scholarly journals A unified simulation model for understanding the diversity of cancer evolution

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8842 ◽  
Author(s):  
Atsushi Niida ◽  
Takanori Hasegawa ◽  
Hideki Innan ◽  
Tatsuhiro Shibata ◽  
Koshi Mimori ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Model ◽  
Mutation Rate ◽  
Evolutionary Dynamics ◽  
Intratumor Heterogeneity ◽  
Cancer Evolution ◽  
Evolutionary Processes ◽  
Stem Cell Hierarchy ◽  
Neutral Mutations ◽  
Short Time

Because cancer evolution underlies the therapeutic difficulties of cancer, it is clinically important to understand the evolutionary dynamics of cancer. Thus far, a number of evolutionary processes have been proposed to be working in cancer evolution. However, there exists no simulation model that can describe the different evolutionary processes in a unified manner. In this study, we constructed a unified simulation model for describing the different evolutionary processes and performed sensitivity analysis on the model to determine the conditions in which cancer growth is driven by each of the different evolutionary processes. Our sensitivity analysis has successfully provided a series of novel insights into the evolutionary dynamics of cancer. For example, we found that, while a high neutral mutation rate shapes neutral intratumor heterogeneity (ITH) characterized by a fractal-like pattern, a stem cell hierarchy can also contribute to shaping neutral ITH by apparently increasing the mutation rate. Although It has been reported that the evolutionary principle shaping ITH shifts from selection to accumulation of neutral mutations during colorectal tumorigenesis, our simulation revealed the possibility that this evolutionary shift is triggered by drastic evolutionary events that occur in a short time and confer a marked fitness increase on one or a few cells. This result helps us understand that each process works not separately but simultaneously and continuously as a series of phases of cancer evolution. Collectively, this study serves as a basis to understand in greater depth the diversity of cancer evolution.

scholarly journals A unified simulation model for understanding the diversity of cancer evolution

2019 ◽  
Author(s):  
Atsushi Niida ◽  
Takanori Hasegawa ◽  
Hideki Innan ◽  
Tatsuhiro Shibata ◽  
Koshi Mimori ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Model ◽  
Mutation Rate ◽  
Evolutionary Dynamics ◽  
Intratumor Heterogeneity ◽  
Cancer Evolution ◽  
Evolutionary Processes ◽  
Stem Cell Hierarchy ◽  
Neutral Mutations ◽  
Short Time

ABSTRACTBecause cancer evolution underlies the therapeutic difficulties of cancer, it is clinically important to understand the evolutionary dynamics of cancer. Thus far, a number of evolutionary processes have been proposed to be working in cancer evolution. However, there exists no simulation model that can describe the different evolutionary processes in a unified manner. In this study, we constructed a unified simulation model for describing the different evolutionary processes and performed sensitivity analysis on the model to determine the conditions in which cancer growth is driven by each of the different evolutionary processes. Our sensitivity analysis has successfully provided a series of novel insights into the evolutionary dynamics of cancer. For example, we found that, while a high neutral mutation rate shapes neutral intratumor heterogeneity (ITH) characterized by a fractal-like pattern, a stem cell hierarchy can also contribute to shaping neutral ITH by apparently increasing the mutation rate. Although It has been reported that the evolutionary principle shaping ITH shifts from selection to accumulation of neutral mutations during colorectal tumorigenesis, our simulation revealed the possibility that this evolutionary shift is triggered by drastic evolutionary events that occur in a a short time and confer a marked fitness increase on one or a few cells. This result helps us understand that each process works not separately but simultaneously and continuously as a series of phases of cancer evolution. Collectively, this study serves as a basis to understand in greater depth the diversity of cancer evolution.

scholarly journals Cancer evolution simulation identifies possible principles underlying intratumor heterogeneity

2015 ◽  
Author(s):  
Atsushi Niida ◽  
Satoshi Ito ◽  
Georg Tremmel ◽  
Seiya Imoto ◽  
Ryutaro Uchi ◽  
...  
Keyword(s):  
Evolutionary Process ◽  
Neutral Evolution ◽  
Intratumor Heterogeneity ◽  
Cancer Evolution ◽  
Driver Genes ◽  
Evolutionary Selection ◽  
Evolution Simulation ◽  
Fractal Patterns ◽  
Selection For ◽  
Stem Cell Hierarchy

Cancer arises from accumulation of somatic mutations and accompanying evolutionary selection for growth advantage. During the evolutionary process, an ancestor clone branches into multiple clones, yielding intratumor heterogeneity. However, principles underlying intratumor heterogeneity have been poorly understood. Here, to explore the principles, we built a cellular automaton model, termed the BEP model, which can reproduce the branching cancer evolution in silico. We then extensively searched for conditions leading to high intratumor heterogeneity by performing simulations with various parameter settings on a supercomputer. Our result suggests that multiple driver genes of moderate strength can shape subclonal structures by positive natural selection. Moreover, we found that high mutation rate and a stem cell hierarchy can contribute to extremely high intratumor heterogeneity, which is characterized by fractal patterns, through neutral evolution. Collectively, This study identified the possible principles underlying intratumor heterogeneity, which provide novel insights into the origin of cancer robustness and evolvability.

scholarly journals Modeling colorectal cancer evolution

2021 ◽  
Author(s):  
Atsushi Niida ◽  
Koshi Mimori ◽  
Tatsuhiro Shibata ◽  
Satoru Miyano
Keyword(s):  
Mathematical Modeling ◽  
Colorectal Cancer ◽  
Early Stage ◽  
Technological Development ◽  
Acquired Resistance ◽  
Genomic Analysis ◽  
Evolutionary Model ◽  
Intratumor Heterogeneity ◽  
Cancer Evolution ◽  
Neutral Mutations

AbstractUnderstanding cancer evolution provides a clue to tackle therapeutic difficulties in colorectal cancer. In this review, together with related works, we will introduce a series of our studies, in which we constructed an evolutionary model of colorectal cancer by combining genomic analysis and mathematical modeling. In our model, multiple subclones were generated by driver mutation acquisition and subsequent clonal expansion in early-stage tumors. Among the subclones, the one obtaining driver copy number alterations is endowed with malignant potentials to constitute a late-stage tumor in which extensive intratumor heterogeneity is generated by the accumulation of neutral mutations. We will also discuss how to translate our understanding of cancer evolution to a solution to the problem related to therapeutic resistance: mathematical modeling suggests that relapse caused by acquired resistance could be suppressed by utilizing clonal competition between sensitive and resistant clones. Considering the current rate of technological development, modeling cancer evolution by combining genomic analysis and mathematical modeling will be an increasingly important approach for understanding and overcoming cancer.

Sensitivity Analysis and Selection of Check Index of Signal Intersection Simulation Model Based on VISSIM

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Mengda Zhang ◽  
Chenjing Zhou ◽  
Tian-tian Zhang ◽  
Yan Han
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Model ◽  
Optimal Process ◽  
Parameter Calibration ◽  
Index Set ◽  
The Core ◽  
Core Module ◽  
Simulation Parameter ◽  
Simulation Parameters ◽  
Selection Of

Selecting check index quantitatively is the core of the calibration of micro traffic simulation parameters at signal intersection. Five indexes in the node (intersection) module of VISSIM were selected as the check index set. Twelve simulation parameters in the core module were selected as the simulation parameters set. Optimal process of parameter calibration was proposed and model of the intersection of Huangcun west street and Xinghua street in Beijing was built in VISSIM to verify it. The sensitivity analysis between each check index and simulation parameter in their own set was conducted respectively. Sensitive parameter sets of different check indices were obtained and compared. The results show that different indexes have different size of set, and average vehicle delay's is maximum, so it's necessary to select index quantitatively. The results can provide references for scientific selection of the check indexes and improve the study efficiency of parameter calibration.

A Simulation Model for Multi-Factor Sensitivity Analysis on Energy Demand

2012 ◽  
Vol 621 ◽  
pp. 352-355
Author(s):  
Zhong Fu Tan ◽  
Shu Xiang Wang ◽  
Chen Zhang ◽  
Li Qiong Lin ◽  
Yin Hui Zhao
Keyword(s):  
Sensitivity Analysis ◽  
Energy Efficiency ◽  
Regression Model ◽  
Simulation Model ◽  
Influencing Factors ◽  
Energy Demand ◽  
Analysis Model ◽  
Demand Forecast ◽  
Population Urbanization

This paper analyses multi influencing factors of energy demand, using energy demand forecast regression model reveals inner relations between each factor and energy demand. Establish simulation model of the relation between GDP, energy intense and energy demand. Under the change in population, urbanization and energy efficiency, this paper gives analysis model of energy demand change.

scholarly journals GENETIC VARIABILITY MAINTAINED BY MUTATION AND OVERDOMINANT SELECTION IN FINITE POPULATIONS

Genetics ◽  
1981 ◽  
Vol 98 (2) ◽  
pp. 441-459 ◽  
Author(s):  
Takeo Maruyama ◽  
Masatoshi Nei
Keyword(s):  
Mutation Rate ◽  
Allozyme Polymorphism ◽  
Random Genetic Drift ◽  
Effective Population ◽  
Mathematical Properties ◽  
Overdominant Selection ◽  
Mean And Variance ◽  
The Mean ◽  
Neutral Mutations ◽  
The Relationship

ABSTRACT Mathematical properties of the overdominance model with mutation and random genetic drift are studied by using the method of stochastic differential equations (Itô and McKean 1974). It is shown that overdominant selection is very powerful in increasing the mean heterozygosity as compared with neutral mutations, and if 2Ns (N = effective population size; s = selective disadvantage for homozygotes) is larger than 10, a very low mutation rate is sufficient to explain the observed level of allozyme polymorphism. The distribution of heterozygosity for overdominant genes is considerably different from that of neutral mutations, and if the ratio of selection coefficient (s) to mutation rate (ν) is large and the mean heterozygosity (h) is lower than 0.2, single-locus heterozygosity is either approximately 0 or 0.5. If h increases further, however, heterozygosity shows a multiple-peak distribution. Reflecting this type of distribution, the relationship between the mean and variance of heterozygosity is considerably different from that for neutral genes. When s/v is large, the proportion of polymorphic loci increases approximately linearly with mean heterozygosity. The distribution of allele frequencies is also drastically different from that of neutral genes, and generally shows a peak at the intermediate gene frequency. Implications of these results on the maintenance of allozyme polymorphism are discussed.

scholarly journals Alien Species vs. Native Species: From Community Ecology to Eco-Evolutionary Dynamics

2019 ◽  
Author(s):  
Andersonn Silveira Prestes
Keyword(s):  
Alien Species ◽  
Exotic Species ◽  
Native Species ◽  
Evolutionary Dynamics ◽  
Evolutionary Processes ◽  
Native Communities ◽  
Individualized Approach ◽  
History Of ◽  
Relationship Of ◽  
The Relationship

The establishment and spread of exotic species is a contemporary major concern. Alien species may become invasive in their new habitat, leading to both/either environmental and/or economic impacts. I briefly reviewed the literature in the last decade about the relationship of exotic species and native communities. I identified that professionals usually approach the subject in two main points of view: (1) researchers tend to point out the impacts of alien species on entire communities, evaluating if the relationship is positive, negative or neutral; (2) they focus on the eco-evolutionary processes involved in the introductions, the dynamics of invasion, and individual study cases. When evaluating the response of introductions to entire communities, evidence seems to be ambiguous and may support positive, negative or neutral relationship, especially depending on the scale approached. The unique eco-evolutionary pathways of each introduction may be a great shortcoming in the searching for generalities. On the other hand, advances have been made in understanding the dynamics of invasion on different lineages through a more selective/individualized approach. I suggest that the dynamics of invasion might be studied through a perspective in which different eco-evolutionary processes, levels of organization (from gene to entire communities), the history of the organism(s) and time are taken into account. Individual cases might be compared in attempt to understand how the relationship exotic and native works and in the search for generalities.

scholarly journals The evolutionary dynamics of Oropouche Virus (OROV) in South America

2019 ◽  
Author(s):  
Bernardo Gutierrez ◽  
Emma Wise ◽  
Steven Pullan ◽  
Christopher Logue ◽  
Thomas A. Bowden ◽  
...  
Keyword(s):  
Viral Genome ◽  
Amazon Basin ◽  
Evolutionary Dynamics ◽  
Surface Proteins ◽  
Human Populations ◽  
Evolutionary Processes ◽  
Viral Pathogens ◽  
Viral Genomes ◽  
Glycosylation Sites ◽  
Variable Evolutionary Rates

AbstractThe Amazon basin is host to numerous arthropod-borne viral pathogens that cause febrile disease in humans. Among these,Oropouche orthobunyavirus(OROV) is a relatively understudied member of the Peribunyavirales that causes periodic outbreaks in human populations in Brazil and other South American countries. Although several studies have described the genetic diversity of the virus, the evolutionary processes that shape the viral genome remain poorly understood. Here we present a comprehensive study of the genomic dynamics of OROV that encompasses phylogenetic analysis, evolutionary rate estimates, inference of natural selective pressures, recombination and reassortment, and structural analysis of OROV variants. Our study includes all available published sequences, as well as a set of new OROV genomes sequences obtained from patients in Ecuador, representing the first set of viral genomes from this country. Our results show that differing evolutionary processes on the three segments that encompass the viral genome lead to variable evolutionary rates and TMRCAs that could be explained by cryptic reassortment. We also present the discovery of previously unobserved putative N-linked glycosylation sites, and codons which evolve under positive selection on the viral surface proteins, and discuss the potential role of these features in the evolution of the virus through a combined phylogenetic and structural approach.

Exploring incomplete information in maintenance materials inventory optimization

2014 ◽  
Vol 114 (1) ◽  
pp. 144-158 ◽  
Author(s):  
Antti Puurunen ◽  
Jukka Majava ◽  
Pekka Kess
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Model ◽  
Input Data ◽  
Real Life ◽  
Significant Risk ◽  
Service Level ◽  
Content Type ◽  
Imperfect Data ◽  
Inventory Optimization ◽  
Critical Materials

Purpose – Ensuring the sufficient service level is essential for critical materials in industrial maintenance. This study aims to evaluate the use of statistically imperfect data in a stochastic simulation-based inventory optimization where items' failure characteristics are derived from historical consumption data, which represents a real-life situation in the implementation of such an optimization model. Design/methodology/approach – The risks of undesired shortages were evaluated through a service-level sensitivity analysis. The service levels were simulated within the error of margin of the key input variables by using StockOptim optimization software and real data from a Finnish steel mill. A random sample of 100 inventory items was selected. Findings – Service-level sensitivity is item specific, but, for many items, statistical imprecision in the input data causes significant uncertainty in the service level. On the other hand, some items seem to be more resistant to variations in the input data than others. Research limitations/implications – The case approach, with one simulation model, limits the generalization of the results. The possibility that the simulation model is not totally realistic exists, due to the model's normality assumptions. Practical implications – Margin of error in input data estimation causes a significant risk of not achieving the required service level. It is proposed that managers work to improve the preciseness of the data, while the sensitivity analysis against statistical uncertainty, and a correction mechanism if necessary, should be integrated into optimization models. Originality/value – The output limitations in the optimization, i.e. service level, are typically stated precisely, but the capabilities of the input data have not been addressed adequately. This study provides valuable insights into ensuring the availability of critical materials.

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