Alex Xu, assistant professor of bioengineering at the University of Maryland and former project scientist at Cedars-Sinai, spoke about advances in spatial biology during a recent seminar at Stony Brook University’s Javits Center. Xu discussed how his research is shifting the approach to predicting cancer outcomes by examining not just which cells are present in tumors, but also their arrangement and interactions.
“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 compared the complexity of human tissue to a pineapple fruit cake, with different cell types and their spatial relationships contributing to overall function. He emphasized that understanding these arrangements—what he called “spatial biology”—could improve predictions for patient risk and treatment responses.
“Spatial biology is making a huge dent on the current state of tissue measurements,” said Xu. “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.”
Xu described his team’s study of ovarian cancer using imaging mass cytometry—a method that allows researchers to map dozens of proteins within tumor samples from 42 patients. While initial efforts to link cell counts with patient outcomes were unsuccessful, further analysis focusing on cell locations revealed patterns related to early relapse. The group developed mathematical metrics describing how immune cells and other components clustered within tumors; these findings were later published in Science Advances (2024). Plasma cells emerged as possible indicators for disease recurrence.
In another set of studies involving Hodgkin lymphoma, Xu’s team mapped thousands of immune-cell interactions. They found that certain arrangements—such as tumor cells surrounded by dense T-cell clusters—were associated with better responses to chemotherapy. These results appeared in JCO (2024) and Nature Biomedical Engineering (2025), highlighting how networks of cellular communication could act as biomarkers for treatment outcomes.
“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 insights closer to clinical use, Xu’s group used machine learning to narrow down from 35 protein markers to a six-marker panel suitable for standard hospital testing equipment.
The seminar drew students and faculty from across Stony Brook University. One biomedical engineering student noted spatial biology’s potential for assessing cancer relapse risk and tailoring treatments based on tissue analysis.
Xu’s research aims to integrate advanced measurement techniques into practical tools for doctors by combining detailed spatial data with accessible technology.
