One more year one more IMO Workshop. This year our group worked on CMML or Chronic MyeloMonocytic Leukemia, a relatively rare blood cancer. As usual in IMO workshops our team included clinical (physician and malignant hematology specialist Eric Padron), cancer biologists (Andriy Marusyk and Daria Miroshnychenko) and mathematical modelers from Moffitt, Cleveland Clinic, Oxford, Yale and Harvard. A crack team of interdisciplinary researchers that I was lucky to be part of.
The JAK pathway is considered a driver of CMML and fortunately a drug known as ruxolitinibruxolitinib can target cells whose growth is driven by JAK. Unfortunately, as it is the case with most targeted treatments, ruxolitinib quickly leads to the emergence of resistance and relapse. While this is not entirely surprising, the interesting bit is that neither allele frequency nor tumor burden are impacted by the treatment. What exactly drives ruxolitinib resistance?
Team member Artem Kaznatcheev has written about the basis of our project before so please start by taking a look there. Our group produced a suite of models where we consider three distinct possibilities: that there is a subtle Darwinian selection force impacting proliferation rates, that a (provocatively named) Lamarckian force is driving resistance or that non cell-autonomous mechanisms are in place. We clearly thought of something that resonated with the workshop judges as we were awarded a pilot grant to test this experimentally so stay tuned.
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.
Today we are hosting in our group at TU Dresden a mini workshop on cellular automata in biology. Three talks (one in the morning and two in the afternoon) are actually about CAs and cancer. It will be a busy but interesting day.
The booklet for the afternoon part of the workshop (the longest part of it) is here.
I am back from sunny Scotland in sunny Saxony. Of the remaining speakers in Dundee, the one whose talk I was looking for the most was the one from Robert Gatenby, Arizona University (as with Vito Quaranta, a life scientist).
I know the work of Gatenby because he is one of the few researchers involved in using evolutionary game theory (although not of the most conventional, fitness-and-payoff-table kind) to study cancer evolution. Specifically he is working on how acidity due to glycolysis (the anaerobic metabolism that constitutes and advantage for tumour cells that lack oxygen due to the distance to a blood vessel) is a necessary step in the evolution towards cancer. The so called Warburg effect is the result of a well known biochemical mechanism but, what is the evolutionary advantage?
As he has shown in other papers, the advantage for glycolytic cells is that the poison the environment of other cells so they face less competition. They also degrade the connective tissue and thus increase the motility of cells, which is a required step for a tumour to become invasive. From my point of view it is interesting that he seemed to imply that this acidification of the microenvironment is not only a facilitator for cancer but a necessary step. I guess that Hanahan and Weinberg could include this in the section for mechanisms for invasion and metastasis.
From the therapeutic point of view, his research suggests that either alkalising the microenvironment (to counteract the progressive acidification resulting from the glycolytic metabolism) or making it even more acidic by reducing the pH in the blood (and thus contributing to self poisoning of glycolytic cells) would be something worth trying.
Many interesting speakers in this workshop in Dundee but most of them fall in the mathematics part of biomathematics. Among the few who do not is the biologist Vito Quaranta (Vanderbilt University). Although I have been told many times that things are changing for the better in that respect, the scarcity of life scientists and medical doctors in these type of conferences tells me that there is still a lot of work to do to convince them that computational and mathematical biology is not only relevant but necessary.
The talk from Vito Quaranta was not so much about science as about doing science at the interface between theory and experiments. He is lucky to count with the resources of the Vanderbilt Integrative Cancer Biology Center. Otherwise the problem of validating the mathematical and computational models with theoreticians come with would be next to impossible. This theoretical models make a number of assumptions about the properties of tumour cells, tissues and micro environments and predict outcomes that in many cases have to be contrasted with in vivo and in vitro experimental results. This experimental work is really challenging given the level of fragmentation of knowledge and expertise in biology and medicine. Different labs with different experimental techniques, machinery, cell lines and the necessary permissions to perform animal experiments and access human clinical data are required to validate one single theoretical model. That means that unless centres like the one in Vanderbilt become much more common most theoretical models will remain experimentally untested unless they proof to come out as the result of the consensus of the theoretical biology community.
I find myself in Dundee, in Scotland, attending a workshop entitled Mathematical modelling and analysis of cancer invasion of tissues. It promises to be an interesting event and some of the attendees are working on topics that are very close to mines so it is good to know what is their contribution to the state of the art.
When I arrived this morning I was expecting good stuff from people like Philip Maini (Oxford), Bob Gatenby (Arizona), Vito Quaranta (Vanderbilt) and Sandy Anderson. Still today’s most relevant talk for me was given by Anna Marciniak-Czochra (Heidelberg) who presented work based on the research presented very recently by Robert Axelrod (and reviewed in this blog here). Axelrod’s work is about how the collaboration between tumour cells could mean that cells do not have to acquire all the necessary capabilities (mentioned in Hanahan and Weinberg’s 2000 work) in order for the tumour to become agressive. This is a word model but in Marciniak-Czochra‘s presentation a mathematical description was shown in which the characteristics of the growth factors (eg. diffusion strength) can determine how useful this collaboration is. It looks like an interesting model and hope a paper will come out soon so I can take a look. Still it seems that a paper that covers Axelrod’s work more comprehensively is still work to be done.
Being a workshop on mathematical biology one of the issues we all face here is how to work with life scientists and thus one of the panel session yesterdays was precisely about that.
It seems that there are different kind of problems theoreticians might find when dealing with clinicians and experimentalists depending on a number of factors:
What kind of people are they? Are they ‘math-skeptic‘? do they have affinity towards theory?
Do you want them to share their expertise with you or do you want to influence the experiments they perform so they can be used in your theoretical model? The latter is significantly more difficult.
Do you work with biologists or with physicians? There is a real difference between the average PhD and the average MD that does some research on the side when it comes to understand the usefulness of theory.
Some tips where also offered by some participants on how to make finding and establishing collaborations. Mainly it helps to attend seminars from the life sciences departments, get yourself familiar with their stuff and get your face known to them so you don’t come as a complete stranger.