Like a menacing shadow, women who have experienced ovarian cancer can't shake the fear of recurrence associated with the disease. “Eighty percent or more of patients treated for stage III ovarian cancer will return,” explained George Vasmatzis, PhD, Co-Director of the Mayo Clinic's Biomarker Discovery Program at the Center for Individualized Medicine in Rochester, Minn. Vasmatzis is also an Associate Professor of Molecular Medicine at the Mayo Clinic. “We don't know when patients will return, but most will. We need more sensitive ways to monitor the disease.”
At the Biomarker Discovery Program, a collaborative team is pursuing several projects that seek to assess how biomarkers may be used to indicate health or disease. The Ovarian Cancer Project is one area of emphasis and the focus of this article. The goal of the Ovarian Cancer Project is to identify biomarkers that can be used to treat ovarian cancers that have not responded to conventional treatments such as debulking and chemotherapy. By customizing treatment, interventions may be more effective at achieving a cure. In addition, the program is working to identify biomarkers that can be used to follow patients over time, allowing early identification of ovarian cancer recurrence.
Minetta C. Liu, MD, is the Research Chair in the Division of Medical Oncology at Mayo Clinic and an Associate Professor in the Department of Oncology. She views the Ovarian Cancer Project as a collaboration of skills and knowledge. “We are fortunate to have a group at the Mayo Clinic that includes clinicians, pathologists, basic scientists, bioinformaticians, and statisticians to help validate the use of circulating tumor cells and circulating tumor DNA from the peripheral blood as potential sources of the ‘liquid biopsy’,” she said.
Proof of Concept
A significant step toward meeting the goals of the program was achieved in 2016 in the form of a proof-of-concept paper (Sci Rep 2016;6. doi: 10.1038/srep29831). Noting that liquid biopsy has shown promise in monitoring tumor burden, the Mayo Clinic-based authors, who included Vasmatzis and Liu, developed their hypothesis with the knowledge that chromosomal rearrangements have demonstrated greater tumor specificity than other approaches. Using quantitative PCR (qPCR), such rearrangements can be identified in the tumor and then detected in plasma.
The Mayo Clinic team used a whole-genome mate pair next generation sequencing protocol to characterize a landscape of genomic rearrangements in the primary tumors of 10 patients with ovarian cancer. They identified individualized tumor-specific primer panels of aberrant chromosomal junctions for each case via qPCR within the cell-free DNA. The researchers detected selected chromosomal junctions in presurgically drawn blood in eight of the 10 patients. Of these, three demonstrated the continued presence of circulating tumor DNA (ctDNA) post-surgery (consistent with their documented presence of disease). In five of the eight patients, ctDNA was undetectable in the post-surgical blood collection (consistent with lack of detectable disease.) The ctDNA fraction was calculated using a novel algorithm designed for the unique challenges of quantifying ctDNA using qPCR, the researchers wrote. This allows observations of real-time tumor dynamics.
The authors concluded that, based on these findings, a panel of individualized junctions derived from tumor DNA could be an effective way to monitor cancer patients for relapse and therapeutic efficacy using ctDNA.
The Next Phase
Now that researchers in the Biomarker Discovery Program have established a proof of concept for the liquid biopsy approach, they are advancing to clinical-level research, monitoring patients using presurgical and postsurgical blood draws. The team has received IRB approval to work with patients in various stages.
As of January 2017, the team had collected eight serial blood collections from three patients, representing 18 months of monitoring. The team had collected fewer blood draws on 10 patients. “When you have many time points, you can better see what is going on,” Vasmatzis said. “We are looking for the DNA of the debris from the cancer cells; it has characteristic abnormal chromosomal structures. The cancer constantly sheds that DNA in the blood, where it can be detected using our protocol.”
He noted that in the time since the proof-of-concept study was performed, the center's genome analysis has become more robust. This allows the Ovarian Cancer Project team to perform accurate personalized testing on more than 90 percent of its patients, Vasmatzis said.
In 2017, the center is working to identify new targets for therapy. Mayo's genome analysis identified certain cell pathways for the first time. “Our goal is to validate those findings,” Vasmatzis said. “An oncologist won't treat the patient unless he or she sees some functional data to show that the drug that seems promising would actually work. One of the things we're doing is trying to use model systems to validate those biomarkers and drugs faster.”
Testing drug and cell pathways is a time-consuming process, typically requiring prolonged laboratory work and follow-up in animal models. Vasmatzis said his team has made a recent breakthrough using three-dimensional model systems that would allow scientists to take tissue from the cancer patient for testing. “We can test drugs much more efficiently using this approach,” he said. “If this works well, we will have a faster and cheaper way to test potential therapies.”
From a clinical application perspective, Liu is encouraged. “The published work demonstrates that individualized blood-based disease monitoring is feasible in ovarian cancer,” she noted. “Chromosomal rearrangements have greater tumor specificity than the point mutations included in most available assays. The ability to determine the pattern of chromosomal rearrangements for a specific tumor and then efficiently translate those unique findings to a personalized blood test has tremendous implications for the field of oncology.
“Reliably monitoring tumor burden in patients with known metastatic disease will enable earlier predictions of treatment efficacy, allowing us to limit exposure to systemic agents associated with toxicity and no treatment benefit, and to improve survival through the timely use of agents with activity against that specific tumor,” Liu continued. “Reliably monitoring for the appearance or persistence of micrometastatic disease for early stage disease, on the other hand, will enable the more appropriate use of adjuvant therapies to minimize the risk of disease recurrence.”
Among U.S. women, ovarian cancer is the ninth most common type of cancer and the fifth leading cause of cancer death, the CDC reports. Ovarian cancer causes more deaths than any other cancer of the female reproductive system, but it accounts for only about 3 percent of all cancers in women. More than 21,000 women in the U.S. were diagnosed with ovarian cancer in 2015, and 14,000 women died of the disease that year. Ovarian cancer has one of the highest mortality rates of all gynecological cancers.
The Mayo Clinic's Ovarian Cancer Program is housed within the system's Women's Cancer Program, which comprises research programs related to breast cancer and gynecologic malignancies. The program seeks to advance the understanding of cancer biology, improve treatment strategies for these cancers, and tailor therapies to the individual patient. “Toward that end, the Women's Cancer Program is well supported by the Mayo Clinic Cancer Center and the Center for Individualized Medicine. It also has Specialized Program of Research Excellence (SPORE) grants from the National Cancer Institute for breast cancer and for ovarian cancer,” Liu said. The Cancer Center is an NCI-designated program.
The NCI established the SPORE concept in 1992 to promote interdisciplinary research and to help basic research findings move quickly from the laboratory to the patient. To earn a highly competitive NCI SPORE grant, institutions must demonstrate a high degree of collaboration between first-rate scientists and clinicians and show excellence in translational research projects.
Michelle Perron is a contributing writer.