Real-Time DNA Analysis Changes the Game for Neurosurgery
Dr. Alena van Bömmel, most recently a postdoc at the MPIMG, Prof. Dr. Helene Kretzmer, most recently group leader „Computational Genomics“ at the MPIMG, and Mara Steiger, PhD student (f. l.) - © MPIMG
Researchers have developed a groundbreaking method that allows neurosurgeons to identify the specific type of brain tumor during surgery, enabling more personalized and precise treatment. According to a press release from the Max Planck Institute, this innovation combines DNA methylation analysis with advanced machine learning to deliver critical information within the timeframe of an operation.
The interdisciplinary team from the University Medical Center Schleswig-Holstein (UKSH), Kiel University, and the Max Planck Institute for Molecular Genetics in Berlin published their findings in Nature Medicine on February 28, 2025.
What makes this approach revolutionary is its speed and accuracy. Using nanopore sequencing, the technique identifies a tumor's "fingerprint" by analyzing methylation patterns. Since surgery provides limited time for sequencing, the researchers applied Bayes' theorem and developed a machine learning model that requires less than 0.1 percent of genetic data to classify tumors in under an hour.
Dr. Carolin Kubelt-Kwamin, senior physician at the Clinic for Neurosurgery, explains that this approach "elevates treatment from a technique-driven procedure to a personalized, disease-centered therapy."
This advancement addresses a significant challenge in neurosurgery. Modern analyses have shown that brain tumors fall into nearly 90 distinct categories, each requiring different treatment approaches. Until now, surgeons operated with limited information about tumor classification, risking damage to healthy brain tissue.
