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Updated: Sep 15, 2025
Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
Published on: March 25, 2020
Advancements in non-invasive visualization of the immune checkpoint TIGIT: a systematic review
Susanne Lütje1,2, Laura Schäfer3, Betül Altunay3
1Department of Nuclear Medicine, RWTH Aachen University Hospital, Pauwelsstraße 30, Aachen, 52074, Germany. sluetje@ukaachen.de.
Purpose:
T cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) is a novel immune checkpoint receptor implicated in tumor immune evasion. Non-invasive imaging of TIGIT expression holds potential for improving patient selection and monitoring in cancer immunotherapy. This systematic review aims to evaluate recent advancements in radiotracer development for non-invasive visualization of TIGIT.
Methods:
A comprehensive literature search was conducted up to February 2025 using databases including PubMed and Web of Science. The search terms "TIGIT imaging", "TIGIT PET", "TIGIT SPECT", and "TIGIT visualization" were used, focusing on those reporting on the development, characterization, or application of immuno-PET tracers targeting TIGIT expression. Both preclinical and clinical studies were reviewed.
Results:
Six studies met the inclusion criteria, exploring tracers targeting TIGIT expression on immune cells. These studies have focused on the development of TIGIT-targeted imaging agents, including radiolabeled antibodies, peptides, and nanobodies for positron emission tomography (PET) and single-photon emission tomography (SPECT) imaging. These agents demonstrated high specificity and enabled visualization of TIGIT expression in preclinical models and one exploratory clinical study.
Conclusion:
Novel radiotracers for non-invasive imaging of TIGIT show potential for enhancing personalized cancer immunotherapy. TIGIT-targeted imaging agents allow for the visualization and quantification of TIGIT expression in tumors/tumor microenvironment, which in future might contribute to better patient selection and treatment monitoring. Further research and clinical validation are necessary to optimize these imaging techniques for routine clinical application.
