Transcriptional dysregulation in tumors can induce the abundant expression of repetitive elements in cancerous cells compared to normal tissues, where they are often transcriptionally silent. Such transcripts have been associated with better outcomes to cancer immunotherapies, as they can modulate the tumor immune microenvironment and generate an under-quantified source of tumor neoantigens. Therefore, it has been hypothesized that the aberrant transcription of repeat RNA is both a critical mechanism for initiating the immune response in the tumor microenvironment and an untapped source of potential therapeutic targets. Using a set of approaches from statistical physics, our team predicted repetitive element RNA directly stimulates receptors of the innate immune system, confirmed this hypothesis in a key subset of immune cells, and showed repeat expression can correlate with response to checkpoint blockade immunotherapies. Repeat RNA is therefore both a novel biomarker for the innate immune response in cancer and a potential therapeutic target to modulate tumor immunity. We will utilize a set of tools, developed by our team, from statistical physics to characterize repeat RNA recognition by innate immune receptors in silico and their role in tumor-immune co-evolution, both with and without the application of immunotherapy (Aim 1). Next, we will characterize the spatial context of repeat RNAs in the tumor immune microenvironment and the co-localization of predicted immunostimulatory RNA with activation of immune signaling, along with in depth immune-phenotyping of the state of the immune microenvironment in vivo (Aim 2). Finally, we will perform functional validation of our predictions on human immune cells to validate mechanisms of recognition and the specific immune subsets responsible for repeat recognition via a set of in vitro assays (Aim 3). Our goal is to use approaches from statistical physics to quantify the role of repetitive elements in tumor immunology, their rules of recognition by innate immune receptors and their part in facilitating cytolytic T cell activity. In doing so we will combine novel RNA detection technologies to study their spatial distribution and localization in cancers; state of the art immune-phenotyping; and mathematical models to characterize their direct role in tumor evolution. We hypothesize that our approach from statistical physics will identify the key structural and sequence features of repeat mediated immune activation in solid tumors and shed light on their specific consequences for tumor evolution and therapeutic efficacy.
An emerging paradigm in cancer immunology states that the aberrant transcription of repeat RNA in cancer is a critical mechanism for engaging tumor intrinsic and extrinsic immune and regulatory factors, and an untapped source of potential therapeutic targets. Using a set of approaches from statistical physics, our team predicted repeat RNA stimulates receptors of the innate immune system, confirmed this hypothesis in a key subset of immune cells, and showed classes of repeat RNA can correlate with response to immunotherapies. Our goal is to identify the classes of structural and sequence features of repeat mediated immune activation in solid tumors and clarify their specific consequences for tumor evolution, the state of the immune microenvironment, and cancer immunotherapies.
