Head and neck cancers have increased significantly over the last 30 years. In Germany, there are about 18,000 to 20,000 new cases of head and neck tumors every year. In particular, the incidence of carcinomas of the middle pharynx has increased, which is associated with the increase in human papillomavirus (HPV) infections.
Using a machine-learning-based method, an interdisciplinary team of researchers led by Sara Wickström at the University of Helsinki, in collaboration with the University of Turku and the Max Planck Institute for Molecular Biomedicine in Germany, has analyzed hundreds of biobank patient samples at the level of individual cells. The new technology combines indicators of cancer cell behavior and the architecture of the tumor and surrounding healthy tissue to create a kind of "fingerprint" for each patient that can be used to assess prognosis and response to cancer therapy . The paper is published in the journal Cell .
Two groups of patients The most important outcome of the study was the development of a new imaging method that combines the analysis of biomarkers of cell behavior with morphological analyses of the shape of individual cells and the structure of the entire tumor tissue. This method identified two new, previously undiscovered patient groups: The first group had an exceptionally good prognosis, while the second had an exceptionally poor prognosis. The difference was explained by a specific combination of a particular cancer cell state and the c.