Accelerated geroncogenesis in hereditary breast-ovarian cancer syndrome

The geroncogenesis hypothesis postulates that the decline in metabolic cellular health that occurs naturally with aging drives a "field effect" predisposing normal tissues for cancer development. We propose that mutations in the cancer susceptibility genes BRCA1/2 might trigger "accelerated geroncogenesis" in breast and ovarian epithelia. By speeding up the rate at which the metabolic threshold becomes "permissive" with survival and expansion of genomically unstable pre-tumoral epithelial cells, BRCA haploinsufficiency-driven metabolic reprogramming would operate as a bona fide oncogenic event enabling malignant transformation and tumor formation in BRCA carriers. The metabolic facet of BRCA1 one-hit might involve tissue-specific alterations in acetyl-CoA, α-ketoglutarate, NAD +, FAD, or S-adenosylmethionine, critical factors for de/methylation or de/acetylation dynamics in the nuclear epigenome. This in turn might induce faulty epigenetic reprogramming at the "install phase" that directs cell-specific differentiation of breast/ovarian epithelial cells, which can ultimately determine the penetrance of BRCA defects during developmental windows of susceptibility. This model offers a framework to study whether metabolic drugs that prevent or revert metabolic reprogramming induced by BRCA haploinsufficiency might displace the "geroncogenic risk" of BRCA carriers to the age typical for those without the mutation. The identification of the key nodes that directly communicate changes in cellular metabolism to the chromatin in BRCA haploinsufficient cells may allow the epigenetic targeting of genomic instability using exclusively metabolic means. The validation of accelerated geroncogenesis as an inherited "one-hit" metabolic "field effect" might offer new strategies to therapeutically revisit the apparently irreversible genetic-hereditary fate of women with hereditary breast-ovarian cancer syndrome

In silico clinical trials for anti-aging therapies

Altres ajuts: CERCA Programme/Generalitat de CatalunyaAltres ajuts: Fundació Oncolliga Girona (Lliga catalana d'ajuda al malalt de càncer, Girona)Altres ajuts: Obra Social La Caixa Foundation on Collaborative Mathematics awarded to the Centre de Recerca Matemàtica (CRM)Therapeutic strategies targeting the hallmarks of aging can be broadly grouped into four categories, namely systemic (blood) factors, metabolic manipulation (diet regimens and dietary restriction mimetics), suppression of cellular senescence (senolytics), and cellular reprogramming, which likely have common characteristics and mechanisms of action. In evaluating the potential synergism of combining such strategies, however, we should consider the possibility of constraining trade-off phenotypes such as impairment in wound healing and immune response, tissue dysfunction and tumorigenesis. Moreover, we are rapidly learning that the benefit/risk ratio of aging-targeted interventions largely depends on intra- and inter-individual variations of susceptibility to the healthspan-, resilience-, and/or lifespan-promoting effects of the interventions. Here, we exemplify how computationally-generated proxies of the efficacy of a given lifespan/healthspan-promoting approach can predict the impact of baseline epigenetic heterogeneity on the positive outcomes of ketogenic diet and mTOR inhibition as single or combined anti-aging strategies. We therefore propose that stochastic biomathematical modeling and computational simulation platforms should be developed as in silico strategies to accelerate the performance of clinical trials targeting human aging, and to provide personalized approaches and robust biomarkers of healthy aging at the individual-to-population levels

A multiscale model of epigenetic heterogeneity-driven cell fate decision-making

Altres ajuts: Obra Social La Caixa Foundation on Collaborative Mathematics awarded to the Centre de Recerca MatemàticaAltres ajuts: CERCA Programme/Generalitat de CatalunyaThe inherent capacity of somatic cells to switch their phenotypic status in response to damage stimuli in vivo might have a pivotal role in ageing and cancer. However, how the entryexit mechanisms of phenotype reprogramming are established remains poorly understood. In an attempt to elucidate such mechanisms, we herein introduce a stochastic model of combined epigenetic regulation (ER)-gene regulatory network (GRN) to study the plastic phenotypic behaviours driven by ER heterogeneity. To deal with such complex system, we additionally formulate a multiscale asymptotic method for stochastic model reduction, from which we derive an efficient hybrid simulation scheme. Our analysis of the coupled system reveals a regime of tristability in which pluripotent stem-like and differentiated steady-states coexist with a third indecisive state, with ER driving transitions between these states. Crucially, ER heterogeneity of differentiation genes is for the most part responsible for conferring abnormal robustness to pluripotent stem-like states. We formulate epigenetic heterogeneity-based strategies capable of unlocking and facilitating the transit from differentiation- refractory (stem-like) to differentiation-primed epistates. The application of the hybrid numerical method validates the likelihood of such switching involving solely kinetic changes in epigenetic factors. Our results suggest that epigenetic heterogeneity regulates the mechanisms and kinetics of phenotypic robustness of cell fate reprogramming. The occurrence of tunable switches capable of modifying the nature of cell fate reprogramming might pave the way for new therapeutic strategies to regulate reparative reprogramming in ageing and cancer

Stochastic modelling of epigenetic regulation: analysis of its heterogeneity and its implications in cell plasticity

En aquesta tesi doctoral, el nostre objectiu principal és entendre la importància de la regulació epigenètica en la determinació del destí cel lular i de les seves possibles tran- sicions cap a altres estats. Per tal d’estudiar-ho, en primer lloc, formulem un model es- tocàstic de regulació epigenètica. En aquest model, ens centrem en l’anàlisi de la reprogra- mació cel·lular, és a dir, la situació on el sistema es mou de l’epi-fenotip diferenciat, carac- teritzat per tenir el sistema de regulació epigenètica pel gen de diferenciació(pluripotència) obert(tancat), cap a l’epi-fenotip pluripotent, definit en aquest cas per tenir el sistema de regulació epigenètica pel gen de diferenciació (pluripotència) tancat(obert). En particular, dins de la heterogeneïtat intrínsica dels sistemes de regulació epigenètica, nosaltres identifiquem l’existència de dos possibles escenaris: l’escenari resistent, on la reprogramació no pot tenir lloc, i l’escenari plàstic, que és el qual permet el canvi de l’epi-fenotip diferenciat a l’epi-fenotip pluripotent. Aquest darrer escenari, relacionat amb l’existència de plasticitat epigenètica, ha estat associat amb envelliment. De fet, quan al model de regulació epigenètica només s’hi consideren efectes d’envelliment, el sistema representa un estat plàstic saludable, on les propietats de cèl·lula mare són adquirides de forma temporal, ja que el sistema de regulació epigenètica pot retornar a l’epi-fenotip diferenciat. Aquesta situació és la que probablement és responsable de regenerar i rejuvenir els teixits i, per tant, és la situació desitjada, ja que permetria un envelliment ‘saludable’. No obstant, quan als efectes de l’envelliment se li sumen alteracions de l’activitat epigenètica, que són freqüents a mesura que s’envelleix, l’estat plàstic esdevé un estat plàstic patològic, on en aquest cas, les propietats de cèl lula mare són adquirides de forma irreversible, és a dir, són permanents. Aquest escenari és el que probablement predisposa el sistema al càncer, ja que implica l’acumulació d’epi-fenotips indecisos que tenen el sistema de regulació epigenètica pel gen de pluripotècia obert, és a dir, que aquest gen es pot expressar. Per tal d’estudiar aquesta situació més en detall, formulem un context general per a l’estudi d’un model estocàstic d’escales múltiples conjunt per a la regulació epigenètica i la xarxa de regulació genètica. En particular, nosaltres ens centrem en una xarxa de regulació genètica formada per 2 gens, un gen que promou la diferenciació i un gen que promou la pluripotència. Quan analitzem aquest model conjunt, veiem que el paper que juga la regulació epigènetica és cabdal ja que permet a la xarxa de regulació epigenètica canviar d’estat, en altres paraules, permet un canvi del destí cel·lular de l’epi-fenotip diferenciat a l’epi-fenotip pluripotent (reprogramació) o el canvi invers (diferenciació). Aquest model conjunt ens permet identificar els sistemes de regulació epigenètica responsables d’atrapar la cèl·lula en un estat de cèl·lula mare, impedint-ne la seva diferenciació. La nostra formulació ens permet disenyar estratègies epigenètiques amb les quals podem aconseguir cèl·lules amb alta probabilitat de diferenciació, partint de cèl lules que inicialment eren resistents a la diferenciació. Com hom pot imaginar, aquestes estratègies són molt rellevants per a l’estudi i el tractament del càncer i altres malalties associades amb l’envelliment.In this thesis, we aim at understanding the importance of epigenetic regulation(ER) in cell fate decisions and transitions. In order to address this issue, we first formulate a stochastic model of epigenetic regulation. Within this model, we focus our discus- sion in cell reprogramming, i.e. the system moves from the differentiated epi-phenotype, characterised by differentiation(pluripotency) ER system open(closed), to the pluripotent epi-phenotype, where the ER system for differentiation(pluripotency) is closed(open). In particular, within the intrinsic heterogeneity existing in ER systems, we identify the appearance of two relevant scenarios: the resilient scenario, where reprogramming cannot occur, and the plastic one, which is the one allowing for the switch from the di erentiated epi-phenotype to the pluripotent epi-phenotype. The latter, which is characterised by ex- hibiting epigenetic plasticity, has been linked to ageing. In fact, when just ageing e ects are considered in the ER model, the system displays a `healthy' plasticity, where the stem-cell like properties can be acquired, but then, the ER system can go back to the dif- ferentiated epi-phenotype. This scenario may be related to regeneration and rejuvenation of tissues. Nevertheless, when ageing is considered along with epigenetic dis-regulations, which are likely to occur withing ageing cells/tissues, the plastic state leads to a patholog- ical plasticity, where stem cell features are acquired irreversibly. This scenario is the one which may predispose the system to cancer, as it implies the accumulation of undecided epi-phenotypes with the pluripotency ER system sustained in its on state. In order to further analyse this issue, we formulate a general framework for the study of a combined epigenetic regulation-gene regulatory network (ER-GRN)stochastic multi- scale model, which we later focus on our particular case of interest, i.e. a 2 gene regulatory network with one gene promoting differentiation and one gene promoting pluripotency. When analysing the ER-GRN model formulated, we show that the role played by ER is central since it allows the GRN to switch state, i.e. cell fate transitions from the differ- entiated phenotype to the pluripotent one (reprogramming) or vice versa (differentiation). The ER-GRN model allows to identify which ER systems are responsible for locking the cell in a stem cell like state and our formulation allows us to design epigenetic-based strategies able to obtain differentiation-primed cells from differentiation-resilient cells. Such strategies are of key relevance in the treatment of cancer and other age-associated diseases

Epigenetic regulation of cell fate reprogramming in aging and disease: A predictive computational model.

Understanding the control of epigenetic regulation is key to explain and modify the aging process. Because histone-modifying enzymes are sensitive to shifts in availability of cofactors (e.g. metabolites), cellular epigenetic states may be tied to changing conditions associated with cofactor variability. The aim of this study is to analyse the relationships between cofactor fluctuations, epigenetic landscapes, and cell state transitions. Using Approximate Bayesian Computation, we generate an ensemble of epigenetic regulation (ER) systems whose heterogeneity reflects variability in cofactor pools used by histone modifiers. The heterogeneity of epigenetic metabolites, which operates as regulator of the kinetic parameters promoting/preventing histone modifications, stochastically drives phenotypic variability. The ensemble of ER configurations reveals the occurrence of distinct epi-states within the ensemble. Whereas resilient states maintain large epigenetic barriers refractory to reprogramming cellular identity, plastic states lower these barriers, and increase the sensitivity to reprogramming. Moreover, fine-tuning of cofactor levels redirects plastic epigenetic states to re-enter epigenetic resilience, and vice versa. Our ensemble model agrees with a model of metabolism-responsive loss of epigenetic resilience as a cellular aging mechanism. Our findings support the notion that cellular aging, and its reversal, might result from stochastic translation of metabolic inputs into resilient/plastic cell states via ER systems

Stochastic modelling of epigenetic regulation : analysis of its heterogeneity and its implications in cell plasticity /

En aquesta tesi doctoral, el nostre objectiu principal és entendre la importància de la regulació epigenètica en la determinació del destí cel lular i de les seves possibles tran- sicions cap a altres estats. Per tal d'estudiar-ho, en primer lloc, formulem un model es- tocàstic de regulació epigenètica. En aquest model, ens centrem en l'anàlisi de la reprogra- mació cel·lular, és a dir, la situació on el sistema es mou de l'epi-fenotip diferenciat, carac- teritzat per tenir el sistema de regulació epigenètica pel gen de diferenciació(pluripotència) obert(tancat), cap a l'epi-fenotip pluripotent, definit en aquest cas per tenir el sistema de regulació epigenètica pel gen de diferenciació (pluripotència) tancat(obert). En particular, dins de la heterogeneïtat intrínsica dels sistemes de regulació epigenètica, nosaltres identifiquem l'existència de dos possibles escenaris: l'escenari resistent, on la reprogramació no pot tenir lloc, i l'escenari plàstic, que és el qual permet el canvi de l'epi-fenotip diferenciat a l'epi-fenotip pluripotent. Aquest darrer escenari, relacionat amb l'existència de plasticitat epigenètica, ha estat associat amb envelliment. De fet, quan al model de regulació epigenètica només s'hi consideren efectes d'envelliment, el sistema representa un estat plàstic saludable, on les propietats de cèl·lula mare són adquirides de forma temporal, ja que el sistema de regulació epigenètica pot retornar a l'epi-fenotip diferenciat. Aquesta situació és la que probablement és responsable de regenerar i rejuvenir els teixits i, per tant, és la situació desitjada, ja que permetria un envelliment 'saludable'. No obstant, quan als efectes de l'envelliment se li sumen alteracions de l'activitat epigenètica, que són freqüents a mesura que s'envelleix, l'estat plàstic esdevé un estat plàstic patològic, on en aquest cas, les propietats de cèl lula mare són adquirides de forma irreversible, és a dir, són permanents. Aquest escenari és el que probablement predisposa el sistema al càncer, ja que implica l'acumulació d'epi-fenotips indecisos que tenen el sistema de regulació epigenètica pel gen de pluripotècia obert, és a dir, que aquest gen es pot expressar. Per tal d'estudiar aquesta situació més en detall, formulem un context general per a l'estudi d'un model estocàstic d'escales múltiples conjunt per a la regulació epigenètica i la xarxa de regulació genètica. En particular, nosaltres ens centrem en una xarxa de regulació genètica formada per 2 gens, un gen que promou la diferenciació i un gen que promou la pluripotència. Quan analitzem aquest model conjunt, veiem que el paper que juga la regulació epigènetica és cabdal ja que permet a la xarxa de regulació epigenètica canviar d'estat, en altres paraules, permet un canvi del destí cel·lular de l'epi-fenotip diferenciat a l'epi-fenotip pluripotent (reprogramació) o el canvi invers (diferenciació). Aquest model conjunt ens permet identificar els sistemes de regulació epigenètica responsables d'atrapar la cèl·lula en un estat de cèl·lula mare, impedint-ne la seva diferenciació. La nostra formulació ens permet disenyar estratègies epigenètiques amb les quals podem aconseguir cèl·lules amb alta probabilitat de diferenciació, partint de cèl lules que inicialment eren resistents a la diferenciació. Com hom pot imaginar, aquestes estratègies són molt rellevants per a l'estudi i el tractament del càncer i altres malalties associades amb l'envelliment.In this thesis, we aim at understanding the importance of epigenetic regulation(ER) in cell fate decisions and transitions. In order to address this issue, we first formulate a stochastic model of epigenetic regulation. Within this model, we focus our discus- sion in cell reprogramming, i.e. the system moves from the differentiated epi-phenotype, characterised by differentiation(pluripotency) ER system open(closed), to the pluripotent epi-phenotype, where the ER system for differentiation(pluripotency) is closed(open). In particular, within the intrinsic heterogeneity existing in ER systems, we identify the appearance of two relevant scenarios: the resilient scenario, where reprogramming cannot occur, and the plastic one, which is the one allowing for the switch from the di erentiated epi-phenotype to the pluripotent epi-phenotype. The latter, which is characterised by ex- hibiting epigenetic plasticity, has been linked to ageing. In fact, when just ageing e ects are considered in the ER model, the system displays a 'healthy' plasticity, where the stem-cell like properties can be acquired, but then, the ER system can go back to the dif- ferentiated epi-phenotype. This scenario may be related to regeneration and rejuvenation of tissues. Nevertheless, when ageing is considered along with epigenetic dis-regulations, which are likely to occur withing ageing cells/tissues, the plastic state leads to a patholog- ical plasticity, where stem cell features are acquired irreversibly. This scenario is the one which may predispose the system to cancer, as it implies the accumulation of undecided epi-phenotypes with the pluripotency ER system sustained in its on state. In order to further analyse this issue, we formulate a general framework for the study of a combined epigenetic regulation-gene regulatory network (ER-GRN)stochastic multi- scale model, which we later focus on our particular case of interest, i.e. a 2 gene regulatory network with one gene promoting differentiation and one gene promoting pluripotency. When analysing the ER-GRN model formulated, we show that the role played by ER is central since it allows the GRN to switch state, i.e. cell fate transitions from the differ- entiated phenotype to the pluripotent one (reprogramming) or vice versa (differentiation). The ER-GRN model allows to identify which ER systems are responsible for locking the cell in a stem cell like state and our formulation allows us to design epigenetic-based strategies able to obtain differentiation-primed cells from differentiation-resilient cells. Such strategies are of key relevance in the treatment of cancer and other age-associated diseases

Epigenetic regulation of cell fate reprogramming in aging and disease: A predictive computational model.

<p>Cell reprogramming, a process that allows differentiated cells to re-acquire stem-like properties, is increasingly considered a critical phenomenon in tissue regeneration, aging, and cancer. In light of the importance of metabolism in controlling cell fate, we designated a computational model capable of predicting the likelihood of cell reprogramming in response to changes in aging-related epigenetic metabolites (EM). Our first-in-class Approximate Bayesian Computation (ABC) approach integrates the biochemical basis of aging-driven metabolite interaction with chromatin-modifying enzymes to predict how aging-driven metabolic reprogramming could alter cell state transitions via reorganisation of chromatin marks without affecting the shape of the Waddingtonian epigenomic landscape. Our predictive mathematical model improves our understanding of how pathological processes that involve changes in cell plasticity, such as tissue repair and cancer, might be accelerated or attenuated by means of metabolic reprogramming-driven changes on the height of phenotypic transitioning barriers.</p

Epigenetic regulation of cell fate reprogramming in aging and disease: A predictive computational model - Fig 3

<p>Plots (a) and (b) show the phase diagrams associated with the QSS approximation for the differentiation and pluripotency promoting genes, respectively. We examine the stability properties of the QSSA as when <i>e</i>_<i>HDM</i> and <i>e</i>_<i>HDAC</i> are varied. The system exhibits bistability in the region between the red and blue lines. In the region above the red line the only stable steady state is the closed state. By contrast, in the region below the blue line only the open steady state is stable. Parameters values are given in Table A in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006052#pcbi.1006052.s001" target="_blank">S1 File</a> for the differentiation-promoting gene and Table B in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006052#pcbi.1006052.s001" target="_blank">S1 File</a> for the pluripotency-promoting gene. Plots (d) and (f) show the combined phase diagram for both the differentiation-promoting and the pluripotency-promoting models of epigenetic regulation for two clinically relevant cases. In both plots, solid (dashed) lines correspond to the stability limits of the pluripotency(differentiation)-promoting gene. In plot (d), the region between the solid red line and the dashed blue line is associated with <i>normal cell</i> behaviour, i.e. open differentiation-promoting gene and silenced pluripotency-promoting gene, whereas in Plot (f), the region marked as <i>Rep</i>. is associated with epigenetic regulation configurations which facilitate cell reprogramming. Plot (d) shows a <i>refractory</i> epigenetic scenario and Plot (f) depicts a <i>plastic</i> scenario. Parameter values for Plot (d) as per Table A in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006052#pcbi.1006052.s001" target="_blank">S1 File</a> (dashed lines) and Table B in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006052#pcbi.1006052.s001" target="_blank">S1 File</a> (solid lines). Parameter values for Plot (f) are given in Table C in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006052#pcbi.1006052.s001" target="_blank">S1 File</a>, and Table D in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006052#pcbi.1006052.s001" target="_blank">S1 File</a>. Plots (c) and (e) show two bifurcation diagrams, i.e. two sections of Plot (a), corresponding to the differentiation-promoting gene, of the QSS approximation. Plot (c) corresponds to fixing <i>e</i>_<i>HDAC</i> = 1 and letting HDM activity to vary. Plot (e) examines the bifurcation properties of the system for <i>e</i>_<i>HDM</i> = 0.2 as HDAC concentration changes.</p

This figure shows the cumulative frequency distribution (CFD) for a sample consisting of the 1401 pluripotency gene ER parameter sets generated by ABC which best fit the synthetic data, i.e. SSA simulated data for the default stochastic ER pluripotency system (see Table B in S1 File).

<p>Out of these 1401 parameter sets, 29 satisfy the constraints associated with the pluripotency epiphenotype. Amongst these, 11 are found to show plastic behaviour. Another 1367 parameter sets generate bistability at <i>e</i>_<i>HDM</i> = <i>e</i>_<i>HDAC</i> = 1. The remaining 5 parameter sets are bistable at <i>e</i>_<i>HDM</i> = <i>e</i>_<i>HDAC</i> = 1 but they are rejected since their steady states do not correspond to open/closed situations. Colour code: blue and red lines correpond to the CFD of the plastic and refractory pluripotency epiphenotypes, respectively. Green lines correspond to the CFD of the parameters that generate bistability at <i>e</i>_<i>HDM</i> = <i>e</i>_<i>HDAC</i> = 1. Cyan lines correspond to the CFD of a uniform distribution, which we add for reference.</p