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In vivo methodology for the discovery and validation of miRNA biomarkers in cancer


In the proposed research, we will develop in vivo methodology that would permit the discovery and validation of miRNA biomarkers in cancer. The approach relies on nanosensors capable of reporting on miRNA expression in vivo. We will employ murine breast cancer models of metastasis to validate the utility of the nanosensors as preclinical tools capable of answering questions about the genesis of metastasis. Specifically, we will profile the expression of key pro-metastatic microRNAs in the primary tumors at the pre-metastatic stage and at different points after metastases arise. This will directly address the question of how the primary tumor changes to initiate and maintain the metastatic cascade. It will also help understand the role of miRNAs as drivers of metastasis. What is unique about the nanosensors described here is that they allow studies in vivo in an authentic anatomical and physiologic environment and thus they reflect the true dynamics of the metastatic process. Specifically, the nanosensors consist of magnetic nanoparticles that carry fluorescent turn-on oligonucleotide probes sensitive to individual microRNA activity. We have shown that: 1. the nanosensors, as designed, are delivered to tumor cells in vivo following systemic injection in a murine breast cancer model; 2. the nanosensors successfully engage the RNA interference machinery in a microRNA-specific way, following in vivo delivery; and 3. the nanosensors, as designed can be used to monitor microRNA expression in vivo. The tools and methods described here are applied to answer one specific question related to metastasis using a breast cancer model. However, the technology has much broader implications because it can be utilized in any solid tumor model to answer questions related to microRNA function. Considering that microRNAs represent highly specific and very early and/or predictive biomarkers of metastatic potential, risk assessment, prognosis, and treatment response, the methodology utilized in our application can have broad significance as a preclinical tool. In particular, it could assist in understanding the ultimate value of miRNAs for forecasting invasive disease and predicting response to specific therapeutic modalities, leading to the design individualized curative or even preventive treatments.

Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.