Pediatric low-grade glioma (pLGG) is the most common childhood brain tumor, but it doesn’t affect every child in the same way. Some tumors remain stable for years, while others grow, return, or don’t respond to treatment as expected. Even tumors that look alike or share the same DNA changes may behave differently.
A new five-year, approximately $3.4 million NIH Research Project Grant (R01) will help researchers study those differences using MRI scans, tumor samples, and medical and genetic information from the Children’s Brain Tumor Network (CBTN).
Led by a multi-principal investigator team of Yuanquan Song, PhD of the Children’s Hospital of Philadelphia (CHOP) and CBTN’s Adam Kraya, PhD, and Ali Nabavizadeh, MD, the team will look for differences inside tumors that may explain why some grow or return. Researchers will test possible treatment targets to find promising leads for future research.
Adam Kraya, PhD
Technical director of Clinical and Translational Data Science
CBTN
Why some tumors progress
The grant builds on earlier CBTN research that helped identify which pLGG tumors may be more likely to grow or return. The team can study detailed information from 1,248 tumor samples, including which genes are active. For 226 of those samples, researchers can also connect that information with MRI scans.
“Identifying risk was only one step,” said Adam Kraya, PhD, Technical Director of Clinical and Translational Data Science at CBTN and a principal investigator on the grant. “Now this grant allows us to move from risk characterization to actionability.”
In other words, the team can begin testing what researchers might be able to do about that risk.
Testing the strongest leads
First, the team will use computational analysis to compare MRI scans and tumor information across lower-, medium-, and higher-risk groups. Researchers will look for patterns connected to tumor growth or recurrence, including clues involving genes that scientists have not studied closely. They will also compare those findings with results from earlier drug testing. This process will help identify the genes and drugs most worth testing in the laboratory.
The Song Lab at CHOP will then test those genes in fruit flies. Flies and humans share many disease-related genes, and flies have a functional nervous system. Researchers can turn certain genes on or off and quickly see what happens to growth and movement, testing many possibilities within weeks.
The strongest candidates will then move into patient-derived pLGG organoids in the CBTN lab led by Mateusz Koptyra, PhD. These three-dimensional models grow from a patient’s tumor cells and keep important traits of the original tumor. Researchers can see how they respond to a genetic change or drug, whether the response lasts, and whether unexpected effects appear. A possible target must show promise in the data, flies, and organoids before moving forward.
The teams and tools behind the work
Three principal investigators lead the project, with expertise spanning the path from patient data to laboratory testing. Yuanquan Song, PhD, a researcher in CHOP’s Department of Pathology and Laboratory Medicine, leads studies of how genes affect tumor behavior. Kraya leads the work to bring different kinds of patient data together, while Ali Nabavizadeh, MD, an assistant professor of radiology at the University of Pennsylvania, leads the MRI analysis. Together, their teams will use patterns found in scans and tumor information to guide what gets tested in laboratory models.
CHOP serves as CBTN’s institutional home, while D3b provides the technology and expertise to organize and analyze the network’s data. CAVATICA offers a secure online workspace for data collected across institutions. PedcBioPortal turns complex cancer data into visual summaries that are easier to explore.
CBTN connects scans, medical information, detailed tumor data, biospecimens, including tumor tissue and other patient samples, and patient-derived models through one research network. The team can start with those established resources instead of spending years assembling them independently.
PNOC brings experience and a multi-institutional network for developing clinical trials in pediatric brain tumors. If the team identifies a promising treatment target, PNOC could help carry that work into a future study, connecting discoveries from this grant with opportunities to test new approaches for children with pLGG.
What the team hopes to deliver
Over five years, the researchers aim to create and test a guide that connects how pLGG tumors look on MRI scans with what is happening inside their cells. The guide could help researchers sort tumors by how likely they are to grow or return. The team also hopes to identify possible treatment targets for higher-risk tumors and test them in several laboratory models.
The project shows CBTN’s M3 Approach in practice: combining several kinds of patient information, studying different layers of each tumor, and bringing experts from different fields together. That shared foundation lets the team move from a pattern in the data to an idea it can test in the laboratory.
None of this would be possible without the children and families who contributed scans, tissue, clinical information, and tumor data to CBTN. A contribution made years ago can support questions that researchers had not yet thought to ask when it was collected.
“Every dataset, every tissue sample, and every image is a result of a family that chose to contribute at one of the most challenging moments of their lives and entrusted it to us,” Kraya said.
This grant shows what researchers can build from that trust. It also gives other investigators a clear example of how they can use CBTN resources, tools, and collaborators to study their own questions in pediatric brain tumor research.
