The Evolutionary Trade-off between Stem Cell Niche Size, Aging, and Tumorigenesis

Vincent L. Cannataro, Scott A. McKinley, Colette M. St. Mary

Abstract

Many epithelial tissues within large multicellular organisms are continually replenished by small independent populations of stem cells. These stem cells divide within their niches and differentiate into the constituent cell types of the tissue, and are largely responsible for maintaining tissue homeostasis. Mutations can accumulate in stem cell niches and change the rate of stem cell division and differentiation, contributing to both aging and tumorigenesis. Here, we create a mathematical model of the intestinal stem cell niche, crypt system, and epithelium. We calculate the expected effect of fixed mutations in stem cell niches and their expected effect on tissue homeostasis throughout the intestinal epithelium over the lifetime of an organism. We find that, due to the small population size of stem cell niches, fixed mutations are expected to accumulate via genetic drift and decrease stem cell fitness, leading to niche and tissue attrition, and contributing to organismal aging. We also explore mutation accumulation at various stem cell niche sizes, and demonstrate that an evolutionary trade-off exists between niche size, tissue aging, and the risk of tumorigenesis; where niches exist at a size that minimizes the probability of tumorigenesis, at the expense of accumulating deleterious mutations due to genetic drift. Finally, we show that the probability of tumorigenesis and the extent of aging trade-off differently depending on whether mutational effects confer a selective advantage, or not, in the stem cell niche.

http://dx.doi.org/10.1101/059279

Evolutionary dynamics of CRISPR gene drives

Charleston Noble, Jason Olejarz, Kevin Esvelt, George Church, Martin Nowak

Abstract

The alteration of wild populations has been discussed as a solution to a number of humanity's most pressing ecological and public health concerns. Enabled by the recent revolution in genome editing, CRISPR gene drives, selfish genetic elements which can spread through populations even if they confer no advantage to their host organism, are rapidly emerging as the most promising approach. But before real-world applications are considered, it is imperative to develop a clear understanding of the outcomes of drive release in nature. Toward this aim, we mathematically study the evolutionary dynamics of CRISPR gene drives. We demonstrate that the emergence of drive-resistant alleles presents a major challenge to previously reported constructs, and we show that an alternative design which selects against resistant alleles greatly improves evolutionary stability. We discuss all results in the context of CRISPR technology and provide insights which inform the engineering of practical gene drive systems.

doi: http://dx.doi.org/10.1101/057281  

link: http://biorxiv.org/content/early/2016/06/06/057281

 

 

tHapMix: simulating tumour samples through haplotype mixtures

Sergii Ivakhno, Camilla Colombo, Stephen Tanner, Philip Tedder, Stefano Berri, Anthony J. Cox

 

Abstract

Motivation: Large-scale rearrangements and copy number changes combined with different modes of clonal evolution create extensive somatic genome diversity, making it difficult to develop versatile and scalable variant calling tools and create well-calibrated benchmarks. Results: We developed a new simulation framework tHapMix that enables the creation of tumour sam-ples with different ploidy, purity and polyclonality features. It easily scales to simulation of hundreds of somatic genomes, while re-use of real read data preserves noise and biases present in sequencing platforms. We further demonstrate tHapMix utility by creating a simulated set of 140 somatic genomes and showing how it can be used in training and testing of somatic copy number variant calling tools. Availability and implementation: tHapMix is distributed under an open source license and can be downloaded from https://github.com/Illumina/tHapMix .

Link: http://biorxiv.org/content/early/2016/06/06/057414

DOI: http://dx.doi.org/10.1101/057414

 

 

Non-linear tumor-immune interactions arising from spatial metabolic heterogeneity

Mark Robertson-Tessi, Robert J Gillies, Robert A Gatenby, Alexander RA Anderson

doi: http://dx.doi.org/10.1101/038273

This article is a preprint and has not been peer-reviewed [what does this mean?].

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Abstract

A hybrid multiscale mathematical model of tumor growth is used to investigate how tumoral and microenvironmental heterogeneity affect the response of the immune system. The model includes vascular dynamics and evolution of metabolic tumor phenotypes. Cytotoxic T cells are simulated, and their effect on tumor growth is shown to be dependent on the structure of the microenvironment and the distribution of tumor phenotypes. Importantly, no single immune strategy is best at all stages of tumor growth.

http://biorxiv.org/content/early/2016/05/04/038273

Toxicity Management in CAR T cell therapy for B-ALL: Mathematical modelling as a new avenue for improvement.

Shalla Hanson, David Robert Grimes, Jake P. Taylor-King, Benedikt Bauer, Pravnam I. Warman, Ziv Frankenstein, Artem Kaznatcheev, Michael J. Bonassar, Vincent L. Cannataro, Zeinab Y. Motawe, Ernesto A. B. F. Lima, Sungjune Kim, Marco L. Davila, Arturo Araujo

Abstract

Advances in genetic engineering have made it possible to reprogram individual immune cells to express receptors that recognise markers on tumour cell surfaces. The process of re-engineering T cell lymphocytes to express Chimeric Antigen Receptors (CARs), and then re-infusing the CAR-modified T cells into patients to treat various cancers is referred to as CAR T cell therapy. This therapy is being explored in clinical trials - most prominently for B Cell Acute Lymphoblastic Leukaemia (B-ALL), a common B cell malignancy, for which CAR T cell therapy has led to remission in up to 90% of patients. Despite this extraordinary response rate, however, potentially fatal inflammatory side effects occur in up to 10% of patients who have positive responses. Further, approximately 50% of patients who initially respond to the therapy relapse. Significant improvement is thus necessary before the therapy can be made widely available for use in the clinic. To inform future development, we develop a mathematical model to explore interactions between CAR T cells, inflammatory toxicity, and individual patients' tumour burdens in silico. This paper outlines the underlying system of coupled ordinary differential equations designed based on well-known immunological principles and widely accepted views on the mechanism of toxicity development in CAR T cell therapy for B-ALL - and reports in silico outcomes in relationship to standard and recently conjectured predictors of toxicity in a heterogeneous, randomly generated patient population. Our initial results and analyses are consistent with and connect immunological mechanisms to the clinically observed, counterintuitive hypothesis that initial tumour burden is a stronger predictor of toxicity than is the dose of CAR T cells administered to patients. We outline how the mechanism of action in CAR T cell therapy can give rise to such non-standard trends in toxicity development, and demonstrate the utility of mathematical modelling in understanding the relationship between predictors of toxicity, mechanism of action, and patient outcomes.

Link:http://biorxiv.org/content/early/2016/04/22/049908

Universal asymptotic clone size distribution for general population growth

Michael D. Nicholson, Tibor Antal

Deterministically growing (wild-type) populations which seed stochastically developing mutant clones have found an expanding number of applications from microbial populations to cancer. The special case of exponential wild-type population growth, usually termed as the Luria-Delbruck or Lea-Coulson model, is often assumed but seldom realistic. In this article we generalise the model to different types of wild-type population growth, with mutants evolving as a birth-death branching process. Our focus is on the size distribution of clones after some time, which can be mapped to the total number of mutants. Exact expressions are derived for exponential, power-law and logistic population growth. We prove that the large time limit of the clone size distribution has a general two-parameter form for a large class of population growth. The large time clone size distribution always has a power-law tail, and for subexponential wild-type growth the probability of a given clone size is inversely proportional to the clone size. We support our results by analysing a data-set on tumour metastasis sizes, and we find that a power-law tail is more likely than an exponential one, in agreement with our predictions.

Link: http://arxiv.org/abs/1604.04936#

Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights

Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silica insights

J. C. L. Alfonso, A. Kohn-Luque, T. Stylianopoulos, F. Feuerhake, A. Deutsch, H. Hatzikirou

There is an ongoing debate on the therapeutic potential of vaso-modulatory interventions against glioma invasion. Prominent vasculature-targeting therapies involve functional tumour-associated blood vessel deterioration and normalisation. The former aims at tumour infarction and nutrient deprivation medi- ated by vascular targeting agents that induce occlusion/collapse of tumour blood vessels. In contrast, the therapeutic intention of normalising the abnormal structure and function of tumour vascular net- works, e.g. via alleviating stress-induced vaso-occlusion, is to improve chemo-, immuno- and radiation therapy efficacy. Although both strategies have shown therapeutic potential, it remains unclear why they often fail to control glioma invasion into the surrounding healthy brain tissue. To shed light on this issue, we propose a mathematical model of glioma invasion focusing on the interplay between the mi- gration/proliferation dichotomy (Go-or-Grow) of glioma cells and modulations of the functional tumour vasculature. Vaso-modulatory interventions are modelled by varying the degree of vaso-occlusion. We discovered the existence of a critical cell proliferation/diffusion ratio that separates glioma invasion re- sponses to vaso-modulatory interventions into two distinct regimes. While for tumours, belonging to one regime, vascular modulations reduce the tumour front speed and increase the infiltration width, for those in the other regime the invasion speed increases and infiltration width decreases. We show how these in silico findings can be used to guide individualised approaches of vaso-modulatory treatment strategies and thereby improve success rates.

Link:arXiv:1604.05082http://arxiv.org/abs/1604.05082