Dysregulated RNA processing is a common hallmark of cancer, with somatic mutations frequently targeting regulators of RNA splicing, localization, and decay. Indeed, a major mechanism governing RNA translation and function is through regulated RNA subcellular localization, and functional genomics studies have frequently identified regulators of RNA localization as selective cancer dependencies. Yet the role of RNA mislocalization in driving cancer phenotypes is poorly understood, largely because of a lack of tools.

By combining my unique background in computation, biophysics, and technology development, I propose to establish a multidisciplinary cancer research program to systematically char...

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Dysregulated RNA processing is a common hallmark of cancer, with somatic mutations frequently targeting regulators of RNA splicing, localization, and decay. Indeed, a major mechanism governing RNA translation and function is through regulated RNA subcellular localization, and functional genomics studies have frequently identified regulators of RNA localization as selective cancer dependencies. Yet the role of RNA mislocalization in driving cancer phenotypes is poorly understood, largely because of a lack of tools.

By combining my unique background in computation, biophysics, and technology development, I propose to establish a multidisciplinary cancer research program to systematically characterize how RNA mislocalization shapes breast cancer proteomes and malignant progression, explore the role of RNA mislocalization in new anti-cancer therapeutics, and develop technologies that enable quantification of RNA mislocalization in tumors and ultimately enable more precise patient-selection strategies for cancer therapy.

My primary research goals for the CPRIT award are:

1. Leverage novel unbiased approaches that I developed to identify RNA cis-elements that drive RNA localization defects and new dependencies in breast cancer.
2. Elucidate how RNA mislocalization contributes to the anti-cancer activity of new classes of therapeutics targeting RNA editing and RNA modifying.
3. Develop new sequencing and computational approaches to quantify subcellular RNA localization in cancer models and primary tumor specimens.

At Baylor College of Medicine, I will establish a cancer research program that leverages novel sequencing technologies, high-throughput reporter screens, imaging, mouse models, and machine learning to identify how RNA localization is dysregulated in malignancies. My long-term goal is to apply our mechanistic insights of RNA regulation to advance personalized cancer therapeutic strategies.

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