Blood Test Analysis Identifies Early-Stage Tumors

To fill this gap investigators at the University of California, Los Angeles have proposed a novel method, CancerLocator, which simultaneously infers the proportion and tissue of origin of circulating DNA in a blood sample using genome-wide DNA methylation data.

CancerLocator identifies specific methylation patterns in circulating cancer DNA from different cancer types and compares the patterns to those in a tumor epigenetics database. Since DNA from tumor cells enters the bloodstream in the earliest stages of cancer, this approach offers a method for early detection of the disease.

In a pre-clinical study CancerLocator and two other programs were used to analyze blood samples from 29 liver cancer patients, 12 lung cancer patients, and five breast cancer patients. CancerLocator correctly identified 25 of 29 liver cancer patients and five of 12 lung cancer patients with early stage cancers. Overall CancerLocator had an overall error rate of 0.265 compared to the other two programs, which had rates of 0.646 and 0.604.

Senior author Dr. Xianghong Jasmine Zhou said, "We built a database of epigenetic markers, specifically methylation patterns, which are common across many types of cancer and also specific to cancers originating from specific tissue, such as the lung or liver. We also compiled the same molecular footprint for non-cancerous samples so we had a baseline footprint to compare the cancer samples against. These markers can be used to deconvolute the DNA found freely in the blood into tumor DNA and non-tumor DNA. Non-invasive diagnosis of cancer is important, as it allows the early diagnosis of cancer, and the earlier the cancer is caught the higher chance a patient has of beating the disease. We have developed a computer-driven test that can detect cancer, and also identify the type of cancer, from a single blood sample. The technology is in its infancy and requires further validation, but the potential benefits to patients are huge."

The CancerLocator program was described in the March 24, 2017, online edition of the journal Genome Biology.