Researchers at The University of Texas MD Anderson Cancer Center have developed a spatial atlas of specialized immune structures known as tertiary lymphoid structures (TLSs), across multiple cancer types, revealing how key features vary across tumor types and influence patient outcomes. Led by Linghua Wang, MD, PhD, professor of genomic medicine, executive director and head of the Center for Cellular Language Intelligence, associate member of the James P. Allison Institute, and focus area co-lead with the Institute for Data Science in Oncology at UT MD Anderson, the team developed scalable artificial intelligence (AI) frameworks to detect, profile and classify TLSs from spatial omics data and routine pathology slides. Tumors can contain TLSs with very different levels of organization, cellular composition and spatial relationships within tumor cells and the researchers’ newly reported study showed that these differences carry important biological and clinical information. The team suggests that their first-of-its-kind atlas indicates that TLS maturation state, spatial location, and composition within tumors may provide clinically meaningful information about cancer prognosis and treatment response. They also created a composite scoring system to more effectively stratify patients by prognosis and treatment response across different cancer types and treatment contexts. “Prior to this study, most of the focus on TLSs as biomarkers was simply on whether or not they were present and, in some cases, whether they were mature,” Wang said. “Here, we show that we can go much deeper. TLSs in tumor tissues are much more complex than that. Their maturation state, spatial location and composition…
