Learning to See Cancer in Early Detection Research

This article explores how scientists learn to detect ‘pre-cancer’, a new diagnostic category defined by the risk of developing the titular disease. This process entails the observation of ‘raw signals’ that stand for potential molecular and metabolic changes in animal and human tissues and their validation as ‘candidate biomarkers’. I draw on ethnographic fieldwork conducted alongside a multidisciplinary group of researchers—physicists, biologists, mathematicians, computer scientists, and engineers, among others—all of whom worked as part of a research programme investigating the early signs and detection of cancer in the UK. ‘Signals’ detected through scientific experiments are intimately entangled with the sensing technologies and analytical techniques used. As previously unknown microscopic realities emerge, scientists seek to negotiate the uncertainty surrounding the identification and validation of signals as candidate biomarkers before they can be tested in clinical trials.