Cancer Research UK scientists report “very promising results” at detecting for the first time signs of glioma through urine, according to a study in EMBO Molecular Medicine.
If future trials are successful, these tests could be used by GPs to monitor patients at high risk of brain tumours, which may be more convenient than having an MRI every three months, the standard method at the moment.
Michelle Mitchell, chief executive of Cancer Research UK said: “While this is early research, it’s opened up the possibility that within the next decade we could be able to detect the presence of a brain tumour with a simple urine or blood test. It’s great to see Cancer Research UK researchers making strides in this important field.”
Sue Humphreys, a brain tumour patient from Walsall, said that these tests could be “life changing” if found to be as accurate as the standard MRI for monitoring brain tumours.
Making monitoring easier
When people have surgery to remove a brain tumour, the likelihood of it returning can be high, so they are monitored with an MRI scan every three months, which is followed by a biopsy if there’s evidence of cancer. To make monitoring easier, scientists are looking for ways to detect cancer in blood, urine or other fluids – so called ‘liquid biopsies’.
“Liquid biopsies are a huge area of research interest right now because of the opportunities they create for improved patient care and early diagnosis,” said Mitchell. Despite the excitement, tests to pick up mutated DNA shed by brain tumour cells when they die, known as cell-free DNA (cfDNA), have proved elusive.
Researchers have previously looked at detecting cfDNA in cerebrospinal fluid (CSF), but the spinal taps needed to obtain it can be dangerous for people with brain tumours, so are not appropriate for patient monitoring.
Detecting brain tumour cfDNA in the blood has historically been difficult because of the blood-brain-barrier, which separates blood from the cerebrospinal fluid that surrounds the brain and spinal cord, preventing the passage of cells and other particles, such as cfDNA.
Scientists have known that cfDNA with similar mutations to the original tumour can be found in blood and other bodily fluids such as urine in very low levels, but the challenge has been developing a test sensitive enough to detect these specific mutations.
The researchers, led by Dr Florent Mouliere at the Cancer Research UK Cambridge Institute and the Amsterdam UMC, and Dr Richard Mair at the Cancer Research UK Cambridge Institute, developed two approaches to overcome the challenge of detecting brain tumour cfDNA.
Test number 1: looking for specific DNA errors
The first approach works for patients who have previously had glioma removed and biopsied. The team designed a test that was able to look for the specific mutations found in the tumour biopsy within cfDNA in the patient’s urine, CSF, and blood plasma.
Eight patients with suspected brain tumours based on MRIs were included in this part of the study. Samples were taken at their initial brain tumour biopsies, alongside CSF, blood and urine samples.
By knowing where in the DNA to look, it was possible for research to pick out mutations even in the tiny amounts of cfDNA found in the blood plasma and urine. The test was able to detect cfDNA in seven out of eight CSF samples, 10 out of the 12 plasma blood samples and 10 out of the 16 urine samples.
Test number 2: using an algorithm to look for patterns
In a second approach, researchers looked for other patterns in the cfDNA that could also indicate the presence of a tumour, without having to identify specific mutations. They analysed 35 samples from glioma patients, 27 people with non-malignant brain disorders, and 26 healthy people.
The team found that fragments of cfDNA in blood or urine samples from patients with brain tumours were different sizes than those from people with non-malignant brain disorders or healthy volunteers. By feeding these data into a machine learning algorithm, they were successfully able to differentiate between the urine samples of people with and without glioma.
The researchers say that while this machine learning test is cheaper and easier, and a tissue biopsy from the tumour is not needed, it’s not as sensitive and is less specific than the first, tumour guided, sequencing approach.
MRIs are not invasive or expensive, but they do require a trip to the hospital, and the three-month gap between checks can be a regular source of anxiety for patients.
“Talking to my patients, I know the three-month scan becomes a focal point for worry. If we could offer a regular blood or urine test, not only will you be picking up recurrence earlier, you can also be doing something positive for the patient’s mental health,” said Mair, who co-leads the Cancer Research UK Cambridge Centre Neuro-Oncology programme.
Humphreys agreed. “If patients can be given a regular and simple test by their GP, it may help not only detect a returning brain tumour in its earliest stages, it can also provide the quick reassurance that nothing is going on which is the main problem we all suffer from, the dreaded ‘Scanxiety’. The problem with three-monthly scans is that these procedures can get disrupted by other things going on, such as what we have seen with the COVID-19 pandemic. As a patient, this causes worry as there is a risk that things may be missed, or delayed, and early intervention is the key to any successful treatment.”
The researchers suggest that their tests could be used between MRI scans, and could ultimately be able to detect a returning brain tumour earlier.
Taking the test to the next level
The next stage of this research will see the team comparing both tests against MRI scans in a trial with patients with brain tumours who are in remission to see if it can detect if their tumours are coming back at the same time or earlier than the MRI.
If the tests prove that they can detect brain tumours earlier than an MRI, then the researchers will look at how they can adapt the tests so they could be offered in the clinic, which could be within the next 10 years.
“We believe the tests we’ve developed could in the future be able to detect a returning glioma earlier and improve patient outcomes,” said Mair.
Fragmentation patterns and personalised sequencing of cell-free DNA in urine and plasma of glioma patients
Florent Mouliere, Christopher G Smith, Katrin Heider, Jing Su, Ymke van der Pol, Mareike Thompson, James Morris, Jonathan C M Wan, Dineika Chandrananda, James Hadfield, Marta Grzelak, Irena Hudecova, Dominique-Laurent Couturier, Wendy Cooper, Hui Zhao, Davina Gale, Matthew Eldridge, Colin Watts, Kevin Brindle, Nitzan Rosenfeld, Richard Mai
Published in EMBO Molecular Medicine, 22 July 2021
Glioma-derived cell-free DNA (cfDNA) is challenging to detect using liquid biopsy because quantities in body fluids are low. We determined the glioma-derived DNA fraction in cerebrospinal fluid (CSF), plasma, and urine samples from patients using sequencing of personalised capture panels guided by analysis of matched tumor biopsies.
By sequencing cfDNA across thousands of mutations, identified individually in each patient’s tumour, we detected tumour-derived DNA in the majority of CSF (7/8), plasma (10/12), and urine samples (10/16), with a median tumour fraction of 6.4 × 10−3, 3.1 × 10−5, and 4.7 × 10−5, respectively. We identified a shift in the size distribution of tumour-derived cfDNA fragments in these body fluids.
We further analysed cfDNA fragment sizes using whole-genome sequencing, in urine samples from 35 glioma patients, 27 individuals with non-malignant brain disorders, and 26 healthy individuals. cfDNA in urine of glioma patients was significantly more fragmented compared to urine from patients with non-malignant brain disorders (P = 1.7 × 10−2) and healthy individuals (P = 5.2 × 10−9). Machine learning models integrating fragment length could differentiate urine samples from glioma patients (AUC = 0.80–0.91) suggesting possibilities for truly non-invasive cancer detection.
First, using tumor-guided sequencing in matched tissue and liquid biopsy, we compared the mutational burden and detection rate of cftDNA in CSF, plasma, and urine from GBM patients. We developed a whole exome sequencing approach that calls mutations that are private to or shared between multiple regions of the same tumor, in doing so affording greater confidence in the mutations calls. These mutations were then used to generate targeted panels for high depth sequencing of CSF, plasma, and urine. By integrating mutation signal across hundreds of mutations, we observed tumour-derived signal in the majority of CSF, plasma, and urine samples.
Then, a second more rapid and cost-effective approach was developed using low coverage WGS. This revealed a possible difference in the fragment sizes of urine cftDNA in cancer patients compared with healthy individuals. Subsequent application of a machine learning approach to this sequencing data led to the creation of classifiers that demonstrated an ‘area under the curve’ of between 0.8 and 0.91 for differentiating samples from patients and healthy controls.
The non-invasive nature of plasma and urine may permit more regular and less restrictive monitoring for GBM patients than CSF sampling. While the role of liquid biopsy for diagnosis has been the focus of much attention, both of the methods presented may provide utility in the follow-up setting in combination with imaging.
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