Computational model from TAU will make it possible to predict increased genetic risk for breast cancer
Findings may contribute towards a policy of personalized early detectionSupport this research
Researchers at Tel Aviv University (TAU) have developed a computational model that makes it possible to predict an individual woman’s genetic risk of developing breast cancer based on her genetic profile.
The research was based on a large-scale international study that included genomic data of about a quarter of a million women with and without breast cancer, then applied the findings to about 2,000 Israeli women. The researchers say that their method will allow health systems to move to a personalized early detection policy, when those who are identified as being at high risk will be tested from a younger age and more frequently. The screening tests may save lives and will save health system resources.
The research was conducted by doctoral student Hagai Levi under the guidance of Professor Rani Elkon of the Department of Human Molecular Genetics and Biochemistry at TAU’s School of Medicine and Professor Ron Shamir at TAU’s Blavatnik School of Computer Science. The study was carried out in collaboration with Professor Shai Carmi of the Faculty of Medicine at Hebrew University; Professor Shay Ben Shachar, Director of Precision Medicine and Genomics at Clalit Research Institute; and Dr. Naama Elefant of the Hadassah University Medical Center. The study was published on July 14, 2023, in the Journal of Medical Genetics.
Professor Elkon explains that in 2003 the sequencing of a draft of the human genome was completed, creating new opportunities for improvement in medicine with an emphasis on personalized medicine. The basic idea was that if doctors can determine whether a certain person is genetically predisposed to a certain disease, the more they can take appropriate preventive measures.
Professor Elkon adds that since then, extensive research effort has been invested to identify genetic differences between people which may indicate a genetic susceptibility to specific diseases, especially common diseases such as cancer, heart disease, diabetes, schizophrenia, and Alzheimer’s. Studies of this type, known as Genome-Wide Association Studies (GWAS), compare the genomes of sick and healthy people and find hundreds of genetic variants whose presence is associated with increased risk of having the disease. Each variant by itself increases the risk to a very small degree, but when a significant number of relevant variants accumulate in the genome of a certain person, their risk of getting sick increases significantly.
The studies assign a “genetic risk score” to each participant, and in large samples these scores typically follow a bell distribution: the majority of the population are in the middle, and at the two extremes are people with extremely high or low risk scores of having the same disease. The challenge of medicine is to identify in advance those people who have a high genetic tendency to get sick, especially from diseases that can be prevented or detected in early stages.
The current study was based on the findings of a huge international GWAS study that identified genetic variants associated with breast cancer by analyzing the genetic profiles of approximately 130,000 breast cancer patients from dozens of medical centers in Europe and the United States alongside approximately 100,000 healthy women who served as a control group.
The TAU researchers wanted to see if the findings of the international study could be used to reliably predict the risk of breast cancer of Israeli women, using a sample of about 1,000 patients and about 1,000 healthy women. “If a genetic predisposition to breast cancer is discovered in a woman, there is something that can be done! Early detection may save lives,” Professor Elkon says.
“It is important to note that at this stage our research focused on Jewish women of Ashkenazi origin, which is the population closest genetically to the participants of the international study on which our model was based,” he adds.
“Our research revealed that we already have the tools to identify, based on their genetic profile, Israeli women with an increased risk of developing breast cancer,” Professor Elkon concludes. “According to the risk score, it is possible to recommend that women at high risk of breast cancer start screening tests for early detection from a younger age, and more frequently. Such a policy may save lives and allow more efficient use of the health system’s resources. We hope that the promising results will lead to clinical use of the prediction method we developed and will improve the early detection of this disease.”