Predictive-AI Algorithm Identifies Common Cancerous Gene Mutation

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Using artificial intelligence, researchers from the Hadassah Cancer Research Institute at the Hadassah University Medical Center in Jerusalem have developed an algorithm to identify, with an unprecedented 96.5% level of accuracy, all possible deleterious mutations of TP53 gene which are commonly found in 50% of tumors. This breakthrough can potentially lead to improved genetic screening and consultation and to improved precision medicine for cancer patients.

This groundbreaking algorithm was trained using AI, huge cancer and normal genomics databases coupled with computational and experimental parameters specific to TP53 gene. Prof. Thierry Soussi (Sorbonne Université, Paris, France), a world leading researcher of TP53 gene, lent his expertise to an international research collaboration, led by Dr. Shai Rosenberg, aimed at increasing identification of variants posing risk of developing cancer from variants that are not, from 190 (in the ClinVar database) to all 2,314 possible missense variants.

This gene-specific, AI approach can be generalized to other cancer genes and thus, contribute to more accurate genetic screening and consultation. Additionally, it can lead to more effective precision medicine for oncological patients by the creation of customized cancer treatment decision support systems that are able to identify and discern the important mutations that require treatment from the total number of somatic mutations of the tumor.

"The research and technology behind this breakthrough not only provide life-saving screening for carriers of previously unknown cancerous mutations who may be at increased risk, but it is also critical for genomic analysis of somatic mutation profiles in all tumors," said Prof. Michal Lotem, MD, Head of the Center for Melanoma and Cancer Immunotherapy, Dept. of Oncology.

"Hadassah Medical Center has been at the forefront of promoting technological innovation in medicine in order to provide patients in our care with the most advanced treatment options," said Prof. Aron Popovtzer a Professor of Radiation Oncology and Head of the Sharett Institute of Oncology. "Following this important milestone, Dr. Rosenberg's research group will continue actively working to develop similar models for additional cancer genes."

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Predictive-AI Algorithm Identifies Common Cancerous Gene Mutation.  Appl Rad Oncol. 

By News Release| February 03, 2022

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