Scientists discover mechanism that links mutations in ‘dark matter’ of genome to cancer

For years the human genome was seen as a book of life in which sections of great eloquence and frugality of expression were interspersed with sprawling gibberish. The readable sections contain the code for making cell proteins; the other regions, representing about 90% of the entire genome, were dismissed as “junk DNA”, with no discernible target.

Research has taught scientists otherwise. Far from being a useless filler, many non-coding sections have been shown to play a key role in regulating gene activity – increasing or decreasing it as needed. For cancer scientists, this has raised its own questions: If mutations in coding regions cause cells to make defective proteins, what do mutations in noncoding regions do? How does a mutation in the genome’s hinterland — in regions without genes — contribute to cancer?

Of course, given that noncoding regions are involved in gene regulation, researchers have hypothesized that mutations in these zones disrupt gene activity in ways that promote cancer. However, study after study has shown that this is generally not the case, leaving the biological impact of noncoding mutations a mystery.

Think local

In a new article in the journal Nature Genetics, Dana-Farber researchers provided an answer. They did this through the scientific equivalent of local thinking – limiting the scope of their research to the specific DNA that contains noncoding mutations. They found that in the overwhelming number of cases studied, such mutations have an epigenetic effect — that is, they alter how tightly the DNA is packed in those locations. That, in turn, affects how open those sites are for binding to other parts of DNA or certain proteins, all of which can affect the activity of genes involved in cancer.

The discovery reveals for the first time a pervasive biological mechanism through which noncoding mutations can influence cancer risk. It also opens the way to therapies that, by disrupting that mechanism, can reduce the risk of developing certain cancers in patients at risk.

“Studies have identified a huge number of mutations in the genome that may be involved in cancer,” says Alexander Gusev, PhD, from Dana-Farber, the Eli and Edythe L. Broad Institute and Brigham and Women’s Hospital, who co-authored the paper with Dana-Farber’s Dennis Grishin, PhD. “The challenge has been understanding the biology through which these variations increase cancer risk. Our study has uncovered an important part of that biology.”

Does mutation change expression?

To identify hereditary or germline mutations that increase a person’s risk of developing cancer, researchers conduct so-called genome-wide association studies, or GWASs. In it, researchers collect blood samples from tens or hundreds of thousands of people and scan their genomes for mutations or other variations that are more common in people with cancer than those without the disease.

Such tests have yielded thousands of such mutations, but only a small percentage of them reside in coding regions of the genome that are relatively easy to link to cancer. Breast cancer is an example of this. “More than 300 mutations have been identified that are associated with an increased risk of the disease,” Gusev said. “Less than 10% of that is actually in genes. The rest are in ‘desert’ regions and it’s not clear how they affect disease risk.”

To make that connection, researchers are collecting two sets of data: one, GWAS data showing mutations in a specific type of cancer; and two, data on another genomic feature of that cancer type — such as an abnormally high or low level of activity in certain genes. By looking for regions of overlap between these data sets, in a process called colocalization, researchers can determine whether the mutations correspond to an increase or decrease in the activity of those genes. If such a connection exists, it would help explain how noncoding mutations can lead to cancer.

However, despite a huge investment in this type of research, colocalization studies have revealed very few such similarities. “The sheer number of mutations identified by GWASs appear to have no colocalizing gene at all,” Gusev notes. “For the most part, noncoding mutations associated with cancer risk do not overlap with changes in gene expression [activity] documented in public datasets.”

Looking closer to home

As that route looked less and less illuminating, Gusev and Grishin tried a different, more fundamental approach. Rather than starting with the premise that noncoding mutations could affect gene expression, they asked how they change their home environment — whether they affect the coiling of DNA in their immediate environment.

“We hypothesized that if you look at the effect of these mutations on local epigenetics — in particular, whether they cause nearby DNA to be wound more tightly or loosely — we would be able to detect changes that wouldn’t be apparent in expression-based studies,” says Gusev.

Their reasoning: “If a mutation has an effect on disease, that effect will probably be too subtle to capture at the level of gene expression, but perhaps not too subtle to capture at the level of local epigenetics — what exactly is happening? around the mutation,” Gusev says.

It’s as if previous studies were trying to understand how a California wildfire could affect Colorado weather, while Gusev and Grishin wanted to see the effect on the hill where it started.

To do that, they conducted a different type of overlay study. They took GWAS data on cancer-related mutations and data on epigenetic changes in seven common cancers and examined whether — and where — they interbred.

The results contrasted sharply with those of colocalization studies. “We found that while most noncoding mutations have no effect on gene expression, most do have an impact on local epigenetic regulation,” Gusev said. “We now have a basic biological explanation of how the vast majority of cancer risk mutations may be related to cancer, when such a mechanism was previously unknown.”

Using this approach, the researchers created a database of mutations that may now be associated with cancer risk through a known biological mechanism. The database can serve as a starting point for research into drugs that, by targeting that mechanism, can lower an individual’s risk of developing certain cancers.

“For example, if we know that a particular transcription factor [a protein involved in switching genes on and off] binds to one of these cancer-related mutations, we could potentially develop drugs that target that factor, reducing the chance that people born with that mutation will develop cancer,” Gusev says.

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