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Details

Autor(en) / Beteiligte
Titel
Predicting Response to Radioimmunotherapy from the Tumor Microenvironment of Colorectal Carcinomas
Ist Teil von
  • Cancer research (Chicago, Ill.), 2007-12, Vol.67 (24), p.11896-11905
Ort / Verlag
Philadelphia, PA: American Association for Cancer Research
Erscheinungsjahr
2007
Quelle
MEDLINE
Beschreibungen/Notizen
  • Solid tumors have a heterogeneous pathophysiology, which directly affects antibody-targeted therapies. Here, we consider the influence of selected tumor parameters on radioimmunotherapy, by comparing the gross biodistribution, microdistribution, and therapeutic efficacy of either radiolabeled or fluorescently labeled antibodies (A5B7 anti-carcinoembryonic antigen antibody and a nonspecific control) after i.v. injection in two contrasting human colorectal xenografts in MF1 nude mice. The LS174T is moderately/poorly differentiated, whereas SW1222 has a well-differentiated glandular structure. Biodistribution studies (1.8 MBq (131)I-labeled A5B7, four mice per group) showed similar gross tumor uptake at 48 h in the two models (25.1% and 24.0% injected dose per gram, respectively). However, in therapy studies (six mice per group), LS174T required a 3-fold increase in dose (18 versus 6 MBq) to equal SW1222 growth inhibition ( approximately 55 versus approximately 60 days, respectively). To investigate the basis of this discrepancy, high-resolution multifluorescence microscopy was used to study antibody localization in relation to tumor parameters (5 min, 1 and 24 h, four mice per time point). Three-dimensional microvascular corrosion casting and transmission electron microscopy showed further structural differences between xenografts. Vascular supply, overall antigen distribution, and tumor structure varied greatly between models, and were principally responsible for major differences in antibody localization and subsequent therapeutic efficacy. The study shows that multiparameter, high-resolution imaging of both therapeutic and tumor microenvironment is required to comprehend complex antibody-tumor interactions, and to determine which tumor regions are being successfully treated. This will inform the design of optimized clinical trials of single and combined agents, and aid individual patient selection for antibody-targeted therapies.

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