Meningioma is the most common brain tumor in adults.

One of the most detailed maps to date of meningioma - the most common brain tumor in adults - reveals how the tumor's surrounding environment helps drive disease behavior and patient outcomes, according to new research from Mayo Clinic. The study, published in Nature Genetics and conducted in collaboration with scientists at Princess Margaret Cancer Centre in Toronto, combines several advanced laboratory techniques to examine tumors at an unprecedented level of detail, offering clues to why some meningiomas grow slowly while others recur or become more aggressive. The findings could lead to more precise ways to predict risk and guide treatment decisions. Growing evidence suggests that traditional grading systems for meningioma do not fully capture the behavior of these complex tumors, prompting the development of molecular classification tools that more accurately predict which tumors are more likely to recur after surgery. These new findings build on recent developments by investigating the signal from individual cells rather than whole tumors, demonstrating that the tumor microenvironment - the mix of immune and support cells surrounding the tumor - plays a critical role in shaping outcomes. We're seeing that it's not just the tumor cells themselves but the ecosystem around them that influences how these tumors grow and respond to treatment." Gelareh Zadeh, M.D., Ph.D., Mayo Clinic neurosurgeon and senior author of the study Understanding tumor behavior An estimated 30,000 to 40,000 people in the U.S. are diagnosed with meningioma each year. While many tumors are benign, others can recur or become life-threatening, and predicting that risk has remained a major challenge. In this study, researchers analyzed hundreds of tumor samples using techniques that allow them to study individual cells rather than averaging signals across the entire tumor. Using single-cell sequencing and spatial transcriptomics, the team mapped more than 500,000 individual cells and millions of data points across tumors. This created a high-resolution "atlas" of the genetic footprint of individual cells and how they differ between aggressive and benign tumors, how they change and evolve over space, and how they interact with other cells in their environment. "Instead of looking at the tumor as a whole, we can now break it down into its individual components and understand what is driving its behavior," says Dr. Zadeh. The researchers identified multiple distinct states of immune cells, particularly myeloid cells, that behave differently depending on the tumor. Some of these cell states were linked to more aggressive disease, while others were associated with better outcomes. Implications for patient care The findings build on earlier work from Mayo Clinic researchers outlining a new era of personalized care for meningioma, where molecular and cellular insights guide clinical decision-making. This latest study adds a critical layer by showing how the tumor microenvironment contributes to that personalization. Researchers found that certain immune cell programs were strongly linked to how quickly tumors returned after treatment. In some cases, these signals were able to add value to tumor grade and even modern molecular classification systems in their ability to predict patient outcomes, suggesting they could help refine decisions about surgery, radiation or closer follow-up in the future. The study also showed that these biological signatures may be detectable through noninvasive approaches, such as blood-based biomarkers, raising the possibility of monitoring patients over time without repeated surgery. "This moves us closer to a future where we can better stratify patients - identifying who needs more aggressive therapy and who may avoid overtreatment," says Dr. Zadeh. Beyond improving prognostic tools, the research highlights potential therapeutic targets. By identifying how immune cells and tumor cells communicate, the study points to pathways that could be disrupted to slow tumor growth or enhance treatment response. Next steps include validating the findings in larger, multicenter cohorts and translating these biological insights into clinical tools and prospective trials.

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