Biotechnology

New cancer drivers and biomarkers identified by mapping hotspot mutations

This artistic representation illustrates the variety of mutational processes that generate cluster mutations in human cancer. Here are shown cyclones, which are molecular cyclones that cause mutations in circular extrachromosomal DNA (eDNA), and omicles, which is a molecular fog that causes mutations in linear chromosomal DNA. Author: Catherine Eng

Researchers led by bioengineers from the University of California, San Diego have identified and characterized a previously unrecognized key player in the evolution of cancer: clusters of mutations that occur in certain regions of the genome. The researchers found that these clusters of mutations contribute to the progression of about 10% of human cancers and can be used to predict patient survival.

The findings were published in an article published in the journal February 9, 2022 Nature.

The work sheds light on a class of mutations called cluster somatic mutations, meaning that they are grouped in specific areas of the cell genome, and somatic meaning that they are not inherited but caused by internal and external factors such as aging or exposure to UV radiation . , for example.

Cluster somatic mutations have so far been an understudied area in cancer development. But researchers in the laboratory of Lyudmila Alexandrova, a professor of bioengineering and cell and molecular medicine at the California College of San Diego, saw something very unusual in these mutations that required further study.

“We usually see somatic mutations that happen randomly in the genome. But if we looked closely at some of these mutations, we saw that they occurred in these hotspots. It’s like throwing swords on the floor, and then suddenly see them coming together in one space, ”Alyaksandrau said. “So we couldn’t help but wonder: what’s going on here? Why are there hotspots? Do they have clinical significance? Do they tell us anything about how cancer developed? ”

“Cluster mutations are largely ignored because they make up only a very small percentage of all mutations,” said Eric Bergstrom, a graduate student in bioengineering at Alexandrov’s lab and the first author of the study. “But as we delved deeper, we found that they play an important role in the etiology of human cancer.”

The team’s discoveries were allowed by creating the most complete and detailed map of known cluster somatic mutations. They began by mapping all mutations (group and unclustered) in the genomes of more than 2,500 cancer patients, an effort that encompassed a total of 30 different types of cancer. The researchers created their map using next-generation artificial intelligence approaches developed in Alexandrov’s laboratory. The team used these algorithms to detect cluster mutations in individual patients and elucidate the underlying mutation processes that cause such events. This led them to conclude that cluster somatic mutations contribute to cancer evolution in approximately 10% of human cancer cases.

Taking it a step further, the researchers also found that some of the cancer-causing clusters, especially those found in known cancer driver genes, could be used to predict overall patient survival. For example, the presence of cluster mutations in the BRAF gene – the most commonly observed driver gene in melanoma – leads to better overall survival of patients compared to individuals with non-cluster mutations. At the same time, the presence of cluster mutations in the EGFR gene – the most commonly observed driver gene in lung cancer – leads to reduced patient survival.

“Interestingly, we see differential survival in terms of only detecting cluster mutations in these genes, and this can be detected using existing platforms commonly used in the clinic. Thus, it acts as a very simple and accurate biomarker for patient survival, ”Bergstrom said.

“This elegant work underscores the importance of developing AI approaches to elucidate tumor biology, as well as to identify biomarkers and rapid development using standard live-to-clinic platforms,” said Scott Lipman, director of the Murcia Cancer Center and vice chancellor. for cancer research and treatment at UC San Diego. “This underscores the strength of UC San Diego in combining engineering approaches in artificial intelligence to address current challenges in cancer medicine.”

A new way of cancer evolution

In this study, the researchers also identified various factors that cause cluster somatic mutations. These factors include UV radiation, alcohol consumption, tobacco smoking and, above all, the activity of a set of antiviral enzymes called APOBEC3.

APOBEC3 enzymes are normally found inside cells as part of their internal immune response. Their main task – to grind any viruses that enter the cell. But in cancer cells, researchers believe the APOBEC3 enzymes may do more harm than good.

Researchers have found that cancer cells, which are often rich in round extrachromosomal rings[{” attribute=””>DNA (ecDNA) that harbor known cancer driver genes—have clusters of mutations occurring across individual ecDNA molecules. The researchers attribute these mutations to the activity of APOBEC3 enzymes. They hypothesize that APOBEC3 enzymes are mistaking the circular rings of ecDNA as foreign viruses and attempt to restrict and chop them up. In doing so, the APOBEC3 enzymes cause clusters of mutations to form within individual ecDNA molecules. This in turn plays a key role in accelerating cancer evolution and likely leads to drug resistance. The researchers named these rings of clustered mutations kyklonas, which is the Greek word for cyclones.

“This is a completely novel mode of oncogenesis,” said Alexandrov. Along with the team’s other findings, he explained, “this lays the foundation for new therapeutic approaches, where clinicians can consider restricting the activity of APOBEC3 enzymes and/or targeting extrachromosomal DNA for cancer treatment.”

Reference: “Mapping clustered mutations in cancer reveals APOBEC3 mutagenesis of ecDNA” by Erik N. Bergstrom, Jens Luebeck, Mia Petljak, Azhar Khandekar, Mark Barnes, Tongwu Zhang, Christopher D. Steele, Nischalan Pillay, Maria Teresa Landi, Vineet Bafna, Paul S. Mischel, Reuben S. Harris and Ludmil B. Alexandrov, 9 February 2022, Nature.
DOI: 10.1038/s41586-022-04398-6

This work was supported by a Cancer Grand Challenge award from Cancer Research UK as well as funding from the U.S. National Institutes of Health, Alfred P. Sloan Foundation, and Packard Foundation.



https://scitechdaily.com/new-cancer-drivers-and-biomarkers-revealed-by-mapping-mutation-hotspots/ New cancer drivers and biomarkers identified by mapping hotspot mutations

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