AIResearchers at the IIT Madras have developed an AI-based tool, PIVOT, that can predict cancer

Researchers at the Indian Institute of Technology Madras have developed an Artificial Intelligence-based tool, PIVOT, that can predict cancer Including Breast Invasive Carcinoma, Colon Adenocarcinoma, and Lung Adenocarcinoma-causing genes in an individual. They are planning to extend it further to many more cancer types. According to World Health Organization (WHO), cancer is a leading cause of death worldwide and accounted for nearly one in six deaths in 2020.

PIVOT will ultimately help in devising personalized cancer treatment strategies. This AI tool is based on a machine learning model that classifies genes as tumor suppressor genes, oncogenes, or neutral genes. The prediction is based on a model that utilizes the information on mutation, expression of genes, and copy number variation in genes and perturbations in the biological network due to an altered gene expression. This early information can not only help prevent cancer but even devise personalized cancer treatment strategies.

PIVOT for cancer prediction and treatment strategies:

IIT Madras research team is working on a list of personalized cancer-causing genes, which help in finding a suitable drug for patients based on their personalized cancer profile. The mechanism behind the PIVOT prediction of cancerous genes is based on a model that utilizes information on mutations, expression of genes, and copy number variation in genes and perturbations in the biological network due to an altered gene expression.

Cancer is an uncontrolled growth of cells that can occur due to mutations in oncogenes or tumor suppressor genes or both. Cancer, being a complex disease, cannot be dealt with in a one-treatment-fits-all fashion. Since all mutations do not necessarily result in cancer, therefore, it is important to identify genes that are causing cancer to devise appropriate personalized cancer treatment strategies. As cancer treatment increasingly shifts towards personalized medicine, such models that build toward pinpointing differences between patients can be very useful.

The PIVOT tool was able to successfully predict both the existing oncogenes and tumor-suppressor genes like TP53, and PIK3CA, among others, and new cancer-related genes such as PRKCA, SOX9, and PSMD4. This AI tool helps push these boundaries and presents prospects for experimental research based on the genes identified. The research area of precision medicine is still at a nascent stage. This study, however, is the first one to use supervised learning and takes into account the functional impact of mutations while making predictions.

Meanwhile, the research was led by Prof. Raghunathan Rengaswamy, Dean (Global Engagement), IIT Madras, and Professor, Department of Chemical Engineering, IIT Madras, Dr. Karthik Raman, Associate Professor, Bhupat and Jyoti Mehta School of Biosciences, IIT Madras and a Core Member, Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), IIT Madras, and Ms. Malvika Sudhakar, a Research Scholar, IIT Madras. Moreover, the findings of the research have been published in a peer-reviewed journal Frontier in Genetics.