Easy diagnosis of brain tumours

The team say that a test for detecting glioma using urine is the first of its kind in the world. Although the research, published in EMBO Molecular Medicine, is in its early stages and only a small number of patients were analysed, the team say their results are promising. Detecting brain tumour cell-free DNA (cfDNA) in the blood has historically been difficult because of the blood-brain-barrier, which separates blood from the cerebrospinal fluid (CSF) that surrounds the brain and spinal cord, preventing the passage of cells and other particles, such as cfDNA. The researchers, led by Dr Florent Mouliere who is based at the Rosenfeld Lab of the Cancer Research UK Cambridge Institute and at the Amsterdam UMC, and Dr Richard Mair, who is based at Cancer Research UK Cambridge Institute and the University of Cambridge developed two approaches in parallel to overcome the challenge of detecting brain tumour cfDNA.

The first approach works for patients who have previously had glioma removed and biopsied. The team designed a tumour-guided sequencing test that was able to look for the mutations found in the tumour tissue within the cfDNA in the patient’s urine, CSF, and blood plasma.

A total of eight patients who had 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. The test was able to detect cfDNA in 7 out of 8 CSF samples, 10 out of the 12 plasma blood samples and 10 out of the 16 urine samples. For the second approach the researchers looked for other patterns in the cfDNA that could also indicate the presence of a tumour, without having to identify the mutations. They analysed 35 samples from glioma patients, 27 people with non-malignant brain disorders, and 26 healthy people. They used whole genome sequencing, where all the cfDNA of the tumour is analysed, not just the mutations. They found in the blood plasma and urine samples that fragments of cfDNA, which came from patients with brain tumours were different sizes than those from patients with no tumours in CSF. They then fed this data into a machine learning algorithm which was able to successfully differentiate between the urine samples of people with and without glioma.

The researchers say that while the machine learning test is cheaper and easier, and a tissue biopsy from the tumour is not needed, it is not as sensitive and is less specific than the first tumour-guided sequencing approach.

Source: University of Cambridge