The system rapidly scans the genome of cancer cells and could help scientists find targets for new drugs. Cancer cells can have thousands of DNA mutations. However, only a small number of those actually drive the progression of cancer; the rest are just along for the ride. Researchers could id
An MIT-led team has built a new system that rapidly scans the genome of cancer cells and could help researchers find targets for new drugs. Credit: Dylan Burnette and Jennifer Lippincott-Schwartz, National Institutes of Health, edited by MIT News
“We created a probabilistic, deep-learning method that allowed us to get a really accurate model of the number of passenger mutations that should exist anywhere in the genome,” says Maxwell Sherman, an MIT graduate student. “Then we can look all across the genome for regions where you have an unexpected accumulation of mutations, which suggests that those are driver mutations.”
While those targets have proven useful, protein-coding genes make up only about 2% of the genome. The other 98% also contains mutations that can occur in cancer cells, but it has been much more difficult to figure out if any of those mutations contribute to cancer development. The data used to train the models came from the Roadmap Epigenomics Project and an international collection of data called the Pan-Cancer Analysis of Whole Genomes . The model’s analysis of this data gave the researchers a map of the expected passenger mutation rate across the genome, such that the expected rate in any set of regions can be compared to the observed mutation count anywhere across the genome.
Targeting these mutations could offer a new way to potentially treat those patients, the researchers say. One possible approach that is still in development uses short strands of RNA called antisense oligonucleotides to patch over a mutated piece of DNA with the correct sequence.
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