Please use this identifier to cite or link to this item: http://ahro.austin.org.au/austinjspui/handle/1/18591
Title: PET-based compartmental modeling of (124)I-A33 antibody: quantitative characterization of patient-specific tumor targeting in colorectal cancer.
Authors: Zanzonico, Pat;Carrasquillo, Jorge A;Pandit-Taskar, Neeta;O'Donoghue, Joseph A;Humm, John L;Smith-Jones, Peter;Ruan, Shutian;Divgi, Chaitanya;Scott, Andrew M;Kemeny, Nancy E;Fong, Yuman;Wong, Douglas;Scheinberg, David;Ritter, Gerd;Jungbluth, Achem;Old, Lloyd J;Larson, Steven M
Affiliation: Ludwig Institute for Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10021, USA
Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
Department of Surgery, City of Hope, Duarte, CA, USA
Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
Columbia University Medical Center, New York, NY, USA
Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
Departments of Psychiatry and Radiology, Stony Brook School of Medicine, Stony Brook, NY, USA
Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia
La Trobe University, Melbourne, Australia
Issue Date: Oct-2015
EDate: 2015-07-21
Citation: European journal of nuclear medicine and molecular imaging 2015; 42(11): 1700-1706
Abstract: The molecular specificity of monoclonal antibodies (mAbs) directed against tumor antigens has proven effective for targeted therapy of human cancers, as shown by a growing list of successful antibody-based drug products. We describe a novel, nonlinear compartmental model using PET-derived data to determine the "best-fit" parameters and model-derived quantities for optimizing biodistribution of intravenously injected (124)I-labeled antitumor antibodies. As an example of this paradigm, quantitative image and kinetic analyses of anti-A33 humanized mAb (also known as "A33") were performed in 11 colorectal cancer patients. Serial whole-body PET scans of (124)I-labeled A33 and blood samples were acquired and the resulting tissue time-activity data for each patient were fit to a nonlinear compartmental model using the SAAM II computer code. Excellent agreement was observed between fitted and measured parameters of tumor uptake, "off-target" uptake in bowel mucosa, blood clearance, tumor antigen levels, and percent antigen occupancy. This approach should be generally applicable to antibody-antigen systems in human tumors for which the masses of antigen-expressing tumor and of normal tissues can be estimated and for which antibody kinetics can be measured with PET. Ultimately, based on each patient's resulting "best-fit" nonlinear model, a patient-specific optimum mAb dose (in micromoles, for example) may be derived.
URI: http://ahro.austin.org.au/austinjspui/handle/1/18591
DOI: 10.1007/s00259-015-3061-2
ORCID: 0000-0002-6656-295X
PubMed URL: 26194713
Type: Journal Article
Research Support, N.I.H., Extramural
Appears in Collections:Journal articles

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