Advancing Disease Modeling through Mathematical Frameworks: Leveraging Single-Cell Spatial Data to Uncover Tissue-Specific Pathways and Immune Responses

The rapid advancement of single-cell spatial imaging technologies, such as Spatial Transcriptomics, Imaging Mass Cytometry (IMC), and CODEX (CO-Detection by Indexing), has revolutionized our understanding of tissue microenvironments by offering unprecedented insights into the spatial organization and interactions of diverse cell types within tissues. These technologies generate large, complex datasets that capture the heterogeneity and dynamic behaviors of tissues at single-cell resolution. However, there remains a significant need for advanced mathematical models that can fully leverage these datasets to interpret the complex biological processes involved. This project seeks to bridge that gap by developing sophisticated mathematical models, particularly using partial differential equations (PDEs), to investigate the spatial interactions between cells and molecules within tissues. Specifically, the models will aim to capture tissue-specific biochemical and biomechanical characteristics to uncover the pathways and mechanisms that influence various diseases and immune responses. Understanding these key factors is essential for revealing how tissue microenvironments regulate disease progression and immune interac- tions. For example, modeling interactions in bone tissue can elucidate mechanisms responsible for conditions like aging, bone deformation, autoimmune diseases such as rheumatoid arthritis (RA), and cancer. By integrating both mechanical and biochemical dynamics into our models, we will develop a comprehensive framework for understanding multi-scale interactions in disease contexts. These models will also serve as predictive tools to simulate how different interventions may influence disease progression and immune responses in various tissues. The spatial dependence introduced in the PDEs will help model the movement of cells, cytokines, and other signaling molecules within tissue environments, a critical factor for processes such as inflammation, immune responses, and tissue remodeling. Ultimately, this project will contribute to the discovery of novel therapeutic targets and the development of personalized treatment strategies by providing a deeper understanding of the pathways and mechanisms that drive complex diseases across different tissues. Project Number: 1R35GM159993-01 | Fiscal Year: 2025 | NIH Institute/Center: National Institute of General Medical Sciences (NIGMS) | Principal Investigator: Leili Shahriyari | Institution: UNIVERSITY OF MASSACHUSETTS AMHERST, HADLEY, MA | Award Amount: $406,250 | Activity Code: R35 | Study Section: Special Emphasis Panel[ZRG1 MCST-Q (55)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11201962