A new computer model created by researchers at the U.K.-based Wellcome Trust Sanger Institute's cancer genome project will help researchers to more accurately determine the various causes of cancer development, according to a study published this month in the journal Cell Reports.
According to an announcement from the institute, cancer genome DNA typically contains mutations from the cancer's development, as well as "an entire lifetime's worth of other mutations that have also been acquired." First author Ludmil Alexandrov compares the setting to a cocktail party with microphones set up throughout the room to record each conversation.
"Each [microphone] will record a mixture of all the conversations," Alexandrov says. "To understand what is going on you need to be able to separate out the individual discussions. The same is true in cancer genomics. We have catalogues of mutations from cancer genomes and each catalogue contains the signatures of all the mutational processes that have acted on that patient's genome since birth."
The computer model enables the researchers to pinpoint signatures within the different mutation-causing processes within each of those catalogues, Alexandrov adds.
To test their model, the researchers looked at the genomes of 21 breast cancer patients; five mutational signatures of cancer causing processes were identified.
"This new approach provides us with a valuable tool for exploring cancer genomes with a clarity and understanding that we haven't had before," co-senior author Mike Stratton, director of the Sanger Institute, said in a statement. "It will enable us to create a compendium of the mutational signatures of the many different DNA-damaging processes that operate during cancer development."
Researchers, more and more, are turning to genomics as a way to better study and understand cancer development. For instance, last March, the Greenville (S.C.) Hospital System's University Medical Center became one of the first to test Life Technologies' Ion Torrent system, which promised to identify the genetic makeup of a patient's cancer and determine the treatment--reducing the time between diagnosis and therapy to about a week.
Additionally, researchers using genomics last January discovered that a subtype of leukemia characterized by a poor prognosis was fueled by mutations in pathways distinctly different from a seemingly similar leukemia generally associated with a much better outcome.