Researchers from the Dana-Farber Cancer Institute in the US have develop a new blood test that can detect ovarian cancer early and accurately, according to a report in the journal eLife.
The team has identified a network of microRNAs – small, non-coding pieces of genetic material – that are associated with risk of ovarian cancer and can be detected from a blood sample.
Most women are diagnosed with ovarian cancer when the disease is at an advanced stage, at which point only about a quarter of patients will survive for at least five years. But for women whose cancer is picked up at an early stage, survival rates are much higher.
Current early detection tests, such as ultrasound or detection of the protein CA125, have a high false positive rate for ovarian cancer. Clinical trials have found that when these tests are used to try to detect early-stage ovarian cancer, they do not have a meaningful impact on survival rates.
The researchers determined that ovarian cancer cells and normal cells have different microRNA profiles. Unlike other parts of the genetic code, microRNAs circulate in the blood, making it possible to measure their levels from a serum sample. They sequenced the microRNAs in blood samples from 135 women (prior to surgery or chemotherapy) to create a training set with which to train a computer program to look for microRNA differences between cases of ovarian cancer and cases of benign tumours.
They then tested this sequencing model in a group of 44 women to determine the accuracy of the test. Once the accuracy of the model was confirmed, the team deployed the model across multiple patient sample sets, using a total of 859 patient samples to measure the sensitivity and specificity of the model. The new technique was far better at predicting ovarian cancer than an ultrasound test: whereas using ultrasound fewer than 5 per cent of abnormal test results would be ovarian cancer, almost 100 per cent of abnormal results using the microRNA test actually represented ovarian cancer.