Genome-wide CRISPR screens identify the YAP/TEAD axis as a driver of persister cells in EGFR mutant lung cancer.

Most lung cancer patients with metastatic cancer eventually relapse with drug-resistant disease following treatment and EGFR mutant lung cancer is no exception. Genome-wide CRISPR screens, to either knock out or overexpress all protein-coding genes in cancer cell lines, revealed the landscape of pathways that cause resistance to the EGFR inhibitors osimertinib or gefitinib in EGFR mutant lung cancer. Among the most recurrent resistance genes were those that regulate the Hippo pathway. Following osimertinib treatment a subpopulation of cancer cells are able to survive and over time develop stable resistance. These 'persister' cells can exploit non-genetic (transcriptional) programs that enable cancer cells to survive drug treatment. Using genetic and pharmacologic tools we identified Hippo signalling as an important non-genetic mechanism of cell survival following osimertinib treatment. Further, we show that combinatorial targeting of the Hippo pathway and EGFR is highly effective in EGFR mutant lung cancer cells and patient-derived organoids, suggesting a new therapeutic strategy for EGFR mutant lung cancer patients.

Flexible Fitting of PROTAC Concentration-Response Curves with Changepoint Gaussian Processes.

A proteolysis-targeting chimera (PROTAC) is a new technology that marks proteins for degradation in a highly specific manner. During screening, PROTAC compounds are tested in concentration-response (CR) assays to determine their potency, and parameters such as the half-maximal degradation concentration (DC50) are estimated from the fitted CR curves. These parameters are used to rank compounds, with lower DC50 values indicating greater potency. However, PROTAC data often exhibit biphasic and polyphasic relationships, making standard sigmoidal CR models inappropriate. A common solution includes manual omitting of points (the so-called masking step), allowing standard models to be used on the reduced data sets. Due to its manual and subjective nature, masking becomes a costly and nonreproducible procedure. We therefore used a Bayesian changepoint Gaussian processes model that can flexibly fit both nonsigmoidal and sigmoidal CR curves without user input. Parameters such as the DC50, maximum effect Dmax, and point of departure (PoD) are estimated from the fitted curves. We then rank compounds based on one or more parameters and propagate the parameter uncertainty into the rankings, enabling us to confidently state if one compound is better than another. Hence, we used a flexible and automated procedure for PROTAC screening experiments. By minimizing subjective decisions, our approach reduces time and cost and ensures reproducibility of the compound-ranking procedure. The code and data are provided on GitHub (https://github.com/elizavetasemenova/gp_concentration_response).

Delivering Robust Candidates to the Drug Pipeline through Computational Analysis of Arrayed CRISPR Screens.

Genome-wide arrayed CRISPR screening is a powerful method for drug target identification as it enables exploration of the effect of individual gene perturbations using diverse highly multiplexed functional and phenotypic assays. Using high-content imaging, we can measure changes in biomarker expression, intracellular localization, and cell morphology. Here we present the computational pipeline we have developed to support the analysis and interpretation of arrayed CRISPR screens. This includes evaluating the quality of guide RNA libraries, performing image analysis, evaluating assay results quality, data processing, hit identification, ranking, visualization, and biological interpretation.

Optimizing the design of population-based patient-derived tumor xenograft studies to better predict clinical response.

The high attrition rate of preclinical agents entering oncology clinical trials has been associated with poor understanding of the heterogeneous patient response, arising from limitations in the preclinical pipeline with cancer models. Patient-derived tumor xenograft (PDX) models have been shown to better recapitulate the patient drug response. However, the platform of evidence generated to support clinical development in a drug discovery project typically employs a limited number of models, which may not accurately predict the response at a population level. Population PDX studies, large-scale screens of PDX models, have been proposed as a strategy to model the patient inter-tumor heterogeneity. Here, we present a freely available interactive tool that explores the design of a population PDX study and how it impacts the sensitivity and false-positive rate experienced. We discuss the reflection process needed to optimize the design for the therapeutic landscape being studied and manage the risk of false-negative and false-positive outcomes that the sponsor is willing to take. The tool has been made freely available to allow the optimal design to be determined for each drug-disease area. This will allow researchers to improve their understanding of treatment efficacy in the presence of genetic variability before taking a drug to clinic. In addition, the tool serves to refine the number of animals to be used for population-based PDX studies, ensuring researchers meet their ethical obligation when performing animal research.

Mitogen-Inducible Gene-6 Mediates Feedback Inhibition from Mutated BRAF towards the Epidermal Growth Factor Receptor and Thereby Limits Malignant Transformation.

BRAF functions in the RAS-extracellular signal-regulated kinase (ERK) signaling cascade. Activation of this pathway is necessary to mediate the transforming potential of oncogenic BRAF, however, it may also cause a negative feedback that inhibits the epidermal growth factor receptor (EGFR). Mitogen-inducible gene-6 (MIG-6) is a potent inhibitor of the EGFR and has been demonstrated to function as a tumor suppressor. As MIG-6 can be induced via RAS-ERK signaling, we investigated its potential involvement in this negative regulatory loop. Focus formation assays were performed and demonstrated that MIG-6 significantly reduces malignant transformation induced by oncogenic BRAF. Although this genetic interaction was mirrored by a physical interaction between MIG-6 and BRAF, we did not observe a direct regulation of BRAF kinase activity by MIG-6. Interestingly, a selective chemical EGFR inhibitor suppressed transformation to a similar degree as MIG-6, whereas combining these approaches had no synergistic effect. By analyzing a range of BRAF mutated and wildtype cell line models, we could show that BRAF V600E causes a strong upregulation of MIG-6, which was mediated at the transcriptional level via the RAS-ERK pathway and resulted in downregulation of EGFR activation. This feedback loop is operational in tumors, as shown by the analysis of almost 400 patients with papillary thyroid cancer (PTC). Presence of BRAF V600E correlated with increased MIG-6 expression on the one hand, and with inactivation of the EGFR and of PI3K/AKT signaling on the other hand. Importantly, we also observed a more aggressive disease phenotype when BRAF V600E coexisted with low MIG-6 expression. Finally, analysis of methylation data was performed and revealed that higher methylation of MIG-6 correlated to its decreased expression. Taken together, we demonstrate that MIG-6 efficiently reduces cellular transformation driven by oncogenic BRAF by orchestrating a negative feedback circuit directed towards the EGFR.

On the impact of discreteness and abstractions on modelling noise in gene regulatory networks.

In this paper, we explore the impact of different forms of model abstraction and the role of discreteness on the dynamical behaviour of a simple model of gene regulation where a transcriptional repressor negatively regulates its own expression. We first investigate the relation between a minimal set of parameters and the system dynamics in a purely discrete stochastic framework, with the twofold purpose of providing an intuitive explanation of the different behavioural patterns exhibited and of identifying the main sources of noise. Then, we explore the effect of combining hybrid approaches and quasi-steady state approximations on model behaviour (and simulation time), to understand to what extent dynamics and quantitative features such as noise intensity can be preserved.

Stochastic models of cellular circadian rhythms in plants help to understand the impact of noise on robustness and clock structure.

Rhythmic behavior is essential for plants; for example, daily (circadian) rhythms control photosynthesis and seasonal rhythms regulate their life cycle. The core of the circadian clock is a genetic network that coordinates the expression of specific clock genes in a circadian rhythm reflecting the 24-h day/night cycle. Circadian clocks exhibit stochastic noise due to the low copy numbers of clock genes and the consequent cell-to-cell variation: this intrinsic noise plays a major role in circadian clocks by inducing more robust oscillatory behavior. Another source of noise is the environment, which causes variation in temperature and light intensity: this extrinsic noise is part of the requirement for the structural complexity of clock networks. Advances in experimental techniques now permit single-cell measurements and the development of single-cell models. Here we present some modeling studies showing the importance of considering both types of noise in understanding how plants adapt to regular and irregular light variations. Stochastic models have proven useful for understanding the effect of regular variations. By contrast, the impact of irregular variations and the interaction of different noise sources are less well studied.

A model of flux regulation in the cholesterol biosynthesis pathway: Immune mediated graduated flux reduction versus statin-like led stepped flux reduction.

The cholesterol biosynthesis pathway has recently been shown to play an important role in the innate immune response to viral infection with host protection occurring through a coordinate down regulation of the enzymes catalysing each metabolic step. In contrast, statin based drugs, which form the principle pharmaceutical agents for decreasing the activity of this pathway, target a single enzyme. Here, we build an ordinary differential equation model of the cholesterol biosynthesis pathway in order to investigate how the two regulatory strategies impact upon the behaviour of the pathway. We employ a modest set of assumptions: that the pathway operates away from saturation, that each metabolite is involved in multiple cellular interactions and that mRNA levels reflect enzyme concentrations. Using data taken from primary bone marrow derived macrophage cells infected with murine cytomegalovirus or treated with IFNγ, we show that, under these assumptions, coordinate down-regulation of enzyme activity imparts a graduated reduction in flux along the pathway. In contrast, modelling a statin-like treatment that achieves the same degree of down-regulation in cholesterol production, we show that this delivers a step change in flux along the pathway. The graduated reduction mediated by physiological coordinate regulation of multiple enzymes supports a mechanism that allows a greater level of specificity, altering cholesterol levels with less impact upon interactions branching from the pathway, than pharmacological step reductions. We argue that coordinate regulation is likely to show a long-term evolutionary advantage over single enzyme regulation. Finally, the results from our models have implications for future pharmaceutical therapies intended to target cholesterol production with greater specificity and fewer off target effects, suggesting that this can be achieved by mimicking the coordinated down-regulation observed in immunological responses.

Stochastic properties of the plant circadian clock.

Circadian clocks are gene regulatory networks whose role is to help the organisms to cope with variations in environmental conditions such as the day/night cycle. In this work, we explored the effects of molecular noise in single cells on the behaviour of the circadian clock in the plant model species Arabidopsis thaliana. The computational modelling language Bio-PEPA enabled us to give a stochastic interpretation of an existing deterministic model of the clock, and to easily compare the results obtained via stochastic simulation and via numerical solution of the deterministic model. First, the introduction of stochasticity in the model allowed us to estimate the unknown size of the system. Moreover, stochasticity improved the description of the available experimental data in several light conditions: noise-induced fluctuations yield a faster entrainment of the plant clock under certain photoperiods and are able to explain the experimentally observed dampening of the oscillations in plants under constant light conditions. The model predicts that the desynchronization between noisy oscillations in single cells contributes to the observed damped oscillations at the level of the cell population. Analysis of the phase, period and amplitude distributions under various light conditions demonstrated robust entrainment of the plant clock to light/dark cycles which closely matched the available experimental data.

Formal methods for checking the consistency of biological models.

Formal modeling approaches such as process algebras and Petri nets seek to provide insight into biological processes by using both symbolic and numerical methods to reveal the dynamics of the process under study. These formal approaches differ from classical methods of investigating the dynamics of the process through numerical integration of ODEs because they additionally provide alternative representations which are amenable to discrete-state analysis and logical reasoning. Backed by these additional analysis methods, formal modeling approaches have been able to identify errors in published and widely-cited biological models. This paper provides an introduction to these analysis methods, and explains the benefits which they can bring to ensuring the consistency of biological models.

Computational modeling of biological pathways by executable biology.

"In silico" experiments (i.e., computer simulation) constitute an aid to traditional biological research, by allowing biologists to execute efficient simulations taking into consideration the data obtained in wet experiments and to generate new hypotheses, which can be later verified in additional wet experiments. In addition to being much cheaper and faster than wet experiments, computer simulation has other advantages: it allows us to run experiments in which several species can be monitored at the same time, to explore quickly various conditions by varying species and parameters in different runs, and in some cases to observe the behavior of the system at a greater level of detail than the one permitted by experimental techniques. In the past few years there has been a considerable effort in the computer science community to develop computational languages and software tools for modeling and analysing biochemical systems. Among the challenges which must be addressed in this context, there are: the definition of languages powerful enough to express all the relevant features of biochemical systems, the development of efficient algorithms to analyze models and interpret the results, and the implementation of modeling platforms which are usable by nonprogrammers. In this chapter, we focus on the use of computational modeling to the analysis of biochemical systems. Computational modeling, in conjunction with the use of formal intuitive modeling languages, enables biologists to define models using a notation very similar to the informal descriptions they commonly use, but formal and, hence, automatically executable. We describe the main features of the existing textual computational languages and the tool support available for model development and analysis.

Narrative-based computational modelling of the Gp130/JAK/STAT signalling pathway.

BACKGROUND: Appropriately formulated quantitative computational models can support researchers in understanding the dynamic behaviour of biological pathways and support hypothesis formulation and selection by "in silico" experimentation. An obstacle to widespread adoption of this approach is the requirement to formulate a biological pathway as machine executable computer code. We have recently proposed a novel, biologically intuitive, narrative-style modelling language for biologists to formulate the pathway which is then automatically translated into an executable format and is, thus, usable for analysis via existing simulation techniques. RESULTS: Here we use a high-level narrative language in designing a computational model of the gp130/JAK/STAT signalling pathway and show that the model reproduces the dynamic behaviour of the pathway derived by biological observation. We then "experiment" on the model by simulation and sensitivity analysis to define those parameters which dominate the dynamic behaviour of the pathway. The model predicts that nuclear compartmentalisation and phosphorylation status of STAT are key determinants of the pathway and that alternative mechanisms of signal attenuation exert their influence on different timescales. CONCLUSION: The described narrative model of the gp130/JAK/STAT pathway represents an interesting case study showing how, by using this approach, researchers can model biological systems without explicitly dealing with formal notations and mathematical expressions (typically used for biochemical modelling), nevertheless being able to obtain simulation and analysis results. We present the model and the sensitivity analysis results we have obtained, that allow us to identify the parameters which are most sensitive to perturbations. The results, which are shown to be in agreement with existing mathematical models of the gp130/JAK/STAT pathway, serve us as a form of validation of the model and of the approach itself.

Jornada de experiências: conhecimento e práticas urbanas / Journey of experiences: knowledge and urban practices

As diversas áreas de atuação e saberes, acrescidas do conhecimento da gerontologia, possibilitaram a alguns profissionais se reconstruírem e ampliarem seus trabalhos com o segmento idoso nas mais diversas práticas, concretizadas na cidade de São Paulo. Observa-se como os "momentos" do corpo humano, o qual ocupa um espaço no território urbano, estão sempre em movimento. O corpo é, então, entendido como o primeiro encontro, pois é ele que mostra a velhice ou a expressão flagrante dos anos vividos. E a busca desse corpo por um abrigo é uma das grandes reflexões apresentadas na segunda experiência. As necessidades do envelhecimento e seu prolongamento cada vez maior demandam modos de morar urbanos que respeitem a dignidade humana quando esse corpo é considerado "inativo" pela sociedade, tema da terceira prática. Ela mostra como tais profissionais souberam criar práticas educativas que ampliam esse corpo desejante e, assim, reencontrando-se, em outro momento, agora inserido no corpo urbano.

Jornada de experiências: conhecimento e práticas urbanas / Journey of experiences: knowledge and urban practices

As diversas áreas de atuação e saberes, acrescidas do conhecimento da gerontologia, possibilitaram a alguns profissionais se reconstruírem e ampliarem seus trabalhos com o segmento idoso nas mais diversas práticas, concretizadas na cidade de São Paulo. Observa-se como os 'momentos' do corpo humano, o qual ocupa um espaço no território urbano, estão sempre em movimento. O corpo é, então, entendido como o primeiro encontro, pois é ele que mostra a velhice ou a expressão flagrante dos anos vividos. E a busca desse corpo por um abrigo é uma das grandes reflexões apresentadas na segunda experiência. As necessidades do envelhecimento e seu prolongamento cada vez maior demandam modos de morar urbanos que respeitem a dignidade humana quando esse corpo é considerado 'inativo' pela sociedade, tema da terceira prática. Ela mostra como tais profissionais souberam criar práticas educativas que ampliam esse corpo desejante e, assim, reencontrando-se, em outro momento, agora inserido no corpo urbano (AU)

O cotidiano dos idosos moradores nas repúblicas da cidade de Santos - São Paulo / The daily life of the elderly who live in senior's homes in the city of Santos - São Paulo

O artigo trata do cotidiano dos moradores nas repúblicas para idosos situadas na cidade de Santos, litoral do estado de São Paulo. Essa modalidade de abrigo proporciona uma estrutura de acolhida e vivência social capaz de assegurar padões satisfatórios de qualidade de vida, inclusão e proteção social, como recomenda a Política Nacional do Idoso.

O cotidiano dos idosos moradores nas repúblicas da cidade de Santos - São Paulo / The daily life of the elderly who live in senior's homes in the city of Santos - São Paulo

O artigo trata do cotidiano dos moradores nas repúblicas para idosos situadas na cidade de Santos, litoral do estado de São Paulo. Essa modalidade de abrigo proporciona uma estrutura de acolhida e vivência social capaz de assegurar padões satisfatórios de qualidade de vida, inclusão e proteção social, como recomenda a Política Nacional do Idoso (AU)