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New blood test could help diagnose ovarian cancer

24 June 2019
Appeared in BioNews 1003

Scientists have discovered a set of biomarkers in the blood that could indicate ovarian cancer, which could be used to help diagnose the disease.

Ovarian cancer has few obvious symptoms and is typically discovered at a late stage, making it hard to treat. It is also hard to detect definitively – most women who undergo surgery for suspected ovarian cancer do not have it. A blood test that can detect the disease could save thousands of lives each year and and reduce the number of women undergoing unnecessary surgery. 

'To detect one cancer, we operate on up to five women... There is a great need for a simple blood test that could identify women who do not need surgery,' said study author Professor Karin Sundfeldt of the University of Gothenburg, Sweden.

The researchers developed the biomarker test based on 11 proteins they found to be higher in women with ovarian cancer. They tried the test on blood samples taken from 90 women with the disease and 79 without. The test distinguished between women who had the disease and those who did not with up to 93 percent accuracy.

'Our results are promising enough to consider screening for early discovery of ovarian cancer,' said Professor Ulf Gyllensten of Uppsala University, who led the team. 'I see great prospects of developing a strategy for screening for ovarian cancer… which could save lives and minimise the need for surgery to rule out cancer.'

In the UK, around 7300 women are diagnosed with ovarian cancer each year and only 30 to 40 percent of patients survive five years after treatment. The researchers hope the new test could one day be used as part of a routine ovarian cancer screening programme, but they first need to confirm their findings using a larger number of blood samples.

'We are now continuing to evaluate the test and are performing a large-scale study of samples collected at all hospitals from the western region and Halland healthcare system,' said Professor Gyllensten.

The research was published in the journal Communications Biology

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