The AI ​​model could be used to provide more effective care for skin cancer patients

The AI ​​model could be used to provide more effective care for skin cancer patients

The artificial intelligence model could be used to provide more effective care for skin cancer patients and could lead to similar breakthroughs in the diagnosis and treatment of other types of cancer.

Researchers from the University of Helsinki, HUS Comprehensive Cancer Center, Aalto University and Stanford University have developed an artificial intelligence model that predicts which skin cancer patients will benefit from a treatment that activates the immune system. In practice, the AI ​​model makes it possible to diagnose skin cancer with a blood test, determine the prognosis and determine targeted therapies with increasing precision.

The skin cancer study was published in the respected journal Nature Communications.

The right medication for the right patient

Strengthening the body's own defenses has proven to be a particularly effective therapy for skin cancer. The problem with therapies that activate the immune system are the differences between patient groups: While some patients can claim a cure, others do not benefit at all from the treatment.

Previous research has been unable to provide doctors with tools that would predict who will benefit from a treatment that activates the immune system. Proper targeting of therapies is extremely important because drug therapies are expensive and serious side effects are quite common.”

Jani Huuhtanen, Doctor and PhD candidate, University of Helsinki and Aalto University

A complex AI model for a simple question

The international research group hypothesized that the immune cells of patients for whom the therapy was ineffective do not recognize skin cancer as an enemy, and therefore the patients do not benefit from the treatment.

Using the AI ​​model, the group analyzed samples from nearly 500 skin cancer patients and compared them with samples from nearly 1,000 healthy people. To aid in the interpretation, the researchers used a different AI model developed by the Mark M. Davis lab at Stanford University. From these samples, the researchers simply calculated the number of immune cells that recognized skin cancer.

As expected, more skin cancer-sensitive immune cells were found in melanoma patients than in healthy patients.

“This finding could make it possible to identify skin cancer from a blood sample in the future,” says Satu Mustjoki, Professor of Translational Hematology at the University of Helsinki.

Additionally, skin cancer patients who had more immune cells that recognized skin cancer were more likely to benefit from therapies that activated the immune system than those who lacked such cells.

Focusing the AI ​​model on other types of cancer

The use of AI models in medicine has increased exponentially, but their application in patient care requires long-term collaboration between doctors and researchers specializing in artificial intelligence.

“In future studies, our goal is to explore the use of the AI ​​model now developed and whether it can also predict treatment response for novel cancer therapies still in development,” says Harri Lähdesmäki, associate professor of computational biology and machine learning of Aalto University.

“Our AI model is agile and adaptable, making it possible to calculate the number of cancer-detecting immune cells in other types of cancer, including breast cancer, lung cancer and blood cancer,” adds Jani Huuhtanen.

“All of our research is based on open source software, which makes our AI model available to other researchers and doctors and also enables its further development,” says Huuhtanen.

Source:

University of Helsinki

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