Modeling stress-induced responses: plasticity in continuous state space and gradual clonal evolution

Mathematical models of cancer and bacterial evolution have generally stemmed from a gene-centric framework, assuming clonal evolution via acquisition of resistance-conferring mutations and selection of their corresponding subpopulations. More recently, the role of phenotypic plasticity has been recognized and models accounting for phenotypic switching between discrete cell states (e.g. epithelial and mesenchymal) have been developed. However, seldom do models incorporate both plasticity and mutationally-driven resistance, particularly when the state space is continuous and resistance evolves in a continuous fashion. In this paper, we develop a framework to model plastic and mutational mechanisms of acquiring resistance in a continuous, gradual fashion. We use this framework to examine ways in which cancer and bacterial populations can respond to stress and consider implications for therapeutic strategies. Although we primarily discuss our framework in the context of cancer and bacteria, it applies broadly to any system capable of evolving via plasticity and genetic evolution.

[1]  Joel s. Brown,et al.  Integrating eco‐evolutionary dynamics into matrix population models for structured populations: Discrete and continuous frameworks , 2023, Methods in Ecology and Evolution.

[2]  W. Shi,et al.  Single-cell profiling of peripheral neuroblastic tumors identifies an aggressive transitional state that bridges an adrenergic-mesenchymal trajectory. , 2022, Cell reports.

[3]  Joel s. Brown,et al.  A life history model of the ecological and evolutionary dynamics of polyaneuploid cancer cells , 2022, Scientific Reports.

[4]  Joel s. Brown,et al.  Stochastic models of Mendelian and reverse transcriptional inheritance in state-structured cancer populations , 2022, Scientific Reports.

[5]  Joel s. Brown,et al.  Coupled Source-Sink Habitats Produce Spatial and Temporal Variation of Cancer Cell Molecular Properties as an Alternative to Branched Clonal Evolution and Stem Cell Paradigms , 2021, Frontiers in Ecology and Evolution.

[6]  K. Pienta,et al.  Cancer recurrence and lethality are enabled by enhanced survival and reversible cell cycle arrest of polyaneuploid cells , 2021, Proceedings of the National Academy of Sciences.

[7]  K. Pienta,et al.  Cancer cells employ an evolutionarily conserved polyploidization program to resist therapy. , 2020, Seminars in cancer biology.

[8]  S. Sivaloganathan,et al.  A mathematical study of the impact of cell plasticity on tumour control probability. , 2020, Mathematical biosciences and engineering : MBE.

[9]  J. Clairambault,et al.  Cell plasticity in cancer cell populations , 2020, F1000Research.

[10]  A. Hillmer,et al.  Linking Cancer Stem Cell Plasticity to Therapeutic Resistance-Mechanism and Novel Therapeutic Strategies in Esophageal Cancer , 2020, Cells.

[11]  Joel s. Brown,et al.  Convergent Evolution, Evolving Evolvability, and the Origins of Lethal Cancer , 2020, Molecular Cancer Research.

[12]  Joel s. Brown,et al.  Poly‐aneuploid cancer cells promote evolvability, generating lethal cancer , 2020, Evolutionary applications.

[13]  Li You,et al.  Towards Multidrug Adaptive Therapy , 2020, Cancer Research.

[14]  G. F. Calvo,et al.  Identification of a transient state during the acquisition of temozolomide resistance in glioblastoma , 2020, Cell Death & Disease.

[15]  H. Caswell,et al.  A matrix model for density-dependent selection in stage-classified populations, with application to pesticide resistance in Tribolium , 2020, Ecological Modelling.

[16]  A. Eggermont,et al.  An epitranscriptomic mechanism underlies selective mRNA translation remodelling in melanoma persister cells , 2019, Nature Communications.

[17]  Neil Vasan,et al.  A view on drug resistance in cancer , 2019, Nature.

[18]  Robert A. Gatenby,et al.  Leveraging transcriptional dynamics to improve BRAF inhibitor responses in melanoma , 2019, EBioMedicine.

[19]  C. Lim,et al.  Epithelial-mesenchymal plasticity-engaging stemness in an interplay of phenotypes. , 2019, Stem cell investigation.

[20]  Ke-Chih Lin,et al.  Polyploid giant cancer cells: Unrecognized actuators of tumorigenesis, metastasis, and resistance , 2019, The Prostate.

[21]  Qingsong Liu,et al.  Transcriptional regulation of autophagy-lysosomal function in BRAF-driven melanoma progression and chemoresistance , 2019, Nature Communications.

[22]  Hal Caswell,et al.  Sensitivity Analysis: Matrix Methods in Demography and Ecology , 2019, Demographic Research Monographs.

[23]  K. Shokat,et al.  Chronic TGF-β exposure drives stabilized EMT, tumor stemness, and cancer drug resistance with vulnerability to bitopic mTOR inhibition , 2019, Science Signaling.

[24]  R. Albert,et al.  Towards control of cellular decision-making networks in the epithelial-to-mesenchymal transition , 2018, Physical biology.

[25]  P. Kočovský,et al.  A spatially discrete, integral projection model and its application to invasive carp , 2018, Ecological Modelling.

[26]  J. Tabernero,et al.  A slow-cycling LGR5 tumour population mediates basal cell carcinoma relapse after therapy , 2018, Nature.

[27]  F. Peale,et al.  A cell identity switch allows residual BCC to survive Hedgehog pathway inhibition , 2018, Nature.

[28]  J. Shih,et al.  Epithelial-mesenchymal transition (EMT) beyond EGFR mutations per se is a common mechanism for acquired resistance to EGFR TKI , 2018, Oncogene.

[29]  K. Flaherty,et al.  Toward Minimal Residual Disease-Directed Therapy in Melanoma , 2018, Cell.

[30]  E. Furth,et al.  EMT Subtype Influences Epithelial Plasticity and Mode of Cell Migration. , 2018, Developmental cell.

[31]  T. Graeber,et al.  Multi-stage Differentiation Defines Melanoma Subtypes with Differential Vulnerability to Drug-Induced Iron-Dependent Oxidative Stress. , 2018, Cancer cell.

[32]  Robert A Gatenby,et al.  Spatial heterogeneity and evolutionary dynamics modulate time to recurrence in continuous and adaptive cancer therapies , 2017, bioRxiv.

[33]  P. Parren,et al.  Cooperative targeting of melanoma heterogeneity with an AXL antibody-drug conjugate and BRAF/MEK inhibitors , 2018, Nature Medicine.

[34]  N. McDowell,et al.  Incorporating variability in simulations of seasonally forced phenology using integral projection models , 2017, Ecology and evolution.

[35]  William F Basener,et al.  The fundamental theorem of natural selection with mutations , 2017, Journal of mathematical biology.

[36]  R. Young,et al.  Suppression of Adaptive Responses to Targeted Cancer Therapy by Transcriptional Repression. , 2017, Cancer discovery.

[37]  P. Giresi,et al.  Repression of Stress-Induced LINE-1 Expression Protects Cancer Cell Subpopulations from Lethal Drug Exposure. , 2017, Cancer cell.

[38]  Jill P. Mesirov,et al.  Dependency of a therapy-resistant state of cancer cells on a lipid peroxidase pathway , 2017, Nature.

[39]  Stuart L. Schreiber,et al.  Drug-tolerant persister cancer cells are vulnerable to GPX4 inhibition , 2017, Nature.

[40]  R. Fisher,et al.  Persistent bacterial infections and persister cells , 2017, Nature Reviews Microbiology.

[41]  Sydney M. Shaffer,et al.  Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance , 2017, Nature.

[42]  S. Rosenberg,et al.  Stress-Induced Mutagenesis: Implications in Cancer and Drug Resistance. , 2017, Annual review of cancer biology.

[43]  Shawn M. Gillespie,et al.  Adaptive Chromatin Remodeling Drives Glioblastoma Stem Cell Plasticity and Drug Tolerance. , 2017, Cell stem cell.

[44]  Sendurai A Mani,et al.  Mathematical modelling of phenotypic plasticity and conversion to a stem-cell state under hypoxia , 2016, Scientific Reports.

[45]  B. Young,et al.  Using integral projection models to compare population dynamics of four closely related species , 2016, Population Ecology.

[46]  A. Graham,et al.  Opportunities and challenges of Integral Projection Models for modelling host–parasite dynamics , 2015, Journal of Animal Ecology.

[47]  N. Vasilevsky,et al.  Author response: Registered report: A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations , 2015 .

[48]  J. Stenvang,et al.  Establishment and characterization of models of chemotherapy resistance in colorectal cancer: Towards a predictive signature of chemoresistance , 2015, Molecular oncology.

[49]  R. Gillies,et al.  Sweat but no gain: Inhibiting proliferation of multidrug resistant cancer cells with “ersatzdroges” , 2015, International journal of cancer.

[50]  Sarah A Heerboth,et al.  Drug Resistance in Cancer: An Overview , 2014, Cancers.

[51]  Cory Merow,et al.  Advancing population ecology with integral projection models: a practical guide , 2014 .

[52]  Dylan Z Childs,et al.  Building integral projection models: a user's guide , 2014, The Journal of animal ecology.

[53]  Tim Coulson,et al.  Integral projections models, their construction and use in posing hypotheses in ecology , 2012 .

[54]  Stephen P Ellner,et al.  Avoiding unintentional eviction from integral projection models. , 2012, Ecology.

[55]  H. Caswell Matrix models and sensitivity analysis of populations classified by age and stage: a vec-permutation matrix approach , 2012, Theoretical Ecology.

[56]  T. Golub,et al.  Tumour micro-environment elicits innate resistance to RAF inhibitors through HGF secretion , 2012, Nature.

[57]  Johan Ehrlén,et al.  Interdependent effects of habitat quality and climate on population growth of an endangered plant , 2011 .

[58]  D. Hanahan,et al.  Hallmarks of Cancer: The Next Generation , 2011, Cell.

[59]  Shripad Tuljapurkar,et al.  Using evolutionary demography to link life history theory, quantitative genetics and population ecology , 2010, The Journal of animal ecology.

[60]  Stephen P Ellner,et al.  Coexistence of perennial plants: an embarrassment of niches. , 2010, Ecology letters.

[61]  Knut Rydgren,et al.  Investigating the interaction between ungulate grazing and resource effects on Vaccinium myrtillus populations with integral projection models , 2010, Oecologia.

[62]  Jennifer L. Williams,et al.  Testing hypotheses for exotic plant success: parallel experiments in the native and introduced ranges. , 2010, Ecology.

[63]  Ben S. Wittner,et al.  A Chromatin-Mediated Reversible Drug-Tolerant State in Cancer Cell Subpopulations , 2010, Cell.

[64]  R. Lande,et al.  Adaptation, Plasticity, and Extinction in a Changing Environment: Towards a Predictive Theory , 2010, PLoS biology.

[65]  Jennifer L. Williams Flowering Life‐History Strategies Differ between the Native and Introduced Ranges of a Monocarpic Perennial , 2009, The American Naturalist.

[66]  Johan Ehrlén,et al.  Linking environmental variation to population dynamics of a forest herb , 2009 .

[67]  M. Yamada,et al.  DinB Upregulation Is the Sole Role of the SOS Response in Stress-Induced Mutagenesis in Escherichia coli , 2009, Genetics.

[68]  James O. Eckberg,et al.  Impacts of insect herbivory on cactus population dynamics: experimental demography across an environmental gradient , 2009 .

[69]  Mark Rees,et al.  Life‐History Variation in Contrasting Habitats: Flowering Decisions in a Clonal Perennial Herb (Veratrum album) , 2008, The American Naturalist.

[70]  S. Lovett Replication arrest-stimulated recombination: Dependence on the RecA paralog, RadA/Sms and translesion polymerase, DinB. , 2006, DNA repair.

[71]  Yi Lu,et al.  Inhibition of interleukin-6 with CNTO328, an anti-interleukin-6 monoclonal antibody, inhibits conversion of androgen-dependent prostate cancer to an androgen-independent phenotype in orchiectomized mice. , 2006, Cancer research.

[72]  A. Badyaev Stress-induced variation in evolution: from behavioural plasticity to genetic assimilation , 2005, Proceedings of the Royal Society B: Biological Sciences.

[73]  M. Rees,et al.  DEMOGRAPHIC AND EVOLUTIONARY IMPACTS OF NATIVE AND INVASIVE INSECT HERBIVORES ON CIRSIUM CANESCENS , 2005 .

[74]  J. Petrosino,et al.  Adaptive Amplification and Point Mutation Are Independent Mechanisms: Evidence for Various Stress-Inducible Mutation Mechanisms , 2004, PLoS biology.

[75]  S. Rosenberg,et al.  General stress response regulator RpoS in adaptive mutation and amplification in Escherichia coli. , 2004, Genetics.

[76]  J. C. Layton,et al.  Error‐prone DNA polymerase IV is controlled by the stress‐response sigma factor, RpoS, in Escherichia coli , 2003, Molecular microbiology.

[77]  Mark Rees,et al.  Evolutionary demography of monocarpic perennials. , 2003 .

[78]  Valeria Souza,et al.  Stress-Induced Mutagenesis in Bacteria , 2003, Science.

[79]  M. Rees,et al.  Evolution of flowering strategies in Oenothera glazioviana: an integral projection model approach , 2002, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[80]  D. O. Logofet Matrix Population Models: Construction, Analysis, and Interpretation , 2002 .

[81]  S. Rosenberg Evolving responsively: adaptive mutation , 2001, Nature Reviews Genetics.

[82]  C. Finch,et al.  Relevance of 'adaptive' mutations arising in non-dividing cells of microorganisms to age-related changes in mutant phenotypes of neurons. , 1997, Trends in neurosciences.

[83]  S. Lessard Fisher's fundamental theorem of natural selection revisited. , 1997, Theoretical population biology.

[84]  B. Hall,et al.  Adaptive mutations in Escherichia coli as a model for the multiple mutational origins of tumors. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[85]  R. S. Harris,et al.  Adaptive mutation by deletions in small mononucleotide repeats. , 1994, Science.

[86]  M Slatkin,et al.  Fisher's fundamental theorem of natural selection. , 1992, Trends in ecology & evolution.

[87]  B. Strauss The origin of point mutations in human tumor cells. , 1992, Cancer research.

[88]  J. Overbaugh,et al.  The origin of mutants , 1988, Nature.

[89]  A. Edwards,et al.  Fundamental Theorem of Natural Selection , 1967, Nature.

[90]  J. Willis The Origin of Species by Large, rather than by Gradual, Change, and by Guppy's Method of Differentiation , 1923 .

[91]  A. Dhawan,et al.  Mathematical modelling of plasticity and phenotype switching in cancer cell populations. , 2017, Mathematical biosciences.

[92]  W. Witte,et al.  Antibiotic resistance. , 2013, International journal of medical microbiology : IJMM.

[93]  M. Hooten,et al.  Climate influences the demography of three dominant sagebrush steppe plants. , 2011, Ecology.

[94]  B. Frieden,et al.  Adaptive therapy. , 2009, Cancer research.

[95]  M. Gordon Inhibition of Interleukin-6 with CNTO328, an Anti-Interleukin-6 Monoclonal Antibody, Inhibits Conversion of Androgen-Dependent Prostate Cancer to an Androgen-Independent Phenotype in Orchiectomized MiceWallner L, Dai J, Escara-Wilke J, et al (Univ of Michigan, Ann Arbor; Univ of Pittsburgh, Pa; Tian , 2007 .

[96]  J. Shapiro Observations on the formation of clones containing araB-lacZ cistron fusions , 2004, Molecular and General Genetics MGG.