Eric Dishman, a former Intel executive now at the National Institutes of Health, was a 19-year-old college sophomore when he was diagnosed with a rare form of kidney cancer. Over the course of the next 23 years, he would receive 62 different kinds of chemotherapy, immunotherapy and radiation. Some slowed the tumor’s growth, but never for long. The cancer spread from his left kidney to right kidney.
Just when it seemed Dishman had run out of options, a chance encounter in 2012 with a scientist working for a now-defunct genome-testing company presented an opportunity he couldn’t refuse. He had his cancerous tissue sequenced, a process that would compare his cancer’s mutated DNA with a healthy patient’s genome. This would let doctors look for genetic mutations and other abnormalities that support cancer growth, and to use that information to devise a treatment strategy. For example, changes in certain genes could indicate that his cancer was more likely to respond to a particular drug, while other mutations might predict little benefit from a specific therapy. Once the doctors sequenced his tumor, all he had to do was wait. And wait.
Dishman says he was “literally at death’s door,” when he got the call from his doctor. It had taken seven months for a team of oncologists, computer scientists and data crunchers to analyze Dishman’s genetic data and pinpoint a drug — for pancreatic cancer — that would target the unique features of his cancer. This experimental drug homes in on the abnormal gene suspected to cause Dishman’s disease. Within three months of starting treatment, he was cancer-free and eligible for the kidney transplant that ultimately saved his life.
Inspired by the treatment, Dishman is now on a campaign to make this kind of tailored cancer care available to more patients. And, ironically, this individually focused approach likely hinges on the efforts of crowds.
