The Children's Tumor Foundation
03/11/2026 | Press release | Distributed by Public on 03/11/2026 08:31
Data to Discovery: Tracking Metabolic Changes in NF1 Tumors
The Children's Tumor Foundation's NF Data Utilization (NDU) Awards support researchers in unlocking new discoveries by analyzing existing data within the NF Data Portal using a visualization platform called Pluto. By re-examining shared datasets to identify disease pathways, therapeutic targets, and biomarkers-and then validating those findings through new experiments-this program turns curated NF research data into a powerful engine for accelerating progress toward treatments for all forms of neurofibromatosis and schwannomatosis.
A man with short curly hair and a beard, wearing a light blue button-up shirt, smiles at the camera with a blurred indoor background.One of this year's awardees is Kimani Njoya, PhD candidate at the Medical College of Wisconsin, who is studying how metabolic changes may signal when NF1 tumors become more dangerous.
Using data from the NF Data Portal and integrating gene expression analysis with detailed lipid profiling, Kimani aims to identify metabolic "fingerprints" linked to tumor progression. His goal: uncover new therapeutic targets and move closer to earlier detection and more personalized treatment for people with NF1.
What drew you to focus your work on NF and what motivated you to apply for this award?
I have always loved science and math, which naturally led me into research. At the same time, I knew that whatever career path I chose, I wanted my work to ultimately help people. NF research offered a way to bring those goals together: pursuing research I enjoy, particularly data analysis, while contributing to improved health outcomes for people with NF. Because NF1 is a rare disease, there are still significant gaps in our understanding of tumor biology and disease progression. Recognizing this unmet need further motivated me to focus on this area.
When I learned about the NF Data Utilization Award, I was already mining existing datasets to better understand the progression of NF1-associated tumors. The award presented an ideal opportunity to continue and expand this work. Importantly, the funding would enable me to pursue research questions that otherwise wouldn't have been feasible.
Congratulations on receiving the NF Data Utilization Award! What does this funding mean for your research and your team?
Receiving the award is incredibly meaningful because it enables me to pursue research questions that are innovative in the NF field and relevant to understanding NF1 tumor biology. This award provides the opportunity to explore ideas that might not be addressed through existing projects, allowing our team to expand the scope of our research in a meaningful way. By mining shared data to generate hypotheses and then testing those hypotheses in the lab, this award will allow us to move efficiently from data-driven discovery to clinically relevant biological insights. In addition to advancing this specific project, the award enhances our lab's ability to fully leverage shared data resources, contribute new findings back to the research community, and help drive progress toward improved outcomes for individuals affected by NF.
Your project studies how NF1 tumors use and store fats (lipids). Can you explain why this is important and what it could reveal about tumor growth?
Tumors are generally more metabolically active than normal cells, which typically divide only when necessary and maintain a stable "maintenance-based" metabolism. In contrast, tumor cells divide uncontrollably, particularly in malignant tumors such as MPNSTs, and this rapid growth requires a large amount of energy and raw materials for building and maintaining cellular structures.
Lipids are especially important because they serve as both a rich source of energy and essential building blocks for cellular structures like cell membranes. By understanding how NF1 tumors acquire, use, and store lipids, we can gain insight into the metabolic requirements that support tumor growth. This knowledge may reveal metabolic vulnerabilities that could be targeted therapeutically.
You're combining NF Data Portal datasets with lab studies from patient samples. How does access to the Portal help you make new discoveries?
The NF Data Portal transforms scientific data from a one-time use resource into a reusable asset for the research community. This not only accelerates discoveries but also maximizes the value of data generated from patient samples, saving both time and resources. Insights gained from NF Data Portal datasets directly inform our lab studies using patient-derived samples. By starting with large-scale datasets, we can generate data-driven hypotheses that are then tested and refined through targeted experiments in the lab. Through the NF Data Portal, I can access data from multiple studies and integrate them into a single dataset that increases statistical power, allowing identification of subtle patterns that would be difficult or impossible to detect in smaller studies. Additionally, the Portal is uniquely valuable because it is organized specifically for the NF research community and includes standardized NF-OSI data processing pipelines, making data easier to find and analyze. Together, these features enable more efficient, reproducible research and help translate shared data into meaningful biological insights.
One goal of your work is to find "fingerprints" that could indicate which tumors might become dangerous. What does a "fingerprint" mean in this context, and how could this help patients and families in real life?
As tumors progress, their metabolic demands evolve to meet the needs of continued tumor growth and survival. Tumors use many different types of lipids, and the specific lipids they rely on can change over time. The abundance of these lipids, what we refer to as a lipid "fingerprint", can reflect the biological characteristics of a tumor.
Through lipidomic profiling, we can comprehensively map how lipid composition changes as tumors progress and use this information to define characteristic fingerprints. These fingerprints could serve as an additional tool for more accurate prognosis and for monitoring of tumor progression, potentially allowing clinicians to intervene earlier. In the longer term, the lipid fingerprints could also help guide personalized treatment strategies, moving toward more precise and effective therapies for patients.
NF Data Utilization Awards are designed to turn shared data into shared progress. How is that reflected in your work through this award?
Shared data is central to my research approach. By building on datasets that have been generated and shared by the NF research community, this work maximizes the impact of existing data while avoiding unnecessary duplication of effort. The insights gained from these analyses are then validated through new experiments, creating knowledge that can be shared back with the community.
Through this award, shared data becomes a starting point for new discoveries that extend beyond a single study or lab. The data and findings generated from this work will contribute to a growing, collective understanding of NF tumor biology and will hopefully be used by other researchers to ask new questions, refine hypotheses, and accelerate progress towards better outcomes for patients and families affected by NF.
Learn more about the NF Data Portal here.
Learn more about Pluto Bio here.
Learn more about funding opportunities from the Children's Tumor Foundation here.
The Children's Tumor Foundation published this content on March 11, 2026, and is solely responsible for the information contained herein. Distributed via Public Technologies (PUBT), unedited and unaltered, on March 11, 2026 at 14:32 UTC. If you believe the information included in the content is inaccurate or outdated and requires editing or removal, please contact us at [email protected]