Comparison of fusion calling platforms in pediatric DIPG and high‐grade glioma

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DIPGs are especially lethal and confer a despairingly short 11-month median survival due to their aggressive phenotype and lack of therapeutic options. Molecular characterization of pediatric brain tumors is stimulating the development and testing of targeted therapies for precision medicine. However, effective targeted options are still unavailable for DIPG.

In our initial cohort of sequencing high-risk brain tumors, we found that over 20% of pHGG harbor fusions, a rate higher than larger datasets published by other groups. As seen in other solid tumors and human cancers, in-frame fusions involving established tumor drivers are frequently pivotal clonal events that are essential to tumor survival and growth. Our collaborative team (Cieslik lab) includes a bioinformatics group that specializes in the optimization of RNA-seq analysis and fusion calling. The CODAC pipeline has transformed the fusion landscape and therapeutic options for adult solid tumors using a novel in house pipeline that had proven effective for advancing oncogenic fusion calling beyond other established tools in use. In this proposal, we will compare CODAC to multiple other fusion-calling tools on two independent datasets of DIPG RNA-seq data, and then perform validation of targeting of CODAC-called fusions in human and mice models

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What are the goals of this project?

The goals of this project are to determine the transformability of unique CODAC-called fusions in DIPG model and to determine the targetability of unique CODAC-called fusions in DIPG models

What is the impact of this project?

Children with DIPG are in great need of harnessing the successes seen in precision medicine in other solid tumors. This proposal will lead to clarification of key computational features to be employed in performing RNA-seq on DIPG tissue. We are optimistic this will lead to an optimized platform for the identification of novel targets for this deadly disease

Why the CBTN request is important to this project?

The CBTN has aggregated RNA-seq data from approximately 100 DIPG samples which it will share along with de-identified clinical data with our investigative team. We will perform fusion calling and comparison on the CBTN data using multiple fusion pipelines

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