tumor cells, and at the immune synapse with resolutions ranging from one micron to tens of nanometers (Aim 1). In parallel, we will utilize computer vision and machine learning to develop “self- driving” microscopes that can automatically capture population-level statistics about immune and tumor cells together with high-resolution information about the structure and organization of immune synapses (Aim 2). Together, we believe that these technologies will allow researchers to profile the expression levels, subcellular distributions, and nanoscale organization of dozens of cellular proteins in single cells and at immune synapses. Automation through computer vision will dramatically increase data throughput compared to a human operator, leading to more significant sample sizes and greater reliability. Overall, we envision that these new capabilities will improve our ability to understand, intelligently design, and functionally evaluate a wide range of cell-based cancer therapies. Project Number: 1R61CA309698-01 | Fiscal Year: 2026 | NIH Institute/Center: National Cancer Institute (NCI) | Principal Investigator: Wesley Legant | Institution: UNIV OF NORTH CAROLINA CHAPEL HILL, CHAPEL HILL, NC | Award Amount: $207,802 | Activity Code: R61 | Study Section: Special Emphasis Panel[ZRG1 BTC-N (55)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11311397