The Ramón y Cajal Hospital applies artificial intelligence for the early detection of familial cancer

The Ramón y Cajal University Hospital, a public center of the Community of Madrid, will develop a tool based on Artificial Intelligence (AI) through the Hereditary Cancer Unit, thanks to a collaboration agreement with the Sener Foundation, to identify cancer risk. It will be developed jointly between the two institutions, based on anonymized information from 10,000 family trees (spanning three or more generations) and individual clinical data. This information includes data such as age at diagnosis, presence and type of tumors or relevant benign pathologies, among others.

Simplifying the decision-making process

The aim of this tool is to assist clinicians in their decision-making process by estimating an individual’s risk of having an inherited genetic susceptibility to cancer. Unlike other medical tests, germline DNA genetic studies can predict future disease development, improve early diagnosis and prevention and, additionally, can be relevant not only to the individual, but also to his or her family members. Currently, only one in 10 people who are decided, according to conventional methods, to undergo genetic testing have an alteration in their genes.

Advances in the understanding of the molecular mechanisms of cancer have made it possible to discover genes whose functional alteration carries a risk of developing certain malignant diseases, representing considerable progress and a challenge in the prevention, diagnosis, and treatment of tumors. It is estimated that between 5 and 10% of all cancers are hereditary, i.e., the person suffering from cancer is born with a genetic alteration that predisposes to a higher risk of developing this disease.

According to Dr. Carmen Guillén Ponce, head of the Medical Oncology section and head of the Family Cancer Unit at the Ramón y Cajal University Hospital, “artificial intelligence provides data analysis tools that can facilitate the decision-making process in clinical practice and, specifically, in the Family Cancer Unit, it will allow us to more accurately select families and individuals who are candidates for genetic testing to identify their hereditary risk of cancer. This has very important implications in terms of their follow-up for early detection of cancer, their treatments, if needed, and their offspring. Our aim is to provide excellent and humane healthcare, centered on the individual, patients, and their families, and to achieve this we seek to transfer knowledge to the well-being of patients and society, through prevention, research and innovation,” concludes Guillén.

The head of the project at Sener, Daniel Martínez, emphasizes that “being able to analyze all the family and clinical data as a whole and thanks to the application of AI techniques will make it possible to obtain an analytical tool of great utility for the clinicians in charge of interpreting the individual’s genogram and to more efficiently select candidates for a germline genetic study. We are pleased to put the knowledge of our engineers at the service of clinicians, with the consequent utility for their work and, ultimately, for the well-being of individuals and families.”