RESUMEN
Inflammatory stimuli triggers the degradation of three inhibitory κB (IκB) proteins, allowing for nuclear translocation of nuclear factor-κB (NFκB) for transcriptional induction of its target genes. Of these three, IκBα is a well-known negative feedback regulator that limits the duration of NFκB activity. We sought to determine whether IκBα's role in enabling or limiting NFκB activation is important for tumor necrosis factor (TNF)-induced gene expression in human breast cancer cells (MCF-7). Contrary to our expectations, many more TNF-response genes showed reduced induction than enhanced induction in IκBα knockdown cells. Mathematical modeling was used to investigate the underlying mechanism. We found that the reduced activation of some NFκB target genes in IκBα-deficient cells could be explained by the incoherent feedforward loop (IFFL) model. In addition, for a subset of genes, prolonged NFκB activity due to loss of negative feedback control did not prolong their transient activation; this implied a multi-state transcription cycle control of gene induction. Genes encoding key inflammation-related transcription factors, such as JUNB and KLF10, were found to be best represented by a model that contained both the IFFL and the transcription cycle motif. Our analysis sheds light on the regulatory strategies that safeguard inflammatory gene expression from overproduction and repositions the function of IκBα not only as a negative feedback regulator of NFκB but also as an enabler of NFκB-regulated stimulus-responsive inflammatory gene expression. This study indicates the complex involvement of IκBα in the inflammatory response to TNF that is induced by radiation therapy in breast cancer.
Asunto(s)
Inhibidor NF-kappaB alfa , FN-kappa B , Factor de Necrosis Tumoral alfa , Regulación de la Expresión Génica , Humanos , Células MCF-7 , Inhibidor NF-kappaB alfa/genética , Inhibidor NF-kappaB alfa/metabolismo , FN-kappa B/genética , FN-kappa B/metabolismoRESUMEN
Cancer cells acquire drug resistance through the following stages: nonresistant, pre-resistant, and resistant. Although the molecular mechanism of drug resistance is well investigated, the process of drug resistance acquisition remains largely unknown. Here we elucidate the molecular mechanisms underlying the process of drug resistance acquisition by sequential analysis of gene expression patterns in tamoxifen-treated breast cancer cells. Single-cell RNA-sequencing indicates that tamoxifen-resistant cells can be subgrouped into two, one showing altered gene expression related to metabolic regulation and another showing high expression levels of adhesion-related molecules and histone-modifying enzymes. Pseudotime analysis showed a cell transition trajectory to the two resistant subgroups that stem from a shared pre-resistant state. An ordinary differential equation model based on the trajectory fitted well with the experimental results of cell growth. Based on the established model, it was predicted and experimentally validated that inhibition of transition to both resistant subtypes would prevent the appearance of tamoxifen resistance.
Asunto(s)
Antineoplásicos Hormonales/uso terapéutico , Neoplasias de la Mama/genética , Resistencia a Antineoplásicos/genética , Modelos Teóricos , Tamoxifeno/uso terapéutico , Antineoplásicos Hormonales/administración & dosificación , Neoplasias de la Mama/tratamiento farmacológico , Proliferación Celular/efectos de los fármacos , Femenino , Regulación Neoplásica de la Expresión Génica/efectos de los fármacos , Humanos , Células MCF-7 , Tamoxifeno/administración & dosificaciónRESUMEN
Crosstalk between the autonomic nervous system and the immune system by means of the sympathetic and parasympathetic pathways is a critical process in host defence. Activation of the sympathetic nervous system results in the release of catecholamines as well as neuropeptide Y (NPY). Here, we investigated whether phagocytes are capable of the de novo production of NPY, as has been described for catecholamines. We show that the synthesis of NPY and its Y1 receptor (Y1R) is increased in phagocytes in lungs following severe influenza virus infection. The genetic deletion of Npy or Y1r specifically in phagocytes greatly improves the pathology of severe influenza virus infection, which is characterized by excessive virus replication and pulmonary inflammation. Mechanistically, it is the induction of suppressor of cytokine signalling 3 (SOCS3) via NPY-Y1R activation that is responsible for impaired antiviral response and promoting pro-inflammatory cytokine production, thereby enhancing the pathology of influenza virus infection. Thus, direct regulation of the NPY-Y1R-SOCS3 pathway on phagocytes may act as a fine-tuner of an innate immune response to virus infection, which could be a therapeutic target for lethal influenza virus infection.
Asunto(s)
Virus de la Influenza A/patogenicidad , Pulmón/patología , Neuropéptido Y/metabolismo , Infecciones por Orthomyxoviridae/patología , Fagocitos/metabolismo , Animales , Citocinas/metabolismo , Eliminación de Gen , Interacciones Huésped-Patógeno , Virus de la Influenza A/fisiología , Pulmón/inmunología , Pulmón/virología , Ratones , Neuropéptido Y/genética , Infecciones por Orthomyxoviridae/inmunología , Infecciones por Orthomyxoviridae/virología , Fagocitos/patología , Fagocitos/virología , Receptores de Neuropéptido Y/genética , Receptores de Neuropéptido Y/metabolismo , Transducción de Señal , Proteína 3 Supresora de la Señalización de Citocinas/genética , Proteína 3 Supresora de la Señalización de Citocinas/metabolismo , Análisis de Supervivencia , Transcripción Genética , Replicación ViralRESUMEN
Feedback control is a key mechanism in signal transduction, intimately involved in regulating the outcome of the cellular response. Here, we report a novel mechanism by which PHLDA1, Pleckstrin homology-like domain, family A, member 1, negatively regulates ErbB receptor signaling by inhibition of receptor oligomerization. We have found that the ErbB3 ligand, heregulin, induces PHILDA1 expression in MCF-7 cells. Transcriptionally-induced PHLDA1 protein directly binds to ErbB3, whereas knockdown of PHLDA1 increases complex formation between ErbB3 and ErbB2. To provide insight into the mechanism for our time-course and single-cell experimental observations, we performed a systematic computational search of network topologies of the mathematical models based on receptor dimer-tetramer formation in the ErbB activation processes. Our results indicate that only a model in which PHLDA1 inhibits formation of both dimers and tetramer can explain the experimental data. Predictions made from this model were further validated by single-molecule imaging experiments. Our studies suggest a unique regulatory feature of PHLDA1 to inhibit the ErbB receptor oligomerization process and thereby control the activity of receptor signaling network.
Asunto(s)
Receptor ErbB-3/metabolismo , Factores de Transcripción/metabolismo , Humanos , Células MCF-7 , Modelos Químicos , Neurregulina-1/metabolismo , Multimerización de Proteína , Transducción de Señal , Imagen Individual de Molécula , Análisis de la Célula Individual , Factores de Transcripción/fisiología , Transcripción GenéticaRESUMEN
The ErbB receptor signaling pathway plays an important role in the regulation of cellular proliferation, survival and differentiation, and dysregulation of the pathway is linked to various types of human cancer. Mathematical models have been developed as a practical complementary approach to deciphering the complexity of ErbB receptor signaling and elucidating how the pathways discriminate between ligands to induce different cell fates. In this study, we developed a simulator to accurately calculate the dynamic sensitivity of extracellular-signal-regulated kinase (ERK) activity (ERK*) and Akt activity (Akt*), downstream of the ErbB receptors stimulated with epidermal growth factor (EGF) and heregulin (HRG). To demonstrate the feasibility of this simulator, we estimated how the reactions critically responsible for ERK* and Akt* change with time and in response to different doses of EGF and HRG, and predicted that only a small number of reactions determine ERK* and Akt*. ERK* increased steeply with increasing HRG dose until saturation, while showing a gently rising response to EGF. Akt* had a gradual wide-range response to HRG and a blunt response to EGF. Akt* was sensitive to perturbations of intracellular kinetics, while ERK* was more robust due to multiple, negative feedback loops. Overall, the simulator predicted reactions that were critically responsible for ERK* and Akt* in response to the dose of EGF and HRG, illustrated the response characteristics of ERK* and Akt*, and estimated mechanisms for generating robustness in the ErbB signaling network.
Asunto(s)
Receptores ErbB/metabolismo , Modelos Biológicos , Simulación por Computador , Factor de Crecimiento Epidérmico/metabolismo , Receptores ErbB/antagonistas & inhibidores , Humanos , Cinética , Sistema de Señalización de MAP Quinasas/efectos de los fármacos , Células MCF-7 , Proteínas/metabolismo , Proteínas Proto-Oncogénicas c-akt/antagonistas & inhibidores , Proteínas Proto-Oncogénicas c-akt/metabolismo , Transducción de Señal/efectos de los fármacosRESUMEN
Understanding how cells use complex transcriptional programs to alter their fate in response to specific stimuli is an important question in biology. For the MCF-7 human breast cancer cell line, we applied gene expression trajectory models to identify the genes involved in driving cell fate transitions. We modified trajectory models to account for the scenario where cells were exposed to different stimuli, in this case epidermal growth factor and heregulin, to arrive at different cell fates, i.e. proliferation and differentiation respectively. Using genome-wide CAGE time series data collected from the FANTOM5 consortium, we identified the sets of promoters that were involved in the transition of MCF-7 cells to their specific fates versus those with expression changes that were generic to both stimuli. Of the 1,552 promoters identified, 1,091 had stimulus-specific expression while 461 promoters had generic expression profiles over the time course surveyed. Many of these stimulus-specific promoters mapped to key regulators of the ERK (extracellular signal-regulated kinases) signaling pathway such as FHL2 (four and a half LIM domains 2). We observed that in general, generic promoters peaked in their expression early on in the time course, while stimulus-specific promoters tended to show activation of their expression at a later stage. The genes that mapped to stimulus-specific promoters were enriched for pathways that control focal adhesion, p53 signaling and MAPK signaling while generic promoters were enriched for cell death, transcription and the cell cycle. We identified 162 genes that were controlled by an alternative promoter during the time course where a subset of 37 genes had separate promoters that were classified as stimulus-specific and generic. The results of our study highlighted the degree of complexity involved in regulating a cell fate transition where multiple promoters mapping to the same gene can demonstrate quite divergent expression profiles.
Asunto(s)
Diferenciación Celular/efectos de los fármacos , Proliferación Celular/efectos de los fármacos , Factor de Crecimiento Epidérmico/farmacología , Receptores ErbB/metabolismo , Neurregulina-1/farmacología , Regiones Promotoras Genéticas/genética , Apoptosis/genética , Neoplasias de la Mama/genética , Ciclo Celular/genética , Línea Celular Tumoral , Activación Enzimática/efectos de los fármacos , Receptores ErbB/genética , Quinasas MAP Reguladas por Señal Extracelular/metabolismo , Femenino , Adhesiones Focales/genética , Expresión Génica/efectos de los fármacos , Perfilación de la Expresión Génica , Regulación de la Expresión Génica/genética , Humanos , Sistema de Señalización de MAP Quinasas/genética , Células MCF-7 , Proteína p53 Supresora de Tumor/genéticaRESUMEN
The analysis of CAGE (Cap Analysis of Gene Expression) time-course has been proposed by the FANTOM5 Consortium to extend the understanding of the sequence of events facilitating cell state transition at the level of promoter regulation. To identify the most prominent transcriptional regulations induced by growth factors in human breast cancer, we apply here the Complexity Invariant Dynamic Time Warping motif EnRichment (CIDER) analysis approach to the CAGE time-course datasets of MCF-7 cells stimulated by epidermal growth factor (EGF) or heregulin (HRG). We identify a multi-level cascade of regulations rooted by the Serum Response Factor (SRF) transcription factor, connecting the MAPK-mediated transduction of the HRG stimulus to the negative regulation of the MAPK pathway by the members of the DUSP family phosphatases. The finding confirms the known primary role of FOS and FOSL1, members of AP-1 family, in shaping gene expression in response to HRG induction. Moreover, we identify a new potential regulation of DUSP5 and RARA (known to antagonize the transcriptional regulation induced by the estrogen receptors) by the activity of the AP-1 complex, specific to HRG response. The results indicate that a divergence in AP-1 regulation determines cellular changes of breast cancer cells stimulated by ErbB receptors.
Asunto(s)
Neoplasias de la Mama/genética , Regulación Neoplásica de la Expresión Génica , Redes Reguladoras de Genes , Regiones Promotoras Genéticas , Receptor ErbB-2/genética , Transcripción Genética , Neoplasias de la Mama/patología , Femenino , Humanos , Células MCF-7RESUMEN
The immediate-early response mediates cell fate in response to a variety of extracellular stimuli and is dysregulated in many cancers. However, the specificity of the response across stimuli and cell types, and the roles of non-coding RNAs are not well understood. Using a large collection of densely-sampled time series expression data we have examined the induction of the immediate-early response in unparalleled detail, across cell types and stimuli. We exploit cap analysis of gene expression (CAGE) time series datasets to directly measure promoter activities over time. Using a novel analysis method for time series data we identify transcripts with expression patterns that closely resemble the dynamics of known immediate-early genes (IEGs) and this enables a comprehensive comparative study of these genes and their chromatin state. Surprisingly, these data suggest that the earliest transcriptional responses often involve promoters generating non-coding RNAs, many of which are produced in advance of canonical protein-coding IEGs. IEGs are known to be capable of induction without de novo protein synthesis. Consistent with this, we find that the response of both protein-coding and non-coding RNA IEGs can be explained by their transcriptionally poised, permissive chromatin state prior to stimulation. We also explore the function of non-coding RNAs in the attenuation of the immediate early response in a small RNA sequencing dataset matched to the CAGE data: We identify a novel set of microRNAs responsible for the attenuation of the IEG response in an estrogen receptor positive cancer cell line. Our computational statistical method is well suited to meta-analyses as there is no requirement for transcripts to pass thresholds for significant differential expression between time points, and it is agnostic to the number of time points per dataset.
Asunto(s)
Proteínas Inmediatas-Precoces/genética , ARN no Traducido/genética , Transcripción Genética/genética , Biología Computacional , Humanos , Proteínas Inmediatas-Precoces/metabolismo , Cinética , Células MCF-7 , MicroARNs/genética , MicroARNs/metabolismo , Modelos Estadísticos , ARN no Traducido/metabolismoRESUMEN
Extracellular signal-regulated kinase (ERK) plays a central role in signal transduction networks and cell fate decisions. Sustained ERK activation induces cell differentiation, whereas transient ERK results in the proliferation of several types of cells. Sustained ERK activity stabilizes the proteins of early-response gene products. However, the effect of ERK activity duration on mRNA stability is unknown. We analyzed the quantitative relationship between the duration of four ERK activity kinetics and the mRNA expression profile in growth factor-treated cells. Time-course transcriptome analysis revealed that the cells with prolonged ERK activity generally showed sustained mRNA expression of late response genes but not early or mid genes. Selected late response genes decayed more rapidly in the presence of a specific ERK inhibitor than a general transcription inhibitor and the decay rate was not related to the number of AU-rich elements. Our results suggest that sustained ERK activity plays an important role in the lifespan of the mRNA encoded by late response genes, in addition to the previously demonstrated role in protein stabilization of early-response genes, including transcription factors regulating the transcription of mid and late genes. This double-positive regulation of ligand-induced genes, also termed feedforward regulation, is critical in cell fate decisions.
Asunto(s)
Receptores ErbB/metabolismo , Quinasas MAP Reguladas por Señal Extracelular/metabolismo , Estabilidad del ARN/genética , Butadienos/farmacología , Diferenciación Celular/efectos de los fármacos , Diferenciación Celular/genética , Diferenciación Celular/fisiología , Dactinomicina/farmacología , Receptores ErbB/genética , Quinasas MAP Reguladas por Señal Extracelular/genética , Humanos , Sistema de Señalización de MAP Quinasas/efectos de los fármacos , Sistema de Señalización de MAP Quinasas/genética , Sistema de Señalización de MAP Quinasas/fisiología , Células MCF-7 , Nitrilos/farmacología , Estabilidad del ARN/efectos de los fármacos , Transducción de Señal/efectos de los fármacos , Transducción de Señal/genética , Transducción de Señal/fisiologíaRESUMEN
To explore the diversity and consistency of the signaling pathways that regulate tumor cell migration, we chose three human tumor cell lines that migrated after treatment with EGF. We then quantified the effect of fifteen inhibitors on the levels of expression or the phosphorylation levels of nine proteins that were induced by EGF stimulation in each of these cell lines. Based on the data obtained in this study and chemical-biological assumptions, we deduced cell migration pathways in each tumor cell line, and then compared them. As a result, we found that both the MEK/ERK and JNK/c-Jun pathways were activated in all three migrating cell lines. Moreover, GSK-3 and p38 were found to regulate PI3K/Akt pathway in only EC109 cells, and JNK was found to crosstalk with p38 and Fos related pathway in only TT cells. Taken together, our analytical system could easily distinguish between the common and cell type-specific pathways responsible for tumor cell migration.
Asunto(s)
Factor de Crecimiento Epidérmico/farmacología , Transducción de Señal/efectos de los fármacos , Línea Celular Tumoral , Movimiento Celular/efectos de los fármacos , Quinasas MAP Reguladas por Señal Extracelular/metabolismo , Glucógeno Sintasa Quinasa 3/metabolismo , Humanos , Proteínas Quinasas JNK Activadas por Mitógenos/metabolismo , Sistema de Señalización de MAP Quinasas/efectos de los fármacosRESUMEN
Cell migration is an essential step for tumor metastasis. The small GTPase Rac1 plays an important role in cell migration. Previously, we reported that epidermal growth factor (EGF) induced two waves of Rac1 activation; namely, at 5 min and 12 h after stimulation. A second wave of EGF-induced Rac1 activation was required for EGF-induced cell migration, however, the spatiotemporal regulation of the second wave of EGF-induced Rac1 activation remains largely unclear. In this study, we found that 5-lipoxygenase (5-LOX) is activated in the process of EGF-induced cell migration, and that leukotriene C4 (LTC4 ) produced by 5-LOX mediated the second wave of Rac1 activation, as well as cell migration. Furthermore, these effects caused by LTC4 were found to be blocked in the presence of the antagonist of cysteinyl leukotriene receptor 1 (CysLT1). This blockage indicates that LTC4 -mediated CysLT1 signaling regulates the second EGF-induced wave of Rac1 activation. We also found that 5-LOX inhibitors, CysLT1 antagonists and the knockdown of CysLT1 inhibited EGF-induced T cell lymphoma invasion and metastasis-inducing protein 1 (Tiam1) expression. Tiam1 expression is required for the second wave of EGF-induced Rac1 activation in A431 cells. Therefore, our results indicate that the 5-LOX/LTC4 /CysLT1 signaling pathway regulates EGF-induced cell migration by increasing Tiam1 expression, leading to a second wave of Rac1 activation. Thus, CysLT1 may serve as a new molecular target for antimetastatic therapy. In addition, the CysLT1 antagonist, montelukast, which is used clinically for allergy treatment, might have great potential as a novel type of antimetastatic agent.
Asunto(s)
Araquidonato 5-Lipooxigenasa/fisiología , Movimiento Celular , Factor de Crecimiento Epidérmico/fisiología , Factores de Intercambio de Guanina Nucleótido/genética , Receptores de Leucotrienos/metabolismo , Proteína de Unión al GTP rac1/metabolismo , Benzoquinonas/farmacología , Línea Celular Tumoral , Dibenzazepinas/farmacología , Activación Enzimática , Factores de Intercambio de Guanina Nucleótido/metabolismo , Humanos , Leucotrieno C4/fisiología , Inhibidores de la Lipooxigenasa/farmacología , Seudópodos/efectos de los fármacos , Seudópodos/metabolismo , Sesquiterpenos/farmacología , Transducción de Señal , Proteína 1 de Invasión e Inducción de Metástasis del Linfoma-T , Regulación hacia ArribaRESUMEN
In the course of screening for an inhibitor of farnesyl transferase (FTase), we identified two compounds, N-benzyl-aclacinomycin A (ACM) and N-allyl-ACM, which are new derivatives of ACM. N-benzyl-ACM and N-allyl-ACM inhibited FTase activity with IC50 values of 0.86 and 2.93 µM, respectively. Not only ACM but also C-10 epimers of each ACM derivative failed to inhibit FTase. The inhibition of FTase by N-benzyl-ACM and N-allyl-ACM seems to be specific, because these two compounds did not inhibit geranylgeranyltransferase or geranylgeranyl pyrophosphate (GGPP) synthase up to 100 µM. In cultured A431 cells, N-benzyl-ACM and N-allyl-ACM also blocked both the membrane localization of H-Ras and activation of the H-Ras-dependent PI3K/Akt pathway. In addition, they inhibited epidermal growth factor (EGF)-induced migration of A431 cells. Thus, N-benzyl-ACM and N-allyl-ACM inhibited EGF-induced migration of A431 cells by inhibiting the farnesylation of H-Ras and subsequent H-Ras-dependent activation of the PI3K/Akt pathway.
Asunto(s)
Aclarubicina/análogos & derivados , Aclarubicina/farmacología , Carcinoma de Células Escamosas/tratamiento farmacológico , Farnesiltransferasa/antagonistas & inhibidores , Aclarubicina/administración & dosificación , Transferasas Alquil y Aril/efectos de los fármacos , Antibióticos Antineoplásicos/administración & dosificación , Antibióticos Antineoplásicos/farmacología , Carcinoma de Células Escamosas/patología , Línea Celular Tumoral , Membrana Celular/metabolismo , Movimiento Celular/efectos de los fármacos , Factor de Crecimiento Epidérmico/administración & dosificación , Genes ras/efectos de los fármacos , Geranilgeranil-Difosfato Geranilgeraniltransferasa/efectos de los fármacos , Humanos , Concentración 50 Inhibidora , Fosfatidilinositol 3-Quinasas/metabolismo , Proteínas Proto-Oncogénicas c-akt/metabolismoRESUMEN
The aim of this study was to analyze the diversity and consistency of regulatory signaling in cancer cell migration, using a chemical genomic approach. The effects of 34 small molecular compounds were assessed quantitatively by wound healing assay in ten types of migrating cells. Hierarchical clustering was performed on the subsequent migration inhibition profile of the compounds and cancer cell types. The result was that hierarchical clustering accurately classified the compounds according to their targets. Furthermore, the cancer cells tested in this study were classified into three clusters, and the compounds were grouped into four clusters. An inhibitor of JNK suppressed all types of cell migration; however, inhibitors of ROCK, GSK-3 and p38MAPK only inhibited the migration of a subset of cell lines. Thus, our analytical system could easily distinguish between the common and cell type-specific signals responsible for cell migration.