Contact
1020 Locust Street
Jefferson Alumni Hall, Suite 314C
Philadelphia, PA 19107
Convergent Systems Pathophysiology for Regenerative Medicine
We are interested in understanding the operational principles of mammalian tissue plasticity, repair, and regeneration. A key goal is to develop novel clinical interventions and decision-support systems for regenerative medicine and cancer treatment. Our transdisciplinary systems biology strategy is based on a convergence of single cell transcriptomics, spatial transcriptomics, high-plex imaging, computational modeling, bioinformatics, artificial intelligence, machine learning, and systems engineering. We are pursuing internationally collaborative projects on:
- cellular and molecular mechanisms disrupting tissue repair in liver failure
- neuromodulatory processes to intervene in heart failure and hypertension
- robustness of signaling mechanisms driving developmental defects
- network interactions regulating tumor microenvironment response to therapy
Research Projects
Multiscale Control of Liver Renewal, Repair & Regeneration
How does liver regenerate? Which control aspects of liver repair go awry in chronic liver disease and acute failure? Can we predict the temporal progression of the regeneration outcome following a suboptimal liver transplant?
Liver regeneration is a clinically important tissue repair process, which involves an interplay of coordinated signals from multiple cell types integrated with the systemic factors to recover functional tissue mass. We pursue a systems biology strategy that combines single cell transcriptomics data and multiscale network modeling to study mechanisms inhibiting regeneration and driving acute liver failure. Ongoing projects are investigating gene regulatory, signaling, and metabolic networks driving alcohol-associated hepatitis. We are using artificial intelligence, histopathology and transcriptomics to determine the regenerative capacity of donor livers to aid clinical evaluation for transplantation suitability.
Collaborators
- Jan Hoek, PhD - Department of Pathology & Genomic Medicine, SKMC Thomas Jefferson University
- Ashesh Shah, MD - Liver Transplant Center, Jefferson Health
- Ramon Bataller, MD, PhD - Liver Clinic, IDIBAPS, Barcelona
- Radhakrishnan Mahadevan, PhD - Chemical Engg, University of Toronto, Canada
Funding: National Institutes of Alcohol Abuse and Alcoholism; Transplant Foundation, Gift of Life
Autonomic Dysregulation & Neuromodulation of Heart Failure & Hypertension
How do the neuronal signaling and cell-cell interactions in the brainstem and peripheral neuronal circuits adapt to heart failure and hypertension? Which neuromodulatory control points should be manipulated for prevention and rescue?
Hypertension is a major chronic disease worldwide; one third of the population in the United States is hypertensive, and alarmingly, nearly half of the individuals using anti-hypertensive medication do not have their blood pressure well controlled. These patients exhibit severe autonomic dysregulation and are susceptible to heart failure. We are identifying molecular, cellular and circuit mechanisms that are essential for robust control of blood pressure and cardioprotection. Our single cell and spatial transcriptomics and physiological modeling studies uncovered extensive plasticity and remodeling of brainstem and peripheral autonomic control circuits in response to cardiovascular injury. Ongoing projects are pursuing a patented approach for microRNA inhibition to prevent essential hypertension, and vagal neuromodulation to enhance cardioprotection for preventing heart failure.
Collaborators
- James Schwaber, PhD - Department of Pathology & Regenerative Medicine, SKMC, Thomas Jefferson University
- Zixi Cheng, PhD - University of Central Florida
- Abraham Lenhoff, PhD - University of Delaware
- Peter Hunter, PhD - Auckland Bioengg Institute
Funding: National Heart, Lung, and Blood Institute; National Institutes of Health Common Fund
Robustness of Embryonic Signaling Mechanisms & Developmental Defects
What are the limits of the homeostatic robustness of cell fate regulation in the early embryo? How do intracellular feedback control loops regulate key signaling pathways to counteract the environmental disturbances within a physiological range?
Robustness is an important characteristic of regulatory signaling pathways. This characteristic allows the cells and tissues to overcome variability due to genetic polymorphisms and respond to environmental disturbances within limits. We are studying the autoregulation and robustness response of retinoic acid signaling in the embryo. Aberrant fluctuations in retinoic acid levels can result in severe developmental malformations. We propose a conceptual paradigm in which signaling robustness emerges from a combination of network-wide feedback adjustments that are affected by genetic variation. We are pursuing a systems biology strategy combining comprehensive targeting of retinoic acid network components and machine learning modeling to unravel the regulatory mechanisms driving the robustness response. We are developing genetic assays for use as early clinical intervention tools in the diagnosis of fetal alcohol spectrum disorders that are known to arise from ethanol-mediated disruption of retinoic acid signaling.
Collaborators
- Abraham Fainsod,PhD - Hebrew University of Jerusalem, Israel
- Geoffrey Hicks, PhD - University of Manitoba, Canada
- Adam Ertel, PhD - Department of Pathology and Genomic Medicine, SKMC, Thomas Jefferson University
Funding: Jefferson Intramural; Philanthropy
Tumor Microenvironment Drivers of Response to Immunotherapy
What are the critical control points in the tumor microenvironment for maximizing the sensitivity to treatment? How to reshape the tumor microenvironment to prevent the development of resistance to therapy?
We are interested in identifying how the cell-cell interactions and the dynamic alterations of the molecular milieu in the tumor microenvironment drive the development of resistance to cancer therapy, including immunotherapy. We are building computational models of cellular phenotypes, state transitions and interactions in the tumor microenvironment. We are fine-tuning the network models for the head and neck cancer context using single cell transcriptomics data from patient-derived tumor samples. We are pursuing artificial intelligence-based methods to analyze large scale histopathology data to extract tumor microenvironment features predictive of treatment response and progression/ metastasis-free survival in prostate cancer.
Collaborators
- Adam Luginbuhl, MD - Department of Otolaryngology - Head & Neck Surgery, SKMC, Thomas Jefferson University
- My Mahoney, PhD - Department of Pharmacology, Physiology & Cancer Biology, SKMC, Thomas Jefferson University
- William Kevin Kelly, MD - Department of Medical Oncology, SKMC, Thomas Jefferson University
- Adam Dicker, MD, PhD - Department of Radiation Oncology, SKMC, Thomas Jefferson University
Funding: Pennsylvania Department of Health; Prostate Cancer Foundation; Philanthropy.