Combination therapy targeting the tumor microenvironment is effective in a model of human ocular melanoma.

BACKGROUND: Ocular melanoma is the leading intraocular malignancy. There is no effective treatment for metastatic ocular melanoma. We sought a treatment targeting the tumor microenvironment as well as the tumor cells. METHODS: Migration of HUVEC cells, the ability of HUVEC cells to form tubes, and proliferative capacity of a human ocular melanoma cell line were tested in the presence of lenalidomide and sorafenib alone and in combination. The compounds were also tested in a rat aortic ring assay and were tested in a highly aggressive human ocular melanoma xenograft model. RESULTS: Lenalidomide and Sorafenib inhibit HUVEC ability to migrate and form tubes and when used in combination the inhibition is increased. The agents alone and in combination inhibit outgrowth in the rat aortic ring model. The combination of the agents improved the inhibition over either single agent. In a xenograft model, combination therapy inhibited tumor growth over inhibition by single agent alone in a significant fashion (p < 0.004: lenalidomide and p < 0.0035: sorafenib). Furthermore, spontaneous lung metastasis development was completely inhibited in the combination treated animals. Sixty percent of vehicle treated animals developed lung metastases compared to 50% of lenalidomide treated animals, and 33% of sorafenib treated animals. CONCLUSION: Lenalidomide and sorafenib are effective at targeting endothelial cells, inhibiting growth of ocular melanoma cells and can inhibit growth of tumors in a xenograft model as well as inhibit development of metastases. Combining these agents works in an additive to synergistic way to inhibit the growth of tumors and development of metastases.

Adoptive cell transfer therapy following non-myeloablative but lymphodepleting chemotherapy for the treatment of patients with refractory metastatic melanoma.

PURPOSE: We investigated the combination of lymphodepleting chemotherapy followed by the adoptive transfer of autologous tumor reactive lymphocytes for the treatment of patients with refractory metastatic melanoma. PATIENTS AND METHODS: Thirty-five patients with metastatic melanoma, all but one with disease refractory to treatment with high-dose interleukin (IL) -2 and many with progressive disease after chemotherapy, underwent lymphodepleting conditioning with two days of cyclophosphamide (60 mg/kg) followed by five days of fludarabine (25 mg/m(2)). On the day following the final dose of fludarabine, all patients received cell infusion with autologous tumor-reactive, rapidly expanded tumor infiltrating lymphocyte cultures and high-dose IL-2 therapy. RESULTS: Eighteen (51%) of 35 treated patients experienced objective clinical responses including three ongoing complete responses and 15 partial responses with a mean duration of 11.5 +/- 2.2 months. Sites of regression included metastases to lung, liver, lymph nodes, brain, and cutaneous and subcutaneous tissues. Toxicities of treatment included the expected hematologic toxicities of chemotherapy including neutropenia, thrombocytopenia, and lymphopenia, the transient toxicities of high-dose IL-2 therapy, two patients who developed Pneumocystis pneumonia and one patient who developed an Epstein-Barr virus-related lymphoproliferation. CONCLUSION: Lymphodepleting chemotherapy followed by the transfer of highly avid antitumor lymphocytes can mediate significant tumor regression in heavily pretreated patients with IL-2 refractory metastatic melanoma.

Expression signature developed from a complex series of mouse models accurately predicts human breast cancer survival.

PURPOSE: The capability of microarray platform to interrogate thousands of genes has led to the development of molecular diagnostic tools for cancer patients. Although large-scale comparative studies on clinical samples are often limited by the access of human tissues, expression profiling databases of various human cancer types are publicly available for researchers. Given that mouse models have been instrumental to our current understanding of cancer progression, we aimed to test the hypothesis that novel gene signatures possessing predictability in clinical outcome can be derived by coupling genomic analyses in mouse models of cancer with publicly available human cancer data sets. EXPERIMENTAL DESIGN: We established a complex series of syngeneic metastatic animal models using a murine breast cancer cell line. Tumor RNA was hybridized on Affymetrix MouseGenome-430A2.0 GeneChips. With the use of Venn logic, gene signatures that represent metastatic competency were derived and tested against publicly available human breast and lung cancer data sets. RESULTS: Survival analyses showed that the spontaneous metastasis gene signature was significantly associated with metastasis-free and overall survival (P < 0.0005). Consequently, the six-gene model was determined and showed statistical predictability in predicting survival in breast cancer patients. In addition, the model was able to stratify poor from good prognosis for lung cancer patients in most data sets analyzed. CONCLUSIONS: Together, our data support that novel gene signature derived from mouse models of cancer can be used for predicting human cancer outcome. Our approaches set precedence that similar strategies may be used to decipher novel gene signatures for clinical utility.