The complex route to metastasis

The latest issue of Nature contains this very interesting article describing two different pieces of research on the topic of prostate cancer to bone metastases. Unfortunately you need to have the right IP address to access these papers free of charge.

Having done some research on prostate cancer to bone metastases (thanks to the Lynch lab) our group has now a better understanding of this disease and about the genetic and cellular drivers that characterize it. We have been working on the role of heterogeneity in cancer before but the source of it gets confounded in metastases: does it generate as one single metastatic cell reaches the bone and the clones acquire mutations? To this now we can add: do heterogeneous metastases in the bone come from a heterogeneous group of  tumor cells traveling together from the prostate? do these metastases start in a homogeneous clonal fashion and become heterogeneous as prostate cancer cells from other metastatic sites go to the bone? A combination of all these possibilities is (wait for it) also a possibility.


A relatively complex model of prostate cancer to bone metastases


CancerEvo got some good news last week. The paper that we have been working together with the Lynch Lab has now been accepted for publication at Cancer Research. Of course being accepted and being published are two different things so it might take a few weeks before those of you with the right subscription get access to the research but we are working to get something in biorxiv in the next few days.

Expect to find a relatively complex model based on the hybrid discrete continuum CA paradigm. That is, an agent based model where cells are governed by rules and molecules like TGF-Beta and RANKL are described by partial differential equations (PDEs).

Did I mention that this model is relatively complex? Well, it kind of is and it is no accident. In general mathematical oncologists pride themselves in producing the simplest mathematical models that fit the problem: the simplest most elegant model is always the best. But I am not sure whether this approach works so well when studying things like homeostasis. Homeostasis in the bone emerges from the interactions of a variety of cells like osteoclasts, osteoblasts, MSCs, etc. Successful metastases to the bone will have to disrupt this homeostasis and co-opt these interactions for their own advantage.

Some of these are mediated by molecules like TGF-Beta and RANKL and that is what we have investigated in this work but I also wonder whether we are missing out by just restricting ourselves to the molecules and cell types that have been the focus of attention by experimentalists. Of course the advantage of doing that is that we have a solid understanding of the known biology thanks to Leah Cook and Conor Lynch.

Which leads me to another point: usually mathematical oncologist work with experimentalist at specific points of the development of a project. Hopefully at inception (not always), then later on when there’s some model results to discuss and finally during the writing of the manuscript. Conor and Leah were involved at every step of this project, which I think is one of the reasons why we could get away with a little bit of extra complexity in this case. It is unfortunate that the current academic publishing system still does not have a way to acknowledge authors in projects with more than one PI and more than one postdoc doing the bulk of the work. At least you, the reader of this post, knows.

Studying metastasis with mathematics

My friend and colleague and all round biomedical scientist Jacob Scott (@CancerConnector) came to work last week and proudly showed us a copy of a book called Experimental metastasis: Modeling and analysis where Jacob led the writing of a chapter on mathematical modelling of metastases.

Experimental metastasis
Jake’s chapter is here

If you have the money click the link and, by any (monetary) means, get the book and read his chapter. But if you do not, be aware that Jake (as well as the rest of the coauthors of this chapter including Jake’s DPhil supervisors Sandy Anderson (@ara_anderson) and Philip Maini as well as  Philip Gerlee (@pgerlee), Alex Fletcher (@alexgfletcher) and yours truly (@dbasanta)) is happy to make his publicly financed research available to the public so here is the ArXiv link for your enjoyment.