Bits of cancer DNA circulating in the blood of lymphoma patients can provide physicians with information on the cancer subtype and identify mutations linked to treatment resistance.
The findings bring lymphoma treatment closer to a personalized approach, where analyses could help determine the right type of treatment for individual patients and spot those likely to have a poor prognosis.
The study, “Distinct biological subtypes and patterns of genome evolution in lymphoma revealed by circulating tumor DNA,” which appeared in Science Translational Medicine, could also be used to track changes in tumors over time, allowing oncologists to discover early when a cancer is turning aggressive.
“Now we can identify the subtype of the tumor, watch how it changes over time, and begin to tailor our chemotherapy choices based on the presence or absence of specific mutations,” Ash Alizadeh, MD, PhD, assistant professor of medicine and one of two senior study authors, said in a news release. “We’ve moved beyond just measuring disease burden based on the amount of tumor DNA in the blood.”
The research team at the Ludwig Center for Cancer Stem Cell Research at Stanford University School of Medicine previously developed a method called CAPP-Seq that can be used to gather and sequence tumor DNA from the blood of patients. Now, an improved version of the method was tested in 92 patients with diffuse large B-cell lymphoma (DLBCL).
It is common that DLBCL tumors become resistant to treatment, or that patients relapse after a treatment that seemed to have conquered the cancer. There is also a specific problem in patients with so-called indolent B-cell lymphoma. This is a cancer type that grows slowly and is often not very bothersome to patients. But it can suddenly transform to a highly aggressive form.
“This transformation is very difficult to detect, and usually requires an invasive biopsy to diagnose,” said Maximilian Diehn, MD, PhD, assistant professor of radiation oncology, and the second senior author. “Our approach will allow us to monitor patients over time with a simple blood test, and may help us identify transformation much earlier.”
The improved method can identify a much larger number of mutations in the cancer DNA compared to earlier versions that were focused on only one lymphoma protein.
To validate the method, the team compared the sequences of the isolated DNA to those obtained from tissue samples, taken through invasive biopsies. Comparing the DNA data to information on the turns of the disease and of patient outcomes, they noted that low levels of cancer DNA just before the start of treatment correlated strongly with the time of progression-free survival. Patients with more cancer DNA in their blood had a poorer prognosis.
Importantly, the team found that cancer DNA appeared in the blood of relapsing patients an average of six months earlier than any symptoms indicating the cancer was returning, and a full 2.5 years before any clinical signs of relapse could be detected.
But in addition to tumor load, determined by the abundance of cancer DNA in the blood, the sequence could tell researchers the type of B-cell lymphoma. Different lymphoma subtypes are linked to variabilities in both treatment response and prognosis, but with current approaches, accurate measurements depend on biopsies and are difficult to perform.
The DNA sequences could also reveal when a lymphoma was transforming into a more aggressive form before symptoms gave an indication of change, and the method could keep track of mutations that block the response to the lymphoma drug Imbruvica (ibrutinib).
“In this study, we’ve shown five distinct ways — by quantifying tumor burden, identifying disease subtype, cataloging mutations, predicting transformation, and providing early warnings of recurrence — that circulating tumor DNA can yield potentially clinically useful information,” Diehn said.
“Now we’re eager to conduct prospective studies in recently diagnosed patients to learn how we can best improve patient care,” he said.