I bought a second-hand copy of The Immortal Cell: Why cancer research fails by Gerald B. Dermer on a whim. The book is out of print, but I had seen someone on a bulletin board recommend it because of its criticism of the use of cell lines in cancer research. I love reading critical (but sensible) accounts of ideas/techniques that have gained mainstream acceptance, so I thought the book would be worth a read.
- The book was written in 1994 (24 years ago!).
- It is obvious from reading the book that the author has an axe to grind — being motivated by equal parts frustration and resentment towards cancer research.
- Although I have a firm biological background, I am not an expert on cancer research. I think it’s important when approaching a book like this to be aware of your previous knowledge, to allow you to assess the plausibility of the arguments, while also acknowledging that some arguments might be relevant (and some may not).
With these caveats in mind, I approached the book as a historical curiosity. Yet, I found it quite an intriguing read.
The book is a criticism of contemporary research culture. Perhaps more so than it is a criticism of the state of cancer research in 1994.
Reading the book, I was surprised how little our overall understanding of cancer biology has changed in the quarter century since the book was written. Perhaps I should not have been, considering how the central thesis of the book is that scientists asking the wrong questions end up on wild goose chases with little tangible benefit.
I am quite certain that some of the statements Dermer makes have since been proven wrong. In addition, one of the horses Dermer is flogging is the failure for age-adjusted cancer mortality to improve. Although there are issues with over-diagnosis which might skew the results, and the improvements (seem to?) have been modest, I think cancer patients are better off these 25 years down the line since the book was written. This shows that although cancer research is not perfect, it does improve treatment, which is reassuring.
Still, Dermer has an interesting perspective on cancer research. Before entering academia, he worked as a hospital pathologist, and had access to plentiful human tumour tissue samples. Through his work, he realised that his understanding of cancer biology was different from the understanding of cancer biology communicated through the scientific literature. Eventually he realised that this was because he was working with genuine samples of human cancer, while many of his non-pathologist colleagues were working on cell lines — which are quite different beasts.
In essence, the book is a criticism of the use of these cell lines, since they make only poor models for human cancers as they exist in the body. The cells of a living tumour are very different from the pampered, immortalised cells at the bottom of a petri dish. Perhaps, Dermer asks, cancer research using this very different model, gives them a picture of cancer that is very different from the real thing?
I think the book is worth reading if only for this reason: what is cancer cell lines actually do not make a good model for research on human cancer?
As Dermer writes:
If their favourite model [the cell lines] was wrong, then all the information and ideas that have flowed from it were also wrong. The work of tens of thousands of scientists, over a period of more than thirty years, would be invalidated. The cell line model of cancer research is like the foundation card in a house of cards—pull it out and the entire “house” of cancer research will come tumbling down.
Throughout my career, I have always stayed away from cell lines, without really knowing why. Partly, I felt they were too ‘hyped up’ to be attractive to my contrarian personality. Secondly, it makes intuitive sense that cell lines might not be the best models for a beast that’s really quite different. I felt the same about using the fruit fly as a cancer model for my D. Phil. work, and I made sure to ask questions that helped me understand fruit fly biology better — while being very cautious to extend the findings to human biology beyond what was necessary to put my results into context (and even then it felt like bit of a stretch).
To some degree, everything we work with is an approximation of the truth. Words can only convey part of our intended meaning, and models will never be a substitute for the real thing. However, as Dermer acknowledges in the book, cancer cell lines are very convenient to use for molecular biology — which explains why they have become so popular. Whenever models — approximations — are used, it is however crucially important to never forget that this is all they are: models. What Dermer is criticising is the blind acceptance of cell lines as genuine substitutes of cancerous tissue:
when today’s researchers discuss “lung cancer”, they are usually not referring to lung cancer in the body but to cells derived from lung cancer that have lived for years in plastic dishes in the laboratory. The distinction between cell lines and human cells in vivo is no longer being made, largely because cell lines are so ideal for the methods of molecular biology.
This distinction is still not being made. Therefore, the book’s central argument is still valid. Are we using the right tools for understanding the biology of cancer? Cell lines are but one tool, to be complemented with animal models, primary cell lines, and tumour tissue. Of course, many research papers unite these models, to build a better understanding of cancer biology. However, many of the findings being tested and applied — and the ideas being generated — stem from work on immortalised cell lines and animal models. If the cell lines are very different from genuine human cancers, perhaps the results of such experiments are not very applicable? The same argument can be made for animal models: how good are they — and, but extension, their results?
Cancer has been cured in mice and petri dishes countless times. These are genuine achievements of the scientific process. However, such breakthroughs will be hard to bring into the clinic unless the cures are more generally applicable. The failure of many of these ‘cures’ in the clinic suggests that the type of cancer we model with cell lines and in mice is very different from the types of cancer that are relevant to human beings. This is typical of answers that have been arrived at through asking the wrong questions. (And very similar to current sentiment towards research on neurodegeneration.)
What are the right questions that we should be asking?
For starters, these would concern the models we use: Are we using the best models? The best models are the ones that are the least different from what we are trying to model. If you lost your keys, it is better to look for them where you lost them, rather than under the street light across the road — even if the light is better on that side. If we can’t experiment of living human cancers, perhaps extracted tumour tissue really is the second-best thing? They are not as easy to access or to work with as cell lines, but they are closer to what we are looking for: the ‘keys’. The cell lines in this analogy would be the equivalent of looking under the street light; it’s a lot more convenient, but also pointless. Whatever we find will not be our keys.
Second, out understanding of cancer should be based on genuine human cancers: the type we can study through genuine tumour material. That way, we can understand what cancer is. After that, we can formulate our hypotheses (what is cancer, really?) and test them using the model that would be the most suitable. Cell lines are tools, and I am certain they are suited to answering some questions. Where I agree with Dermer is that they have been given a prominence that is hard to justify: everyone is working with cell lines. Have all of these researchers, independently, asked themselves if these really are the best models to use? Or is an entire research programme looking for their keys across the street, because it never occurred to them to look anywhere else? (It should be noted that Dermer reserves his criticism for molecular biologists, and not pathologists — he seems to believe, perhaps rightly?, that pathologists study the ‘real’ cancer, and therefore have a better understanding of what ‘cancer’ actually is.)
Another interesting thing that stood out to me was how much people knew about cancer already by the 1960’s. Immunotherapy is not a new idea. As a non-cancer biologist, this was news to me. I was also much intrigued by Dermer’s criticism of immunotherapy to treat cancer, since I was of the belief that immunotherapy might success where other treatments have failed previously. Taking some time to ponder the issue, perhaps immunotherapy has been oversold? If the immune system protects against cancer, suppressing it would be expected to promote its development. Rapamycin/sirolimus is an immunosuppressant. Its use in human patients is however associated with a decreased incidence of cancer. Its just one example, but it does suggest that the hypothesis that cancer arises through immune system failure does not explain everything.
Interestingly, Dermer makes several allusions to the developmental nature of cancer (and rapamycin fits snugly into this mold, by inhibiting TOR: a key regulator of cell development and biology). What he writes about hormones near the end of the book was particularly intriguing, where he discusses the epidemiological findings that early pregnancy in humans (and rats, experimentally), is associated with a decline in the life-time risk of developing breast cancer. This, he says, might be because pregnancy causes the cells in the breast tissue to differentiate — making them less likely to become cancerous. This is followed by a suggestion that a pill that somehow mimics pregnancy (and better so than current hormonal contraceptives) might be protective against breast cancers if taken early in female adulthood, by allowing the developing cells to differentiate. Perhaps someone with better knowledge of the field can correct me if this is wrong (please do!), but this suggestion made sense to me. I will update this post if/when I have figured this one out.
Stimulating ideas aside, Dermer has an issue with the ‘toxic’ chemicals that compose most chemotherapies. He mentions that some of these are derived from mustard gas, which is pure scare-mongering. There are several parts of the book where he criticises such treatment of cancer, sometimes even suggesting that untreated cancer would make a more dignified cause of death. Such statements show that Dermer is a pathologist and not a clinician, since my understanding (from clinicians) is that untreated cancer is a horrible way to go. It was while reading these sections that I worried that Dermer would best be classified as a maverick crackpot (of which cancer research has several). However, just because not all of someone’s opinions make sense, doesn’t mean that they don’t have anything useful to say. For example, I am reminded of Mikhail Blagosklonny, who is a bit quirky, by all accounts, but who has some provocative ideas about the biology of ageing — including cancer. There are intriguing parallels between the pre-cell line model of cancer (according to Dermer) and the hyperfunction theory of ageing, for example; through the theories’ common emphasis on the role of development and differentiation.
For anyone who is interested in the history of science and/or cancer biology (and with some knowledge of the field(s), and an open mind), I would definitely recommend this book. It is out of print, but a Kindle version is available. It is well-written, and can easily be read in one or two sittings.
Overall, I really enjoyed the book, and it has provided me with some definite food for thought. Perhaps this is confirmation bias, but I think Dermer’s main points are correct: that cell lines make poor models of human cancer, and that it’s important to ask the right questions (by using the right models, or acknowledge their limitations) when doing any kind of research. The latter is common sense. Perhaps we need more of that in science, and in society more generally.
To begin with, we can change the incentives that pervert the scientific enterprise by valuing quantity over quality. Let us make scientific research less of a scramble up the academic career ladder, and more about a job where you get to spend your days thinking about cool ideas and the best way to test them — and then doing just that.