As much as I like science (doing science or reading about it) I also like running. Luckily running and thinking are quite complementary activities so I do not see the time I spend running as something detracting from my work. Since I arrived to +Moffitt Cancer Center
in the summer of 2008 I have participated in a charity race called Miles 4 Moffitt.
This event, organised for +Moffitt Cancer Center
, raises money for local cancer researchers. I know a few of my colleagues that applied and received some of that money and I know how much it helps junior researchers at Moffitt to get a little bit of funding so they can test new ideas that would go untested otherwise. This year I am not only running but also trying to raise a very modest sum of money for this cause.
If you live in the Tampa Bay area you should definitely join us on the 10th of May this year. Click on the first image of this post and sign up. But if you cannot make it in person and want to help one way to do this is by donating money to the cause. The following link will take you to the donation page generated for my participation for Miles 4 Moffitt:
Some of my friends and colleagues at Moffitt’s IMO are also running and they could do with your help as well:
A couple of months ago +Jacob Scott and I (as well as +Anita Hjelmeland , +Prakash Chinaiyan and +Alexander Anderson ) got our work accepted in PLOS Computational Biology and finally it is available online here.
This is an example of a simulation where on the left you can see the different types of cells (stem in red and non stem in green and blue) as well as blood vessels; whereas on the right you can see the concentration of oxygen (from white where there is abundance to red where there is hypoxia). The work is available to anybody since it is a PLOS paper. +Jacob Scott
has also produced a nice description on his blog here
. So go ahead and take a look if you are interested in mathematical oncology, cancer stem cells, both or either.
Also thanks to +Alexander Anderson
for this paper. This work started a few years ago when I was a postdoc at his group using a mathematical tool, the hybrid discrete-continuum cellular automaton, that I learned from him. Nonetheless he let me take responsibility for the project while at the same time contributing to it with his expertise and ideas.
Expect to see new results from this model soon, it is difficult to stop +Jacob Scott
when he has an idea and I am afraid he has quite a few involving versions of this model.
Followers of this blog (or even just casual readers) know that heterogeneity is a key aspect of cancer. Not that I am saying that this is my idea, far from it. Many people have championed it in the last few years including my colleague +Alexander Anderson. A couple of years ago CRUK’s Charles Swanton and his team produced convincing clinical evidence of the existence of phenotypic heterogeneity in kidney cancer [news,article] and a lot more people started paying attention. Since then researchers have found evidence of heterogeneity in other types of cancer such as prostate, bone or Barrett’s esophagus.
Why is this important you say (or not…)? Because we are moving towards the use of targeted therapies. Therapies that, for the most part, assume that there are critical *targetable* mutations that all tumour cells share. Sadly this is unlikely to be true for most cancers.
An exception could be CML or Chronic Myeloid Leukemia, a type of tumour in which I started working recently during the IMO workshop (+Artem Kaznatcheev describes it nicely here [link]). Our clinical experts were quite clear that there is no heterogeneity in CML. There is only a key mutation, BCR-ABL, driving CML that if messed with, controls the cancer. That lack of genetic heterogeneity could explain why treatments like imatinib are so effective.
But it does not work every time, it does not work the same for everybody and even if there is not substantial genetic heterogeneity there are other elements that explain intra-tumour heterogeneity. +Chandler Gatenbee and I came with this list, which is certainly not exhaustive, during a brainstorming session:
There are tumour cells with different degrees of stemness, cells at different states of the cell cycle, different proliferative potential, expresion of Beta-catenin…and that is before we even start considering the microenvironment of the tumour (access to oxygen, other cells, that is, non-tumour cells…). Could it be the reason why not all patients respond the same way to the, otherwise very successful imatinib? I think there is a good chance that heterogeneity could be behind that. Let’s now see if our clinicians at Moffitt (or maybe elsewhere) can give us a information we could use to correlate CML heterogeneity and response to imatinib.