Quick and simple tests to accurately detect and track tumours would make keeping on top of cancer a lot easier for doctors and their patients. Right now, a lot of information about a tumour comes from specialised scans or tissue samples (biopsies).

So the race is on to develop simple, non-invasive tests for cancer. And DNA-based blood tests in particular are showing great promise.

Tests that search for tumour cells and DNA in the blood, also known as liquid biopsies, have been used in cancer research for many years (and we’ve blogged about them before).

And now, a team of Cancer Research UK-funded scientists at the University of Cambridge, publishing their findings in the journal PLoS Medicine, have developed a blood test that could help track how patients with a type of ovarian cancer respond to treatment.

And it’s based on fishing tumour DNA from blood samples.

In the blood

As cells die and break down, which they do all the time, the molecules and DNA that are inside the cell find their way into the bloodstream.

It’s a similar process that allows doctors to check on a developing baby by looking for pieces of DNA from a foetus in the blood of the mother. It can also be used in the hunt for viral DNA in the blood of someone who has been infected.

And as the animation below explains, it’s now possible to search for DNA clues that cancer cells leave in the blood when they die.

Tracking ovarian cancer

In their latest study, the Cambridge team focused on the most common type of ovarian cancer, called high-grade serous ovarian carcinoma.

A different type of blood test already exists for monitoring ovarian cancer. But according to one of the lead researchers, Dr James Brenton, it has issues.

The test looks for a molecule called CA-125 in the blood, says Brenton. “But it’s also released by normal cells as well as cancerous cells. And its levels don’t change quickly enough in response to initial rounds of chemotherapy.”

Collectively, says Brenton, this means the CA-125 test isn’t specific enough for the disease, and it’s not sensitive enough to pick up early how a tumour is responding to treatment.

So the team went on the hunt for a DNA marker that might be better.

The stretch of DNA they looked for carries the recipe for a key molecule linked to cancer, called p53.

It’s a chief controller of decisions on when a cell, normal or cancerous, decides to grow or divide – we’ve previously blogged about it here.

Crucially, it’s faulty in almost all ovarian cancer patients, so the researchers could look specifically for this faulty DNA that tumour cells might be releasing into to blood.

To do this, the team looked at blood samples from a group of 40 women with ovarian cancer taken before, during and after treatment, as well as CT scans which showed the size of the tumour and information on how long it took for the cancer to progress.

What did they find?

And they compared all the data to the results of tests for CA-125.

First of all, the researchers focused on the samples collected before the women’s cancers were treated with chemotherapy. They looked at how well levels of CA-125 and the faulty p53 DNA each compared to the initial size of the tumour as seen on a CT scan.

Importantly, the researchers found that levels of faulty p53 DNA matched up well with tumour size. This wasn’t the case for levels of CA-125. This means that p53 DNA could be a better measure of ovarian cancer than what is used today.

Next, they examined how the amount of faulty p53 DNA in the blood samples changed after chemotherapy treatment. The theory being that if the tumour shrinks following treatment then the levels of faulty p53 DNA in the blood will drop. And these changes could point to how long the tumour might be held under control.

The researchers found that when chemotherapy triggered a fall of over 60% in the amount of p53 DNA in the blood, these patients had a longer time before their disease got worse.

“Though we’re at an early stage, the results are an exciting signal that levels of faulty DNA in the blood are related to the tumour size, and that changes in these levels could one day be a signpost for doctors and patients to decide if treatment is working for them,” says Brenton.

We’re not there yet

While these early results are positive, the researchers do point out a few issues.

First of all, the kind of trial they carried out is what’s known as retrospective. This means that they didn’t plan the samples they would collect ahead of time, rather they went back and looked at samples that were already available and analysed them.

This also means the researchers can’t account for differences among these samples that may affect the results. This includes the kind of treatment the women received – they didn’t all have the same therapy and so this could be an influencing factor.

The research world believes that measuring faulty DNA in blood will be very useful

– Dr James Brenton

And for now this was just a small study of 40 women. The more people there are in a trial the more confident we can be in the results, as chance has less of an opportunity to skew results.

The researchers are already working on this by using the test in larger groups of women who are participating in clinical trials.

Step by step

These are positive early signs. Science builds on knowledge and this work adds to what’s already known and will be added to in turn.

Larger, more controlled trials will be needed before the technique could be rolled out to clinics and patients as standard. But these results move us a step closer to improving the way doctors monitor ovarian cancer.

“The research world believes that measuring faulty DNA in blood will be very useful,” says Brenton.

And the potential these tests have is far reaching. Having early information on a patient’s response could help doctors switch to a different treatment if needed, says Brenton.

So much of the progress we’ve yet to make is around helping diagnosis and prognosis to happen more quickly and simply. Even though it might be some way off, tests like these would be a great addition to a doctor’s toolkit.