Scientists in the US have identified a common genomic signature in tumour DNA that is shared by five different kinds of cancer. The finding could lead to the development of a simple blood test that might be able to diagnose a variety of cancers at early stages.
This telltale signature results from a chemical modification of DNA called methylation, which controls the expression of genes. Having identified this methylation biomarker, scientists uncovered consistent evidence of it in five different kinds of tumours: Colon, lung, breast, stomach, and endometrial cancers.
“Finding a distinctive methylation based signature is like looking for a spruce tree in a pine forest,” said computational biologist Laura Elnitski from the US National Human Genome Research Institute (NHGRI). “It’s a technical challenge to identify, but we found an elevated methylation signature around the gene known as ZNF154 that is unique to tumours.”
The findings, reported in The Journal of Molecular Diagnostics, build upon previous research by Elnitski’s team, which initially detected methylation signatures around ZNF154 in 2013 and suspected it as a possible universal cancer biomarker.
In the new research, the scientists developed a series of steps that uncovered the signature in a variety of tumours. The team used a technique called polymerase chain reaction to amplify DNA taken from tumours and analysed the results, finding elevated levels of ZNF154 across the different tumour types.
Sifting through huge amounts of genomic data to find the markers wasn’t easy, but isolating the signature was worth the effort.
“Finding the methylation signature was an incredibly arduous and valuable process,” said NHGRI scientific director Dan Kastner. “These findings could be an important step in developing a test to identify early cancers through a blood test.”
The researchers will now be looking at whether the signature can be used to identify cancers in blood samples from patients with bladder, breast, colon, pancreatic and prostate cancers. They will also investigate whether their method of analysis leads to improved outcomes in women with ovarian cancers, via better detection of recurrent cancer cells.
