Glioblastoma is a fast and aggressively growing tumour in the brain and spinal cord. The average life expectancy post diagnosis is 14-16 months, just about 1% of patients survive at least 10 years. This form of tumour does not have any cure but treatments might slow cancer growth and reduce symptoms. Despite the ongoing research being done to understand this tumour, therapeutic options remain very limited and expected survival rate of less than 2 years post initial diagnosis. Keeping in mind these facts about this deadly tumour, researchers at IIT Madras, India have developed a machine learning-based computational tool named ‘GBMDriver’ (GlioBlastoma Mutiforme Drivers)for better detection of cancer-causing tumours (both driver mutations and passenger mutations) in the spinal cord and brain.
The research team has successfully identified the important amino acid features for identifying cancer-causing mutations and achieved the highest accuracy for differentiating between driver and neutral mutations. The team hopes that this tool will aid in prioritizing driver mutations in Glioblastoma and assist in identifying potential therapeutic targets to thus help in developing drug design strategies. Presently this tool is publicly available online.
Source: Thehindubusinessline.com
