

A gene signature that accurately predicts the functioning of P53 variants has been discovered by Maureen Murphy, Ph.D., Deputy Director of Wistar’s Ellen and Ronald Caplan Cancer Centre, and Ira Brind Professor and Program Leader in the Molecular & Cellular Oncogenesis Program. This finding is significant for determining cancer risk and optimizing options for cancer therapeutics.
“There are so many genetic variants of P53,” explained Murphy. “A lot of P53 variants are classified as having uncertain significance with current methods of testing. This does not help people determine whether they have increased cancer risk. The signature we identified does.”
The Murphy team looked for any genetic indicators that would indicate if a p53 variation is acting less normally by comparing differences in activity between mutant and normal p53 proteins. The research team used machine learning to find a gene signature that consistently and accurately predicted the distinction between a normally functioning or benign p53 and a lower functioning variant of the protein in collaboration with Andrew Kossenkov, Ph.D., assistant professor in Wistar’s Vaccine and Immunotherapy Centre.
Using this information, people with p53 genetic variations might be screened and given important insights about their risk of developing cancer and how well they respond to treatment. In order to develop the gene signature into a blood-based genetic test that people may use to determine their p53 status, Murphy plans to continue this study.
“The promise of this research is personalized medicine,” Murphy elaborated. “This work could not have happened in any other place except Wistar where our environment is so collaborative and cutting edge.”
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