Researchers used cervical screening samples as a surrogate tissue for measuring the marks on the DNA of cervical cells. Credit: EUTOPS Institute, Unversity of Innsbruck.

Researchers from University College London’s (UCL) Institute for Women’s Health are developing a new test that can detect breast and ovarian cancer from a single sample collected during a routine cervical screening.

The test can also help to detect or predict the risk of two further cancers.

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UCL stated that the test may detect up to 30% more women with a high risk of ovarian or breast cancer, compared to existing genetics-based tests.

During the research, samples from more than 3,000 women from 15 European centres were evaluated.

Later, researchers used cervical screening samples as a surrogate tissue for measuring the marks on cervical cells’ DNA (DNA methylation).

They found that the marks can specifically relate to whether a person has ovarian or breast cancer.

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In the research, the new WID-Test outperformed a currently used process for determining the risk of breast cancer by combining genetic variants information.

The WID-Test identified 76.6% of women with breast cancer in the highest risk group, while the current process identified 47.5% of them.

Similarly, the WID-Test identified 61.7% of women with ovarian cancer in the highest risk group and the current test identified 35.1%.

UCL stated that further results are due to be published regarding the ability of the WID-test to predict cervical and womb cancer.

UCL Institute for Women’s Health professor Martin Widschwendter said: “The WID-test will look for the footprints on a woman’s DNA as she goes through life, recording the track she is taking and whether she is heading towards cancer.

“The WID-test will revolutionise screening and enable a more personalised approach to cancer prevention and detection, where women will be screened, monitored or treated based on their individual, and changing, risk.”

The researchers are now planning large population trials for the new WID-Test, to see whether it can accurately predict cancer before occurrence as well as compare it with current tests.