Research

Meningiomas are the most common primary brain tumor, and most are slow-growing and curable with surgery. But the standard grading system, based on how a tumor looks under the microscope, doesn't always predict how an individual tumor will behave. We are working to build a more precise molecular fingerprint for each meningioma, so that a patient's risk is defined by their tumor's biology, not just its appearance.

In a study of more than 1,000 meningiomas published in Nature Communications, Ruchit Patel and colleagues mapped how tumors gain or lose pieces of chromosomes, and showed that small differences in how these changes are measured can shift a tumor between a low- and high-risk category for as many as 1 in 5 patients. This work is helping refine the thresholds pathologists use to grade tumors.

We also asked whether Ki-67, the standard marker doctors use to gauge how fast a tumor is growing, was measuring what everyone assumed. Using single-cell technology across more than 120,000 individual cells, Xiaopeng Guo and colleagues found that Ki-67 is produced not only by tumor cells but also by immune cells within the tumor, especially in lower-grade disease, and that this balance shifts with tumor grade, prior radiation, and patient age. That means the same Ki-67 result can mean different things from one tumor to the next.

Most recently, work led with Zach Moynihan showed that a meningioma's immune environment is not fixed: it evolves as the tumor's biology changes, including after treatment. Andrew Dunbar, a medical student in the lab, is now helping extend this work, combining genomic and immune fingerprinting to understand how treatment can reshape a tumor's biology, with the goal of identifying which tumors are truly high-risk and which patients might safely need less treatment.

Most pituitary tumors are benign, but a subset behave aggressively and resist standard treatment. Over the past decade, the lab has mapped the genomic drivers of these tumors, from early work identifying recurrent oncogenic mutations and copy-number changes in pituitary adenomas, to more recent profiling of how immune cells interact with pituitary tumor cells and express immune checkpoint molecules.

Building on that foundation, the team is now characterizing the pituitary tumor microenvironment in greater detail: the non-tumor cells, blood vessels, and signaling molecules that surround and interact with tumor cells, to understand what allows some pituitary tumors to grow aggressively or resist treatment, and to identify new therapeutic targets. This work is ongoing and not yet published.

Epidermoid cysts are rare, slow-growing tumors thought to arise from skin cells trapped during early development. Most are benign, but in very rare cases they can become locally aggressive or transform into cancer, and almost nothing is known about what drives that process.

Gabrielle Luiselli and Ellie Shahbo are developing an animal model of epidermoid cyst formation alongside molecular profiling of patient tumor samples, aiming to identify the genetic changes that drive cyst growth and, in rare cases, malignant transformation. This work is currently being prepared for publication.