Liquid biopsies can detect ovarian cancer recurrence before tumor appears

With 21,000 new diagnoses and 14,000 deaths, ovarian cancer is undoubtedly one of the most lethal forms of cancer. A major factor leading to the high mortality rate is the fact that the cancer is often not detected until the later stages and has a 75 percent chance of returning. Faced with these odds, researchers at the Mayo Clinic Center for Individualized Medicine have been working to develop a new way to tract and treat ovarian cancer.

George Vasmatzis, PhD, of the Department of Laboratory Medicine and Pathology at Mayo Clinic and leader of the study, found that using liquid biopsies taken from blood tests and DNA sequencing can detect if ovarian cancer will return to a patient even before it re-emerges. This method could change how physicians are able to treat cancer patients with more personalized care and a higher detection rate, leading to earlier treatment.

"With liquid biopsies, we don't have to wait for tumor growth to get a DNA sample," said Vasmatzis. "This important discovery makes it possible for us detect recurrence of the disease earlier than other diagnostic methods. We can repeat liquid biopsies to monitor the progression of the cancer. That gives hope of a better treatment plan over time."

A study was conducted on 10 patients with advanced stages of ovarian cancer by taking blood from before and after surgery. When DNA from the liquid blood biopsies was compared to the DNA of the tumor, researchers found that the patient had a recurrence of ovarian cancer when the DNA samples matched one another. When the DNA did not match, the patient went into remission.

"In this study, the blood drawn before and after surgery and the surgical tissue was used to identify DNA fragments with abnormal junctions that can only be seen in this patient's tumor DNA," explained Vasmatzis. "Next generation mate-pair sequencing was used to identify specific DNA changes of the tumor to create an individualized monitoring panel for liquid biopsy. This allows us to shape treatment to the individual patient rather than using a standard treatment that may not work for everyone."