Indian Institute of Technology Madras researchers have developed an Artificial Intelligence-based tool, ‘PIVOT’, that can predict cancer-causing genes in an individual and help in devising personalised cancer treatment strategies.

“The prediction is based on a model that utilises information on mutations, expression of genes, and copy-number variation in genes and perturbations in the biological network due to an altered gene expression”, says a release.

The research was led by Raghunathan Rengaswamy, Dean (Global Engagement), IIT Madras, and Professor, Department of Chemical Engineering; Karthik Raman, Associate Professor, Bhupat and Jyoti Mehta School of Biosciences, and a Core Member, Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI) and Malvika Sudhakar, Research Scholar.

The findings of the research have been published in a peer-reviewed journal Frontier in Genetics (https://doi.org/10.3389/fgene.2022.854190).

The tool is based on a machine learning model that classifies genes as tumour suppressor genes, oncogenes or neutral genes. The tool was able to successfully predict both the existing oncogenes and tumour-suppressor genes. Although there are tools available to identify personalised cancer genes, they use unsupervised learning and predict based on presence and absence of mutations in cancer-related genes.

This study, however, is the first one to use supervised learning and takes into account the functional impact of mutations while making predictions, the release said.

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