Early analyses by our group and others have suggested that semi-quantitative radiographic (radiomic) features prior to and following therapy may aid disease classification at diagnosis, prognostication, and improve our ability to distinguish between challenging imaging phenotypes following therapy (i.e. pseudoprogression and progression). Recent advances in analyses of ctDNA from biofluids such as CSF and plasma have potential to improve our understanding of tumor natural history and the evolution of tumor subpopulations during therapy. These changes in ctDNA also appear to have a strong relationship to imaging changes during therapy. Corresponding advances in medical imaging analytics have facilitated the identification of molecularly homogeneous patient subgroups and tumor subregions/habitats which may closely correlate with sub clonal evolution during and following combined modality therapy. These advanced analytical approaches have moved beyond their infancy and are now ready to be applied to large scale imaging datasets from clinical trials. As a result, we propose two primary goals in the following investigation, the first of which is to explore the inter-relationship between pre-treatment imaging features and tumor genomics.
What are the goals of this project?
The goals of this project are to define the relationship between quantitative and qualitative imaging features and molecularly defined subtypes of pediatric brainstem glioma and to evaluate the relationship between longitudinal changes in tumor and tumor habitat/subregion volumetric changes over time and patient-derived liquid biopsy specimens
What is the impact of this project?
It is anticipated that exploring the inter-relation between tumor imaging and genomics will facilitate improved patient classification and prognostication. The second goal is to develop a deeper understanding of the connection between the evolution of imaging defined tumor subregions/habitats and changes in biofluid derived circulating tumor DNA markers. We predict that certain tumor imaging defined habitats will have a stronger relationship to ctDNA markers of disease and that this will improve patient endpoint assessment and selection of subsequent therapies.
The Children's Brain Tumor Network contributed to this project by providing clinical, genomic and imaging data.
PI: John Lucas, St. Jude Children's Hospital
Christopher Tinkle, St. Jude Children's Hospital
Chi-Yang Hsu, St. Jude Children's Hospital
Zoltan Patay, St. Jude Children's Hospital
Gang Wu, Bioinformatician, St. Jude Children's Hospital
Adam Resnick, PhD
Adam Resnick is the Director of Data Driven Discovery in Biomedicine (D3b) at Children’s Hospital of Philadelphia (CHOP) responsible for leading a multidisciplinary team to build and support a scalable, patient-focused healthcare and educational discovery ecosystem on behalf of all children. He i
Children’s Hospital of Philadelphia
Sabine Mueller, MD, PhD
Dr. Sabine Mueller is a pediatric neuro-oncologist who specializes in caring for children with brain tumors and related genetic syndromes. Before completing medical school, she worked as a scientist, director of genomics and project leader for a brain tumor program at AGY Therapeutics, a biotechn
UCSF Benioff Children's Hospital
Brainstem glioma- Diffuse intrinsic pontine glioma
A presumptive diagnosis of DIPG based on classic imaging features, in the absence of a histologic diagnosis, has been routinely employed. Increasingly however, histologic confirmation is obtained for both entry into research studies and molecular characterization of the tumor.[