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Immuno-PET molecular imaging of RANKL in cancer

Journal Contribution - e-publication

Purpose: The involvement of RANK/RANKL signaling in the tumor microenvironment (TME) in driving response or resistance to immunotherapy has only very recently been recognized. Current quantification methods of RANKL expression suffer from issues such as sensitivity, variability, and uncertainty on the spatial heterogeneity within the TME, resulting in conflicting reports on its reliability and limited use in clinical practice. Non-invasive molecular imaging using immuno-PET is a promising approach combining superior targeting specificity of monoclonal antibodies (mAb) and spatial, temporal and functional information of PET. Here, we evaluated radiolabeled anti-RANKL mAbs as a non-invasive biomarker of RANKL expression in the TME. Experimental design: Anti-human RANKL mAbs (AMG161 and AMG162) were radiolabeled with 89Zr using the bifunctional chelator DFO in high yield, purity and with intact binding affinity. After assessing the biodistribution in healthy CD-1 nude mice, [89Zr]Zr-DFO-AMG162 was selected for further evaluation in ME-180 (RANKL-transduced), UM-SCC-22B (RANKL-positive) and HCT-116 (RANKL-negative) human cancer xenografts to assess the feasibility of in vivo immuno-PET imaging of RANKL. Results: [89Zr]Zr-DFO-AMG162 was selected as the most promising tracer for further validation based on biodistribution experiments. We demonstrated specific accumulation of [89Zr]Zr-DFO-AMG162 in RANKL transduced ME-180 xenografts. In UM-SCC-22B xenograft models expressing physiological RANKL levels, [89Zr]Zr-DFO-AMG162 imaging detected significantly higher signal compared to control [89Zr]Zr-DFO-IgG2 and to RANKL negative HCT-116 xenografts. There was good visual agreement with tumor autoradiography and immunohistochemistry on adjacent slides, confirming these findings. Conclusions: [89Zr]Zr-DFO-AMG162 can detect heterogeneous RANKL expression in the TME of human cancer xenografts, supporting further translation of RANKL immuno-PET to evaluate tumor RANKL distribution in patients.
Journal: Cancers
ISSN: 2072-6694
Volume: 13
Publication year:2021
Keywords:A1 Journal article
BOF-keylabel:yes
BOF-publication weight:2
CSS-citation score:1
Authors from:Higher Education
Accessibility:Open