“Bad luck” cancer

Two years ago, a paper published in Science caused a big ruckus in the field when it argued that “the majority [of cancer risk] is due to “bad luck,” that is, random mutations arising during DNA replication in normal, noncancerous stem cells.” (Unfortunately Science is closed-access, if you’d like me to send you the pdf please let me know. That’s a story for another day though.)

There was a lot of pushback on the implications of their findings (which is also a story for another day – why do we get all huffed up when researchers make ethically-charged statements about diseases like cancer but not necessarily ones like HIV, TB, malaria, or infectious diarrhea?) and they just published a follow-up to their original study. If you can let your eyes glaze over the one or two paragraphs that are a bit technical, I think it’s actually a fairly easy and interesting read. I’m not going to comment on the science in this paper, but rather on the three things that struck me as I read it:

  1. Zooming out of US- or Euro-centric studies multiplies the possibilities we have for meaningful insights.
  2. Public data is powerful.
  3. Responding to public criticism with balanced, thorough science is awesome!

“This hypothesis has generated much scientific and public debate and confusion, in part because our analysis was confined to explaining the relative risk of cancer among tissues rather than the contribution of each of the three potential sources of mutations ([environmental, hereditary, and replication error]) to any single cancer type or cancer case.”

I really appreciate how the authors directly confront the public debate that happened around their previous paper. I also heartily commend the authors for their neutral tone throughout this paper – they’re not defensively justifying their previous analyses, nor are they aggressively telling detractors that they’re wrong. They’re simply clarifying their position, and responding to criticisms by putting in the legwork to figure out how to address them. In this case, they had to back up their problematic claims with a more thorough analysis. It was probably pretty hard to do, and I’m really glad they did it. More scientists should work this way, responding to feedback with “yeah but that’s hard” and also “okay we’ll give it a try.” Too often, we’re satisfied with only that first part of the answer.

“In this study, we have evaluated cancer incidence in 69 countries, representing a variety of environments distributed throughout the world and representing 4.8 billion people (two-thirds of the world’s population). Cancer incidences were determined from analysis of 423 cancer registries that were made available by the International Agency for Research on Cancer (IARC) (http://ci5.iarc.fr/CI5-X/Pages/download.aspx).”

Public data is powerful. Public data repositories and consolidated efforts to systematically collect data are so important as a public good.

Looking at data from populations around the world is also important – and something we tend to forget to do. The Human Microbiome Project is actually 300 individuals from the US, recruited from basically only 2-4 cities. And yet in my field, it’s one of the standard datasets we use as a gold standard comparison for what a “normal” human microbiome looks like.

“Second, these results explicitly and quantitatively address the difference between cancer etiology and cancer preventability. As illustrated in Figs. 2 and 3, these concepts are not equivalent. A cancer in which 50% of the mutations are due to R can still be preventable. The reason for this is that it generally requires more than one mutation to develop the disease.”

We often talk about correlation and causation, and this paper forced my mind to wrap around a third: preventability. It’s not the same, and it’s one of the reasons basic science (for the sake of basic science) doesn’t excite me – just because you figure out how a certain disease works, doesn’t mean you’ll know what to do about it!

“Our studies complement, rather than oppose, those of classic epidemiology.”

Again with the really clear, neutral, forward-looking tone here. Love it. Also really appreciate that they provide ways that this study is complementary: cancers which don’t seem to be driven by random errors are probably the best target for further investigation as to what environmental or hereditary factors may be contributing.

“Recognition of a third contributor to cancer—R mutations—does not diminish the importance of primary prevention but emphasizes that not all cancers can be prevented by avoiding environmental risk factors (Figs. 2 and 3). Fortunately, primary prevention is not the only type of prevention that exists or can be improved in the future. Secondary prevention, i.e., early detection and intervention, can also be lifesaving.”

In other words, we’re not saying that if you have cancer you just had bad luck and everyone should just give up on any cancer prevention efforts (pass me the cigarettes!). We’re saying that some cancers are more about reducing environmental exposures whereas others are mostly about being unlucky, and so we should be approaching those two cases very differently! For the former, typical public health measures to reduce exposure; for the latter, more thorough screening even in people without traditional risk factors.

I only briefly skimmed the methods and don’t know much about cancer biology, so can’t speak to the actual validity of the paper too well, but I am certainly interested in what the follow up conversation in the field will be. Especially because the authors have set up an environment in which a productive discussion can flourish through the neutral presentation of their findings.

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