Diversity working together: cancer, immune system, and microbiome

After a much needed few weeks of recovery, I’ve found some time to post about our annual IMO workshop held this year on the topic of viruses in cancer. Our group had the challenge of learning about all of the complexities of the human microbiome and its interactions with a cancerous lesion. The human microbiome, in a nutshell, is the ecological community of commensal, symbiotic, and pathogenic microorganisms that live on our inner and outer surfaces including bacteria, fungi, and viruses. The number of cells in the human microbiome is more than 10 times the amount of cells in our bodes (Costello et al., 2009), which means that 2-6 pounds of us is made of, not exactly us, but microorganisms. The microbiome has become a popular topic as of recent, with more than just human-centric studies sparking interest (see links for kittens, seagrass, the University of Chicago’s hospital, and the earth). See the video below for a nice introduction to the microbiome (and the cutest depiction of a colon you will ever see):

The first thing that I learned about the human microbiome is the extreme diversity of the bacterial communities. We have quite unique microbiomes, though they are shared through kissing, similar diets, and among families and pets (Song et al., 2013; Kort et al., 2014)! Further, there are huge discrepancies of the microbial communities that live in our hair, nose, ear, gut and foot (Human Microbiome Project Consortium, 2012). So the challenge to find a project that would address this diverse microbiome and its interaction with cancer in a way that we could test with real data to BOTH answer a clinically-relevant question AND be mathematically modeled in 4 days (what!?) was a little daunting. Good thing we had an epidemiologist and expert in the microbiome (Christine Pierce Campbell), a medical oncologist specializing in head and neck cancers (Jeffery Russell), and an excellent team of biologists, mathematicians, computer scientists, and biophysicists (#teamFecal) ready to rumble.

Memes, compound strategies, and factoring the replicator equation

When you work with evolutionary game theory for a while, you end up accumulating an arsenal of cute tools and tricks. A lot of them are obvious once you’ve seen them, but you usually wouldn’t bother looking for them if you hadn’t know they existed. In particular, you become very good friends with the replicator equation. A trick that I find useful at times — and that has come up recently in my on-going project with Robert Vander Veldge, David Basanta, and Jacob Scott — is nesting replicator dynamics (or the dual notion of factoring the replicator equation). I wanted to share a relatively general version of this trick with you, and provide an interpretation of it that is of interest to people — like me — who care about the interaction of evolution in learning. In particular, we will consider a world of evolving agents where each agent is complex enough to learn through reinforcement and pass its knowledge to its offspring. We will see that in this setting, the dynamics of the basic ideas — or memes — that the agents consider can be studied in a world of selfish memes independent of the agents that host them.

Is cancer really a game?

A couple of weeks ago a post here on TheEGG, which was about evolutionary game theory (EGT) and cancer, sparked a debate on Twitter between proponents and opponents of the idea of using EGT to study cancer. Mainly due to the limitations inherent to Twitter the dialogue fizzled. Instead, here we are expanding ideas in this guest blog post, and eagerly await comments from the others in the debate. The post is written by Philip Gerlee and Philipp Altrock, with some editing from Artem. We will situate the discussion by giving a brief summary of evolutionary game theory, and then offer commentary and two main critiques: how spatial structure is handled, and how to make game theoretic models correspond to reality.