Test Markers Identify Cancer DNA and Pinpoint Tumor Location

A team of molecular geneticists has developed a diagnostic tool that identifies circulating cancer DNA and determines the organ in which the tumor is located.

Investigators at the University of California San Diego based their method on the presence of methylation haplotype blocks in the genome. A haplotype is a set of single-nucleotide polymorphisms (SNPs) on one chromosome that tend statistically to always occur together. It is thought that identifying these statistical associations and few alleles of a specific haplotype sequence can facilitate identifying all other such polymorphic sites that are nearby on the chromosome.

The investigators focused on a systematic search and investigation of regions in the full human genome that showed highly coordinated methylation. They defined 147,888 methylation haplotype blocks of tightly coupled CpG sites. CpG sites are regions of DNA where a cytosine nucleotide is followed by a guanine nucleotide in the linear sequence of bases along its 5' to 3' direction. CpG is shorthand for 5'-C-phosphate-G-3', that is, cytosine and guanine separated by only one phosphate; phosphate links any two nucleosides together in DNA. Each tissue in the body can be identified by its unique signature of methylation haplotypes.

Using methylation haplotype data, the investigators compiled a database of the complete CpG methylation patterns of 10 different normal tissues (liver, intestine, colon, lung, brain, kidney, pancreas, spleen, stomach, and blood). They then analyzed tumor and blood samples from cancer patients to assemble a database of cancer-specific genetic markers. Using this database the investigators demonstrated quantitative estimation of tumor load and tissue-of-origin mapping in the circulating cell-free DNA of 59 patients with lung or colorectal cancer.

"Knowing the tumor's location is critical for effective early detection," said senior author Dr. Kun Zhang, professor of bioengineering at the University of California, San Diego. "This is a proof of concept. To move this research to the clinical stage, we need to work with oncologists to further optimize and refine this method."

"We made this discovery by accident. Initially, we were taking the conventional approach and just looking for cancer cell signals and trying to find out where they were coming from. But we were also seeing signals from other cells and realized that if we integrate both sets of signals together, we could actually determine the presence or absence of a tumor, and where the tumor is growing," said Dr. Zhang.

The method was described in detail in the March 6, 2017, online edition of the journal Nature Genetics.