NORMAN, Okla. – Marmar Moussa, an assistant professor in the School of Computer Science and Stephenson School of Biomedical Engineering at the University of Oklahoma, has received a distinguished U.S. National Science Foundation CAREER award to develop advanced computational tools that could transform how scientists study disease at the cellular level, particularly in cancer and tissue remodeling.
Moussa will lead a five-year project to create advanced algorithms that combine molecular profiling with spatial tissue analysis. This innovative approach addresses a critical gap in current research by connecting what scientists can observe of cellular organization, e.g. under a microscope, with what is happening at the molecular level within individual cells.
“Usually, when we study disease with single-cell technologies, we examine cells in isolation – outside of their native tissue environment,” said Moussa. “However, when pathological processes such as malignancy occur, cells’ microenvironment changes in ways that can be visible under the microscope and within the broader tissue context. Our goal is to tie these changes with what’s happening on the molecular level inside the cell.”
Traditionally, scientists either study the molecular profile of cells through genomic sequencing – a method for determining an organism’s DNA or RNA – or examine tissue structure through imaging, but rarely simultaneously in their natural context. Moussa’s project will develop algorithms for spatial transcriptomics, a technology that merges these approaches, creating a more complete picture of how diseases develop and spread.
The project will develop three key innovations:
The web tool will serve as more than just a data repository. The platform will house both newly generated data from the project and existing publicly available datasets in an integrated form, all processed through the new algorithms. According to Moussa, the tool will help researchers build collections of data that are relevant to their studies.
These innovations will help scientists better understand tumor progression, extracellular matrix remodeling and other dynamic processes in cancer and beyond. While cancer is a key application, the tools and methods developed will also apply to other diseases and even plant science.