New Blood Test May Improve Ovarian Cancer Diagnosis, Study Suggests

A blood test that examines a panel of 11 specific proteins could help distinguish between benign tumors and malignant ovarian cancer, reducing the need for unnecessary surgeries and leading to an earlier diagnosis, a study shows.

Conducted by researchers at Uppsala University and Sahlgrenska Academy at the University of Gothenburg in Sweden, the study, “High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer,” was published in the journal Communications Biology.

Ovarian cancer is one of the leading causes of cancer-related death in women around the world, mostly because the disease has no specific signs and symptoms and is often caught late, when the chances of curing it are low.

When a woman is suspected of having ovarian cancer after an ultrasound, the only way to determine if it’s a benign or malignant tumor is through surgery. This means that women who do not have cancer will undergo a surgical procedure they do not need, putting them at risk of side effects that could otherwise be avoided.

“We need to develop more accurate pre-surgery diagnostics. To detect one cancer, we operate on up to five women — yet this is currently the best option when abnormalities are detected by ultrasound and cancer is suspected,” Karin Sundfeldt, a professor and senior consultant in the department of obstetrics and gynecology at Sahlgrenska’s Institute of Clinical Sciences, said in a press release.

There is a great need for a simple blood test that could identify women who do not need surgery,” she added.

Aiming to develop such a blood-based test that could distinguish between benign and malignant ovarian masses, researchers in Sweden teamed up with Uppsala-based biotech company Olink Proteomics, which has extensive expertise in protein biomarker discovery.

Using blood samples from 417 women with benign or malignant ovarian tumors, they examined the levels of more than 500 unique proteins and generated computer models that could distinguish ovarian cancers at different stages.

Among the 484 models, one stood out. It included a total of 11 proteins — including the ovarian cancer biomarker CA125 — and showed an accuracy of 95% at distinguishing benign tumors from ovarian cancer.

“[This] protein signature could be used to improve the diagnosis of women with … ovarian mass or in screening to identify women that should be referred to specialized examination,” the researchers wrote.

The model performed better at distinguishing late-stage (stage 3–4) ovarian cancers from benign tumors than it did for earlier-stage (stage 1–2) cancers. It also performed poorly when asked to distinguish between early- and late-stage cancers.

“I see great prospects of developing a strategy for screening for ovarian cancer as well, which could save lives and minimize the need for surgery to rule out cancer,” said Ulf Gyllensten, PhD, a professor at Uppsala University and senior author of the study.

“We are now continuing to evaluate the test and are performing a large-scale study of samples collected at all hospitals from the [Swedish] western region and Halland healthcare system,” he added.