“Gene expression methods measure how much of the protein is going to be made, how quickly the body is transcribing the DNA in that protein, and if there are epigenetic changes or chemical modifiers that affect the rate of transcription of DNA that gets made into protein,” said Pepke. Genomics researcher and former NASA data scientist, Shirley Pepke, and Greg Ver Steeg with his Correlation Explanation machine learning algorithm (which extracts hidden patterns in large, high-dimensional data sets) may have helped drive Pepke's ovarian cancer into remission. The team also found that the gene therapy worked by boosting a protein called PD-1, which is known to be involved in regulating cell growth. Pepke and Ver Steeg are working to confirm the results in a larger population of patients.
Genomics researcher and former NASA data scientist, Shirley Pepke, and Greg Ver Steeg with his Correlation Explanation machine learning algorithm (which extracts hidden patterns in large, high-dimensional data sets) may have helped drive Pepke's ovarian cancer into remission. The team also found that the gene therapy worked by boosting a protein called PD-1, which is known to be involved in regulating cell growth. Pepke and Ver Steeg are working to confirm the results in a larger population of patients.