Before human intervention the rules of disease were simpler. The competitors: pathogen vs. host. The rules: in order to win, the pathogen must ‘divide and conquer’, attacking the host’s defences and increasing in numbers; the host, on the other hand, must stay strong and defend hard in order to keep a united front, before finally striking back and wiping out the invaders. It was a game of risk, and the winner would ultimately find themselves stronger and better prepared for the next battle. This is because the hosts and pathogens necessarily need to coevolve – that is to adapt to each other simultaneously – in order to stay in the game. This concept was famously captured in a quote by the Red Queen in Lewis Carroll’s ‘Through the Looking-Glass’,
“Well, in our country,” said Alice, still panting a little, “you’d generally get to somewhere else — if you run very fast for a long time, as we’ve been doing.”
“A slow sort of country!” said the Queen. “Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!”
However, since modern medicine came along, the dynamics of the game have become more complex; and it is only recently that evolutionary biology has been considered a potential weapon against disease – by trying to predict and manipulate the pathogen’s strategies, in order to stay one move ahead. The application of evolutionary theory to understanding health and disease is known as evolutionary or Darwinian medicine – and it is being used to try and find answers for all sorts of medical ailments, such as: autoimmune diseases, diabetes, anxiety disorders, antibiotic resistance, and cancers (to name just a few). As such, Darwin – the “medical school dropout” – turns out to be having a bigger impact on the world of medicine than he could ever have imagined.
A multi-resistant menace!
Perhaps the most well-known application for evolutionary thinking to medicine is the problem we now face with antibiotics. Hailed as a medical revolution, antibiotics were used to treat nearly every ailment in the recent years after their discovery, but no-one predicted the problems we now face with antibiotic resistance. Here, evolution is utilising two inputs: variation and selection. A bacterium will go through hundreds of generations in the course of a week, and their population sizes can reach trillions, so the opportunity for a variation is very big indeed. By hitting a bacterial population with a strong dose of antibiotics you are also imposing a very strong selection pressure. If, by chance, a bacterium acquires a mutation which enables it to resist the antibiotic attack (which in a large rapidly replicating population is very likely), it will persist and divide, and eventually the new population will all carry the mutation which confers resistance to the particular antibiotic. And so, you hit them with a new antibiotic, but a new bacterial population is established which is resistant to the new antibiotic as well – and so the cycle continues until we are faced with multi-resistant strains, such as the media’s favourite, ‘MRSA’.
The problem comes when we attempt to treat a living organism with a non-living chemical. The bacterium has evolved in order to cope with all of the problems associated with staying alive for billions of years – so if we hope to have any chance our approach needs to be more sophisticated. One option is to be more methodical with treatments. Antibiotics target different parts of the bacterium, and so if we can target multiple areas at once we might be able to make it more difficult for a bacterium to mutate in all the ways necessary to avoid antibiotic destruction. “Antibiotic cocktails” are frequently administered to patients which require longer term antibiotic treatment (such as cystic fibrosis sufferers), in the hope of at least slowing the rate at which multidrug resistance evolves. However, inevitably the drugs stop working and the prognosis quickly deteriorates. Scientists are working at finding the best combination in order to slow the evolution of resistance – cyclical and combination treatments are all being tried and tested, but the jury is still out on which is the best way to treat long term illness.
The alternative is to use something against the bacteria which will coevolve, so that if the bacteria evolve resistance – it has the ability to evolve a counter attack. There are many examples of natural organisms which have antibiotic properties: bacteriophage (see previous post), fungi, and even other bacteria which secrete toxins, can all be used to kill off unwanted bacteria. The trick here is to determine how we can keep the red queen dynamic running. The danger is, if we evolve a super resistant strain which eventually “wins” and beats the natural antibiotic such that it can no longer infect the pathogen – we risk finding ourselves right back where we started. However, using evolutionary thinking scientists are getting a better understand of the rules and tricks of the game – providing light at the end, of what was once, a very dark and dreary tunnel.
But how can the above logic be used to help us beat cancers? Cancers are not a pathogen, they are our own cells gone haywire. So finding a drug which targets the cancer cells but not your own healthy cells is a very tricky problem – and the reason why most cancer treatments leave the patient feeling pretty awful. Cancer cells, or tumours, can be thought of as a population of cells with an alternative strategy – rather than cooperating with the rest of the cells in the body and promoting survival of the host, they exploit their surroundings, dividing as fast as possible and using up all available resources. So by thinking of these tumours as a population of clonal cells acting selfishly to promote growth, we can apply evolutionary principles to predict why they behave the way they do, and try and develop treatments which can manipulate them into doing what we want them to do – which is essentially stay still, so we can safely target, or remove them.
Current cancer treatments might be creating a similar dilemma as caused by antibiotics – imposing strong selection for those who are resistant to the treatment, thus making the cancer more difficult to treat over time. Cancers are more dangerous the more motile they become, and these metastatic cancers can spread rapidly throughout the body. For a long time it was not understood why cells would migrate from the tumour, because the probability of successfully establishing a new population somewhere else in the body is very small. However, cancer cells rapidly exploit available resources in the surrounding tissues, and therefore competition between cells becomes fierce, quickly. The idea is that this competition might be selecting for more motile cells, increasing the chances that one will successfully establish somewhere else in the body. So, counter intuitively, this may mean that by ‘feeding’ the primary tumour and increasing available resources you might reduce the number of metastatic cells released, and reduce the chance of spreading. This is still theoretical, but work has begun on testing some of these ideas in the lab, with a hope that one day we might be able to out-smart the crafty cells – and beat them at their own game.