Share Email Print
cover

Proceedings Paper • new

Predicting antibody penetration in a first-in-human clinical trial of head and neck cancers (Conference Presentation)
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Low response rates in solid tumors including head and neck cancers (HNCs) have been attributed to failure of the drug to reach its intended target. However, investigation of drug delivery has been limited due to difficulties in measuring concentrations in the tumor and the ability to localizing drugs in human tissues. Factors determining intratumoral antibody distribution in primary tumor and metastatic lymph nodes have not been well-studied in human patients. To address this challenge, we propose to leverage fluorescently labeled antibodies to investigate antibody delivery into HNCs. To this end, we have conducted a first-in-human clinical trial to assess the delivery of panitumumab-IRDye800 in HNCs. Twenty-two patients enrolled in this study received intravenous administration of panitumumab-IRDye800 at multiple subtherapeutic doses: (1) 0.06mg/kg, (2) 0.5 mg/kg, (3) 1 mg/kg, (4) 50 mg flat dose, (5) 25 mg flat dose. To quantify the antibody delivery, fresh tumor samples were procured and the amount of antibody in the tumor was quantified as ng/mg of tissue, which was then correlated with tumor characteristics. Immunohistochemistry of multiple protein markers, including EGFR, ERG, cytokeratin, Ki67, alpha-smooth muscle actin, etc., have been implemented in serial sections of primary tumors and metastatic lymph nodes. A quantitative image analysis pipeline was developed to analyze these IHC images and score the staining on both global and local scale. A predictive model was built to identify the most important predictors for antibody penetration from pharmacological factors, tumor pathophysiological factors, and tumor microenvironmental factors.

Paper Details

Date Published: 4 March 2019
PDF
Proc. SPIE 10859, Visualizing and Quantifying Drug Distribution in Tissue III, 1085905 (4 March 2019); doi: 10.1117/12.2513258
Show Author Affiliations
Guolan Lu, Stanford Univ. (United States)
Shayan Fakurnejad, Stanford Univ. (United States)
Brock Martin, Stanford Univ. (United States)
Ashley Zhu, Stanford Univ. (United States)
Nynke van den Berg, Stanford Univ. (United States)
Stan van Keulen, Stanford Univ. (United States)
Quan Zhou, Stanford Univ. (United States)
Tarn Teraphongphom, Stanford Univ. (United States)
Rebecca Gao, Stanford Univ. (United States)
Nicholas Oberhelman, Stanford Univ. (United States)
Stefania Chirita, Stanford Univ. (United States)
Robert Erstey, Stanford Univ. (United States)
Christina Kong, Stanford Univ. (United States)
Dimitrios Colevas, Stanford Univ. (United States)
Eben Rosenthal, Stanford Univ. (United States)


Published in SPIE Proceedings Vol. 10859:
Visualizing and Quantifying Drug Distribution in Tissue III
Kin Foong Chan; Conor L. Evans, Editor(s)

© SPIE. Terms of Use
Back to Top