This is an early, and longer, version of a piece that was published in the Lancet Oncology, March 2012, 13(3):236
Phase i trialists
There is a new breed of clinical trialist on the block in cancer research. You might not have seen them yet - they won’t be knocking down your door in the clinic. They don’t know what HIPAA stands for. They don’t know what to do in a code. They don’t wear a white coat, you’ll be lucky if they wear a tie. They’re not biologists - if you ask them to change the media, they’ll likely bring you some music you haven’t heard. They are Phase i trialists.
What’s a Phase i trial? It’s a pre-clinical trial, but no cell, mice or rats will be harmed. Before one begins killing cells in a dish, there is the step to decide how to treat those cells, or mice in a sensible, yet new way. It is this step, before even stepping into a ‘lab’, where we are just now seeing an influx of other types of scientists - physicists, engineers, computer scientists and mathematicians. Some of these folks have run out of problems in their field and have found fertile ground for their tools in the dizzying biological complexity of cancer. Others have become frustrated by the esoteric nature of their first field - it takes a special mind to be happy studying things in other galaxies, or so small that you need a super collider spanning three countries to learn anything new.
And then, some are just naturally dreamers, or follow their hearts into a field that has affected their life (cancer touches so many of us). It is these folks that I call Phase i trialists (i for the imaginary number, the square root of -1), they are the smartest bunch of scientists that you’ve never met. Happy dreamers who turn coffee into biological hypotheses. Mid-career scientists who trade their radiotelescope time for hospital badges. And what do you get when you turn these folks loose in cancer research? You get crazy ideas that you might be able to apply information theory to genetics or the helmholtz free energy to mitochondrian. You get people who dream that biology can be explained by first principles - that we can build models on a chalkboard or a computer chip that can predict how a tumor will grow and evolve, how a person may live or die. You get Phase i.
The biggest difficulty encountered right now is trying to get clinicians and scientists, many of whom are already dogmatized, to listen to a physicist with a crazy idea. To be willing to bet some of their hard earned grant money and time on an mathematician’s model that very well might be nuts. To be willing to think back 30 years to the last time they took a calculus class and bite down hard on whatever they can find until the testable hypothesis comes out from the equations. But, without scientists on both sides listening to each other though, these crazy (and possibly transformative) ideas will never come to light, and we could miss out on something worthwhile.
It is becoming more and more apparent that cancer isn’t just a collection of mutated cells - but instead a richly varied combination of different cell types, both normal and tumor, producing different factors and with different skills. We have known for a long time that tumors have mechanisms by which to hijack angiogenesis (the process by which new growing tissue gets blood vessels), but now we are finding out that it may hijack other ‘normal’ mechanisms as well: chemotaxis and motility, likely stolen from wound healing or the migration needed to form a sensible embryo; limitless replicative potential, likely stolen from stem cells; and most importantly, the ability to evolve under pressure, inherited honestly by cancer’s virtue of being mostly us.
Taken together, all of these concepts make the task of treating a tumor with a single cytotoxic agent (chemotherapy), or even targeted therapy seem like an unlikely strategy for success. Indeed - most cancers are treated with at least two agents now, and some with many more. It would be a daunting task to try all possible combinations of agents, especially when human lives are at stake in trials and it is a daunting task to understand how all of these attributes combine to make a whole. Fortunately, we aren’t the first minds to try to tackle this sort of complexity. In many quite salient ways, this level of complexity is akin to an ecosystem - there is symbiosis between different players, competition for space and resources and various environmental factors that affect the whole game. Why not then climb up on the shoulders of some giants and look around? Why not try the tools that our conservation ecologists use to manage invasive species? That macroeconomists use to understand predatory business strategists? That agronomists use to manage pest infestations?
Well, these Phase i trialists have, and continue to. They have hijacked the beautiful differential equation system proposed by Lotka and Volterra to understand predator-prey systems to try to understand how the dynamic interplay between healthy and normal is effected by various traits or strategies1. They have used Maynard Smith’s evolutionary game theory to tease out the relationship between the shift to aerobic glycolysis (the Warburg shift) and cancer invasion2. They have studied the prisoner’s dilemma to understand cooperation between tumor cells of disparate lineage3.
Sometimes, the use of a new concept just raises more questions, but the questions are often ones that can be answered with relatively simple experiments that can elucidate new "big picture" information. It was once said that if an experiment in physics needs statistics to prove its validity (as we expect every biomedical experiment to need) then it is not a real result! (credit to Ernest Rutherford I believe) As an example, using physics to understand hematogenous metastasis: the first thing a physicist would do is draw a diagram. Drawing the circulatory system as a flow network immediately highlights organ system connections that explain the preferential spread of some, but not all cancers4. Cancers of the gut preferentially spread to the liver - the next stop; prostate cancers however, spread almost always to bone first, necessitating a tortuous route through several capillary beds. How do these cancers differ? Can we measure, as we would electric current, the relative amount of circulating tumor cells (the vector of metastasis) in each portion of the network? Do conservation laws exist, like Kirchoff’s loops? These types of questions have not been answered to date, and only very recently even have they been asked! The list of insights from Phase i trials keeps growing. The field of cancer research has been dominated by a single group of scientists for a long time and, like a field farmed for one crop, we have seen yields diminishing. Letting the field lie fallow is certainly not an option - so we must sew new seeds and tend them with teams of scientists who have different viewpoints to realize the full potential of the harvest.
1. Gatenby RA, Vincent TL. “Application of quantitative models from population biology and evolutionary game theory to tumor therapeutic strategies” Molecular Cancer Therapeutics 2003;2(9):919-927
2. Basanta D, Simon M, Hatzikirou H, Deutsch A. “Evolutionary game theory elucidates the role of glycolysis in glioma progression and invasion” Cell Proliferation 2008;41(6):980-987
3. Axelrod R, Axelrod DE, Pienta KJ. “Evolution of cooperation among tumor cells” PNAS 2006;103(36):13474-13479
4. Scott JG, Kuhn P, Anderson ARA. “Unifying Metastasis”, Nature Reviews Cancer Jul 2012, 12 445-446.