Chennai, May 1 : The Indian Institute of Technology Madras (IIT-M)
Researchers have developed a Machine Learning-based computational
tool for better detection of cancer-causing tumours in the brain and spinal
cord.
Called ‘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, a IIT-M release said
today.
It said it is important to evaluate the functional consequences of variants
in proteins, which are involved in Glioblastoma to advance the therape
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 (passenger mutations are neutral mutations)
in Glioblastoma.
In order to develop this web server, a variety of factors such as amino
acid properties, di- and tri-peptide motifs, conservation scores, and
Position Specific Scoring Matrices (PSSM) were taken into account.
In this study, 9,386 driver mutations and 8728 passenger mutations in
glioblastoma were analysed. Driver mutations in glioblastoma were
identified with an accuracy of 81.99 percent, in a blind set of 1,809
mutants, which is better than existing computational methods. This
method is completely dependent on protein sequence.
The research was led by Prof.M.Michael Gromiha, Department of
Biotechnology, IIT-Madras. His team included Ms. Medha Pandey,
PhD Student, IIT-Madras and two IIT-Madras alumni Dr. P. Anoosha
currently in The Ohio State University, Columbus, and Dr. Dhanusha
Yesudhas who is now at the National Institute of Health, U.S.
Their findings were published in the reputed peer-reviewed journal
Briefings in Bioinformatics.(UNI)