Childhood Cancer

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Single Cell RNA Sequencing of Pediatric High- and Low-Grade Gliomas

University of Colorado Denver
Adam Green, MD and Jean Mulcahy Levy, MD
Grant Type: 
Single-cell Pediatric Cancer Atlas Grant
Year Awarded: 
Type of Childhood Cancer: 
Brain Tumors, Astrocytoma, Diffuse Intrinsic Pontine Glioma (DIPG), Ganglioglioma, Glioblastoma Multiforme (GBM), Glioma
Project Description: 

Lay Summary: Low-grade gliomas (LGG) are the most common brain tumors diagnosed in children, and high-grade gliomas (HGG) are the most common cause of death. While many children can be treated with surgery alone for LGG, a large number of patients are unable to undergo surgery due to the location of the tumor, while others carry higher risk factors due to underlying mutations in the tumor. While low-grade gliomas are often characterized as "benign" tumors, for patients with aggressive tumor markers or a tumor located in critical brain structures, there is significant morbidity and mortality associated with their tumor. A better understanding of these tumors is necessary to identify new treatment methods and ways to identify patients who need an aggressive approach versus patients who may show a more indolent course. For high-grade gliomas, the only proven therapy is radiation, which is not curative, and these patients suffer nearly 100% mortality; improved treatments are desperately needed. We believe a deeper understanding of these tumors through single-cell RNA-Seq will help provide this knowledge leading to new treatment options.

Lay Summary Project Goal: We will use our well-established pediatric brain tumor bank, for which we have been collecting patient samples for single-cell RNA-seq for 10 years, to characterize a variety of pediatric high- and low-grade glioma tumors by RNA-Seq. We have complete patient information on these tumors that we can compare to the biological data we find through RNA-Seq. We aim to better understand the different types of cells that make up these tumors and subtypes of tumors so we can understand why certain features lead to worse outcomes for patients, and how we can better kill the cells most crucial to tumor growth.