Saturday, April 30, 2022

Study Nearly Doubles Known Cancer-Linked Mutational Signatures

Update of 5/8/2022: Here is another article about this Trove of tumour genomes offers clues to cancer origins Largest-ever study uncovers patterns of mutations that might pinpoint cancer’s causes.

Good news! Cancer is history (soon)!

"... The work, published yesterday (April 21) in Science, also includes a new tool to allow clinicians to search for such patterns of mutations in individual cancer patients, something the team argues could point to beneficial therapies. ...
The researchers conducted their analysis on samples from 12,222 patients in the 100,000 Genomes Project as well as a few thousand other genomes from existing datasets, for a total of 18,640 genomes across 19 cancer types—the largest set of whole genome sequences to date. In the end, they confirmed 51 of the more than 70 mutation patterns listed in the Catalogue of Somatic Mutations in Cancer (COSMIC) and identified 58 additional signatures. ..."

Science editors call this a "A signature accomplishment
Tumor development is associated with the accumulation of mutations in the genome. Depending on the causes of a given cancer, such as environmental exposures or DNA repair abnormalities, these mutations can form a specific pattern called a mutational signature. Many mutational signatures have already been reported in cancer, but by performing whole-genome sequencing on a particularly large collection of cancer samples, Degasperi et al. not only confirmed previously reported signatures, but also discovered many rarer ones (see the Perspective by Szüts). The authors characterized these signatures, tried to elucidate the underlying biology where possible, and then provided an algorithm for applying these findings to individual patients to help personalize cancer treatments. —YN"

Study Nearly Doubles Known Cancer-Linked Mutational Signatures | The Scientist Magazine® Analyzing the whole genome sequences of more than 18,000 tumors, researchers catalog nearly 60 new patterns of mutations that could inform cancer treatment.




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