Abstract

PURPOSE: The efficacy of antibody-based therapeutics depends on successful drug delivery into solid tumors, therefore there is a clinical need to measure intratumoral antibody distribution. This study aims to develop and validate an imaging and computation platform to directly quantify and predict antibody delivery into human head and neck cancers in a clinical study.EXPERIMENTAL DESIGN: Twenty-four patients received systemic infusion of a near-infrared (NIR) fluorescence-labeled therapeutic antibody followed by surgical tumor resection. A computational platform was developed to quantify the extent of heterogeneity of intratumoral antibody distribution. Both univariate and multivariate regression analysis were used to select the most predictive tumor biological factors for antibody delivery. Quantitative image features from the pre-treatment magnetic resonance imaging (MRI) were extracted and correlated with fluorescence imaging of antibody delivery.RESULTS: This study not only confirmed heterogeneous intratumoral antibody distribution in line with many preclinical reports, but also quantified the extent of inter-patient, inter-tumor, and intra-tumor heterogeneity of antibody delivery. This study demonstrated the strong predictive value of tumor size for intratumoral antibody accumulation and its significant impact on antibody distribution in both primary tumor and lymph node metastasis. Furthermore, this study established the feasibility of using contrast-enhanced MRI to predict antibody delivery.CONCLUSIONS: This study provides a clinically translatable platform to measure antibody delivery into solid tumors and yields valuable insight into clinically relevant antibody tumor penetration, with implications in the selection of patients amenable to antibody therapy and the design of more effective dosing strategies.

View details for DOI 10.1158/1078-0432.CCR-19-3717

View details for PubMedID 31980465