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IIT Madras Researchers Develop Machine Learning Tool to detect Tumour in the Brain & Spinal Cord

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.

CHENNAI, 1 st May 2023: Indian Institute of Technology Madras (IIT Madras) 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.

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

(passenger mutations are neutral mutations) in Glioblastoma. GBMDriver can be accessed

using the following link

- https://web.iitm.ac.in/bioinfo2/GBMDriver/index.html.

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, 9386 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 1809 mutants, which is better than existing computational methods. This method is

completely dependent on protein sequence.

This 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, U.S., 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

(https://doi.org/10.1093/bib/bbac451).

Explaining the key findings of their research, Prof. 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 (GBMDriver) could help to

prioritize driver mutations in glioblastoma and assist in identifying potential therapeutic targets,

thus helping to develop drug design strategies.”

The Key Applications of this research include

  •  The methodology and features are portable to apply for other diseases.
  •  This method could serve as one of the important criteria for disease prognosis.
  •  Valuable resource to identify mutation-specific drug targets to design therapeutic

strategies.

Ms. Medha Pandey, a PhD Student at IIT Madras, said, “Our method showed an accuracy

and AUC of 73.59% and 0.82 respectively on 10-fold cross-validation and 81.99% and 0.87 in a

blind set of 1809 mutants. We envisage that the present method is helpful to prioritize driver

mutations in glioblastoma and assist in identifying therapeutic targets.”

ABOUT IIT MADRAS

Indian Institute of Technology Madras (IITM) was established in 1959 by the Government of India as an

‘Institute of National Importance.’ The activities of the Institute in various fields of Science and Technology

are carried out in 16 academic departments and several advanced interdisciplinary research academic

centres. The Institute offers undergraduate and postgraduate programmes leading to B.Tech., M.Sc.,

M.B.A., M.Tech., M.S., and Ph.D., degrees in a variety of specialisations. IITM is a residential institute

with more than 600 faculty and 9,500 students. Students from 18 countries are enrolled here. IITM fosters

an active entrepreneurial culture with strong curricular support and through the IITM Incubation Cell.

Recognized as an Institution of Eminence (IoE) in 2019, IITM has been ranked No.1 in the ‘Overall’

Category for the fourth consecutive year in India Ranking 2022 released by National Institutional Ranking

Framework, Ministry of Education, Govt. of India. The Institute has also been ranked No.1 in the

‘Engineering Institutions’ category in the same Rankings for seven consecutive years – from 2016 to

2022. It was also adjudged as the ‘Top innovative Institution’ in the country in Atal Ranking of Institutions

on Innovation Achievements (ARIIA) in 2019, 2020 and 2021. ARIIA Ranking was launched by the

Innovation Cell of Ministry of Education.

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