RT Journal Article
SR Electronic
T1 The Advantage of Antibody Cocktails for Targeted Alpha Therapy Depends on Specific Activity
JF Journal of Nuclear Medicine
JO J Nucl Med
FD Society of Nuclear Medicine
SP 2012
OP 2019
DO 10.2967/jnumed.114.141580
VO 55
IS 12
A1 Pasternack, Jordan B.
A1 Domogauer, Jason D.
A1 Khullar, Alisha
A1 Akudugu, John M.
A1 Howell, Roger W.
YR 2014
UL http://jnm.snmjournals.org/content/55/12/2012.abstract
AB Nonuniform dose distributions among disseminated tumor cells can be a significant limiting factor in targeted α therapy. This study examines how cocktails of radiolabeled antibodies can be formulated to overcome this limitation. Methods: Cultured MDA-MB-231 human breast cancer cells were treated with different concentrations of a cocktail of 4 fluorochrome-conjugated monoclonal antibodies. The amount of each antibody bound to each cell was quantified using flow cytometry. A spreadsheet was developed to “arm” the antibodies with any desired radionuclide and specific activity, calculate the absorbed dose to each cell, and perform a Monte Carlo simulation of the surviving fraction of cells after exposure to cocktails of different antibody combinations. Simulations were performed for the α-particle emitters 211At, 213Bi, and 225Ac. Results: Activity delivered to the least labeled cell can be increased by 200%–400% with antibody cocktails, relative to the best-performing single antibody. Specific activity determined whether a cocktail or a single antibody achieved greater cell killing. With certain specific activities, cocktails outperformed single antibodies by a factor of up to 244. There was a profound difference (≤16 logs) in the surviving fraction when a uniform antibody distribution was assumed and compared with the experimentally observed nonuniform distribution. Conclusion: These findings suggest that targeted α therapy can be improved with customized radiolabeled antibody cocktails. Depending on the antibody combination and specific activity of the radiolabeled antibodies, cocktails can provide a substantial advantage in tumor cell killing. The methodology used in this analysis provides a foundation for pretreatment prediction of tumor cell survival in the context of personalized cancer therapy.