Researchers at IIT Madras have developed an AI-based mathematical model to identify cancer-causing alterations in cells. The algorithm uses a relatively unexplored technique of leveraging DNA composition to pinpoint genetic alterations responsible for cancer progression.

Cancer is caused due to the uncontrolled growth of cells driven mainly by genetic alterations. In recent years, high-throughput DNA Sequencing has revolutionised the area of cancer research by enabling the measurement of these alterations. However, due to the complexity and size of these sequencing datasets, pinpointing the exact changes from the genomes of cancer patients is notoriously difficult.

The research was led by Prof. B. Ravindran, Head, Robert Bosch Centre for Data Science and AI (RBCDSAI), Dr. Karthik Raman, Coordinator, Centre for Integrative Biology and Systems Medicine (IBSC), and Mr. Shayantan Banerjee, a Master’s student. The results of the experiment have been published in the peer-reviewed journal Cancers.

"One of the major challenges involves the differentiation between the relatively small number of ‘driver’ mutations that enable cancer cells to grow and the large number of ‘passenger’ mutations that do not have any effect on the progress of the disease,” Prof Ravindran said.

The research will help identify the most appropriate treatment strategy for a patient. Further, it will help tailor the treatments not only to a specific illness but also to a specific person’s genetic make-up. The researchers hope that the driver mutations predicted through their mathematical model will ultimately help discover potentially novel drug targets and will advance the notion of prescribing the “right drug to the right person at the right time.”