Multi-Tensor Decompositions for Personalized Pediatric Glioma Diagnostics and Prognostics

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Sri Priya Ponnapalli.jfif

Sri Priya Ponnapalli

Palo Alto, CA



About this


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.

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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.

Specimen Data

The Children's Brain Tumor Network contributed to this project by providing access to the Pediatric Brain Tumor Atlas.

Explore the data in these informatics portals