Signals Blog

By Sara Nolte

Over two years ago, an article published in Science took the Internet and media by storm. The paper, “Variation in cancer risk among tissues can be explained by the number of stem cell divisions,” better known as “The ‘Bad Luck’ Cancer Study,” used mathematical modeling to demonstrate that most cancers were a result of chance mutations, rather than inherited genetics or environmental factors. It was presented by many media outlets in a way that minimized the effects of lifestyle and environment, promoting the idea that cancer was “just bad luck” – and there was nothing to be done about it. Science bloggers – myself included (see my post here) – were not as excited by the study, commenting on its scientific design flaws, and criticizing the fact that its conclusion was distracting from messages of public health and preventative medicine.

Well, authors Drs. Tomasetti (PhD) and Vogelstein (MD) from Johns Hopkins are back with a follow-up study published April 2017 in Science. The new study, “Stem cell divisions, somatic mutations, cancer etiology, and cancer prevention,” tells a story similar to that of the 2015 article, but, as the title suggests, makes a much more vague, yet appropriate, conclusion.

Why don’t we take a closer look at the methodology and conclusions?

In this study, the authors examine the roles of three variables for cancer etiology: environmental, hereditary, and random mutations.

Environmental factors are external factors that can contribute to the development of cancer by inducing mutations (these are often also referred to as mutagens because of this property); an example of this would be the strong link between smoking and lung cancer.

Hereditary factors refer to a genetic predisposition to developing cancer-inducing mutations; examples here would include the BRCA1/2 gene in breast cancer, and the familial cancer syndromes in colorectal cancer.

Lastly, random mutations refer to the mistakes in DNA (mutations) that occur during regular cell division. This a completely natural and beneficial occurrence, necessary for evolution and genetic diversity; however, sometimes mutations can accumulate, leading to more sinister outcomes, such as cancer.

The authors hypothesize that random mutations are the primary variable for explaining the different cancer rates for different tissues in the body. They further suggest that the number of stem cell divisions in a tissue is directly correlated with cancer frequency, and is the source of the cancer-causing random mutations. This is a pretty familiar story: not only is this their hypothesis from the previous paper, but the first part of it is pretty much found in any biology or genetics textbook.

So, what makes this study any different, and potentially more successful, than the last?

Well, it appears they listened to all the criticism they received in 2015. This time, the authors put more emphasis on the roles of environmental and hereditary factors in their mathematical modelling, and added a couple of other improvements along the way.

The first big upgrade to this study is that the authors have used multiple extensive databases, which include data from 69 countries, rather than only the U.S. This change means that they are better able to tease out the role of the environmental and hereditary factors from the random events that promote cancer development in various tissues.

How the authors actually performed the mathematical modelling and statistics is far beyond my scope of expertise. However, the main point I was able to take home was their primary assumption: the more lifetime stem cell divisions (a product of the frequency of stem cells in a given tissue, the estimated frequency of divisions, and time), the more likely genetic mutations are able to accumulate.

The improvement on this assumption is of particular interest to me, given that it was a strong criticism I, and others in the cancer stem cell community, had last time. The authors revised their values of stem cell frequency to be based entirely off of human estimates; they had previously used mouse data for some estimates. Some values are still based on in vitro experiments (with human tissue), but given the ethics of performing experiments in living humans, it is a reasonable compromise.

The last, and probably biggest, change this time around is the way the authors present their data and conclusions. One of my favourite (and in my opinion, most meaningful) figures is a heat-map-like scale on a sketch of the human body for each random mutation, environmental, and hereditary factor. Not only is this a great way to visually demonstrate the role of each variable in the development of cancer in various tissues, but it is also understandable by lay and scientific audiences alike. My only wish is that it had been more prevalent in the social media coverage.

Along with this new display of data, the authors are more cautious about their conclusions. They explain that their findings are a correlation, rather than causation, as they did not have data directly and prospectively linking stem cell divisions to cancer incidence. They also unified their findings with the message of cancer prevention strategies (e.g. smoking cessation to prevent lung cancer) both in their research article and in their interviews with the media (Scientific American and CNN coverage).

I assure you, there are still some areas that are lacking in the paper. For example, the assumption that all tissues follow the cancer stem cell model as the origin of cancer (which has yet to be proven in all cases). Also, the fact that they seem to gloss over the role of age as a contributing factor. However, it seems Tomasetti and Vogelstein made a huge effort to address the criticisms from 2015.

And that’s why I’m blogging about this April study in September. For most of you, your ‘New Year’ likely begins in September, rather than January, and with it, new struggles for a successful, and publishable project.

The transformation seen from the ‘Bad Luck’ (2015) to ‘Bad Luck 2.0’ (2017) on cancer development highlights some invaluable tips for success in academia:

Listen to your critics. They’re not always jealous that you came up with the idea first, and often have great suggestions for improvements to make your findings more scientifically sound. Yes, even Reviewer Number 3.

  • Bad Luck 2.0’ incorporated many of the critiques from the cancer stem cell community to strengthen their argument.

Acknowledge your shortcomings. No project is ever perfect or finished. Demonstrate insight into the limitations and future directions of your project.

  • ‘Bad Luck 2.0’ stressed the correlation, rather than causation, conclusions of their work.

Fit your message into the bigger picture. How does your research affect the life of the everyday person? Is there an ethics conundrum or potentially life-altering findings?

  • ‘Bad Luck 2.0’ refocussed some of their conclusions on the importance of cancer prevention.

Good luck to all of you this New Academic Year! And may the odds be ever in your favour.

The following two tabs change content below.

Sara M. Nolte

Sara Nolte holds a Bachelor of Health Sciences and Masters of Science in Biochemistry & Biomedical Sciences from McMaster University. Her MSc research focused on developing of cancer stem model to study brain metastases from the lung. She then spent a year working on developing cell-based cancer immunotherapies. Throughout a highly productive graduate career, Sara became interested in scientific communication and education. She is now involved in developing undergraduate programs and courses in the health sciences at McMaster, and is looking for ways to improve scientific communication with the public. Outside of science, Sara enjoys participating in a variety of sports, and is a competitive Olympic weightlifter hoping to compete at the National level soon!

Latest posts by Sara M. Nolte (see all)