This researcher used big data to beat her cancer diagnosis

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After being diagnosed with ovarian center, genomics researcher Shirley Pepke, PhD, decided to put her research instincts to the test and use big data to help stop her cancer from spreading. And it worked.

Since being diagnosed with stage IIIC ovarian cancer in 2013, Dr. Pepke has been working on a tool capable of tailoring ovarian cancer treatment to each patient using genomics data, according to The Washington Post.

Dr. Pepke said a colleague at Caltech first put her in touch with local researchers with access to genomic sequencing technology to measure her tumor. The technology, however, provided data that was difficult to sift through.

That's when she connected with Greg Ver Steeg, PhD, a University of Southern California assistant professor specializing in mining complex data. Dr. Ver Steeg developed a machine called correlation explanation, capable of discovering hidden patterns in large data sets.

Using CorEx results and the data recovered through her own tumor, Dr. Pepke went against her oncologist's recommendation for treatment, choosing to try an immunotherapy drug not yet approved for ovarian cancer patients. After completing her dose of the drug, she underwent an additional round of surgery and chemotherapy. Two months later, her tumor was gone. Dr. Pepke has been in remission for over a year.

Since using herself as a test subject, Dr. Pepke and Dr. Ver Steeg are in the process of evaluating the results in a larger population of patients. Their ultimate goal is to have all women with ovarian cancer utilize precision medicine to create tailored treatment options, according to the article.

"Some people get cancer and do fundraisers — I'm good at doing computational research on complex systems, so it seemed really natural for me to work on this," said Dr. Pepke. "Because I have really young children, I felt that I had to pursue every avenue to try and extend my life, and I owed it to them."

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