Alex Xu, an assistant professor of bioengineering at the University of Maryland and former project scientist at Cedars-Sinai, spoke at a recent biomedical engineering seminar at Stony Brook University’s Javits Center. During his presentation, Xu discussed how his transition from engineering devices to studying cells through spatial biology has changed his approach to medicine.
Xu emphasized the importance of finding biomarkers—measurable biological features that can indicate a patient’s risk or potential outcome with treatment. “We’re asking, is there a single thing we can measure that tells us the most about what’s going on in a patient?” Xu explained.
Throughout his lecture, Xu used an analogy comparing human tissue complexity to a pineapple fruit cake, where various components coexist as spatial biology and their arrangement influences outcomes. He said, “Spatial biology is making a huge dent on the current state of tissue measurements. For the future, the excitement comes from getting a clearer picture of human biology than ever before, and it will be on us to develop new computational tools, new experimental models, and new engineered therapies that take full advantage of this knowledge.”
Spatial biology combines imaging and molecular mapping to determine cell locations and interactions within tissues. This approach aims to explain differences in how patients respond to treatments.
In one study on ovarian cancer—a disease often diagnosed late with complex tissue structure—Xu’s team analyzed tumor samples from 42 patients using imaging mass cytometry. This technique uses metal-tagged antibodies and vaporization to detect multiple proteins simultaneously. Initial results did not show correlations between cell counts and patient outcomes. However, when researchers quantified both cell types and their locations within tissues using mathematical spatial metrics, they found patterns linked to early relapse. The team also identified plasma cells as possible indicators for disease recurrence; these findings were published in Science Advances (2024).
Expanding on his analogy, Xu described the “gooey” part of fruitcake as representing molecular interactions between tumor and immune cells—interactions he believes are key to predicting cancer behavior.
In another study focused on Hodgkin lymphoma, Xu’s group mapped thousands of immune-cell interactions. They discovered that certain spatial arrangements—such as tumor cells surrounded by dense T-cell clusters—were associated with chemotherapy responses. These results appeared in JCO (2024) and Nature Biomedical Engineering (2025), suggesting that networks formed by cell-to-cell communication could be valuable biomarkers for predicting treatment success.
“It’s not only about the type of fruit or where it’s placed,” Xu said. “It’s about what happens in between, the communication that makes the whole thing hold together.”
To bring these methods into clinical practice, Xu's group applied machine learning to reduce their panel from 35 protein markers down to six markers detectable with standard hospital equipment.
The event drew students and faculty from across Stony Brook University. One student commented that spatial biology could help analyze cancer tissue for relapse likelihood or guide effective treatments.
Xu’s research reflects an emerging field blending precise measurement with practical application in medicine by translating spatial data into tools usable by doctors.