While viruses cause significant proportion of cancers, their real impact in cancer etiology and complications is still unknown. Indeed, viruses may be implicated in cancer more frequently than previously considered, which may lead to rethinking cancer treatment and prevention strategies. Little effort so far has been exerted to screen for infectious agents associated with cancer. Our long-term goal is to determine how cancer treatment and prevention can be improved in virus-associated cancers.
The objectives of the proposed research are to develop a computational pipeline to improve our technological ability to detect and identify new viruses associated with the disease; and to determine genetic variables associated with these viruses. Our working hypothesis is that there are previously unknown viruses associated with cancer that may induce an alternative etiology. We will test our working hypothesis on publicly available sequencing and clinical data. The rationale of this aim is that successful viral typing is critical for hypothesizing their causative role, and thus, the determination the future directions in cancer research, involving potential biomarkers, outcome prediction, or tumor classification. Our central hypothesis will be tested by pursuing one specific aim: Identify new viruses potentially involved in human cancers.
The proposed research focuses on an innovative approach, namely: utilizing high-throughput sequencing data to screen for all known viruses in various cancer types. This is the first study that will screen at least eighteen cancer types. Fifteen out of eighteen cancers were previously shown to have increased incidence in immunosuppressed patients or were linked to viral infection, thereby hypothesizing virus causality. The data we want to use may provide valuable and timely return for the aim of the proposal.
This contribution is significant because it is an essential step in the continuum of research that is expected to lead to new treatment strategies in patients with virus-positive tumors and better prevention through vaccine development and implementation procedures to prevent viral infection and the cancers they may promote. Once explicit information on cancer-associated viruses becomes available, regardless causal or not, virus-positivity may be used as biomarker for patients’ outcome prediction, early cancer detection, tumor localization and classification, as well as guide the type and intensity of therapy.