Friday, July 28, 2017

Recasting the cancer stem cell hypothesis: unification using a continuum model of microenvironmental forces

New Results

Recasting the cancer stem cell hypothesis: unification using a continuum model of microenvironmental forces

Jacob G. ScottAndrew DhawanAnita HjelmelandJustin LathiaMasahiro HitomiAlexander G. FletcherPhilip K. MainiAlexander R. A. Anderson

Abstract

Since the first evidence for cancer stem cells in leukemia, experimentalists have sought to identify tumorigenic subpopulations in solid tumors. In parallel, scientists have argued over the implications of the existence of this subpopulation. On one side, the cancer stem cell hypothesis posits that a small subset of cells within a tumor are responsible for tumorigenesis and are capable of recapitulating the entire tumor on their own. Under this hypothesis, a tumor may be conceptualized as a series of coupled compartments, representing populations of progressively differentiated cell types, starting from stem cells. The allure of this model is that it elegantly explains our therapeutic failures: we have been targeting the wrong cells. Alternatively, the stochastic model states that all cells in a tumor can have stem-like properties, and have an equally small capability of forming a tumor. As tumors are, by nature, heterogeneous, there is ample evidence to support both hypotheses. We propose a mechanistic mathematical description that integrates these two theories, settling the dissonance between the schools of thought and providing a road map for integrating disparate experimental results into a single theoretical framework. We present experimental results from clonogenic assays that demonstrate the importance of defining this novel formulation, and the clarity that is provided when interpreting these results through the lens of this formulation.

http://www.biorxiv.org/content/early/2017/07/28/169615

Monday, July 3, 2017

The effects of mutational process and selection on driver mutations across cancer types

New Results

The effects of mutational process and selection on driver mutations across cancer types

Daniel TemkoIan TomlinsonSimone SeveriniBenjamin Schuster-BoecklerTrevor Graham

Abstract

Epidemiological evidence has long associated environmental mutagens with increased cancer risk. However, links between specific mutation-causing processes and the acquisition of individual driver mutations have remained obscure. Here we have used public cancer sequencing data to infer the independent effects of mutation and selection on driver mutation complement. First, we detect associations between a range of mutational processes, including those linked to smoking, ageing, APOBEC and DNA mismatch repair (MMR) and the presence of key driver mutations across cancer types. Second, we quantify differential selection between well-known alternative driver mutations, including differences in selection between distinct mutant residues in the same gene. These results show that while mutational processes play a large role in determining which driver mutations are present in a cancer, the role of selection frequently dominates.

http://www.biorxiv.org/content/early/2017/06/12/149096

Thursday, May 11, 2017

Extinction Times In Tumor Public Goods Games

Extinction Times In Tumor Public Goods Games

Philip GerleePhilipp M. Altrock

Abstract

Cancer evolution and progression are shaped by Darwinian selection and cell-to-cell interactions. Evolutionary game theory incorporates both of these principles, and has been recently as a framework to describe tumor cell population dynamics. A cornerstone of evolutionary dynamics is the replicator equation, which describes changes in the relative abundance of different cell types, and is able to predict evolutionary equilibria. Typically, the replicator equation focuses on differences in relative fitness. We here show that this framework might not be sufficient under all circumstances, as it neglects important aspects of population growth. Standard replicator dynamics might miss critical differences in the time it takes to reach an equilibrium, as this time also depends on cellular birth and death rates in growing but bounded populations. As the system reaches a stable manifold, the time to reach equilibrium depends on cellular death and birth rates. These rates shape evolutionary timescales, in particular in competitive co-evolutionary dynamics of growth factor producers and free-riders. Replicator dynamics might be an appropriate framework only when birth and death rates are of comparable magnitude. Otherwise, population growth effects cannot be neglected when predicting the time to reach an equilibrium, and cellular events have to be accounted for explicitly.

http://biorxiv.org/content/early/2017/05/04/134361

Wednesday, May 10, 2017

Mechanistic Modeling Quantifies The Influence Of Tumor Growth Kinetics On The Response To Anti-Angiogenic Treatment

Mechanistic Modeling Quantifies The Influence Of Tumor Growth Kinetics On The Response To Anti-Angiogenic Treatment

Thomas D. Gaddy, Stacey D. Finley

Abstract

Tumors exploit angiogenesis, the formation of new blood vessels from pre-existing vasculature, in order to obtain nutrients required for continued growth and proliferation. Targeting factors that regulate angiogenesis, including the potent promoter vascular endothelial growth factor (VEGF), is therefore an attractive strategy for inhibiting tumor growth. Systems biology modeling enables us to identify tumor-specific properties that influence the response to those anti-angiogenic strategies. Here, we build on our previous systems biology model of VEGF transport and kinetics in tumor-bearing mice to include a tumor compartment whose volume depends on the “angiogenic signal” produced when VEGF binds to its receptors on tumor endothelial cells. We trained and validated the model using in vivo measurements of xenograft tumor volume to produce a model that accurately predicts the tumor's response to anti-angiogenic treatment. We applied the model to investigate how tumor growth kinetics influence the response to anti-angiogenic treatment targeting VEGF. Based on multivariate regression analysis, we found that certain intrinsic kinetic parameters that characterize the growth of tumors could successfully predict response to anti-VEGF treatment. This model is a useful tool for predicting which tumors will respond to anti-VEGF treatment, complementing pre-clinical in vivo studies.

Tuesday, March 14, 2017

Stochastic model of contact inhibition and the proliferation of melanoma in situ

Stochastic model of contact inhibition and the proliferation of melanoma in situ

Mauro Cesar C MoraisIzabella StuhlAlan U SabinoWillian W LautenschlagerAlexandre S QueirogaTharcisio C TortelliRoger ChammasYuri SuhovAlexandre F Ramos

Abstract

Contact inhibition is a central feature orchestrating cell proliferation in culture experiments with its loss being associated with malignant transformation and tumorigenesis. We performed a co-culture experiment with human metastatic melanoma cell line (SK-MEL-147) and immortalized keratinocyte cells (HaCaT). After 8 days a spatial pattern was detected, characterized by the formation of clusters of melanoma cells surrounded by keratinocytes constraining their proliferation. In addition, we observed that the proportion of melanoma cells within the total population has increased. To explain our results we propose a spatial stochastic model (following a philosophy of the Widom-Rowlinson model from Statistical Physics and Molecular Chemistry) where we consider cell proliferation, death, migration, and cell-to-cell interaction through contact inhibition. Our numerical simulations demonstrate that loss of contact inhibition is a sufficient mechanism, appropriate for an explanation of the increase in the proportion of tumor cells and generation of spatial patterns established in conducted experiments.
http://biorxiv.org/content/early/2017/03/02/110007