Friday, December 29, 2017

New publication, just in time for the new year: A tale of two papers and two new friends.

About a month before I left Moffitt, in June of 2016, I got a twitter direct message from Steven Strogatz that said he had read one of my earlier posts on evolutionary graph theory and he mentioned there might be some fun to be had with the more 'math-y' aspects of the problem.

This led to a long series of fun phone calls and discussions about how network connected structures related to the biology of cancer (and even infections within hosts). One of Steven's students at Cornell, Bertrand, grabbed ahold of the idea and ran some initial simulations of a few of our ideas and found a striking result: that the fixation time for a simple Moran process on a large number of known graph structures followed, almost perfectly, a simple log-normal distribution.

An except from a much more complete, and fun to read document from Bertrand....

This finding struck us as something worth chasing down a bit more. What we found ended up opening up several really fun cans of worms, and began an interesting and fruitful collaboration.
I ended up making the move to Cleveland Clinic, and in the mean time Bertrand and Steven continued to chew on this problem and we published the first paper of the collaboration Takeover times for a simple model of network infection, in Physical Review E. It was in this paper where we first realized that the distributions we were observing were not, in fact, log normal, but instead were a kind of extreme value distribution called a Gumbel distribution, which has been known to masquerade as log-normal.

We kept chewing on the problem, and I went to visit Cornell and took a long walk with Bertrand and Steven and Murray (the Strogatz family dog) and even more lightbulbs went off concerning a quite technical, but important detail of the models of evolutionary dynamics - in particular, the choice of the order of update (Birth or Death first) and how fitness biases are implemented (whether you choose which node to replace based on fitness, or how probable it is for a given node to divide).

I gave a short talk the next day, which was live streamed and can be seen here on Cornell's Applied Math colloquium page.  Overall it was a super nice visit, and we were able, I think, to solidify some of our thinking on this issue, which we dutifully scribbled on a napkin:

This led to some further thinking, and then Bertrand opened another kettle of fish when he found a series of papers that discussed 'Sartwell's Law' - which was a phenomenological law describing the 'log-normal' distribution of incubations times (within host) for a long list of diseases, including cancers. While this has been observed for over 100 years, there had yet to be any real work done describing WHY, and it seemed that our model formulation, and results to date, could help explain this. In fact, replotting some old data made for a nice figure one...

and if you want to know WHY??  you'll have to go read the paper that just came out: Evolutionary dynamics of incubation periods in eLife (aside: the review and publication experience was really stellar - 5 stars).

I'm looking forward to what comes next. I think this work has opened up a few doors for folks to go through in probability and network theory for maths folks, possibly in condensed matter/percolation theory for the more physics-y crowd and maybe even in biology and epidemiology. Only time will tell.

Sunday, August 27, 2017

A return to blogging and two new papers: Experimental measurement of evolutionary games and Evolutionary instability in collateral sensitivity networks

Well, the last year has been hectic. I moved my clinical practice to Cleveland Clinic, wrote and defended my thesis (corrections pending...) and have started to grow a research group here in the department of Translational Hematology and Oncology Research. I will begin asking each of the new group members to introduce themselves with short posts here soon, and hope to have at least bi-weekly update posts starting next month.

Before then however, I'm excited to highlight that the two posters that I highlighted on this blog just as I moved, are now full manuscripts. The first, led by +Andrew Dhawan studies how drug sensitivities change over the course of treatment, and even during drug holidays.

This work, which appeared in Scientific Reports, has gotten some attention and we were asked to write a more clinical follow on for Oncology Times called "Evading therapeutic resistance through collateral sensitivities: a paradigm shift?", which you can read here.

The most exciting result from this work was the idea that we need to think about collateral sensitivities a bit harder before we translate them directly to the clinic as they are dynamic even on very short timescales. The full paper, "Collateral sensitivity networks reveal evolutionary instability and novel treatment strategies in ALK mutated non-small cell lung cancer" can be read here:

A tantalizing piece of info here too was the not only did drug sensitivity change over the course of treatment, but so did radiation sensitivity...  More on this later.

The second project, an experimental method to directly measure the evolutionary games cancer cells play during the evolution of resistance has just yielded a new pre-print from the group, led by +Artem Kaznatcheev . Readers of this blog and #mathonco work in general will know that we've been working on evolutionary game theory and cancer for some time - really work started by +David Basanta. David and +Alexander Anderson and +Artem Kaznatcheev and I have now published something like 10 total papers between us on cancer and game theory ranging from studying how hormone therapy timing should work in prostate cancer to how we should think about how our drug scheduling affects tumor composition  and even more abstract ideas like how local cell topology affects evolutionary stable states and dynamics.

Transforming the payoff matrix using the Ohtsuki-Nowak transform allows an understanding of how spatial organization (locally) might change the game... (See Intercace paper linked above)

At issue is that the payoff matrix, the heart of evolutionary games, is usually invented rather than parameterized in any meaningful way. And even when it is it is done indirectly (from literature, or disparate measurements...).  To address this, +Artem Kaznatcheev came up with a clever experimental method to directly measure these games, and we found that the qualitative nature of the game itself can be changed!

So, if this piques your interest, wander over to the bioRxiv and check out the pre-print. With any luck it will be appearing soon in the pages of your favorite journal.

Here you can find "Cancer associated fibroblasts and alectinib switch the evolutionary games that non-small cell lung cancer plays"

OK, see you soon!  Happy reading.

Wednesday, January 25, 2017

Society for experimental biology meeting, Oxford, September 2016

Having just handed in my thesis, after many travails, I am eager to get back to blogging regularly, and to keeping a record of my thoughts.

To begin, I'm going to start by addressing some back-log. So, here, I'd like to briefly describe a great meeting I was able to attend this past September in Oxford. Specifically, 12-15 September, at Lady Margaret Hall in Jericho, I attended a meeting hosted by the Society of Experimental Biology, and organized by my two friends, Ruth Baker and Alex Fletcher - both of whom I know from my own time in Oxford.

For nitty gritty details of the meeting, you can still see the speaker list and abstracts that were presented here:

I'd like to take a moment, instead of the nitty gritty, to describe what were some really nice points (outside the science itself - which was also great) about the meeting that I'd like to carry forward to any meeting I'm lucky enough to organize.

First, the size and scope of the meeting. I often find when I go to meetings like ASCO or ASTRO or even the larger mathematical biology meetings like ECMTB+SMB joint meetings, that I'm overwhelmed by parallel sessions and too many people to possibly wrap my head around.  There is often so much going on that I almost would rather isolate myself and speak only to my closest collaborators - which sort of defeats the purpose of the meeting itself. This meeting, called 'The Tisuee Issue', struck a very nice balance on this point. The size of the full attendance, which I would estimate around 50, was just right. It was large enough that there were people I didn't know, and single voices couldn't take over conversations, but small enough that it wasn't overwhelming, and I felt I could branch outside of my normal circle of friends.

I must admit, that there were also a number of my friends/collaborators gave me some confidence to branch out somewhat. Further, the organizers did a clever thing, which was to break us into discussion groups to discuss aspects of multi-scale (and multi-disciplinary) modelling ranging from education of multi-disciplinary scientists to mathematical limitations of these models. The small group discussions were then brought to the larger forum for a full group session. These sessions were great to break the ice between folks that didn't know eachother, and also allowed more junior members opportunities to present to the larger group.

I think the nicest thing about the meeting, however, was that there were two groups there who don't usually come together.  Namely, developmental biologists and oncologists. There are many commonalities between the disciplines, but there is little cross-over. This meeting allowed us to get to know one another, to see how we were using similar techniques for different problems and to learn some new techniques as well.  While I didn't understand all of what the DevBio crowd was talking about, I was able to appreciate the methods and see new ways to apply them to my own work.

On the whole it was a great experience, and we owe Alex and Ruth, and the Society for Experimental Biology a lot for a great meeting.  Hoping to have a repeat in a couple years time!

We also had some great tweeting going on, which you can see in this storify: