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The Fas/Fas Ligand Pathway Is Important for Optimal Tumor Regression in a Mouse Model of CTL Adoptive Immunotherapy of Experimental CMS4 Lung Metastases

Laboratory of Tumor Immunology and Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892

The mechanisms of CTL-mediated tumor regression in vivo remain to be fully understood. If CTL do mediate tumor regression in vivo by direct cytotoxicity, this may occur via two major effector mechanisms involving the secretion of perforin/granzymes and/or engagement of Fas by Fas ligand (FasL) expressed by the activated CTL. Although the perforin pathway has been considered the dominant player, it is unclear whether Fas-mediated cytotoxicity is additionally required for optimal tumor rejection. Previously, we produced H-2L^d-restricted CTL reactive against the CMS4 sarcoma, which expresses a naturally occurring rejection Ag recognized by these CTL and harbors a cytokine (IFN- plus TNF)-inducible, Fas-responsive phenotype. The adoptive transfer of these CTL to syngeneic BALB/c mice with minimal (day 3 established) or extensive (day 10 established) experimental pulmonary metastases resulted in strong antitumor responses. Here we investigated whether a FasL-dependent CTL effector mechanism was important for optimal tumor regression in this adoptive immunotherapy model. The approach taken was to compare the therapeutic efficacy of wild-type to FasL-deficient (gld) CTL clones by adoptive transfer. In comparison with wild-type CTL, gld-CTL efficiently mediated tumor cytolysis and produced comparable amounts of IFN-, after tumor-specific stimulation, as in vitro assessments of Ag recognition. Moreover, gld-CTL mediated comparably potent antitumor effects in a minimal disease setting, but were significantly less effective under conditions of an extensive tumor burden. Overall, under conditions of extensive lung metastases, these data revealed for the first time an important role for a FasL-dependent CTL effector mechanism in optimal tumor regression.

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