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Johns Hopkins Pediatric

Using Big Data to Beat Kidney Cancer

January 01, 2017

Urologic oncologist Michael Johnson, M.D., recent graduate of the Ralph T. and Esther L. Warburton Foundation and Dr. Hugh Judge Jewett Fellowship program and now on the Brady faculty, believes the key to improving kidney cancer care is to work smarter. “The speed of DNA sequencing has increased a billion times since the first genome was sequenced in the 1970s,” he notes. “The cost of sequencing a human genome is approaching the cost of a CT scan. Yet, we don’t often use these data when treating kidney cancer. Why not?” One reason is that it’s hard for doctors to know what to do with so much data, and “that’s where Big Data computing comes in.”

“We are at a turning point in kidney cancer care, where we have more data than we know how to use.”

Johnson has teamed up with Kimmel Cancer Center scientist Charles Drake, M.D., Ph.D., to use a tumor’s specific genetic information to design personalized cancer therapy. With grant support from the National Institutes of Health’s Big Data to Knowledge Program, Johnson demonstrated that “neoantigens,” tumors with more genetic differences that can be detected by the immune system, are less likely to be aggressive. In a true translational research effort, he is performing DNA sequencing on selected kidney tumors that he removes during surgery. Then, using large-scale computing to predict neoantigens, he and Drake are testing ways to select and grow immune cell populations that recognize tumor- specific DNA changes. With support from the Greenberg Bladder Cancer Institute, he will also be taking the same approach with selected bladder cancer patients.

“We are at a turning point in kidney cancer care,” Johnson notes, “where we have more data than we know how to use. By combining surgery, bioinformatics, and immunology, we can transform our treatment by personalizing it for every patient.”

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