MiR-192-Mediated Positive Feedback Loop Controls the Robustness of Stress-Induced p53 Oscillations in Breast Cancer Cells

miR-192 family in breast cancer: Regulatory mechanisms and diagnostic value

There is a growing interest in the role of the miRNA family in human cancer. The miRNA-192 family is a group of conserved small RNAs, including miR-192, miR-194, and miR-215. Recent studies have shown that the incidence and mortality of breast cancer have been increasing epidemiologically year by year, and it is urgent to clarify the pathogenesis of breast cancer and seek new diagnostic and therapeutic methods. There is increasing evidence that miR-192 family members may be involved in the occurrence and development of breast cancer. This review describes the regulatory mechanism of the miRNA-192 family affecting the malignant behavior of breast cancer cells and evaluates the value of the miRNA-192 family as a diagnostic and prognostic biomarker for breast cancer. It is expected that summarizing and discussing the relationship between miRNA-192 family members and breast cancer, it will provide a new direction for the clinical diagnosis and treatment of breast cancer and basic medical research.

The Role of Circulating MicroRNAs in the Prediction of Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer in the Indian Population

INTRODUCTION

MicroRNAs (miRNAs) are known to play an important role in cancer cell proliferation, susceptibility of cancer cells to chemotherapy, and patient survival. Identifying miRNAs that can predict response to chemotherapy in locally advanced breast cancer (LABC), the most common variant, can help to choose appropriate drug regimens to suit the epigenetic profile of individual patients.

OBJECTIVE

To investigate the expression of the differentially expressed miRNAs identified by next-generation sequencing from a pilot study involving cases and controls, in peripheral blood mononuclear cells (PBMC) of patients with LABC during the course of neoadjuvant chemotherapy (NAC) and determine their role in response to chemotherapy.

METHODS

This study included 30 newly diagnosed LABC patients. Peripheral blood from every participant was collected before the start of chemotherapy, at the end of the third cycle, and at the end of the seventh cycle of NAC. Based on the results of a pilot study in a similar population with suitable controls, four differentially expressed miRNAs namely miR-24-2, miR-192-5p, miR-3609, and miR-664b-3p were considered to be validated in this study. The expression of these four miRNAs was examined by qRT-PCR, and their association with response to chemotherapy was analyzed.

RESULT

 A significant change in the expression of miR-192-5p was found in responders (p = 0.001) over a period of seven cycles and the difference between the expression of miR-24-2 from baseline to the seventh cycle of NAC was higher in responders while compared to the non-responders (p < 0.05).

CONCLUSION

miR-192-5p and miR-24-2 were identified as predictive biomarkers for response to NAC in south Indian patients with LABC.

Protective role of naftidrofuryl against methotrexate-induced testicular damage via the amelioration of the p53/miRNA-29a/CDC42 apoptotic pathway, inflammation, and oxidative stress

This study aimed to assess the possible protective effects of naftidrofuryl (Naf) against methotrexate (MTX)-induced testicular toxicity in rats. Male rats were randomly distributed into four groups: control, Naf, MTX, and MTX+Naf groups. MTX administration induced oxidative stress, inflammation, and apoptosis in the testicular tissue, while pretreatment with Naf attenuated these pathways. Naf pretreatment significantly decreased malondialdehyde and interleukin-6 contents, microRNA-29a (miRNA-29a) expression level, and nuclear factor kappa B and p53 immunostaining in the testicular tissues compared to the MTX group. Conversely, it significantly increased Johnsen's score, serum testosterone level, serum total antioxidant capacity, testicular superoxide dismutase activity, testicular catalase activity, and testicular cell division cycle 42 (CDC42) expression compared to the MTX group. In conclusion, Naf exerted a significant protective effect against MTX-induced testicular toxicity via antioxidant and anti-inflammatory mechanisms and modulating the p53/miRNA-29a/CDC42 apoptotic pathway.

Encoding and Decoding of p53 Dynamics in Cellular Response to Stresses

In the cellular response to stresses, the tumor suppressor p53 is activated to maintain genomic integrity and fidelity. As a transcription factor, p53 exhibits rich dynamics to allow for discrimination of the type and intensity of stresses and to direct the selective activation of target genes involved in different processes including cell cycle arrest and apoptosis. In this review, we focused on how stresses are encoded into p53 dynamics and how the dynamics are decoded into cellular outcomes. Theoretical modeling may provide a global view of signaling in the p53 network by coupling the encoding and decoding processes. We discussed the significance of modeling in revealing the mechanisms of the transition between p53 dynamic modes. Moreover, we shed light on the crosstalk between the p53 network and other signaling networks. This review may advance the understanding of operating principles of the p53 signaling network comprehensively and provide insights into p53 dynamics-based cancer therapy.

microRNA-Mediated Encoding and Decoding of Time-Dependent Signals in Tumorigenesis

microRNAs, pivotal post-transcriptional regulators of gene expression, in the past decades have caught the attention of researchers for their involvement in different biological processes, ranging from cell development to cancer. Although lots of effort has been devoted to elucidate the topological features and the equilibrium properties of microRNA-mediated motifs, little is known about how the information encoded in frequency, amplitude, duration, and other features of their regulatory signals can affect the resulting gene expression patterns. Here, we review the current knowledge about microRNA-mediated gene regulatory networks characterized by time-dependent input signals, such as pulses, transient inputs, and oscillations. First, we identify the general characteristic of the main motifs underlying temporal patterns. Then, we analyze their impact on two commonly studied oncogenic networks, showing how their dysfunction can lead to tumorigenesis.

MicroRNAs and the DNA damage response: How is cell fate determined?

It is becoming clear that the DNA damage response orchestrates an appropriate response to a given level of DNA damage, whether that is cell cycle arrest and repair, senescence or apoptosis. It is plausible that the alternative regulation of the DNA damage response (DDR) plays a role in deciding cell fate following damage. MicroRNAs (miRNAs) are associated with the transcriptional regulation of many cellular processes. They have diverse functions, affecting, presumably, all aspects of cell biology. Many have been shown to be DNA damage inducible and it is conceivable that miRNA species play a role in deciding cell fate following DNA damage by regulating the expression and activation of key DDR proteins. From a clinical perspective, miRNAs are attractive targets to improve cancer patient outcomes to DNA-damaging chemotherapy. However, cancer tissue is known to be, or to become, well adapted to DNA damage as a means of inducing chemoresistance. This frequently results from an altered DDR, possibly owing to miRNA dysregulation. Though many studies provide an overview of miRNAs that are dysregulated within cancerous tissues, a tangible, functional association is often lacking. While miRNAs are well-documented in 'ectopic biology', the physiological significance of endogenous miRNAs in the context of the DDR requires clarification. This review discusses miRNAs of biological relevance and their role in DNA damage response by potentially 'fine-tuning' the DDR towards a particular cell fate in response to DNA damage. MiRNAs are thus potential therapeutic targets/strategies to limit chemoresistance, or improve chemotherapeutic efficacy.

Uncoupling gene expression noise along the central dogma using genome engineered human cell lines

Eukaryotic protein synthesis is an inherently stochastic process. This stochasticity stems not only from variations in cell content between cells but also from thermodynamic fluctuations in a single cell. Ultimately, these inherently stochastic processes manifest as noise in gene expression, where even genetically identical cells in the same environment exhibit variation in their protein abundances. In order to elucidate the underlying sources that contribute to gene expression noise, we quantify the contribution of each step within the process of protein synthesis along the central dogma. We uncouple gene expression at the transcriptional, translational, and post-translational level using custom engineered circuits stably integrated in human cells using CRISPR. We provide a generalized framework to approximate intrinsic and extrinsic noise in a population of cells expressing an unbalanced two-reporter system. Our decomposition shows that the majority of intrinsic fluctuations stem from transcription and that coupling the two genes along the central dogma forces the fluctuations to propagate and accumulate along the same path, resulting in increased observed global correlation between the products.

Oscillatory Dynamics of p53-Mdm2 Circuit in Response to DNA Damage Caused by Ionizing Radiation

Although the dynamical behavior of the p53-Mdm2 loop has been extensively studied, the understanding of the mechanism underlying the regulation of this pathway still remains limited. Herein, we developed an integrated model with five basic components and three ubiquitous time delays for the p53-Mdm2 interaction in response to DNA damage following ionizing radiation (IR). We showed that a sufficient amount of activated ATM level can initiate the p53 oscillations with nearly the same amplitude over a wide range of the ATM level; a proper range of p53 level is also required for generating the oscillations, for too high or too low levels it would fail to generate the oscillations; and increased Mdm2 level leads to decreased amplitude of the p53 oscillation and reduced expression of the p53 activity. Moreover, we found that the negative feedback loop formed between p53 and nuclear Mdm2 plays a dominant role in determining the p53 dynamics, whereas when interaction strength of the negative feedback loop becomes weaker, the positive feedback loop formed between p53 and cytoplasmatic Mdm2 can induce different types of dynamics. Furthermore, we demonstrated that the total time delay required for protein production and nuclear translocation of Mdm2 can induce p53 oscillations even when the p53 level is at a certain stable high steady state or at a certain stable low steady state. In addition, the two important features of the oscillatory dynamics-amplitude and period-can be controlled by such time delay. These results are in agreement with multiple experimental observations and may enrich our understanding of the dynamics of the p53 network.

Effects of Mycoplasmas on the Host Cell Signaling Pathways

Mycoplasmas are the smallest free-living organisms. Reduced sizes of their genomes put constraints on the ability of these bacteria to live autonomously and make them highly dependent on the nutrients produced by host cells. Importantly, at the organism level, mycoplasmal infections may cause pathological changes to the host, including cancer and severe immunological reactions. At the molecular level, mycoplasmas often activate the NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) inflammatory response and concomitantly inhibit the p53-mediated response, which normally triggers the cell cycle and apoptosis. Thus, mycoplasmal infections may be considered as cancer-associated factors. At the same time, mycoplasmas through their membrane lipoproteins (LAMPs) along with lipoprotein derivatives (lipopeptide MALP-2, macrophage-activating lipopeptide-2) are able to modulate anti-inflammatory responses via nuclear translocation and activation of Nrf2 (the nuclear factor-E2-related anti-inflammatory transcription factor 2). Thus, interactions between mycoplasmas and host cells are multifaceted and depend on the cellular context. In this review, we summarize the current information on the role of mycoplasmas in affecting the host’s intracellular signaling mediated by the interactions between transcriptional factors p53, Nrf2, and NF-κB. A better understanding of the mechanisms underlying pathologic processes associated with reprogramming eukaryotic cells that arise during the mycoplasma-host cell interaction should facilitate the development of new therapeutic approaches to treat oncogenic and inflammatory processes.

Dynamic Behavior of p53 Driven by Delay and a Microrna-34a-Mediated Feedback Loop

The tumor suppressor protein p53 is a critical hub in the comprehensive transcriptional network that inhibits the growth of cells after acute stress stimulation. In this paper, an integrated model of the p53 signaling pathway in response to DNA damage is proposed and the p53 stability and oscillatory dynamics are analyzed. Through theoretical analysis and numerical simulation, we find that the delay as a bifurcation parameter can drive the p53-Mdm2 module to undergo a supercritical Hopf bifurcation, thereby producing oscillation behavior. Moreover, we demonstrate how the positive feedback loop formed by p53* and microRNA-34a (miR-34a) with the feature of double-negative regulation produces limit-cycle oscillations. Further, we find that miR-34a can affect the critical value of Hopf bifurcation in delay-induced p53 networks. In addition, we show that ATM, once activated by DNA damage, makes p53* undergo two Hopf bifurcations. These results revealed that both time delay and miR-34a can have tumor suppressing roles by promoting p53 oscillation or high level expression, which will provide a perspective for promoting the development of anti-cancer drugs by targeting miR-34a and time delay.

From Endogenous to Synthetic microRNA-Mediated Regulatory Circuits: An Overview

MicroRNAs are short non-coding RNAs that are evolutionarily conserved and are pivotal post-transcriptional mediators of gene regulation. Together with transcription factors and epigenetic regulators, they form a highly interconnected network whose building blocks can be classified depending on the number of molecular species involved and the type of interactions amongst them. Depending on their topology, these molecular circuits may carry out specific functions that years of studies have related to the processing of gene expression noise. In this review, we first present the different over-represented network motifs involving microRNAs and their specific role in implementing relevant biological functions, reviewing both theoretical and experimental studies. We then illustrate the recent advances in synthetic biology, such as the construction of artificially synthesised circuits, which provide a controlled tool to test experimentally the possible microRNA regulatory tasks and constitute a starting point for clinical applications.

Mathematical Modeling of p53 Pathways

Cells have evolved balanced systems that ensure an appropriate response to stress. The systems elicit repair responses in temporary or moderate stress but eliminate irreparable cells via apoptosis in detrimental conditions of prolonged or severe stress. The tumor suppressor p53 is a central player in these stress response systems. When activated under DNA damage stress, p53 regulates hundreds of genes that are involved in DNA repair, cell cycle, and apoptosis. Recently, increasing studies have demonstrated additional regulatory roles of p53 in metabolism and mitochondrial physiology. Due to the inherent complexity of feedback loops between p53 and its target genes, the application of mathematical modeling has emerged as a novel approach to better understand the multifaceted functions and dynamics of p53. In this review, we discuss several mathematical modeling approaches in exploring the p53 pathways.

Coordination of miR-192 and miR-22 in p53-Mediated Cell Fate Decision

p53-targeted microRNAs (miRNAs) markedly affect cellular response to DNA damage. These miRNAs may contribute to either cell cycle arrest or apoptosis induction. However, how these miRNAs coordinate to modulate the decision between cell survival and death remains less understood. Here, we developed an integrated model of p53 signaling network to investigate how p53-targeted miR-192 and miR-22 modulate cellular outcome in response to DNA damage. By numerical simulations, we found that p53 is activated progressively depending on the extent of DNA damage. Upon moderate damage, p53 rises to medium levels and induces miR-192 to promote its own activation, facilitating p21 induction and cell cycle arrest. Upon severe damage, p53 reaches high levels and is fully activated due to phosphatase and tensin homolog (PTEN) induction. As a result, it transactivates miR-22 to repress p21 expression and activate E2F1, resulting in apoptosis. Therefore, miR-192 promotes primary activation of p53, while miR-22 promotes apoptosis by downregulating p21. This work may advance the understanding of the mechanism for cell fate decision between life and death by p53-inducible miRNAs.

Incoherent Inputs Enhance the Robustness of Biological Oscillators

Robust biological oscillators retain the critical ability to function in the presence of environmental perturbations. Although central architectures that support robust oscillations have been extensively studied, networks containing the same core vary drastically in their potential to oscillate, and it remains elusive what peripheral modifications to the core contribute to this functional variation. Here, we have generated a complete atlas of two- and three-node oscillators computationally, then systematically analyzed the association between network structure and robustness. We found that, while certain core topologies are essential for producing a robust oscillator, local structures can substantially modulate the robustness of oscillations. Notably, local nodes receiving incoherent or coherent inputs respectively promote or attenuate the overall network robustness in an additive manner. We validated these relationships in larger-scale networks reflective of real biological oscillators. Our findings provide an explanation for why auxiliary structures not required for oscillation are evolutionarily conserved and suggest simple ways to evolve or design robust oscillators.

Integrated Regulation of HuR by Translation Repression and Protein Degradation Determines Pulsatile Expression of p53 Under DNA Damage

Expression of tumor suppressor p53 is regulated at multiple levels, disruption of which often leads to cancer. We have adopted an approach combining computational systems modeling with experimental validation to elucidate the translation regulatory network that controls p53 expression post DNA damage. The RNA-binding protein HuR activates p53 mRNA translation in response to UVC-induced DNA damage in breast carcinoma cells. p53 and HuR levels show pulsatile change post UV irradiation. The computed model fitted with the observed pulse of p53 and HuR only when hypothetical regulators of synthesis and degradation of HuR were incorporated. miR-125b, a UV-responsive microRNA, was found to represses the translation of HuR mRNA. Furthermore, UV irradiation triggered proteasomal degradation of HuR mediated by an E3-ubiquitin ligase tripartite motif-containing 21 (TRIM21). The integrated action of miR-125b and TRIM21 constitutes an intricate control system that regulates pulsatile expression of HuR and p53 and determines cell viability in response to DNA damage.

Central role of the p53 pathway in the noncoding-RNA response to oxidative stress

Oxidative stress plays a fundamental role in many conditions. Specifically, redox imbalance inhibits endothelial cell (EC) growth, inducing cell death and senescence. We used global transcriptome profiling to investigate the involvement of noncoding-RNAs in these phenotypes. By RNA-sequencing, transcriptome changes were analyzed in human ECs exposed to H₂O₂, highlighting a pivotal role of p53-signaling. Bioinformatic analysis and validation in p53-silenced ECs, identified several p53-targets among both mRNAs and long noncoding-RNAs (lncRNAs), including MALAT1 and NEAT1. Among microRNAs (miRNAs), miR-192-5p was the most induced by H₂O₂ treatment, in a p53-dependent manner. Down-modulated mRNA-targets of miR-192-5p were involved in cell cycle, DNA repair and stress response. Accordingly, miR-192-5p overexpression significantly decreased EC proliferation, inducing cell death. A central role of the p53-pathway was also confirmed by the analysis of differential exon usage: Upon H₂O₂ treatment, the expression of p53-dependent 5'-isoforms of MDM2 and PVT1 increased selectively. The transcriptomic alterations identified in H₂O₂-treated ECs were also observed in other physiological and pathological conditions where redox control plays a fundamental role, such as ECs undergoing replicative senescence, skeletal muscles of critical limb-ischemia patients and the peripheral-blood mononuclear cells of long-living individuals. Collectively, these findings indicate a prominent role of noncoding-RNAs in oxidative stress response.

Mechanistic Computational Models of MicroRNA-Mediated Signaling Networks in Human Diseases

MicroRNAs (miRs) are endogenous non-coding RNA molecules that play important roles in human health and disease by regulating gene expression and cellular processes. In recent years, with the increasing scientific knowledge and new discovery of miRs and their gene targets, as well as the plentiful experimental evidence that shows dysregulation of miRs in a wide variety of human diseases, the computational modeling approach has emerged as an effective tool to help researchers identify novel functional associations between differential miR expression and diseases, dissect the phenotypic expression patterns of miRs in gene regulatory networks, and elucidate the critical roles of miRs in the modulation of disease pathways from mechanistic and quantitative perspectives. Here we will review the recent systems biology studies that employed different kinetic modeling techniques to provide mechanistic insights relating to the regulatory function and therapeutic potential of miRs in human diseases. Some of the key computational aspects to be discussed in detail in this review include (i) models of miR-mediated network motifs in the regulation of gene expression, (ii) models of miR biogenesis and miR⁻target interactions, and (iii) the incorporation of such models into complex disease pathways in order to generate mechanistic, molecular- and systems-level understanding of pathophysiology. Other related bioinformatics tools such as computational platforms that predict miR-disease associations will also be discussed, and we will provide perspectives on the challenges and opportunities in the future development and translational application of data-driven systems biology models that involve miRs and their regulatory pathways in human diseases.

XPD suppresses cell proliferation and migration via miR-29a-3p-Mdm2/PDGF-B axis in HCC

Objective

The aim of this study was to investigate the role of XPD in migration and invasion of hepatocellular carcinoma (HCC) cells.

Methods

The expression of XPD and miR-29a-3p was examined by western blot and qRT-PCR, cell proliferation was detected by MTT assay, cell migration was detected by transwell assay. TargetScan was used to predict potential targets of miR-29a-3p.

Results

In this study, we found that the expression of XPD and miR-29a-3p was downregulated in HCC samples and HCC cell lines. XPD suppressed proliferation and migration of HCC cell via regulating miR-29a-3p expression. Target prediction analysis and dual-luciferase reporter assay confirmed Mdm2 and PDGF-B were direct targets of miR-29a-3p, and miR-29a-3p suppressed proliferation and migration of HCC cells via regulating the expression of Mdm2 or PDGF-B.

Conclusions

Our data indicated that XPD suppressed cell proliferation and migration via miR-29a-3p-Mdm2/PDGF-B axis in HCC.

miR-192 Is Overexpressed and Promotes Cell Proliferation in Prostate Cancer

OBJECTIVE

Prostate cancer (PCa) is one of the most prevalent types of cancer among men worldwide. The incidence of PCa is increasing in China. Therefore, there is an urgent need to identify novel diagnostic and prognostic markers for PCa to improve the treatment of the disease.

METHODS

The Cancer Genome Atlas (TCGA) and GEO database were used to analyze the expression of miR-192, and the relationship between miR-192 and the clinical features of patients with PCa. Cell cycle and cell proliferation assay were used to detect the functional roles of miR-192 in PCa. Bioinformatic analysis for miR-192-5p was performed using gene ontology and KEGG analysis.

RESULTS

By analyzing the dataset of TCGA, we found that miR-192 was overexpressed in PCa samples compared to normal tissues and was upregulated in high-grade PCa compared to low-grade PCa. We also observed that higher miR-192 expression was associated with a shorter biochemical recurrence-free survival time. Our results also demonstrated that miR-192 promoted PCa cell proliferation and cell cycle progression.

CONCLUSION

These results suggest that miR-192 may be considered for use as a potential diagnostic and therapeutic target of PCa.

CRISPR-Based Editing Reveals Edge-Specific Effects in Biological Networks

Unraveling the properties of biological networks is central to understanding both normal and disease cellular phenotypes. Networks consist of functional elements (nodes) that form a variety of diverse connections (edges), with each node being a hub for multiple edges. Herein, in contrast to node-centric network perturbation and analysis approaches, we present a high-throughput CRISPR-based methodology for delineating the role of network edges. Ablation of network edges using a library targeting 93 miRNA target sites in 71 genes reveals numerous edges that control, with variable importance, cellular growth and survival under stress. To compare the impact of removing nodes versus edges in a biological network, we dissect a specific p53-microRNA pathway. We show that removal of the miR-34a target site from the anti-apoptotic gene BCL2 desensitizes the cell to ectopic delivery of miR-34a in a p53-dependent manner. In summary, we demonstrate that network edges are critical to the function and stability of biological networks. Our results introduce a novel genetic screening opportunity via edge ablation and highlight a new dimension in biological network analysis.

Mapping the operational landscape of microRNAs in synthetic gene circuits

MicroRNAs are a class of short, noncoding RNAs that are ubiquitous modulators of gene expression, with roles in development, homeostasis, and disease. Engineered microRNAs are now frequently used as regulatory modules in synthetic biology. Moreover, synthetic gene circuits equipped with engineered microRNA targets with perfect complementarity to endogenous microRNAs establish an interface with the endogenous milieu at the single-cell level. The function of engineered microRNAs and sensor systems is typically optimized through extensive trial-and-error. Here, using a combination of synthetic biology experimentation in human embryonic kidney cells and quantitative analysis, we investigate the relationship between input genetic template abundance, microRNA concentration, and output under microRNA control. We provide a framework that employs the complete operational landscape of a synthetic gene circuit and enables the stepwise development of mathematical models. We derive a phenomenological model that recapitulates experimentally observed nonlinearities and contains features that provide insight into the microRNA function at various abundances. Our work facilitates the characterization and engineering of multi-component genetic circuits and specifically points to new insights on the operation of microRNAs as mediators of endogenous information and regulators of gene expression in synthetic biology.

A dynamical framework for complex fractional killing

When chemotherapy drugs are applied to tumor cells with the same or similar genotypes, some cells are killed, while others survive. This fractional killing contributes to drug resistance in cancer. Through an incoherent feedforward loop, chemotherapy drugs not only activate p53 to induce cell death, but also promote the expression of apoptosis inhibitors which inhibit cell death. Consequently, cells in which p53 is activated early undergo apoptosis while cells in which p53 is activated late survive. The incoherent feedforward loop and the essential role of p53 activation timing makes fractional killing a complex dynamical challenge, which is hard to understand with intuition alone. To better understand this process, we have constructed a representative model by integrating the control of apoptosis with the relevant signaling pathways. After the model was trained to recapture the observed properties of fractional killing, it was analyzed with nonlinear dynamical tools. The analysis suggested a simple dynamical framework for fractional killing, which predicts that cell fate can be altered in three possible ways: alteration of bifurcation geometry, alteration of cell trajectories, or both. These predicted categories can explain existing strategies known to combat fractional killing and facilitate the design of novel strategies.

Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes

Multiple biological processes are driven by oscillatory gene expression at different time scales. Pulsatile dynamics are thought to be widespread, and single-cell live imaging of gene expression has lead to a surge of dynamic, possibly oscillatory, data for different gene networks. However, the regulation of gene expression at the level of an individual cell involves reactions between finite numbers of molecules, and this can result in inherent randomness in expression dynamics, which blurs the boundaries between aperiodic fluctuations and noisy oscillators. This underlies a new challenge to the experimentalist because neither intuition nor pre-existing methods work well for identifying oscillatory activity in noisy biological time series. Thus, there is an acute need for an objective statistical method for classifying whether an experimentally derived noisy time series is periodic. Here, we present a new data analysis method that combines mechanistic stochastic modelling with the powerful methods of non-parametric regression with Gaussian processes. Our method can distinguish oscillatory gene expression from random fluctuations of non-oscillatory expression in single-cell time series, despite peak-to-peak variability in period and amplitude of single-cell oscillations. We show that our method outperforms the Lomb-Scargle periodogram in successfully classifying cells as oscillatory or non-oscillatory in data simulated from a simple genetic oscillator model and in experimental data. Analysis of bioluminescent live-cell imaging shows a significantly greater number of oscillatory cells when luciferase is driven by a Hes1 promoter (10/19), which has previously been reported to oscillate, than the constitutive MoMuLV 5’ LTR (MMLV) promoter (0/25). The method can be applied to data from any gene network to both quantify the proportion of oscillating cells within a population and to measure the period and quality of oscillations. It is publicly available as a MATLAB package.

Technological advances now allow us to observe gene expression in real-time at a single-cell level. In a wide variety of biological contexts this new data has revealed that gene expression is highly dynamic and possibly oscillatory. It is thought that periodic gene expression may be useful for keeping track of time and space, as well as transmitting information about signalling cues. Classifying a time series as periodic from single cell data is difficult because it is necessary to distinguish whether peaks and troughs are generated from an underlying oscillator or whether they are aperiodic fluctuations. To this end, we present a novel tool to classify live-cell data as oscillatory or non-oscillatory that accounts for inherent biological noise. We first demonstrate that the method outperforms a competing scheme in classifying computationally simulated single-cell data, and we subsequently analyse live-cell imaging time series. Our method is able to successfully detect oscillations in a known genetic oscillator, but it classifies data from a constitutively expressed gene as aperiodic. The method forms a basis for discovering new gene expression oscillators and quantifying how oscillatory activity alters in response to changes in cell fate and environmental or genetic perturbations.

Recent progress and open challenges in modeling p53 dynamics in single cells

In mammalian cells, the tumor suppressor p53 is activated upon a variety of cellular stresses and ensures an appropriate response ranging from arrest and repair to the induction of senescence and apoptosis. Quantitative measurements in individual living cells showed stimulus-dependent dynamics of p53 accumulation upon stress induction. Due to the complexity of the underlying biochemical interactions, mathematical models were indispensable for understanding the topology of the network regulating p53 dynamics. Recent work provides furhter insights into the causes of heterogeneous responses in individual cells, the rewiring of the network in response to different inputs and the role of the downstream processes in determining the cellular fate upon stress.

Combining Anti-Mir-155 with Chemotherapy for the Treatment of Lung Cancers

Purpose: The oncogenic miR-155 is upregulated in many human cancers, and its expression is increased in more aggressive and therapy-resistant tumors, but the molecular mechanisms underlying miR-155-induced therapy resistance are not fully understood. The main objectives of this study were to determine the role of miR-155 in resistance to chemotherapy and to evaluate anti-miR-155 treatment to chemosensitize tumors.Experimental Design: We performed in vitro studies on cell lines to investigate the role of miR-155 in therapy resistance. To assess the effects of miR-155 inhibition on chemoresistance, we used an in vivo orthotopic lung cancer model of athymic nude mice, which we treated with anti-miR-155 alone or in combination with chemotherapy. To analyze the association of miR-155 expression and the combination of miR-155 and TP53 expression with cancer survival, we studied 956 patients with lung cancer, chronic lymphocytic leukemia, and acute lymphoblastic leukemia.Results: We demonstrate that miR-155 induces resistance to multiple chemotherapeutic agents in vitro, and that downregulation of miR-155 successfully resensitizes tumors to chemotherapy in vivo We show that anti-miR-155-DOPC can be considered non-toxic in vivo We further demonstrate that miR-155 and TP53 are linked in a negative feedback mechanism and that a combination of high expression of miR-155 and low expression of TP53 is significantly associated with shorter survival in lung cancer.Conclusions: Our findings support the existence of an miR-155/TP53 feedback loop, which is involved in resistance to chemotherapy and which can be specifically targeted to overcome drug resistance, an important cause of cancer-related death. Clin Cancer Res; 23(11); 2891-904. ©2016 AACR.

Understanding microRNA-mediated gene regulatory networks through mathematical modelling

The discovery of microRNAs (miRNAs) has added a new player to the regulation of gene expression. With the increasing number of molecular species involved in gene regulatory networks, it is hard to obtain an intuitive understanding of network dynamics. Mathematical modelling can help dissecting the role of miRNAs in gene regulatory networks, and we shall here review the most recent developments that utilise different mathematical modelling approaches to provide quantitative insights into the function of miRNAs in the regulation of gene expression. Key miRNA regulation features that have been elucidated via modelling include: (i) the role of miRNA-mediated feedback and feedforward loops in fine-tuning of gene expression; (ii) the miRNA–target interaction properties determining the effectiveness of miRNA-mediated gene repression; and (iii) the competition for shared miRNAs leading to the cross-regulation of genes. However, there is still lack of mechanistic understanding of many other properties of miRNA regulation like unconventional miRNA–target interactions, miRNA regulation at different sub-cellular locations and functional miRNA variant, which will need future modelling efforts to deal with. This review provides an overview of recent developments and challenges in this field.