Our goal is to improve cancer patient outcomes by integrating artificial intelligence (AI), machine learning, computational methods, and experimental approaches. Our interdisciplinary research spans spatial biology, single-cell analysis, digital pathology, biomarker discovery, spatial microbiome analysis, and therapeutic development, including immunotherapy and cellular therapies.
We develop AI-driven 3D and 4D tumor models to investigate the complex interactions between cellular, molecular, and microbiome components. This approach enables the identification of novel biomarkers, therapeutic targets, and personalized treatment strategies. By integrating advanced technologies, the Hwang Lab advances personalized medicine, with a focus on the tumor immune microenvironment (TIME), ultimately benefiting cancer patients.
These are a few examples for our current projects:
AI-Driven 3D and 4D Molecular Tumor Modeling to Understand Pre-Cancer and Cancer Progression
This project aims to map the multidimensional evolution of tumors from pre-cancerous stages to full malignancy by integrating AI-driven 3D and 4D tumor models with subcellular-resolution imaging and molecular data. By focusing on spatial and temporal dynamics, we gain critical insights into how cancers develop and respond to treatments. This research is essential for identifying novel therapeutic strategies and improving patient outcomes by targeting early-stage disease progression.Subcellular-Resolution 4D Cell, Organoid, and Tissue Atlas Models for Cancer and Therapeutic Response
This project focuses on developing subcellular-resolution 3D and 4D models of cells, organoids, and tissues to study how individual cells and their suborganelles contribute to disease initiation, metastasis, and treatment response. By using live 3D and 4D holotomography combined with molecular data, we capture cellular dynamics in real-time. Our goal is to understand how cellular states, plasticity, migration, and interactions within 3D tissue structures influence carcinogenesis and therapeutic efficacy.Spatial Microbiome and Its Role in Tumor Progression, Immune Modulation, and Treatment Response
Using spatial sorting technology, we isolate individual microorganisms within the microbiome and their surrounding cellular and non-cellular components to study how they influence tumor progression, immune modulation, and treatment response. This approach also extends to studying the roles of fungi, viruses, and other pathogens in cancer. By mapping these complex interactions, we aim to uncover new therapeutic targets and understand how the microbiome contributes to cancer and therapy outcomes.Real-Time Drug Delivery and Response Monitoring Using Organotypic Models
We employ organotypic models to study the real-time dynamics of drug delivery and response, focusing on therapies like antibody-drug conjugates (ADCs), CAR-T cells, and mRNA therapeutics. By leveraging hybrid holotomography and light sheet microscopy, we trace drug penetration and interactions within the tumor immune microenvironment (TIME). This project aims to optimize drug delivery and therapeutic response at a precision scale, providing better patient outcomes.