A massive data analysis of natural genetic variants in humans and variants in cancer tumors has implicated dozens of mutations in the development of breast and prostate cancer, a Yale-led team has found.
The newly discovered mutations are in regions of DNA that do not code
for proteins but instead influence activity of other genes. These areas
represent an unexplored world that will allow researchers and doctors to
gain new insight into the causes and treatment of cancer, said the
scientists.
"This allows us to take a systematic approach to cancer genomics," said
Mark Gerstein, the Albert L. Williams Professor of Biomedical
Informatics and co-senior author of the paper, which appears in the
journal Science. "Now we do not need to limit ourselves to the
roughly 1% of the genome that codes for proteins but can explore the
rest of our DNA."
The analysis - led by Yale researchers and scientists from the Wellcome
Trust Sanger Institute, as well as Weill Cornell Medical Colleges and
other institutions - is a statistical marriage of separate mammoth
research projects, each providing groundbreaking insights in our genome,
the genetic blueprint of life.
The 1000 Genomes project is compiling the personal genomes of many
individuals. The data help pinpoint regions of DNA that vary little
within the population and thus are of crucial importance to human
health. The Encyclopedia of DNA Elements (ENCODE) project is working
toward cataloguing the function of each location in the human genome.
The team took non-coding DNA elements from ENCODE project and looked for
those that are highly conserved in the 1000 Genomes data. They then
contrasted the data with mutations in tumor
samples from about 90 patients with breast or prostate cancer. They
found dozens in areas of DNA that vary little and therefore are likely
to drive tumor progression. They also looked for additional features of
the cancer mutations such as their proximity to regulatory-network hubs,
which also indicate they may be particularly damaging.
While the research focused on variants of single base pairs, many of
conclusions also apply to other, larger forms of genetic variation, the
authors say.
The great diversity of variants found proves that massive data projects
have direct relevance to cancer in individuals, the authors said.
"Our approach can be directly used in the context of precision
medicine," says Ekta Khurana, an associate research scientist in
Gerstein's lab and a first author of the study.
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