The new biomarker that predicts cancer (lat. Carcinoma) was developed by investigators from the Institute of Cancer Research, London, and the University of Edinburgh. Scientists have used artificial intelligence to predict how cancers will progress and evolve – so that doctors can design the most effective treatment for each patient. They developed a new technique called REVOLVER (Repeated evolution of cancer), which picks out patterns in DNA mutation within cancers and uses the information to forecast future genetic changes. The ever-changing nature of tumors is one of the biggest challenges in treating cancer – with cancers often evolving to a drug-resistant form.
Scientists were able to use their analysis of genetic changes to predict cancer’s next move – allowing doctors to stay one step ahead. If doctors can predict how a tumor will evolve, they could intervene earlier to stop cancer in its tracks before it has had a chance to evolve or develop resistance, increasing the patient’s chances of survival. Scientists at the ICR and the University of Edinburgh working collaboratively with colleagues from the University of Birmingham, Stanford University and Queen Mary University London, also found that there was a link between certain sequences of repeated tumor mutations and survival outcome.
This suggests that repeating patterns of DNA mutations could be used as an indicator of prognosis, helping to shape future treatment. For example, the researchers found that breast tumors which had a sequence of errors in the genetic material that codes for the tumor-suppressing protein p53, followed by mutations in chromosome 8, survived less time than those with other similar trajectories of genetic changes. The ICR team and their colleagues developed a new machine learning technique which transfers knowledge about tumors across similar patients. This method identifies patterns in the order that genetic mutations occur in tumors that are repeated both within and between patients’ tumors, applying one tumor’s pattern of mutations to predict another’s.
The researchers used 768 tumor samples from 178 patients reported in previous studies for lung, breast, kidney and bowel cancer, and analyzed the data within each cancer type respectively to accurately detect and compare changes in each tumor. By identifying repeating patterns and combining this with current knowledge of cancer biology and evolution, the scientists could predict the future trajectory of tumor development.
If tumors with certain patterns are found to develop resistance to a particular treatment, this novel methodology could be used to predict if patients will develop resistance in the future. According to study leader Dr. Andrea Sottoriva, the team leader in Evolutionary Genomics and Modelling at the ICR, they have developed a powerful artificial intelligence tool which can make predictions about the future steps in the evolution of tumours based on certain patterns of mutation that have so far remained hidden within complex data sets. With this tool, scientists hope to remove one of cancer’s trump cards – the fact that it evolves unpredictably.