Adding to the CNS Tumor Toolbox

To appropriately diagnose and treat a tumor, it’s essential to understand its origins – particularly when it comes to central nervous system (CNS) tumors, says Stefan Pfister, Director of the preclinical program at NCT Heidelberg’s Hopp Children’s Cancer Center. “The reason I wanted to focus on CNS tumor classification is the notion that a substantial proportion of diagnostic reports are ambiguous and can leave the neuro-oncologist in a guessing situation when making treatment decisions. We think this affects about 10-15 percent of patients, with an enrichment in the pediatric population.” Treating one in every 10 brain tumor patients using guesswork is far from ideal, so Pfister led a large, multi-institutional research group in creating a DNA methylation-based approach to classifying CNS tumors. They used specific DNA methylation signatures found in different cell types to determine in which cells the tumor originated. Next, they developed an algorithm to sort 82 different CNS tumors based on their methylation signatures (1).

Pfister says, “[The algorithm] adds an additional, highly powerful tool to the neuropathologists’ toolbox. It is robust, can be done from very small amounts of FFPE tissue (even previously stained sections), and gives a confidence score. It’s not meant to replace the neuropathologist by any means, but rather to improve diagnostic accuracy.” The researchers have also created an online portal (molecularneuropathology.org); with it, they hope to grow the number of tumors they can help diagnose by crowdsourcing datasets from fellow neurologists. The more data the algorithm has, the smarter it will become. So far, the interface has over 10,000 datasets uploaded, with 75 percent of participants agreeing to use the classification for further refinement of their samples. Pfister says, “I think this is a great example of community-based learning!” Algorithms – and their implementation – will  continue to evolve, and Pfister believes that DNA methylation analysis will become a “general and universal tool that could one day replace many gene-specific tests.”

Newsletters

Receive the latest pathology news, personalities, education, and career development – weekly to your inbox.

I have read and understand the Privacy Notice*

Subscribe

References

1. D Capper et al., “DNA methylation-based classification of central nervous system tumours”, Nature, 555, 469 – 474 (2018). PMID: 29539639.

About the Author(s)

William Aryitey

My fascination with science, gaming, and writing led to my studying biology at university, while simultaneously working as an online games journalist. After university, I travelled across Europe, working on a novel and developing a game, before finding my way to Texere. As Associate Editor, I’m evolving my loves of science and writing, while continuing to pursue my passion for gaming and creative writing in a personal capacity.

More Articles by William Aryitey