Spatial omic imaging and machine learning are rapidly transforming the nature of biology research, providing new avenues for discovery at the nexus of AI and mechanistic interpretation. The Chuang lab uses computational, mathematical, and high-throughput data generation approaches to study how cancer ecosystems function, evolve, and respond to therapeutic treatment. In particular, we specialize in the analysis of cancer multi-omic images to discover treatment-targetable processes in the tumor microenvironment. These projects span multiple cancer types including breast cancer, colorectal cancer, melanoma, and lung cancer. We collaborate closely with experimental and computational colleagues at JAX Genomic Medicine, JAX Mammalian Genetics, and other scientists around the world.
For the most up-to-date information on our work, see the Publications page.
Cancer Ecosystems
We study the evolutionary dynamics and mechanistic interactions among cells within tumors that can be deciphered from imaging and omics data. For example, the way cells interact plays a critical role in whether tumors grow or respond to treatment—but these interactions are notoriously hard to detect. Our lab recently developed a method that identifies where cells are interacting by analyzing how proteins accumulate at points of contact (Wang et al 2024). Using this approach, we discovered that interactions between two types of immune cells—T cells and B cells—within tumors are linked to better patient survival. This finding opens a promising new strategy for identifying patients who may respond well to treatment and potentially improving outcomes by targeting these immune cell interactions. We identify and study cellular behaviors using techniques such as 3D confocal microscopy (Mukashyaka, Kumar, et al 2023), subcellular protein imaging, and single cell spatial profiling.
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Patient-Derived Xenografts
The Chuang lab is a leader in the field of patient-derived xenografts (PDXs), a model system in which human tumors are engrafted and studied in NSG mice. Xenografts play a critical role in cancer research, as they are used in therapeutic testing to verify drug activity before embarking on a clinical trial. Since 2017, Dr. Chuang has led the Data Coordination Center for the PDX Network, a multi-institute consortium supported by the US National Cancer Institute. We are partnering with institutes including the Huntsman Cancer Institute, Baylor College of Medicine, MD Anderson, Washington University, the Wistar Institute, the University of Pennsylvania, Dana Farber Cancer Institute, Virginia Commonwealth University, the University of California-Davis, and Frederick National Laboratory, to study cancer using xenografts. Our work has produced pioneering studies on the genetic (Woo, Giordano et al 2021) and therapeutic (Evard et al 2020) robustness of xenografts for preclinical testing. Our lab also contributes to the PIVOT Consortium, an NCI project to test the efficacy of drugs for pediatric cancers using xenografts. Within these xenograft projects, our lab is especially focused on the dynamic response of cancers to treatment (Rubinstein, Domanskyii et al, 2025), as xenografts make it possible to reproducibly interrogate this process at critical moments including pre-treatment, early treatment, minimal residual disease, and the onset of resistance.