IIT-M researchers develop AI tool for ‘personalised cancer diagnosis’
‘PIVOT,’ developed by IIT-Madras researchers, is designed to predict genes that are responsible for causing cancer in an individual.
CHENNAI: Indian Institute of Technology Madras (IIT Madras) Researchers have developed an Artificial Intelligence-based tool, ‘PIVOT’, that can predict cancer-causing genes in an individual. This tool will ultimately help in devising personalised cancer treatment strategies.
According to World Health Organisation, cancer is a leading cause of death worldwide and accounted for nearly one in six deaths in 2020.
Cancer is an uncontrolled growth of cells that can occur due to mutations in oncogenes or by tumor suppressor genes or both. However, not all mutations necessarily result in cancer. Therefore, it is important to identify genes that are causing cancer to devise appropriate personalised cancer treatment strategies.
‘PIVOT,’ developed by IIT-Madras researchers, is designed to predict genes that are responsible for causing cancer in an individual. 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, the institution release on Wednesday said.
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, said, “Cancer, being a complex disease, cannot be dealt with in a one-treatment-fits-all fashion. As cancer treatment increasingly shifts towards personalized medicine, such models that build toward pinpointing differences between patients can be very useful.”
According to him, the tool is based on a machine learning model that classifies genes as tumor suppressor genes, oncogenes or neutral genes. The 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.
Current cancer treatments are known to be detrimental to the overall health of the patient. Knowledge of the genes responsible for the initiation and progression of cancer in patients can help determine the combination of drugs and therapy most suitable for a patient’s recovery.