Wednesday, January 6, 2016

Rotating student: Jeff Peacock - working on evolution of resistance in ALKmut NSCLC using CRISPR

+Andriy Marusyk and I have a medical student rotating through our collaborative lab for the next couple of months, here's an intro with a couple figures from a recent grant of mine.

Also, here's Jeff:



Hello,
As an aspiring radiation oncologist, what originally drew me to the field is its investment in scientific research. My name is Jeffrey Peacock, and I am a visiting 4th year student from UCF who is working in Jake’s lab for the first 2 months of 2016. I am excited to work on some really cool projects that Jake has started. I have spent a few years in a wetlab, both during undergrad and before and during medical school, performing genetic engineering on bacteria and yeast to produce commodity chemicals. One experiment that I designed was a directed evolution study to increase turnover of a bottlenecked enzyme in a metabolic pathway. I have always been fascinated with using mother nature to our advantage in the laboratory, especially when curing cancer is the goal.  When I heard a talk given by Jake at Moffitt during an away rotation for radiation oncology in mid-2015, I knew he was doing some really exciting work that I was interested in doing and that was tangentially similar to work I had done in the past. We spoke briefly after his talk and threw around the idea of me returning during January and February to work in his lab. After meeting with Jake a few times, everything fell into place, and I am on board to start doing research with Jake for the next 2 months.




Although 2 months is not a long time to spend in a wetlab, I am excited to begin a handful of projects that will hopefully produce impactful data. Jake was the first to introduce me to the concept of mapping evolutionary landscapes. A paper published in Science in 2006 showed that there exist certain pathways that populations take in order to evolve to handle a selective pressure (see http://www.ncbi.nlm.nih.gov/pubmed/16601193). Once these landscapes are mapped, they can be used to steer populations along certains paths, such as a path that leads cancer cells to be sensitive to a drug (see Figure 1). In order to begin creating these maps, cancer cell lines need to be evolved to gain resistance to various drugs. My active role in this project will be performing radiation sensitivity and genetic assays on these cancer cell lines at different time points during their evolution against various chemotherapy drugs (see Figure 4). The idea is to gain insight into temporal changes cancer cells experience when exposed to chemotherapy drugs and to determine if there are key time points when synergism between chemo and radiation are at its best and its worst.



The next project involves engineering non small cell lung cancer strains with common mutations that confer resistance to chemotherapy drugs to measure evolutionary landscape. Rather than relying on mother nature to create these mutations, I will be utilizing CRISPR/cas9 to perform common genomic edits on non small cell lung cancer strains to create resistance. These cell lines will then be used to infer evolutionary landscapes developed in prior evolutionary experiments and to create mathematical models to predict chemotherapy regimens that minimize resistance.
I remember being asked during my interviews for medical school the question of where I see myself in 5 years. I would answer that I imagined myself as a clinician who is actively involved in research. At the time, I did not know what type of clinician I wanted to be or what role I would play in research, but I knew that both aspects of medicine were necessary to satisfy my insatiable curiosity and my desire to help people directly. I can honestly say as I approach that 5 year mark that I am beginning to see my vision become a reality, and this beautiful marriage between scientist and clinician is more perfect than I could have ever hoped.

Jeff can be found on twitter at: @ggcancer898





Saturday, October 31, 2015

bioRxiv vs. arXiv

If you've been reading along since the beginning, you'll know that I'm a huge #openaccess fan, and, really, am something of an oversharer. When I began my scientific career, I was posting all of my work on the qBio section of the arXiv. Me and some colleagues responded to the increase in utilisation of #preprint servers by making Warburg's Lens, a blog inspired by Haldane's Sieve to help aggregate mathematical oncology pre-prints, and allow for discussion. We've had a ton of success with Warburg's Lens, and it has been helpful for many folks. One of the nice aspects of it, that the arXiv didn't have, was the ability to comment, and to link in to social media in general.

A couple years ago, Richard Sever contacted me about an upcoming project, the bioRxiv, and asked me to be an affiliate - which I eagerly accepted. It seemed the perfect way to help convince my more open minded biological colleagues - something to which there are still quite a few (unsubstantiated) barriers.

This past summer, at the annual Society for Mathematical Biology Meeting, I gave a talk on pre-print servers and social media in science. While I was preparing for the talk, I ran across a great infographic about the arXiv and was blown away how LITTLE qBio there actually is... (something like 1.6% - TONS MORE info here)



Anyways, I recently asked Richard if there were any stats on publications/utilization of the bioRxiv. At the time, there were no stats done, but today I saw on this twitter:


Within just a year, more than half have been published!  Good news. I'm hoping that my newest preprint (which is also on Warburgs Lens here) joins the majority ASAP :)

Anyways, I'm heartened to see the increase in utilisation.  I have to say, having submitted I think 6 manuscripts to the bioRxiv, and around the same number to the arXiv, the process at the bioRxiv is MUCH easier. It can be done in minutes, rather than fighting with the LaTeX compiler on the arXiv istelf. My current practice is to send everything to the bioRxiv, though I still read and monitor the qBio section of the arXiv... what are your practices?


Thursday, October 22, 2015

Some fun with evolutionary graph theory - and application to cancer?



For a few years now I've been interested in evolutionary graph theory - a branch of mathematics at the nexus of evolutionary dynamics and graph theory. To my knowledge this was all kicked off by Martin Nowak and colleagues with the 2005 Nature paper:  Evolutionary Dynamics on Graphs. One of the coolest results was that certain graph topologies exhibit striking changes in probabilities of fixation (assuming a Moran process) - particularly symmetric graphs called 'stars'.


A beautiful follow on paper by our friends at the Max Planck for evolutionary biology, led by +Arne Traulsen showed that this amplification of probability of selection led to a dramatic increase in time to fixation - sort of balancing out the advantage. You can read more about this in this terse paper in the Royal Society B entitled: The effect of population structure on the rate of evolution.

Since reading these two papers, I have given a fair amount of thought to this problem, but have not come to any sensible conclusions. +Alex Fletcher and +David Basanta and I spent a week or so once coming up with some code to think about how a cancer cell might invade an epithelial sheet (a biological structure that is topologically lattice-like). We never really figured out where to go from there (still working on it!!!), but in the mean time, conversations with Laura Hindersin and Benedikt Bauer at Max Planck about Laura's Phd work (example paper here: Almost all random graphs are amplifiers of selection for birth-death processes, but suppressors of selection for death-birth processes) has sparked a lot of interesting thought and conversation.

Further, at the recent conference: Cancer Evolution Through Space and Time the conversation continued and we started talking more about 'mixed' topology structures. The conversation has continued on twitter, culminating with a new student in my lab +Sudhir Manickavel starting some work simulating evolution. Here's where our thinking is going:







When he first started considering this project +Sudhir Manickavel , a medical student asked of the Royal Society paper mentioned above:

"I read the paper and I found it interesting, especially the idea that even though star structured populations have a greater fixation probability it actually takes them longer to fix.

I do have one question about the paper, in reference to a tumor how would you define a tumor population as well mixed or star structured?" 

A great question...  to which I responded:

"What is the topology of an epithelial sheet? What is the topology of a colonic crypt?  Does the topology of the stem cell niche within the crypt differ from that of the walls of the crypt?  How would you characterize the topology of bone marrow? Or - in infectious diasese: Of a blood borne pathogen? Of a biofilm?"

And included a link to a Gatenby classic which opens with:

"The human body plays with evolutionary fire" and discusses the unique (changing) topology of the colonic crypt and how this may influece evolutionary dynamics...

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3744108/

Which seemed to sell him on the topic as just this morning, I looked in my dropbox, and it looks like +Sudhir Manickavel is making some progress (though there seems to be a missing node...  :) ):

initial condition plotted with networkx to study the moran process evolving on a 'mixed' topology structure... is it a ring or is it a star?
Anyways, the start of a fun project either way.

Sunday, September 27, 2015

Full storification of Cancer Evolution Through Space and Time: #CEST15

My friend, supervisor and department Chair +Alexander Anderson compiled a full storification of the recent Cancer Evolution Through Space and Time meeting with the hashtag #CEST15.

You can find it on his storify page here:

https://storify.com/ara_anderson/cancer-evolution-through-space-time

but I've also embedded it below.  It was an AMAZING week bringing together folks from the bacterial evolution community, game theorists and the cancer evolution world (theory, experiment and genomics). I've already heard calls to repeat the meeting next year. Personally, I can't wait to follow up on the relationships I made, which are myriad!

Thanks to Sandy and +Arne Traulsen and all the crew at The Max Planck for Evolutionary Biology who made the visit so nice.  Enjoy the storification that Sandy compiled.


Monday, September 14, 2015

The first ever mathematical model to capture cancer growth dynamics, published 2015...

Last week saw one of the most striking oversells of a paper I've seen in the recent past, and it frustrated a lot of people in my field.

The paper -

A spatial model predicts that dispersal and cell turnover limit intratumour heterogeneity

can be found here: http://www.nature.com/nature/journal/v525/n7568/full/nature14971.html

It is a spatial cellular automaton model (beautifully visualized) that looks at cancer growth and migration in a 3-d spatial context. The authors did a good job citing appopriate work (>100 citations) and never made any claims that were over the top. The press release, however...  well...  I'll let the twitter backlash speak.

I think the most striking thing about all of this was the the senior author, Martin Nowak, one of the fathers of evolutionary dynamics and most successful mathematical biologists in the world, came on to twitter to apologize for the Press Release (see final tweet). Class move.

At the end of the day, we have little control of the press releases for our papers. And, while we certainly all want to see our work publicized (how else can people find out about it?), seeing good work cheapened in some way by an oversold press release doesn't help anyone.

Anyways, here is a tour of spatial models of cancer, twitter style. #notthe1sttime


Monday, April 13, 2015

Author Manuscripts - clarification of PLoS Comp Biol's policy

Just a quick post. I and some colleagues recently submitted one of our papers "Steering Evolution with Combination Therapy to Prevent the Emergence of Bacterial Antibiotic Resistance" (which you can read a nice post on +Artem Kaznatcheev's blog here) to PLoS Computational Biology, and I was surprised that an option to submit a full 'author manuscript' wasn't present, but instead that we had to upload images separately, reformat and the like.  This surprised me, because the first time I submitted there, in a paper I wrote with +David Basanta and +Alexander Anderson I didn't remember having to do this. It might be that I just misread, but at the time I was confused.

So, I tweeted to them a quick question and it turns out they DO accept author manuscripts, but that their instructions are on the fritz right now!  

Anyways, they replied quickly with an email as well stating:

We allow a single PDF to be submitted at initial submission, although as the paper is subsequently revised, we require the manuscript to be submitted in separate parts to begin to prepare the manuscript for production. This is to avoid asking authors to do everything at once at acceptance, a process that can, in some instances, be a substantial task.
I understand that this is not clear on the author instructions and we are looking at ways of improving our instructions.

So - submit away. And, thank for the quick reply to PLoS CB... now it's just fingers crossed for our submission.