Researchers at IIT Madras have developed a machine learning-based computational tool for better detection of cancer-causing tumours in the brain and spinal cord. Named ‘GBMDriver’ (GlioBlastoma Mutiforme Drivers), this tool is publicly available online.

Glioblastoma is a fast and aggressively growing tumour in the brain and spinal cord. Although there has been research undertaken to understand this tumour, therapeutic options remain limited with an expected survival rate of less than two years from the initial diagnosis.

It is important to evaluate the functional consequences of variants in proteins, which are involved in Glioblastoma to advance the therapeutic options for patients. However, functional validations to identify driver mutations (disease-causing mutations) from all the observed variants would be strenuous work.

The GBMDriver was developed specifically to identify driver mutations and passenger mutations in Glioblastoma.

GBMDriver can be accessed using the following link:

Explaining the key findings of their research, M Michael Gromiha, Department of Biotechnology, IIT Madras, said, “We have identified the important amino acid features for identifying cancer-causing mutations and achieved the highest accuracy for distinguishing between driver and neutral mutations. We hope that this tool could help to prioritise driver mutations in Glioblastoma and assist in identifying potential therapeutic targets, thus helping to develop drug design strategies.”