# Germline Structural Variant Identification and Functional Determination in Childhood Cancer

> **NIH NIH F31** · BAYLOR COLLEGE OF MEDICINE · 2022 · $44,347

## Abstract

Abstract
A few germline pathogenic structural variants (SV) have been identified in cancer predisposition syndromes,
e.g., MSH2 inversion in Lynch syndrome. The advent of short-read whole-genome sequencing (WGS) has
facilitated the detection of SVs. However, a pitfall of this sequencing methodology is the inability to capture all
SVs, given the reads do not map well to low complexity regions, and current algorithms used to identify SVs from
short-read data have very low sensitivity and very high false-positive rates. One of the objectives of this fellowship
is to optimize and implement an SV calling pipeline that utilizes multiple algorithms to increase the sensitivity
and specificity of variant identification from germline short-read WGS trios. This pipeline is currently being
developed and tested on pediatric cancer patients enrolled in the NIH-funded Baylor Advancing Sequencing into
Childhood Cancer Care (BASIC3) exome study, which consists of ethnically and racially diverse pediatric
patients with solid (CNS and non-CNS) tumors. This BASIC3 subset includes 63 proband/parent trios who have
subsequently undergone germline short-read WGS. Five SV callers are run and then filtered using either a
percent reciprocal overlap filter or a proposed Artificial Intelligence-based proximity graph filter to identify de
novo and inherited SVs. This cohort has recently been selected for a long-read sequencing pilot, data which
serves as the gold standard for SV detection. Comparison of short-read WGS generated SV calls with the long-
read data will help determine the sensitivity and specificity of variant calls and further improve the short read
pipeline (Aim 1A). Once optimized this short-read WGS SV pipeline will be applied to the Kids First Genetics of
Embryonal and Alveolar Rhabdomyosarcoma cohort (n=900), as an independent assessment of the method and
also to identify recurrent germline SVs in this cancer which has not yet been well characterized (Aim 1B). The
second training and scientific objective is to explore the functional effect of a novel de novo SV identified through
the initial analysis. A de novo germline duplication of the Prostaglandin Reductase 2 (PTGR2) enhancer and
promoter region was found in a pediatric Posterior Fossa subtype A (PF–A) ependymoma patient. Transcriptome
data from the patient’s tumor revealed increased PTGR2 expression. The PTGR2 protein converts 15-keto-
prostaglandin E2 to 15-keto-13,14-dihydro-PGE2. Studies in adult malignancies suggest that increased 15-keto-
13,14-dihydro-PGE2 is associated with cancer risk potentially through the STAT3 signaling pathway. Increased
STAT3 signaling is reported as a distinct feature of PF-A ependymoma. The identified partial duplication of
PTGR2 will be engineered into ependymoma progenitor cells, to functionally assess the effects on STAT3
signaling, cell proliferation, and DNA synthesis. In parallel, further analysis of PTGR2 expression and structural
variants will be analyzed in pe...

## Key facts

- **NIH application ID:** 10438577
- **Project number:** 5F31CA265163-02
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Owen R Hirschi
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $44,347
- **Award type:** 5
- **Project period:** 2021-07-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10438577

## Citation

> US National Institutes of Health, RePORTER application 10438577, Germline Structural Variant Identification and Functional Determination in Childhood Cancer (5F31CA265163-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10438577. Licensed CC0.

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