Cancer prediction

The identification of individual or clusters of predictive genetic alterations might help in defining the outcome of cancer treatment, allowing for the stratification of patients into distinct cohorts for selective therapeutic protocols. This approach, currently developed with the aid of Artificial Intelligence and Machine Learning, might result in maximising the therapeutic success and minimizing harmful effects in cancer patients. Here, we showcase some recent papers which describe distinct aspects of precision oncology, the ability to stratify patients with distinct prognostic features and therapeutic requirements, as well as its liaison with the current complexity of the underlying molecular mechanisms.