Algorithm Predicts Response to Measles Virus Therapy in Ovarian, Other Cancers, Study Shows

Algorithm Predicts Response to Measles Virus Therapy in Ovarian, Other Cancers, Study Shows
Researchers at the Mayo Clinic developed an algorithm to predict the response of ovarian cancer patients to measles virus therapy, an investigational anti-cancer treatment being developed by the large U.S.-based medical center. Analyzing the response of human tumors and mouse cancer models, they found a specific pattern of gene activation that is key to determining ovarian and brain cancer response to oncolytic measles virus therapy. This discovery allowed researchers to create a computational model capable of predicting the treatment's effectiveness, and which may help pre-select patients to receive the viral therapy alone or in combination with drugs that aid the circumvention of cancer viral resistance. The findings appeared in the study, “Constitutive Interferon Pathway Activation in Tumors as an Efficacy Determinant Following Oncolytic Virotherapy,” published in the Journal of the National Cancer Institute. Mayo Clinic is investing in the clinical development of attenuated measles virus as a new therapy against solid tumors and blood cancers. The virus carries promising properties as an anti-cancer agent, including its selectivity for entering and killing cancer cells, its ability to kill bystander tumor cells adjacent to the virus, and the positive safety profile it has demonstrated in clinical trials. Several Phase 1 and Phase 2 clinical trials are currently evaluating the use of measles virus derivatives — called oncolytic measles virus — for the treatment of ovarian, fallopian, or peritoneal cancer (NCT02364713); glioblastoma (aggressive brain tumors, NCT00390299); multiple myeloma (NCT00450814); head and neck and breast cancer (NCT01846091); and mesothelioma (aggressive cancer of the lining of organs, NCT01503177). Recogniz
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