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Park Laboratory

The overarching goal of our research program is to understand the mechanisms of tissue regeneration and tumorigenesis by employing genetically engineered mice and organoids, with a specific interest in WNT signaling. Our recent investigations have aimed to address two critical questions: Is tumor cell plasticity a therapeutic vulnerability of cancer? Can manipulating cell plasticity promote tissue regeneration, or even prevent tissue damage?

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WNT Signaling

WNT signaling is crucial for development, tissue homeostasis, and tissue regeneration. However, the deregulation of WNT signaling leads to human diseases, including cancer. We study how WNT signaling contributes to various pathophysiological processes. 

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Cell Plasticity and Cancer

Tumor cell plasticity contributes to tumor progression, therapy resistance, relapse, and metastasis. We study the mechanisms of cell plasticity and apply such knowledge to lay a foundation for developing cancer therapies.   Images: Dynamo (artificial intelligence)-based inference of cell lineage trajectories showing the impact of gene knock-out on cell plasticity (by Shengzhe Zhang)

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Genetically Engineered Organoids and Disease Modeling

3D cultured organoids mimic the pathophysiology of human diseases. We genetically manipulate organoids to model human diseases and dissect the mechanisms of disease development.   Images: Genetically engineered gastric organoids (by Gengyi Zou)

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Tissue Regeneration

Fine control of cell dynamics orchestrates tissue homeostasis and regeneration. Using organoids and animal models, we study how cell plasticity contributes to tissue regeneration. Image: Single-cell RNA-sequencing-based cell lineage trajectory analysis of regenerating lung tissues (by Bongjun Kim)

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Endoderm-Derived Cancers

We study the tumorigenic mechanisms of endoderm-derived cancers (intestine, stomach, esophagus, and lung). Esophageal squamous cell cancer is detected at a later stage, limiting treatment options. Using genetically engineered esophageal organoids and single-cell transcriptomics of patient samples, we classify patients into specific treatment responders vs. non-responders.   Image: Single-cell RNA-seq-based analysis of 69 ESCC patient samples and genetically engineered esophageal organoids; integration (right) and unsupervised stratification of patients (left) (by Kyung-Pil Ko)

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