The diagnosis, treatment, and ongoing assessment of pediatric gliomas requires researchers to have access to comprehensive information regarding the genome of such cancers. Researchers will apply recently developed algorithms, used by computers to analyze data, to information from the Pediatric Brain Tumor Atlas. Previous studies have been proven successful in the analysis of adult astrocytomas, identifying genetic signatures that predict patient survival and response to chemotherapy and radiation. Using data across various tumor types in conjunction with patient-data, researchers hope to create personalized, effective, and robust tests for diagnosis and ongoing assessment of treatments in pediatric brain cancers.
What are the goals of this project?
Researchers will apply newly developed algorithms to data from the Pediatric Brain Tumor Atlas in an effort to identify genetic signatures that could inform treatment.
What is the impact of this project?
Previous studies have shown that identifying genetic signatures in adult brain cancers can predict patient survival and response to treatment. This study aims to find genetic signatures in pediatric brain cancers that could lead to personalized therapies.
Why is the CBTN request important to this project?
The Pediatric Brain Tumor Atlas provides researchers with a robust dataset on pediatric brain cancers for analysis by their algorithms.
The Children's Brain Tumor Network contributed to this project by providing access to the Pediatric Brain Tumor Atlas.
Sri Priya Ponnapalli, PhD
I am a leader on a global business, Amazon Machine Learning (ML) Solutions Lab, whose mission is to work with companies and organizations from all industries to solve their business needs using machine learning. I have delivered high-impact ML products and solutions in finance (e.g., Bloomberg, JP
High-grade Gliomas (HGG) or astrocytomas in children nearly always result in a dismal prognosis. Although novel therapeutic approaches are currently in development, preclinical testing has been limited, due to a lack of pediatric-specific HGG preclinical models. These models are needed to help test
Low-Grade Gliomas also called astrocytomas are the most common cancer of the central nervous system in children. They represent a heterogeneous group of tumors that can be discovered anywhere within the brain or spinal cord. Although surgical resection may be curative, up to 20% of children still su