Had this piece run in the April issue of Scientific American, and got a bit of flack from the precision medicine enthusiasts out there. They were particularly incensed that I wrote dismissively of Gleevec, the cancer drug that made headlines back in 2001, when it was found to work against CML (chronic myelogenous leukemia). Gleevec is a targeted therapy; it works by blocking a pathway that’s present in CML tumors, but not in healthy tissue. The drug was big news when it first came out, and for good reason: at the time, only 30% of patients with CML survived for even five years after being diagnosed; with Gleevec, that number rose to around 89%. But as I say in the article, the drug’s triumph was short-lived for some folks (17% of that 89%) because their tumors eventually developed resistance to it.
My critics argued that that last fact doesn’t wholly mitigate the success of Gleevec, which is a fair point. Cancer is an awful beast; something that cures a fraction of patients (or buys an even smaller fraction of patients a few extra years) is worth celebrating.
But we can celebrate an individual success for what it’s worth, without concluding that it represents the best path forward.
In other words, my criticism of targeted cancer therapy still stands.
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Here’s why: a few isolated successes notwithstanding, the idea that cancer can be beaten by targeting individual mutations has proven far too simplistic to sustain a whole paradigm of care, let alone a “moonshot” cure. (From Nature: “Indeed, while later scientists would go on to discover that nearly all cancer cells have some kind of abnormal chromosome pattern, no other pattern displays the same consistency as CML does…”).
First, malignant tumors are constantly evolving beasts. This from Sharon Begley, at STAT:
…as a tumor grows, it accumulates so many genetic changes that it’s not always clear which one is the “driver mutation” fueling its uncontrolled growth. As a result, it might not be clear which drug to use. Oncologists can also be stymied because they are shooting at a moving target. Even if they correctly identify one driver mutation, another can emerge weeks or months later, making the previous drug regiment ineffective at fighting the tumor… [in addition] cancer cells are genetically unstable as they accumulate mutations. As a result, a biopsy might turn up dozens of mutations, but it is not always clear which ones are along for the ride, and which are driving the cancer.
(Incidentally, some studies have found that the driver mutations might not even necessarily be located in the tumor itself, but may instead be hiding in the ‘healthy’ tissue around its edges).
Second, even if you do find all the driver mutations, and conquer each one of them in turn, there’s no reason to believe that that will fully vanquish the cancer. As scientists are learning, tumor proliferation is about much more than genetics. Begley again, on a 2012 study published in Science:
The cancer cells were not behaving the way the textbooks say they should. Some of the cells in colonies that were started with colorectal tumor cells were propagating like mad; others were hardly multiplying. Some were dropping dead from chemotherapy and others were no more slowed by the drug than is a tsunami by a tissue. Yet the cells from each “clone” all had identical genomes, supposedly the all-powerful determinant of how cancer cells behave.
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The current precision medicine initiative is worthwhile, as a research endeavor, precisely because it goes beyond therapies like Gleevec that target individual genetic mutations. The problem with precision medicine has always been that it relies too heavily on DNA to tell us everything. That hasn’t worked so far, and there’s no reason to believe that it’s going to start working now.
But we are learning more and more everyday about the other pieces of the health / illness puzzle: about epigenetics and the microbiome, and about the importance of that other nucleic acid, RNA. That information should be mined, not in lieu of more traditional health indicators like age, weight, lifestyle and location, but in conjunction with them; and not as “moonshot” to rid the world of illness, but as a matter of basic research.
So while the tone of my piece was fairly disparaging, I meant what I said in that last graph: it’s smart and fair and right to start pulling together what we’re learning from disparate corners of biomedicine in a rigorous and systematic way. It will be complicated and expensive to build the data infrastructure for this merging, and it will likely be many years before anything useful comes of it (which is why we should stop thinking of it as a health initiative). But it is the logical next step in life science research.
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Some of my favorite reads related to this:
The Social Life of Genes, by David Dobbs in Pacific Standard (On the role of epigenetics in shaping behavior)
The Google of Spit, by Lisa Miller in New York (On the personal genomics company 23andMe)
Fat Factors, by Robin Henig in The New York Times Magazine (On what the microbiome might have to do with obesity)
Science & Story 