VCAM-1 Density and Tumor Perfusion Predict T-cell Infiltration and Treatment Response in Preclinical Models

Autor: Johannes Riegler, Herman Gill, Annie Ogasawara, Maj Hedehus, Vincent Javinal, Jason Oeh, Gregory Z. Ferl, Jan Marik, Simon Williams, Deepak Sampath, Jill Schartner, Richard A.D. Carano
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Neoplasia: An International Journal for Oncology Research, Vol 21, Iss 10, Pp 1036-1050 (2019)
Druh dokumentu: article
ISSN: 1476-5586
DOI: 10.1016/j.neo.2019.08.003
Popis: Cancer immunotherapies have demonstrated durable responses in a range of different cancers. However, only a subset of patients responds to these therapies. We set out to test if non-invasive imaging of tumor perfusion and vascular inflammation may be able to explain differences in T-cell infiltration in pre-clinical tumor models, relevant for treatment outcomes. Tumor perfusion and vascular cell adhesion molecule (VCAM-1) density were quantified using magnetic resonance imaging (MRI) and correlated with infiltration of adoptively transferred and endogenous T-cells. MRI biomarkers were evaluated for their ability to detect tumor rejection 3 days after T-cell transfer. Baseline levels of these markers were used to assess their ability to predict PD-L1 treatment response. We found correlations between MRI-derived VCAM-1 density and infiltration of endogenous or adoptively transferred T-cells in some preclinical tumor models. Blocking T-cell binding to endothelial cell adhesion molecules (VCAM-1/ICAM) prevented T-cell mediated tumor rejection. Tumor rejection could be detected 3 days after adoptive T-cell transfer prior to tumor volume changes by monitoring the extracellular extravascular volume fraction. Imaging tumor perfusion and VCAM-1 density before treatment initiation was able to predict the response of MC38 tumors to PD-L1 blockade. These results indicate that MRI based assessment of tumor perfusion and VCAM-1 density can inform about the permissibility of the tumor vasculature for T-cell infiltration which may explain some of the observed variance in treatment response for cancer immunotherapies.
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