IIT develops AI-based model to help identify cancer genomes

This technique will tackle the complexity and size of DNA sequencing datasets and can greatly help in pinpointing key changes in the genomes, a difficult proposition with present methodologies. 

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 difficult. 

Explaining the rationale behind this study, B Ravindran, head, Robert Bosch Centre for Data Science and AI (RBCDSAI), IIT Madras, said, “One of the major challenges faced by cancer researchers involves the differentiation between the relatively small number of ‘driver’ mutations that enable the cancer cells to grow and the large number of ‘passenger’ mutations that do not have any effect on the progression of the disease.” 

The practical applications of the research include, given their vital role in tumour progression and development, computational prioritisation of cancer driver mutations. Understanding the underlying mechanism of these alterations will help identify the most appropriate treatment strategy for a patient in an approach known as ‘precision oncology’. 

The researchers hope that the driver mutations predicted through 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.”