Scientific thinking is the only type of thinking that allows us to be critical and advance in improving patient health. It is our duty and our responsibility to carry out applied research
Skin cancer is the most common cancer in humans and, among the various common skin tumours, melanoma is the most aggressive and has the worst prognosis. Sun exposure habits and the ageing population are, nowadays, a growing problem in western societies.
The group focuses on the study of melanoma and non-melanoma skin cancer, as well as other skin conditions related to the risk of developing these cancers. The purpose is to improve prevention, early diagnosis and the achievement of a more personalised treatment of melanoma and non-melanoma skin cancer.
The group’s research is multidisciplinary and its members include dermatologists, pathologists, nurses, biologists, biotechnologists, engineers, physicists, technicians and other specialists.
Its research is translational. In other words, it combines clinical studies with more molecular studies and projects that combine the two aspects, with the aim of identifying improvements both in prevention and in patient diagnosis, management, monitoring and treatment. These improvements are transferred directly to patients, improving their quality of life and that of their families. The group uses a combination of new imaging technologies, molecular studies and artificial intelligence tools.
Thanks to the studies the group has carried out, it has been able to improve early diagnosis of skin cancer, reducing the number of benign lesions removed and diagnosing melanomas that are not very thick and have a good prognosis.
In addition, it has described the main melanoma susceptibility genes in the population and it has identified several molecular prognostic markers useful in clinical practice. With the group’s new research lines, it intends to improve the classification of patients into specific prognosis groups to improve their management and treatment. The group is aiming to identify prognostic and predictive biomarkers.