PROJECT SUMMARY
Brain tumors are the most common form of cancer in children between 0-19 years of age in the United States,
and are the largest cause of cancer-related deaths. Our long term goal is to improve the outcomes of children
diagnosed with brain tumors by characterizing the germline and somatic events driving tumorigenesis so that
rational, evidence-based therapies can be developed. Our objective here is to perform an integrative germline-
tumor analysis of the Gabriela Miller Kids First (GMKF) X01 CA267587 pediatric brain tumor cohort to identify
both inherited and de novo pathogenic or likely pathogenic (P-LP) genetic variants that may be exploitable for
subtyping, risk prediction, and/or therapeutic intervention. Data from the GMKF cohort will be combined with
extant sequencing data from the Pediatric Brain Tumor Atlas (PBTA) to yield 3,849 germline DNA and 4,438
tumor DNA/RNA sequences. The combined cohort spans seventeen broad histologies and includes robustly-
annotated patient-parent triads/dyads (n=771). Our central hypothesis is that both inherited and de novo P-LP
germline variants influence the initiation and progression of pediatric brain tumors. Here, we will test our
hypothesis and accomplish our objective in two specific aims: Aim 1) Identify and assess heritability of rare
P-LP variants in pediatric brain tumor triads and dyads. Rare single nucleotide variants (SNVs) and insertion-
deletions (INDELS) will be investigated through a well-developed computational pipeline. Pathogenicity will be
assessed using our American College of Medical Genetics (ACMG)-guided approach. Triad/dyads will be studied
to assess whether variants are inherited or acquired de novo. Rare variant burden testing will be performed
through comparison to multiple cancer-free cohorts. Clinical and tumor-biological correlative studies and survival
analyses will be undertaken. Aim 2) Perform integrative tumor-normal analyses to elucidate functional
relevance of germline P-LP variants. Somatic second hits at the gene and pathway level will be assessed for
the entire cohort (N=2,558). Next, using pediatric high-grade glioma (pHGG) as a model, an expanded integrative
in silico evaluation of recurrent or aggregate germline events using matched tumor DNA and RNA sequencing
will be performed (N=367 pHGGs). Germline copy number variants (CNVs) will be identified and heritability
assessed. Tumor sequencing data will be processed through OpenPBTA somatic workflows designed to
evaluate SNV, INDELS, structural variants (SVs), and mutational signatures in DNA and account for expression
profiles, isoforms, fusions and other novel transcripts in RNA. Through integration of the X01 CA267587 pediatric
brain tumor cohort with extant childhood cancer and structural birth defect data, we expect to advance our
understanding of the genetic basis of a diverse array of pediatric brain tumors, with insights here being applicable
to the genetic basis of other childhood conditions. Moreover, we will address, for the first time, whether pediatric
brain tumor genetic risk factors are inherited or acquired de novo. Completion of this project will have a sustained
and positive impact on the field by identifying clinically actionable genetic alterations in these important cancers.