Grant: Catalyst Grant: Bioinformatics Approaches to Cancer Research

An oncolytic virus is a viral strain that has been engineered to selectively infect and destroy cancer cells. Pre-clinical studies on virus JX-594 (a vaccinia-derived oncolytic virus) show promise that it could be effective in treating a wide array of cancers given its potency and broad-spectrum oncolytic activity. Several clinical trials have been already approved and are currently ongoing in South Korea, USA and Canada. However, it is known that not all tumors are equally sensitive to JX-594. Some of them show resistance to infection even at high viral doses. Thus, in order to fully develop this promising new therapy, it is necessary to identify which cancer types are more susceptible to be infected and destroyed by the virus, as well as what makes some cancers to be resistant. Our study will look at the molecular data profiles of 60 different human cancer cell lines for which we have measures of sensitivity to JX-594. The molecular profiles of these 60 cancer cell lines are already available at publicly accessible databases. By analizing them it is possible to determine which genes are highly expressed in a particular cell type. Using computational approaches on these data we will determine biomarkers (mainly genes) that are correlated with increased sensitivity to the virus, and we will point to the cellular mechanisms that are likely to confer resistance. We expect that in the future, these markers will allow us to predict whether a particular tumor will be an adequate target for the virus. Moreover, we expect to identify the molecular mechanisms associated with resistance that should be targeted in order to curb the resistance of non-susceptible tumors in future developments of this therapy.