Analytics leads to cancer cures

By: Alison Bolen, SAS Insights Editor

Harrison McKinion was 10 years old when he was diagnosed with acute lymphoblastic leukemia, the most common type of childhood cancer.

After two weeks of intense chemotherapy, Harrison suffered a life-threatening seizure, and his doctors conceded the chemotherapy was not working.

But a series of DNA tests brought hope.

While the DNA profile of Harrison’s cancer was now known to be resistant to chemo, doctors offered another treatment option. A new type of targeted therapy, administered in conjunction with the chemo, showed promise for treating Harrison’s specific type of cancer, EBF1-PDGFRB-positive acute lymphoblastic leukemia.

Doctors explained that Imatinib could work by blocking a protein that triggered Harrison’s cancer cells to grow.

Yet there were risks. This new treatment was so new that it had never been used on children. While the drug was untested on anyone like Harrison, it was his only chance.

Miraculously, the targeted therapy worked on Harrison, and he went into remission shortly after receiving it. At times the treatments were grueling but they worked. In a little under two months, Harrison had been diagnosed with cancer, told it was incurable, offered a long-shot treatment and then went into remission.

The answer is in the data

Harrison’s story illustrates the importance of cancer research and shows how researchers are using analytics to move beyond a one-size-fits-all approach to cancer treatment, instead delivering more personalized treatments based on genetics and other individual factors.

For Harrison, these next-generation treatments could not emerge fast enough.

“The importance of data and analytics is that it allows researchers to identify reasons why kids like Harrison don’t respond to standard therapy,” says McKinion. “The answer is in the data somewhere, and analytics helped researchers find the answers in time to save Harrison’s life.”

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