Trained in molecular biology, tissue engineering and systems biology, I am interested in how cells and tissue process diverse environmental signals and output various phenotypes. Understanding how biological systems work could help us target disease phenotypes and even predict potential health complications. Specifically, I would like to target some major questions in the area of cardiac valve tissue engineering and drug-induced cardiotoxicity.
My PhD work focuses on understanding the molecular mechanisms of cardiac valve calcification. Despite the recognized importance of matrix stiffness in regulating the function and differentiation of fibroblasts, the effect of matrix stiffness is still debated and many questions remain about how the biomechanical cue of elasticity is translated into intracellular signaling. My study addresses this question by showing that valvular fibroblasts sense the changes in matrix elasticity through the PI3K/AKT pathway, provides potential downstream targets for developing disease treatment and suggests appropriate stiffness for bioscaffold design in cardiac valve tissue engineering.
For my recent postdoc, I study an emerging clinical issue of cancer drug induced cardiotoxicity. Development of drugs targeted at specific oncogenes has revolutionized cancer care, but many patients suffer from drug-induced cardiovascular disease. Tyrosine kinase inhibitors (TKIs) are exemplars of promising anti-cancer drugs plagued by cardiotoxicity. Whether this reflects drug-mediated inhibition of the same signaling pathways as those involved in oncogenesis remains unclear. While it is suggested that oxidative stress, mitochondrial damage and pAMPK off-target inhibition could all contribute to cardiotoxicity, it is still unclear how these processes work together in a systematic way to regulate cellular function and eventually cardiac health. To tackle these questions, I utilize computational and experimental systems pharmacology methods to investigate the mechanisms of how TKIs perturb human stem cell derived cardiomyocytes at both molecular and phenotypic levels. I aim to identify molecular signatures that enable early detection of cardiac damage, to understand molecular mechanisms in order to intervene and mitigate cardiotoxicity, and to effectively distinguish safe and toxic drugs. I hypothesize that true molecular signatures are casually linked with a cellular phenotype associated with cardiotoxicity. To identify “driver” molecular signatures, I use statistical regression and machine learning methods, such as partial least square regression, elastic net and random forest, to regress cellular toxic phenotypes on gene expression changes. I have identified interesting gene signatures associated with cell cycle, metabolism and mitochondrial activity.
All these experience has equipped me with the knowledge and the skills to tackle more challenging questions in the area of cardiac tissue engineering and clinical cardiotoxicity.