Introducing mathematical oncology to cancer biology and medical students

This Wednesday, as I did last year ago, I am helping with a lecture series entitled Modern Basic Tools of Research at the Moffitt Cancer Center. Last year's was a pleasurable experience and for 2h we talked about different ways to model growth in tumours. First with growth laws describing population change over time (examples of those laws can be found here), then with more mechanistic models where the dynamics of the tumour growth emerge from the way that different cells interact with each other and with their environment.

This year going that far will be more difficult: my 2h have been reduced to 30m. Thus I am trying to change the focus of the lecture and maybe limit my ambitions. Interestingly this could be a blessing in disguise since I might be forced to try to figure out what is the essence of mathematical modelling of cancer and explain that to smart people that do not have a background (or maybe not even an interesting) in mathematical modelling.

And why 30m this year? Because due to time constraints, the same 2h lecture slot will be used to teach about biostatistics, bioinformatics and mathematical modelling. And that is good: since I have been working in this field every biologist and medical professional I met expected me to be a statistician after describing myself as a mathematical oncologist. This is going to be a great opportunity to explain what we have in common but also the ways in which we work differently.

Hoping to not misrepresent excessively what biostastisticians and bioinformaticians do (expect a line saying UPDATE at the end of this post very soon!), their work is incredibly useful to both cancer biologists and doctors since it allows them to figure out what the data says about a specific biological process or clinical trend. It also allows them to know whether that trend or pattern is meaningful or not or whether they have collected enough experimental points or clinical data to make any statement about it.

The best part is that all that extra information usually comes at very little cost to the experimentalists. Mathematical oncologists on the other hand, we tend to be somewhat more difficult to work with since we need to have an understanding of the biological mechanisms underpinning the cancer we are studying. We, for instance, take a look at the diagram after the first paragraph and think: do all these cell interact with each other? if so how? these tumour cells, are they all the same? where do they come from? do they come alone or together? do they usually arrive in the neighbourhood of the other cells in the diagram? if not, do they sit and wait? Maybe some of the questions would be part of the conversation between experimentalists and but many of them seem to arise when mathematical and computational modellers are involved. When implementing these ideas into a computer, ambiguities are not an option. Ideas that might work in your mind or mine come crashing down when subjected to the cold logic of a computer.

It takes time.

The advantage? We can test new hypotheses, generate novel ones, get molecular, clinical, cellular data and integrate it into the model, we can get all those single cell level measuraments and feed them directly into the model, we can take all these population level experiments and figure out what hypothesis explain them better. We can use that to understand the biology of the cancer, to design new biological experiments, to predict better clinical treatments, to hypothethise how new ones would impact patients in the clinic.

If you are an experimentalist you should know that using mathematical model will require you to work in a different way, to ask different questions and to view of your research with different lenses but it is worth it.

By the way, all the figures in the post have been crafted by our very own +Arturo Araujo .

Pint of Science

+Arturo Araujo and myself think that our mission as scientists consists, not only in producing new and interesting discoveries, not only contributing to research a cure to cancer but also in making sure that the society at large understands the nature of what we do and the implications of our work.

Is for that reason that, together with +Angela Rey, we jumped into the opportunity to help +Parmvir Bahia start +Pint of Science US , and offshoot of the UK based Pint of Science, but with a twist: that we will produce regular meetings and podcasts where people in Tampa and beyond will have the chance to interact with our local scientists.

The first of these events will take place tomorrow at The New World Brewery in Ybor City and will feature a friend and colleague at +Moffitt Cancer Center 's IMO: +Jacob Scott. So science, medicine and mathematics will be the ingredients for tomorrow's event at 7pm (9/3/2013). Come if you can, more details at Pint of Science US.

The story of a paper

Together with my good friend and collaborator +Jacob Scott and our new collaborator +Artem Kaznatcheev , we have recently wrote (what I hope you will find) an interesting paper where we explored one of older games (emergence of motility in tumours mostly made of rapidly proliferating cells) and studied what happened when cells grow and reach an edge or a boundary. Normally I would try to recapitulate how did we do our work and what the results are but this time I do not need to bother since my collaborators are so much faster and better than me at this.

For a story of how this work started and how we did this work take a look at +Jacob Scott's latest post.

The work itself has been described in detail by +Artem Kaznatcheev on his own blog in the following post.

Writing grants

Unfortunately, a good deal of the work of a professional biomedical scientist in the US involves writing grants. It might provide a consolation to some to know that almost 100 years ago scientists still had to write grant proposals. I am not sure how many would have looked like this though:

Dr. Arturo Araujo

Congratulations to one of our members, Arturo Araujo on switching his Mr. to Dr. having successfully defended his PhD thesis at University College London last week.

 

Here we can see +Arturo Araujo celebrating with his PhD supervisor +Peter Bentley and his examiners +Alex Fletcher and +Philip Gerlee 

Exploiting ecological principles to better understand cancer progression and treatment

I talked about this before in Google+ but the paper +Alexander Anderson and myself authored at the Royal Society Interface focus is now available for everybody to see. This is a somewhat unconventional type of paper as it is not exactly a research paper, a review paper or an opinion piece but a combination of all those. I must apologise that the article is not in an open access journal but the version in arXiv has all the content (even if it's not as pretty as the journal version). Also, at least for some time, the article can be downloaded from Interface Focus [PDF].

By the way, the visuals of the article, including the following sketch by +Arturo Araujo describing the ecosystem of prostate cancer metastasis to bone, are quite impressive I think.

More on game theory and the evolution of invasive phenotypes

+Artem Kaznatcheev , a colleague at McGill University, has taken an old paper of ours and decided to do further analysis on it. The emergence of invasiveness is one of the hallmarks of cancer progression and space is likely to play a very important role. For that reason, I used both standard evolutionary game theory and cellular automata to see how much our original results would change if space is explicitly considered. The results can be found here. Now +Artem Kaznatcheev has worked on a Ohtsuki-Nowak transform so that we could still try to understand the role of space without sacrificing the analytical power of game theory. He blogged about it here and the preliminary results look promising. The number of neighbours a tumour cell has impacts the likelihood of motility to emerge in a tumour population. Hope we can learn more about this technique in the next few days now that +Artem Kaznatcheev is in Florida.

Back to blogger

I am back to blogger! Or to be more precise, we are. When I left blogger  a few years ago the idea was to start using a blogging platform that would allow me to share my ideas with likeminded people. That initially was Nature Networks, and eventually Google+. Now we are starting another experiment with blogger, one in which this blog will capture all the news and events related to the CancerEvo group at the Integrated Mathematical Oncology department at the H. Lee Moffitt Cancer Center in Tampa. Hope to see you all very often around these pages!

David and the CancerEvo group.

Moving to Nature Networks

Dear everybody.

From now on this blog is moving to Nature Networks. Find it following this link.

See you there!

Mini workshop in Oxford

Today Marcus Tindall has organised a mini symposium (for lack of a better name) for me and the guys here working on mathematical models of cancer to get to know each other. I have given a very small presentation [PDF] (<30m) that covers stuff I presented before.

From the CMB I got to know the work of:

• Philip Murray, who has created a CA model to study the role of the cell cycle in tumours and that is now trying to obtain a continuous model that displays the same behaviour.
• Alex Fletcher who studies hypoxia in tumour development at the sub-cellular scale.
• Matt Johnston who works with W. Bodmer (whose game theory models have inspired my own work) to study the dynamics of cell populations in a colon crypt in colorectal cancer. His model shows how a homeostatic population could explode by slightly altering some of the paramers.
• Natasha Li who collaborates with Gatenby to study, using Cellular Automaton and continuous models, the role of glycolysis in tumour invasion and the influence of the stromal environment. This is specially relevant to me since it is one of my two main lines of work at the moment. She mention in her talk that glycolytic cells are especially sensitive to glucose deprivation.
  
• Rebecca Carter works on multiscale models of fluid and drug transportation in tumours.
• Marcus Tindall gave a brief introduction to his multiscale model of interaction between the cell cycle and cell density.

The presentations were all quite short but I hope to hear more from these people in the coming days.