A model-based approach for the optimization of radioimmunotherapy through antibody design and radionuclide selection.
BACKGROUND
The effectiveness of radioimmunotherapy (RIT) is known to depend on at least six factors: total absorbed dose and pattern of delivery, radiosensitivity, rate of repair of sublethal damage, ongoing proliferation during treatment, tumor heterogeneity, and tumor size. The purpose of this study was to develop a mathematic model that would relate the absorbed dose and its pattern of delivery to tumor response by incorporating information on each factor. This model was used to optimize therapeutic efficacy in mice by matching the antibody and radionuclide characteristics while ensuring recoverable marrow toxicity.


METHODS
Pharmacokinetic data were acquired in mice for a range of antibodies that varied in molecular weight, specificity, affinity, and avidity, and for a range of tumor sizes. This information was combined with the properties of iodine-131, rhenium-86, and yttrium-90 to determine the pattern of dose delivery. Tumor response was characterized in terms of radiosensitivity, rate of repair, and proliferation. Values for these parameters were obtained from in vitro assays and were incorporated into a response model based on the linear-quadratic model. Storage phosphor plate technology was used to acquire images of antibody distribution in tumor sections. These were registered with corresponding images showing tumor morphology, which were subsequently used to delineate regions that were distinct in terms of their response to radiation: oxygenated, radiosensitive areas that contained viable cells and hypoxic areas containing resistant viable cells and necrotic cells. Beta point dose kernels were then used to estimate the absorbed dose distribution in these regions.


RESULTS
Therapy in normoxic areas was more effective than in hypoxic areas. The multivalent, tumor-specific antibodies, with intermediate clearance rates, delivered the highest absorbed dose to viable tumor cells. Antibody affinity and avidity facilitated the prolonged retention in radiosensitive areas of tumor, where most of the dose was deposited. The effectiveness of therapy could be enhanced further by matching the radionuclide with the antibody and tumor size.


CONCLUSIONS
The model presented in this article allows the interaction between important radiobiologic parameters to be assessed and provides a tool for optimizing therapy in animal models and in patients.
Flynn
Aiden A
AA
CRC Targeting and Imaging Group, Department of Oncology, Royal Free and University College Medical School, University College London, London, United Kingdom. AQF30355@GSK.com
Green
Alan J
AJ
Pedley
R Barbara
RB
Boxer
Geoffrey M
GM
Dearling
Jason
J
Watson
Rebecca
R
Boden
Robert
R
Begent
Richard H J
RH
D000818:Animals; D000912:Antibodies, Neoplasm / Q000737:chemistry / Q000276:immunology*; D004195:Disease Models, Animal; D006801:Humans; D051379:Mice; D008954:Models, Biological; D009368:Neoplasm Transplantation; D009374:Neoplasms, Experimental / Q000378:metabolism / Q000532:radiotherapy*; D011829:Radiation Dosage; D011836:Radiation Tolerance; D011868:Radioisotopes / Q000737:chemistry / Q000493:pharmacokinetics / Q000627:therapeutic use*; D014407:Tumor Cells, Cultured
D000912:Antibodies, Neoplasm; D011868:Radioisotopes