Unexpected Double Mutations Detected in Tumor DNA

Cancer cells on dna stand background. 3d illustration
Credit: Mohammed Haneefa Nizamudeen/Getty Images

Researchers from KU Leuven in Belgium and The Francis Crick Institute in London have discovered that approximately one in five tumors have mutations in the same position on both strands of DNA, challenging the previously held assumption that every position in the genome is mutated no more than once.

Furthermore, certain sites in the genome are more sensitive to these biallelic mutations than others, report Jonas Demeulemeester, postdoctoral researcher at KU Leuven – University of Leuven, and colleagues in Nature Genetics.

Demeulemeester told Inside Precision Medicine that “commonly used models of molecular evolution assume the genome is sufficiently big such that the probability of mutating the same position twice is basically zero.”

“We rely on these models when analyzing various aspects of cancer genetics, from finding important cancer-driving mutations to reconstructing tumor evolution using DNA sequencing data.”

However, Demeulemeester noted that these models had not previously tested on cancer genome data.

To address this, he and his team developed a novel computational approach to screen 2,658 tumor samples representing 38 different tumor types from the Pan-Cancer Analysis of Whole Genomes Study.

They identified 18,295 biallelic mutations in 559 (21%) samples, including those from people with esophageal, stomach, colorectal, or skin cancers.

“That number is too large to be a coincidence,” said Demeulemeester.

In the case of skin cancer, the researchers found that specific short DNA sequences, highly sensitive to UV light, frequently gave rise to these biallelic mutations.

Demeulemeester pointed out that, in the past, biallelic mutations would have been considered artefacts, not worthy of further investigation.

Using the methods his team have developed, researchers “can now include those mutations and study their effects and importance in a persons’ tumor,” he said.

He added that his team will now “continue to develop innovative computational approaches to analyze cancer sequencing data and reveal novel insights into all aspects of tumor evolution and heterogeneity.”

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