Metastatic Cancers

We are integrating human liver microphysiology systems (MPS) to recapitulate the human liver acinus as an advanced human experimental model for use in the QSP approach for developing repurposed and novel therapeutics for metastatic breast and cutaneous melanoma cancers in the liver. Computational and systems biology approaches complement the human experimental models.

The liver TME regulates enhanced estrogen-dependent growth phenotypes conferred by clinically observed ESR1 mutations. While D538G-expressing cells (hashed green) show enhanced estrogen-dependent growth exclusively in 2D monoculture (A), Y537S-expressing cells (hashed red) display this growth advantage in liver acinus microphysiology systems (LAMPS) models (B), demonstrating a phenotypic switch in estrogen-dependent growth that depends upon TME composition.

The liver TME regulates enhanced estrogen-dependent growth phenotypes conferred by clinically observed ESR1 mutations. While D538G-expressing cells (hashed green) show enhanced estrogen-dependent growth exclusively in 2D monoculture (A), Y537S-expressing cells (hashed red) display this growth advantage in liver acinus microphysiology systems (LAMPS) models (B), demonstrating a phenotypic switch in estrogen-dependent growth that depends upon TME composition.

Our collaborations in breast cancer include Adrian Lee, PhD, Director of the Institute for Precision Medicine and an internal advisory board member for the UPDDI, Chakra Chennubhotla, PhD, Department of Computational and Systems Biology, Timothy Lezon, PhD, Department of Computational and Systems Biology, as well as Andy Stern, PhD, Bert Gough, PhD, Mark Miedel, PhD, all from the Department of Computational and Systems Biology and the UPDDI.  In addition, a spin-off company, SpIntellx, a computational and systems pathology company, was formed to commercialize the intellectual property based on spatial analytics, explainable artificial intelligence (xAI) and systems biology applied to primary tumors in order to generate prognostic and diagnostic tests, as well as to guide personalized therapeutic strategies.

The goal of the metastatic melanoma program is to develop therapeutics for metastatic melanoma using QSP. We take advantage of the strengths in melanoma cancer within the UPMC Hillman Cancer Center with John Kirkwood, MD, Co-leader of the UPMC Hillman Cancer Center melanoma program together with Hassane Zarour, MD, Co-leader of the UPMC Hillman Cancer Center melanoma program, and a member of the UPDDI internal advisory board.  We also harness the strengths in cancer, biomedical engineering and organoid engineering at Vanderbilt with John Wikswo, PhD, Biomedical Engineering, Molecular Physiology & Biophysics and Physics and the University of Wisconsin with William Murphy, PhD,  Department of Biomedical Engineering and Pharmacology and Co-Director of the Stem Cell and Regenerative Medicine Center.  The UPDDI, Vanderbilt and Wisconsin have an NIH UO1 grant to apply the integrated technologies to develop therapeutics.  Key faculty also include  Alex Soto-Gutierrez, MD, PhDDepartment of Pathology and the McGowan Institute of Regenerative Medicine, as well as Albert Gough, PhD, Larry Vernetti, PhD, Mark Miedel, PhD all from the Department of Computational and Systems Biology and the UPDDI.

Metastatic melanoma cells grow within the hepatocyte layer in LAMPS models. The spatial relationship between GFP-expressing hepatocytes and mCherry-expressing melanoma cells was examined over a 16-day time course in the LAMPS models. Over time, melanoma cells (red) were found infiltrating within the hepatocyte (green) layer, demonstrated by the xz sections shown at days 8 (top panel) and 16 (bottom panel).