Suppression of lymphoma and epithelial malignancies effected by interferon gamma

The immunosurveillance of transformed cells by the immune system remains one of the most controversial and poorly understood areas of immunity. Gene-targeted mice have greatly aided our understanding of the key effector molecules in tumor immunity. Herein, we describe spontaneous tumor development in gene-targeted mice lacking interferon (IFN)-gamma and/or perform (pfp), or the immunoregulatory cytokines, interleukin (IL)-12, IL-18, and tumor necrosis factor (TNF). Both IFN-gamma and pfp were critical for suppression of lymphomagenesis, however the level of protection afforded by IFN-gamma was strain specific. Lymphomas arising in IFN-gamma deficient mice were very nonimmunogenic compared with those derived from pfp-deficient mice, suggesting a comparatively weaker immunoselection pressure by IFN-gamma. Single loss of IL-12, IL-18, or TNF was not sufficient for spontaneous tumor development. A significant incidence of late onset adenocarcinoma observed in both IFN-gamma- and pfp-deficient mice indicated that some epithelial tissues were also subject to immunosurveillance.

Efficacy of Lentivirus-mediated and MUC1 antibody-targeted VP22-TK/GCV suicide gene therapy for ovarian cancer

Transfer of the herpes simplex virus type I thymidine kinase (HSV-TK) gene into tumor cells using virus-based vectors in conjunction with ganciclovir (GCV) exposure provides a potential gene therapy strategy for the treatment of cancer. Effective gene therapy,, depends on the efficient transfer and specific targeting of therapeutic genes and their protein products to target cells. The purpose of this study was to investigate the anti-tumor effect of Lentivirus-mediated and MUC1 antibody-targeted VP22-TK/GCV suicide gene therapy in animal models. Mouse models were generated with intraperitoneal injection of human epithelial ovarian cancer cells 3AO, which are MUC1-positive. HTV-1-based lentiviral vectors carrying VP22-TK or scFv-VP22-TK were prepared. The animals were injected intraperitoneally with lentivirus containing scFv-VP22-TK, VP22-TK followed by GCV treatment. Combined treatment of lentivirus-expressed scFv-VP22-TK or VP22-TK with GCV inhibited the proliferation and prolonged survival times compared with the control vector. The survival time of animals treated with scFv-VP22-TK/GCV was significantly longer than that of animals treated with VP22-TK/GCV (p = 0.006). Conclusion: Our results suggest that MUC1 antibody-targeted VP22-TK/GCV suicide gene therapy can efficiently inhibit ovarian tumor growth and increase survival in a nude mouse model of ovarian carcinoma. These data support the development of this method for human clinical trials.

Innate immune surveillance of spontaneous B cell lymphomas by natural killer cells and gamma delta T cells

Few studies have demonstrated that innate lymphocytes play a major role in preventing spontaneous tumor formation. We evaluated the development of spontaneous tumors in mice lacking beta-2 microglobulin (beta2m; and thus MHC class I, CD1d, and CD16) and/or perform, since these tumor cells would be expected to activate innate effector cells. Approximately half the cohort of perform gene-targeted mice succumbed to spontaneous disseminated B cell lymphomas and in mice that also lacked beta2m, the lymphomas developed earlier (by more than 100 d) and with greater incidence (84%). B cell lymphomas from perforin/beta2m gene-targeted mice effectively primed cell-mediated cytotoxicity and perform, but not IFN-gamma, IL-12, or IL-18, was absolutely essential for tumor rejection. Activated NK1.1(+) and gammadeltaTCR(+) T cells were abundant at the tumor site, and transplanted tumors were strongly rejected by either, or both, of these cell types. Blockade of a number of different known costimulatory pathways failed to prevent tumor rejection. These results reflect a critical role for NK cells and gammadeltaTCP(+) T cells in innate immune surveillance of B cell lymphomas, mediated by as yet undetermined pathway(s) of tumor recognition.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.