My visit to the Mathematical Neuro-Oncology group at NorthWestern and the talk I gave about glioblastoma evolutionary dynamics and metastasis

I recently was honored by an invitation to visit Chicago and present some of my recent research to my friends and collaborators in a new group formed there by +Kristin Swanson called Mathematical Neuro-Oncology. I spent my time visiting their new, beautiful lab;

celebrating +Russ Rockne's transition;

having some coffee;

visiting my roots;

finding out that a paper long in the works, based on an opinion piece I wrote a few years ago about the effects of the #IDH1 mutation in secondary #glioblastoma, is finally in press at Neuro-Oncology (aside: Somehow there is an editorial written about it that is available (if you PAY, which I haven't yet), but the article is not yet itself available); listening to +Kristin Swanson practice for her +TEDx talk, which I've heard went well, but haven't seen yet (more info here: http://www.tedxuchicago.com/kristin-swanson); and actually giving a talk.

I couldn't decide what to talk about, and since the audience was going to be half computational neuro-oncologists (casual dress) and half general scientific/medical folks (white coast, ties, scrubs), I decided to give a talk in two parts - about a half an hour each.

I spent the first half hour talking about an exciting (to me at least) extension to previous work I've done here at IMO with +Alexander Anderson and +David Basanta and others on glioblastoma stem cells. I've blogged on this topic before, from posts about our recent paper in PLoS Comp Biology to a recent grant we submitted - which, frustratingly didn't get scored due to a very prototypical reviewer #3 (reviewers 1 and 2 gave us 1's 2's and 3's and reviewer #3 gave us 7's, 8's and 9's).

The second half I talked about the work I've done with +Philip Gerlee and +Alexander Anderson and others to understand how a filter-flow paradigm of metastatic spread can help us understand (and intervene) in the process of #metastasis itself. We've published most of this work as a perspective piece in Nature Reviews Cancer, a test of the self-seeding hypothesis in J. Roy. Soc. Interface, a review in a Springer textbook (pre-print here) and recently, a more clinically oriented piece under review at Clinical and Experimental Metastasis (you can see a pre-print here on the +bioRxiv Preprints site). Both I and Philip Gerlee have blogged about it (including a shared post here in response to a Cancer Research UK blog post which we took exception to (at least to parts of it)) in the past as well.

So - anyways, here are the slides. The first half is work in progress, and we're pretty excited about it. I'd love to know if anyone has any feedback.

Investigating the effects of microenvironmental perturbation on a stem driven tumor

I've been interested in the cancer stem cell hypothesis for some time, a subject that my colleague +Heiko Enderling has been thinking about and modeling for some time (list of his pubs here). I first became interested in this concept before I became a DPhil student and member of the Integrated Mathematical Oncology group, when I was a clinical resident in radiation oncology at the Moffitt Cancer Center.  One of the first papers that I saw that truly scared me was a paper by Tamura and colleagues (abstract) that showed that recurrent glioblastomas had a significant increase in CD-133 staining (a stain commonly associated with stemness in this cancer and others), and that this increase is correlated with (maybe causes, jury yet out) an increase in aggressiveness of the recurrent tumor and a decrease in its sensitivity to treatment.

The standard rationale for the latter is that these special 'stem cells' have a higher intrinsic resistance to radiation therapy (which I don't argue), but I subsequently wrote down a series of simple (some might say Noddy) ODE models which suggested, at least to me, that there might also be a stem promoting effect of radiation.  Since then, I have found that this effect has been shown in breast cancer, and further, that there have been a number of microenvironmental perturbations that have been shown to do the same thing, though only in a qualitative way - many of these articles have had my collaborator, +Anita Hjelmeland as a co-author, and I talked about them quite a bit in a previous blog post on our recent R-01 submission.

When I first started on this problem from the theoretical standpoint, it was with ODE models, as I mentioned.  But since then, +David Basanta and +Alexander Anderson and I have worked to build a cellular automaton model of a stem-driven tumor which included blood vessels as sources of oxygen. We built this simple model to test if there were some sort of intrinsic/emergent change in the resultant tissue phenotype when the overall levels of oxygen supplied to it went down (when we reduced the density of the vessels).  Below you can see the schematic of our model system.  On the left is the canonical Cancer Stem Cell hypothesis (which I have major issues with...  more to come in a few weeks I hope) and on the right there is our CA model rules.

After much simulation and effort we found... in short, that no, there is not. Our initial, negative results, were frustrating, but after discussions with +Anita Hjelmeland and Prakash Chinnaiyan (a biologist and clinician, respectively) we found that the model was telling us more...  while we found little qualitative effect when we changed the vascular density, changing the instrinsic stem behavior parameters in the presence of a minimalistic environment revealed that there were only three major meta-phentypic behaviors possible: extinction, dormancy (homeostasis) and overgrowth as seen below.

Our frustration at not seeing the emergence of greater stem-fraction upon lowering the oxygen levels however, led to the rather obvious (in retrospect) conclusion that only through a modification of the symmetric division rate of the stem cells (modified by hypoxia) could this effect be recapitulated. Interestingly, this is a conclusion we had come to in the past using a simpler model system (ODEs) but it was never convincing (though there is a nice piece in J Theoretical Biology which gave me some confidence... here).  Initial testing of this hypothesis, by modification of the CA rules to include this change are striking - surrounding the area of hypoxia, we have an emergent stem cell niche.

Stem cells (red) emerge in areas surrounding necrosis (white/center) when the CA rules allow biased symmetric division in the presence of moderate hypoxia (right).

We have just begun exploring this phenomenon, and indeed there is quite a bit of work to do, both theoretically and experimentally, to validate and better characterize what is going on - so that's why we wrote an R-01.

Anyways, if you want more details, you can read the paper on the bioRxiv now, or in a few days on PLoS Computational Biology where it has been accepted and is nearing publication.  We've also made the baseline code freely available on sourceforge here.

If you have comments on the paper itself, please leave them on the bioRxiv site so anyone can see them (or wait to put them on the PLoS CB site). Ok, back to work.

Glioblastoma: Stem cells, plasticity and the niche(s). A summary and introduction to our R-01 submission.

I've had an interest, both clinically and scientifically, in glioblastoma for about 6 years.  This started out because I was given a project as a medical student looking at outcomes of treatment for elderly patients, but has continued and consumed more and more of my conscious and unconscious thought in the intervening years.  For a long time, patients over 70 weren't given the same care as their younger counterparts because it was felt that the treatment was too harsh for them.  This paradigm has begun to change, thanks in some part to the work I was a part of, but the outcomes remain very poor, for all patients.  While I had success in this initial clinical research (first two figs), I was frustrated at what I perceived as a lack of progress, and didn't feel that I was really contributing to this.  This feeling is really what pushed me into basic research...

Unsurprisingly, adding more therapy extends survival in the elderly.  Taken from:

Scott, J. G., Suh, J. H., Elson, P., Barnett, G. H., Vogelbaum, M. A., Peereboom, D. M., et al. (2011). Aggressive treatment is appropriate for glioblastoma multiforme patients 70 years old or older: a retrospective review of 206 cases. Neuro-oncology, 13(4), 428–436. doi:10.1093/neuonc/nor005

Anyways, my story aside, this post is supposed to be about this new research project. So, let me first provide some background. Glioblastoma is the most common primary malignancy of the brain in adults. It carries a poor prognosis of about 1.5-2 years from diagnosis - even with advanced surgery, radiation and chemotherapy.  The nature of this tumor is quite different from all others - it is incredibly invasive, with rogue cells appearing many centimeters from the primary mass.  This is different than most solid tumors, which typically have a sharp edge where the tumor stops and healthy tissue begins.  There may be some small number of cells that slip over, but usually surgeons are able to get a 'clean margin'.  This is not so in glioblastoma - even if the margin appears clean (no cells visible under the microscope), we know from prior experience that there are viable cells at quite a distance.  There is a famous surgical study from the 1930s where doctors removed THE ENTIRE HEMISPHERE of the brain in which these tumors resided, and the patients recurred on the other side (first reported by Dandy, JAMA 1928).

Recursive Partitioning Analysis showing prognostic subgroups for patients over 70.
Taken from: Scott, J. G., Bauchet, L., Fraum, T. J., Nayak, L., Cooper, A. R., Chao, S. T., et al. (2012). Recursive partitioning analysis of prognostic factors for glioblastoma patients aged 70 years or older. Cancer, 118(22), 5595–5600. doi:10.1002/cncr.27570

To combat this, we have tried treating patient's entire brains with radiation (whole brain radiation therapy), but were not able to control these distant recurrences using safe doses, and given every flavor of chemotherapy you can imagine.  Sadly, only one chemotherapy, temozolomide, has been shown to be effective, providing approximately a 6-8 week survival advantage - far from a home run.

Probably the most famous figure in all glioblastoma research - evidence that a chemotherapy significantly improved survival: by about 6 weeks.  Taken from: 

Stupp, R., Mason, W. P., Bent, M. J. V. D., Weller, M., Fisher, B., Taphoorn, M. J. B., et al. (2005). Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. The New England journal of medicine, 352(10), 987–996. doi:10.1056/NEJMoa043330

So, our standard of care is to treat where the tumor was before surgery and a smallish margin around the edges, and hoping that our chemotherapy will take care of the more distant cells.  In 2004, a famous paper from Singh and colleagues identified a small subset of cells within a glioblastoma which seemed to be responsible for these recurrences - and these cells shared many attributes of non-cancer stem cells.  It turned out that these cells were more resistant to radiation - and this gave us hope: maybe we weren't curing these patients because we were targeting the wrong cells!  The field of glioma stem cell biology has advanced rapidly and many scientists are working on the problem.  A prominent group in this field is led by Jeremy Rich at the Cleveland Clinic's Lerner Research Institute.  They have made many advances, but recently their focus has been on the effect of physical/chemical factors within the 'microenvironment' of the tumor that promote these special 'stem' cells - for example acidity, low oxygen tension and low glucose levels.

One of the scientists from this lab in Cleveland, Anita Hjelmeland, recently took a faculty position at the University of Alabama in Birmingham, where they have a massive brain tumor center (called a SPORE) to continue her work.  She and I met when I was visiting her lab in Cleveland and gave a talk about some of the theory work that +David Basanta and I have done.  She and I hit it off, scientifically, and we decided to start a collaboration.  We've worked together now on a few different projects that are in various phases of development, and just yesterday, we submitted an R-01 (a large scale, 5 year grant) proposal that is led by Anita and David, with participation from myself, +Alexander Anderson and +Heiko Enderling.  We are hoping to leverage the strengths of her biological laboratory with our theoretical modeling techniques to try to make some progress against this cancer. Her work previously has shown, convincingly, that hyoxia (low oxygen levels), acidic pH and low glucose levels promote these 'stem' cells, but trying to understand how they all work together is a difficult task - especially in a living system.  This is where our computational models can help.

Anyways, we have our fingers crossed for the success of our grant, and I'll be sure to keep you updated as to our progress.  As a teaser, I am including a figure from our grant.  Mind you, this is unpublished preliminary data (SHARING IN SCIENCE IS GOOD!), so don't draw too many conclusions from it.

Taken from: 

Heddleston, J. M., Li, Z., Mclendon, R. E., Hjelmeland, A. B., & Rich, J. N. (2009). The hypoxic microenvironment maintains glioblastoma stem cells and promotes reprogramming towards a cancer stem cell phenotype. Cell cycle (Georgetown, Tex.), 8(20), 3274–3284.

Some background: it seems that these special 'stem' cells in the tumor preferentially live in special areas called 'niches'. These niches come in (at least) two different varieties, near to the vasculature, where nutrients are abundant, and near to areas of necrosis (cell death) where nutrients are scarce. This difference is intriguing and some observations have suggested that they might contribute to differences in treatment response.  So - the preliminary finding...  our model suggests that the physical microenvironmental history of these niches is very different, and that the evolutionary dynamics within them are as well!  If we can better understand how these niches are created and maintained, maybe we can make some inroads against the progression of this tumor.

Our model, center, has two different areas in which stem cells seem to reside - near to vessels, where the environment is stable, and near to the areas of necrosis, where the environment is harsh. (unpublished data)

So - wish us luck.  The model that we have extended to make the above prediction is under review at PLoS Computational Biology, but you can see a preprint here.  Anita has published a TON of papers on this subject, which you can find on pubmed.  David has also written several papers (a couple with me) on glioblastoma, but only the preprint so far on stem cells in this disease. Our resident stem cell modeling expert, +Heiko Enderling, will be of great help as well.  You can see his long publication record on his website.