UNLABELLED: Targeted α-therapy (TAT) appears to be an ideal therapeutic technique for eliminating malignant circulating, minimal residual, or micrometastatic cells. These types of malignancies are typically infraclinical, complicating the evaluation of potential treatments. This study presents a method of ex vivo activity quantification with an α-camera device, allowing measurement of the activity taken up by tumor cells in biologic structures a few tens of microns. METHODS: We examined micrometastases from a murine model of ovarian carcinoma after injection of a radioimmunoconjugate labeled with (211)At for TAT. At different time points, biologic samples were excised and cryosectioned. The activity level and the number of tumor cells were determined by combined information from 2 adjacent sections: one exposed to the α-camera and the other stained with hematoxylin and eosin. The time-activity curves for tumor cell clusters, comprising fewer than 10 cells, were derived for 2 different injected activities (6 and 1 MBq). RESULTS: High uptake and good retention of the radioimmunoconjugate were observed at the surface of tumor cells. Dosimetric calculations based on the measured time-integrated activity indicated that for an injected activity of 1 MBq, isolated tumor cells received at least 12 Gy. In larger micrometastases (≤ 100 μm in diameter), the activity uptake per cell was lower, possibly because of hindered penetration of radiolabeled antibodies; however, the mean absorbed dose delivered to tumor cells was above 30 Gy, due to cross-fire irradiation. CONCLUSION: Using the α-camera, we developed a method of ex vivo activity quantification at the cellular scale, which was further applied to characterize the behavior of a radiolabeled antibody administered in vivo against ovarian carcinoma. This study demonstrated a reliable measurement of activity. This method of activity quantification, based on experimentally measured data, is expected to improve the relevance of small-scale dosimetry studies and thus to accelerate the optimization of TAT.
UNLABELLED: Targeted α-therapy (TAT) appears to be an ideal therapeutic technique for eliminating malignant circulating, minimal residual, or micrometastatic cells. These types of malignancies are typically infraclinical, complicating the evaluation of potential treatments. This study presents a method of ex vivo activity quantification with an α-camera device, allowing measurement of the activity taken up by tumor cells in biologic structures a few tens of microns. METHODS: We examined micrometastases from a murine model of ovarian carcinoma after injection of a radioimmunoconjugate labeled with (211)At for TAT. At different time points, biologic samples were excised and cryosectioned. The activity level and the number of tumor cells were determined by combined information from 2 adjacent sections: one exposed to the α-camera and the other stained with hematoxylin and eosin. The time-activity curves for tumor cell clusters, comprising fewer than 10 cells, were derived for 2 different injected activities (6 and 1 MBq). RESULTS: High uptake and good retention of the radioimmunoconjugate were observed at the surface of tumor cells. Dosimetric calculations based on the measured time-integrated activity indicated that for an injected activity of 1 MBq, isolated tumor cells received at least 12 Gy. In larger micrometastases (≤ 100 μm in diameter), the activity uptake per cell was lower, possibly because of hindered penetration of radiolabeled antibodies; however, the mean absorbed dose delivered to tumor cells was above 30 Gy, due to cross-fire irradiation. CONCLUSION: Using the α-camera, we developed a method of ex vivo activity quantification at the cellular scale, which was further applied to characterize the behavior of a radiolabeled antibody administered in vivo against ovarian carcinoma. This study demonstrated a reliable measurement of activity. This method of activity quantification, based on experimentally measured data, is expected to improve the relevance of small-scale dosimetry studies and thus to accelerate the optimization of TAT.
Authors: Damian J Green; Mazyar Shadman; Jon C Jones; Shani L Frayo; Aimee L Kenoyer; Mark D Hylarides; Donald K Hamlin; D Scott Wilbur; Ethan R Balkan; Yukang Lin; Brian W Miller; Sofia H L Frost; Ajay K Gopal; Johnnie J Orozco; Theodore A Gooley; Kelly L Laird; Brian G Till; Tom Bäck; Brenda M Sandmaier; John M Pagel; Oliver W Press Journal: Blood Date: 2015-01-27 Impact factor: 22.113
Authors: Calvin N Leung; Brian S Canter; Didier Rajon; Tom A Bäck; J Christopher Fritton; Edouard I Azzam; Roger W Howell Journal: J Nucl Med Date: 2019-09-13 Impact factor: 10.057
Authors: Sofia H L Frost; Brian W Miller; Tom A Bäck; Erlinda B Santos; Donald K Hamlin; Sue E Knoblaugh; Shani L Frayo; Aimee L Kenoyer; Rainer Storb; Oliver W Press; D Scott Wilbur; John M Pagel; Brenda M Sandmaier Journal: J Nucl Med Date: 2015-09-03 Impact factor: 10.057
Authors: Ruqaya A L Darwish; Alexander Hugo Staudacher; Eva Bezak; Michael Paul Brown Journal: Comput Math Methods Med Date: 2015-01-22 Impact factor: 2.238
Authors: Stephanie Lamart; Brian W Miller; Anne Van der Meeren; Anissa Tazrart; Jaime F Angulo; Nina M Griffiths Journal: PLoS One Date: 2017-10-12 Impact factor: 3.240