Written by: Stephen Hsu
Primary Source: Information Processing
A great article in Esquire on the frontier of cancer genomics. It’s only a matter of time before many wealthy individuals diagnosed with cancer seek out this standard of care. (I’m told that sequencing alone can lead to actionable conclusions in more than a few percent of all cases, even now.) The resulting advances will hopefully eventually reach everyone else.
Biomathematician Eric Schadt, shown above.
Esquire: … When [Schadt] graduated high school, he joined the Air Force with the idea of subjecting himself to the rigors of Special Forces training. Instead, he blew out his shoulder on a climb, and the Air Force tried to salvage its investment by putting him through a battery of tests. He took them; when the scores came back, he was asked by stunned superiors if math had always come easily to him. Then he was sent to college and undertook the task of complete intellectual self-transformation. He received an undergraduate degree in applied mathematics and computer science at Cal Poly and his master’s in pure mathematics at UC Davis. Pure math was, to him, the Special Forces of the mind—he took it because it was so hard, and he wanted to find out just how smart he was. He was pretty smart, as it turned out, but he despaired of working on problems that existed on the level of pure abstraction and had no bearing on the problems of the world. It seemed like, well, a sin. He went to UCLA to get a Ph.D. in the emerging field of biomathematics. The one problem was that the degree required a Ph.D.-level mastery of molecular biology, and the last biology course he’d taken was in high school. So he taught himself by reading textbooks. It wasn’t hard. Pure math was hard. Molecular biology, after pure math, struck him as ridiculously easy.
… Schadt told Merck that this was a strategy doomed to fail, because disease arose not from single genes or pathways but rather out of vast networks of genes and pathways whose interactions could be understood only by supercomputers guided by abstruse algorithms. Evangelical still, though now evangelical on behalf of irreducible complexity, he asked Merck to remake itself in the image of the network model he was determined to pioneer. Merck declined and Schadt headed to Silicon Valley, to the land of data.
… In September, Mount Sinai announced that he would be head of the newly created Institute for Genomics and Multiscale Biology. A little more than a year later, Sinai announced that Schadt’s operation would be renamed the Icahn Institute, just as the entire medical school would be renamed the Icahn School of Medicine at Mount Sinai. For the privilege, Carl Icahn had given Eric Schadt $150 million to claim the future of biology.
The article focuses on the treatment of Stephanie Lee’s colon cancer.
Esquire: … The first thing that needs to be understood about Stephanie’s data is that there would be a lot of it. From the samples of Stephanie’s blood, the gene sequencers would generate the data about the genes in her “germline”—the genes (and the gene mutations) that she inherited from her parents and that existed in every cell of her body. From the samples sliced from her colon, the sequencers would generate data about her cancer and the mutations that produced it. But the data would be raw. It would contain millions of bits of genetic information, each one a sentence in the horror story that Stephanie’s cancer was telling—and all those sentences, at least initially, adding up to a bewildering Babel. The data would exist right on the edge of incoherence; then Schadt and his scientists would strive both to make sense of it and complicate it. That’s their trademark, and why they need a supercomputer. The genes that Stephanie was born with would be compared with the genes that were driving Stephanie’s cancer. The genes that were driving Stephanie’s cancer would be compared with the vast libraries of reference data-bases that already exist on all kinds of cancers. Then they would be plotted against the “network models” that the Icahn Institute is constructing, the millions of individual data points mined for their billions and even trillions of connections.
… Schadt’s scientists—his biologists and his mathematicians—were from all over the world. Many had followed Schadt from the West Coast, but before they came to America, they lived in China and India and Russia. Now they had access to near infinities of information; indeed, they would soon have access to the near infinity of information generated by the DNA of a woman in Mississippi who had been given no information at all, except the information that she was going to die. It was a point lost on no one, least of all Schadt.
… A month earlier, Cagan had started doing something that he said “had never been done before.” He started creating “personalized flies” for cancer patients. He took the mutations that scientists like Schadt had revealed and loaded them into flies, essentially giving the flies the same cancer that the patient had. Then he treated them. “Why a fly? You can do this in a fly. You can capture the complexities of the tumor.”
… By October 11, however, Cagan already had “one possible drug suggestion for her”—or one possible combination of drugs, since he always tests at least two at a time.
… Now the oncologists at Mount Sinai were asking Schadt and Cagan if there was something they could do in their own intractable cases. And Dr. Holcombe was asking what studies had to be done to incorporate personalized therapy into the standard of care…a standard of care derived in part from none other than little ol’ Stephanie Lee. There had been the imposition of obstacles at every step of the way, and the odds against her remaining on what Schadt called “a path to fight on” had beggared even his mathematical imagination. And yet here she was. Her tumor had become, in Ross Cagan’s words, “at this point in time, the most fussed-over tumor that I’m aware of.” …
Here’s a peek at some of the computing infrastructure behind this kind of work.
Latest posts by Stephen Hsu (see all)
- MSU Research Update (video) - April 17, 2019
- Interview with Genetic Engineering & Biotechnology News - April 17, 2019
- Precision Genomic Medicine and the UK - February 15, 2019