Vision & Direction of Research: Precision Medicine for Improving Long-term Outcomes after LT
1) HCC evolution in different environments.
We are examining the molecular basis of HCC that evolves in different environments, particularly in the immunosuppressed setting post-transplant. We are employing both animal models and prospective biopsies of recurrent HCC tumours post-transplant, with the ultimate goal of developing a more personalized approach to prevention and therapy based on mutation burden. We are also investigating the role of a fluorescent lipid nanoparticle (porphysomes) for image-guided treatment of HCC, using an animal model of HCC.
2) Metabolic Disease Post-Transplant:
Our clinical studies into NAFLD and diabetes post-transplant have informed studies examining different ‘omics in these conditions. We plan to continue examining the molecular basis of Post-transplant NAFLD and developing screening protocols for this based on a combination of clinical, ‘omics and transient elastography data. Our work has also demonstrated a role for the microbiome in post-transplant complications. We have been working to characterize the microbiome in transplant recipients, and to establish causality using fecal microbiota transplantation into germ-free mice. This will ultimately inform preventive and therapeutic strategies for transplant recipients with metabolic disease. We have experience with animal models of NAFLD to enable validation of different therapeutic targets.
3) Machine learning algorithms and biostatistical modelling to predict long-term complications Post- Transplant.
With collaborators at the Vector Institute, we have developed a risk calculator for individualized prediction of post-transplant complications. The ranked features that predict each complication will guide physicians in preventive care and therapy (including changes in immunosuppression).
In developing our precision-medicine program on long-term complications of liver transplantation, we have been leveraging Toronto’s unique strengths in molecular/computational biology and machine learning with the UHN-MOT, the largest transplant program in the Western hemisphere. Through a better understanding of the molecular pathogenesis of long-term metabolic and malignant complications, we will identify appropriate preventive and therapeutic strategies to enhance long-term survival in our patients and inform clinical practice guidelines.