Assay Shows Potential in Predicting Ovarian Cancer Response to Chemotherapy

A new assay that grows patients’ cancer tissue in the lab and tests for treatment sensitivity may be able to spot ovarian cancer patients likely to respond best to first-line chemotherapy, a study showed.

The ex vivo 3D cell culture (EV3D) assay, developed by Kiyatec, may lead to better informed treatment decisions and superior patient outcomes.

The study, “Prospective Validation of an Ex Vivo, Patient-Derived 3D Spheroid Model for Response Predictions in Newly Diagnosed Ovarian Cancer,” was published in the journal Scientific Reports.

First-line chemotherapy is initially effective for as many as 80% of ovarian cancer patients, but most eventually relapse. Figuring out which patients will respond well – or not – to this kind of treatment may allow for better, more personalized therapeutic approaches, but this is easier said than done.

“At present, clinicians have no way of knowing, prior to treatment, which of our newly diagnosed or relapsed ovarian cancer patients will respond or not to approved drug therapies,” a study co-author, Larry Maxwell, MD, who is the co-director of Inova’s Women’s Health Integrated Research Center, said in a press release.

Researchers tested an assay that may help differentiate between ovarian cancer patients who will or won’t respond to therapy, relying on three-dimensional ex vivo tissue culture.

Essentially, cancer cells are taken from the patient (via biopsy or as part of surgery); these cells are then grown in dishes in a manner reminiscent of the 3D architecture of actual cells in the body. This also mimics the immune environment seen in the original tumor.

These cultures can then be treated with chemotherapeutic drugs, and based on how the cells respond (i.e., dying or not), the patient is predicted to be a responder or a non-responder. The whole process only takes about a week, which is much less time than it would take to actually see a response, or lack thereof, in a person.

The assay was performed for 83 newly diagnosed ovarian cancer patients given standard chemotherapy independent of the assay results. Only the 44 patients followed for at least six months were included in this analysis.

Patient classification based on the assay (responder or non-responder) was compared to the clinical results (whether the patient actually had a detectable clinical response at six months) to determine the accuracy of the test.

Of the 44 people, 32 were correctly identified as responders by the assay, and seven were correctly labeled non-responders. There were five false-negatives (people labeled as non-responders by the assay who did respond to treatment) and no false positives.

Overall, the assay correctly predicted response to treatment in 89% of the patients. This is a higher accuracy rate than has been achieved by similar tests that use cells in dishes, but without the 3D culturing.

Predicted responders lived significantly longer without their disease worsening than the predicted non-responders (20 months vs. 9 months).

The data support this assay as being a reasonably accurate measurement of patient response to first-line chemotherapy, although larger studies need to validate these findings.

“For ovarian cancer patients and their physicians, this study represents an important step in demonstrating our ability to deliver a robust predictive assay with the potential to positively support therapeutic decision-making and improve patient outcomes,” said Matthew Gevaert, the chief executive officer of Kiyatec.

“To predict a complex future result with very high accuracy is a meaningful achievement, especially given that sometimes these outcomes take months to define,” Maxwell added. “Similar test performance in larger, follow-on studies would establish this as a go-to tool in cancer drug selection that should help improve patient outcomes in ovarian cancer.”

Kiyatec is sponsoring a clinical trial (NCT03561207) to test out this methodology in about 500 people with newly diagnosed and recurrent ovarian cancer or glioblastoma. The trial, taking place at sites across the U.S., is enrolling patients by invitation.