Dr. Rinat Meir
Faculty of Engineering & The Institute of Nanotechnology and Advanced Materials, Bar-Ilan University
Cancer immunotherapy has made enormous progress in offering safer and more effective treatments for the disease. Specifically, PDL1 antibody, designed to perform immune check-point blockade (ICB), is now considered a pillar in cancer immunotherapy.
However, due to the complexity and heterogeneity of tumors, as well as the diversity in patient response, ICB therapy only has a 30% success rate, at most; moreover, the efficacy of ICB can be evaluated only two months after start of treatment. Therefore, early identification of potential responders and nonresponders to therapy, using noninvasive means, is crucial for improving treatment decisions. We report a straightforward approach for fast, image-guided prediction of therapeutic response to ICB. In a colon cancer mouse model, we demonstrate that the combination of computed tomography imaging and gold nanoparticles conjugated to αPDL1 allowed prediction of therapeutic response, as early as 48 h after treatment. This was achieved by noninvasive measurement of nanoparticle accumulation levels within the tumors. Moreover, we show that the nanoparticles efficiently prevented tumor growth with only a fifth of the standard dosage of clinical care. This technology may be developed into a powerful tool for early and noninvasive patient stratification as responders or non-responders.