Paul Campagnola Ph.D
Department Chair & Professor
Department of Biomedical Engineering
University of Wisconsin-Madison
Title: High resolution imaging and biological consequences of collagen architecture alterations in ovarian cancer and pancreatic cancer
Abstract: Most cancers are characterized by alterations in the collagen organization relative to normal tissues. We have developed Second Harmonic Generation (SHG) microscope tools to selectively and specifically probe all levels of collagen architecture organization in human ovarian cancer. Using a novel form of 3D machine learning, we successfully classified six types of ovarian tumors based on the observed collagen fiber morphology. We also developed polarization sensitive SHG methods to extract collagen macro/supramolecular structural aspects and found significant differences between normal and malignant ovarian tissues. We have also developed an SHG image-based fabrication approach to creating tissue engineered scaffolds of ovarian cancer to study the effects of collagen remodeling on cell-matrix interactions including migration and cytoskeletal dynamics. We found the remodeled matrix drives the cell behavior to a larger extent than the initial cell phenotype. Similar trends were found in a series of pancreatic cancer cell lines. We have also developed a machine learning approach using generative adversarial networks (GANSs) to optimize the scaffold design.
Bio: Paul J. Campagnola obtained his PhD in Chemistry from Yale University in 1992 and was a postdoctoral associate at the University of Colorado from 1992-1995. He is currently the Tong Biomedical Engineering Department Chair and UW Kellett Faculty Fellow. He is a Fellow of Optica and the American Institute for Medical and Bioengineering, and was a Fellow in the Big 10 Alliance Academic Leadership Program. He has over 100 peer-reviewed journal articles, several review articles and book chapters, co-edited a book “Second Harmonic Generation microscopy.” His research focuses on modifications in the extracellular matrix in diseases in including cancers and fibroses.
