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Algorithm Identifies Noncoding Genetic Mutations That Play Role in 5 Pediatric Cancers


Using a computational algorithm, researchers at Children's Hospital of Philadelphia analyzed noncoding genetic mutations to discover how they factor into 5 pediatric cancers.

Noncoding mutations make up the majority of DNA, and scientists once thought of them as “junk DNA.” But with rapid advances in understanding more about the interactions of gene expression, researchers are learning that these noncoding mutations may act as switches or modifiers and have a bigger role than previously known.

Understanding how these noncoding mutations behave in cancer has been a particular challenge. But in a study published Friday, researchers said they created an algorithm that identified a spectrum of mutations in the noncoding portion of the human genome across 5 pediatric cancers: B cell acute lymphoblastic leukemia (B-ALL), acute myeloid leukemia (AML), neuroblastoma (NBL), Wilms tumor (WT), and osteosarcoma (OS).

The algorithm, called PANGEA (predictive analysis of noncoding genomic enhancer/promoter alterations) identified all types of mutations that are associated with gene expression changes, including single nucleotide variants (SNVs), small indels, copy number variations, and large structural variants.

Previous studies of noncoding mutations have focused on SNVs and small indels, noted the authors, writing in Science Advances.1 SNVs and small indels are insertions or deletions of bases in the genome that are short in length. SNVs, although noncoded, “may be may be responsible for much of the variation of phenotypes observed. Mutations in the noncoding part of pre-mRNAs often reveal new and meaningful insights into the regulation of cellular gene expression.”2

Structural variants, meanwhile, are much larger regions of DNA; they are more difficult to identify but likely factor into oncogenic roles, said the authors, “by redirecting enhancers/promoters to oncogenes or from tumor suppressor genes.”

Using PANGEA, the researchers found that the larger SVs are the most frequent cause of potentially cancer-causing mutations, identifying 1137 SVs that affect the expression of more than 2000 genes across the 5 cancers.

The study, conducted at Children's Hospital of Philadelphia (CHOP), analyzed these noncoding mutations and their impact on gene expression on samples from 501 children with whole-genome sequencing and RNA-sequencing data: 163 patients with B-ALL, 153 patients with AML, 100 patients with NBL, 53 patients with WT, and 32 patients with OS.

The authors said they “found that coding and noncoding mutations affect distinct sets of genes and pathways. This mutual exclusivity is likely due to the different genomic locations of these two classes of genes.”

Genes involved in metabolism are more frequently affected by noncoding mutations, but the extent of the impact of these noncoding mutations on metabolism rewiring in these 5 cancer types is unclear, the authors said. The results “highlight the need for comparative analysis of both coding and noncoding because novel cancer-related genes and pathways may be unveiled with comprehensive noncoding mutation analysis.”

"Identifying putative mutations is a starting point that will facilitate experimental work to validates these predictions," Kai Tan, PhD, professor of pediatrics at CHOP and senior author of the study, said in a statement.


1. He B, Gao P, Ding. YY, et al. "Diverse noncoding mutations contribute to deregulation of cis-regulatory landscape in pediatric cancers," Science Advances. Published online July 24, 2020. doi:10.1126/sciadv.aba3064

2. Wachs, AS, Bohne J. Two sides of the same medal: Noncoding mutations reveal new pathological mechanisms and insights into the regulation of gene expression. Wiley Interdiscip Rev RNA. Published online July 6. doi:10.1002/wrna.1616

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