Improving our ability to predict how a tumour will evolve by overcoming the limitations of analyses that only consider individual genetic mutations. This goal is possible thanks to a new method called ASCETIC (Agony-baSed Cancer EvoluTion InferenCe), developed by Milano-Bicocca, which is capable of reconstructing patterns of tumour evolution for each patient and subsequently identifying evolutionary patterns that are repeated in different patients.
The method, described in the article "Evolutionary signatures of human cancers revealed via genomic analysis of over 35,000 patients" just published in Nature Communications, was developed by a multidisciplinary team led by Daniele Ramazzotti, Professor of Informatics at the Department of Medicine and Surgery of the University of Milano-Bicocca, in collaboration with Alex Graudenzi (Department of Informatics), Luca Mologni (Department of Medicine and Surgery) and the researchers Diletta Fontana, Ilaria Crespiatico and Valentina Crippa, for the evaluation and validation of the results.
In this study, ASCETIC was applied to data from over 35,000 tumours, including patients with various blood disorders, patients with early or advanced lung cancer and many others. In addition, the results were validated against independent datasets to ensure their reliability and generalisability.