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The brain tumor diagnostic conundrum

Cancer is a leading cause of death worldwide, and brain tumors are the most common cause of cancer death in children. Luna Djirackor works at the Oslo University Hospital, Norway, where her team sees around 300 adults and 30 children with brain tumors every year. A typical case they observe is that of a preadolescent coming to the clinic with their parents, who has become increasingly unsteady, started to spill their drink, and recently developed slurred speech. A magnetic resonance imaging (MRI) scan of their brain reveals a mass, which, as Luna described,* “you can imagine is completely devastating and so emotionally challenging for the family.”

The first thought of the clinician is, could this be an ependymoma—a tumor in the brain or spinal cord—of which there are four molecular subgroups based on their genomic/epigenomic alterations. Survival prognosis varies widely for these subgroups. It could alternatively be a medulloblastoma, of which there are also four subgroups, and again, each with differing prognoses. As the outcomes are so variable between tumor types, it is critical to identify which type of tumor is present. The location of the tumor also needs to be confirmed: the location of the tumor itself and its potential expansion, plus consequences of its resection, will vary depending on the location. Together, these variables can lead to difficult risk vs. benefit scenarios—the growth of the tumor vs. damage from resection could each lead to substantially reduced quality of life.

The current typical workflow for a patient arriving in Luna’s neurosurgery ward is as follows: the referred patient will have an MRI scan, which is followed by surgery within several days or weeks, with the aim of relieving pressure within the brain and debulking the tumor tissue. A biopsy is taken during surgery and sent to histology, from which a diagnosis is arrived at within an hour or so, for the surgeon to then decide whether to do a partial resection or completely remove the tumor. Yet this workflow is based on a clear diagnosis, which is not always the case—in some instances for example, after the histological analysis, further molecular subtyping can reach a conflicting conclusion. Luna sought to find a faster and more specific workflow here, with the overall vision of improving patient management and outcomes in the not-too-distant future.

DNA methylation is the key

In 2018, a study was published detailing successful, precise DNA methylation-based classification of central nervous system tumors. Luna emphasised that “this study was such a landmark study for the field”, changing diagnostic grading criteria and patient management. However, the turnaround time for the workflow presented was days to weeks.

At London Calling 2017, Philipp Euskirchen presented a study on how nanopore sequencing showed the potential for same-day, accurate genomic and epigenomic subtyping of brain tumors. “That was absolutely amazing.” Luna’s team saw the truly transformative potential for brain tumor surgery if turnaround times could be within 2 hours and sought to investigate the possibilities of this.

To that end, they set up a whole-genome nanopore sequencing and methylation classification workflow, using the Rapid Barcoding Kit for library preparation and the MinION sequencer, barcoding 10–12 samples per run, and sequencing for 24 hours (for samples from both retrospective and prospective cases). One intraoperative run  was also performed for one individual. The team used the nanoDx pipeline for analysis; this package contains all the necessary software needed, and outputs a PDF report containing the copy number profile, methylation-based classification results, and a plot of the subtypes.

Demonstrating Nanopore’s potential for rapid tumor classification

On research samples from 55 adults and 50 children, the methylation analysis results obtained from a couple of hours of nanopore sequencing matched the pathology results from weeks later. Nanopore DNA methylation analysis (NDMA) also correctly classified tumor tissue for which histology results had been inconclusive. This suggested that “even on a really tiny little piece of tissue with not too much tumor” the nanopore sequence data could deliver the correct result.

Having confirmed that their NDMA workflow was sensitive, Luna’s team next tested it out on a further 20 intraoperative research biopsy samples, reducing the sequencing time to 30–60 minutes; plus an NDMA analysis time of a median of 28 minutes. The first report could be returned within 91–161 minutes. Their sequencing statistics suggested that only 30 minutes, or sometimes even less, was required to detect ~3,500 CpG sites, which usually provided “a really solid call.”

Furthermore, out of the 20 intraoperative samples analyzed, the data suggested that nanopore-based DNA methylation analysis had the potential to impact surgical strategy and management in 12 of those cases.

Overall, Luna’s work demonstrated the potential impact that nanopore sequencing technology could have on the rapid and precise classification of brain tumors, allowing Luna to get one step closer to reaching her goal of “giving the best chance possible to these families and these patients.”

* London Calling 2021 online conference, hosted by Oxford Nanopore Technologies; May 19–21, 2021.

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