Vol. 297, Issue 3, 1144-1151, June 2001

A High-Capacity Quantitative Mouse Model of Drug-Mediated Immunosuppression Based on Rejection of an Allogeneic Subcutaneous Tumor

Denise Hammond-McKibben¹, Philip Lake, Jin Zhang, Nicole Tart-Risher, Ronald Hugo and Marla Weetall

Transplantation Research, Novartis Pharmaceuticals, Summit, New Jersey

We describe a high-capacity in vivo assay to measure drug-mediated transplant immunosuppression using a mouse model of Sa1 tumor rejection. Sa1 grew poorly and was rejected by 14 days in immunocompetent allogeneic recipient mice. In nude (nu/nu) mice, Sa1 grew more rapidly and was not rejected, confirming the T cell dependence of this response. In immunocompetent animals, administration of immunosuppressive agents resulted in increased tumor growth relative to vehicle-treated animals. Treatment with immunosuppressive drugs such as cyclosporin A (CsA), 40-O-(2-hydroxyethyl)-rapamycin (SDZ RAD), or 2-amino-2-[2-(4-octylphenyl)ethyl]-1,2-propanediol hydrochloride (FTY720) produced dose-dependent inhibition of tumor rejection. By contrast, the drugs did not affect Sa1 tumor growth in nu/nu mice, which is consistent with their predicted indirect effect on tumor size by suppressing immunity, rather than by directly stimulating Sa1 growth. Drug potency, which is usually not described for immunosuppressive agents, was calculated from the linear relationship between drug dose and tumor volume. The potency of CsA was inversely related to the stringency of the histocompatibility barrier. Another advantage of this assay is that the endpoint is an objective size measurement over a short time period, compared with transplant models where the endpoint may not be reached for many weeks and may be more subjective. In addition, this model can measure the potency of combination drug treatments and compare new immunosuppressive drug regimens. For example, the administration of SDZ RAD or FTY720 with CsA resulted in a more than additive increase in potency, compared with the sum of the drugs as single agents.