RESUMEN
PURPOSE: To uncover the role of EZH2 and its opponent ASHL2, a polycomb and trithorax group protein, respectively, on the radioresponsiveness of glioma cell lines. MATERIALS AND METHODS: Expression of EZH2 and ASHL2 was inhibited by siRNA in glioma cell lines. The effect on histone methylation, gene expression, DNA damage repair signaling, cell cycle checkpoints, apoptosis and tumor control were evaluated. RESULTS: Inhibition of EZH2 (EZH2i) led to a transcriptional dysregulation with upregulation of 544 and downregulation of 445 genes. In comparison, ASH2L inhibition (ASH2Li) had an opposed effect with upregulation of 289 and downregulation of 970 genes. EZH2i and ASH2Li significantly reduced methylation of H3K27 and increased methylation of H3K9, respectively. EZH2i and ASH2Li significantly increased and decreased the number of residual γH2AX foci at 24 h after IR, respectively. The former significantly increased radiation-induced cell cycle arrest in G2/M and apoptotic cell death, while ASH2Li decreased both. In addition, a significant shift of the radioresponse curve by -1.22 + 0.23 Gy (p < 0.0001) in the plaque monolayer assay was found after EZH2i in A7 but not in M059K. CONCLUSION: Overall, epigenetic modulation is a promising approach to evaluate the role of chromatin structure for the radioresponsiveness of glioma cell lines.
Asunto(s)
Proteínas de Unión al ADN/genética , Proteína Potenciadora del Homólogo Zeste 2/genética , Epigénesis Genética/genética , Glioma/genética , Glioma/radioterapia , Proteínas Nucleares/genética , Tolerancia a Radiación/genética , Factores de Transcripción/genética , Activación Transcripcional/genética , Apoptosis/genética , Apoptosis/efectos de la radiación , Línea Celular Tumoral , Relación Dosis-Respuesta en la Radiación , Epigénesis Genética/efectos de la radiación , Regulación Neoplásica de la Expresión Génica/genética , Regulación Neoplásica de la Expresión Génica/efectos de la radiación , Silenciador del Gen/efectos de la radiación , Glioma/patología , Humanos , Dosis de Radiación , Activación Transcripcional/efectos de la radiaciónRESUMEN
PURPOSE: This collaboration of five established European gene expression labs investigated the potential impact of culture conditions on the transcriptional response of peripheral blood to radiation exposure. MATERIALS AND METHODS: Blood from one healthy donor was exposed ex vivo to a Cobalt 60 source to produce a calibration curve in addition to four unknown doses. After exposure, the blood samples were either diluted with RPMI medium or left untouched. After 24-h incubation at 37 °C the diluted blood samples were lysed, while the undiluted samples were mixed with the preservative RNALater and all samples were shipped frozen to the participating labs. Samples were processed by each lab using microarray (one lab) and QRT-PCR (four labs). RESULTS: We show that although culture conditions affect the total amount of RNA recovered (p < .0001) and its integrity (p < .0001), it does not significantly affect dose estimates (except for the true dose at 1.1 Gy). Most importantly, the different analysis approaches provide comparable mean absolute difference of estimated doses relative to the true doses (p = .9) and number of out of range (>0.5 Gy) measurements (p = .6). CONCLUSION: This study confirms the robustness of gene expression as a method for biological dosimetry.
Asunto(s)
Bioensayo/métodos , Proteínas Sanguíneas/análisis , Recolección de Muestras de Sangre/métodos , Perfilación de la Expresión Génica/métodos , Exposición a la Radiación/análisis , Monitoreo de Radiación/métodos , Análisis Químico de la Sangre/métodos , Europa (Continente) , Dosis de Radiación , Reproducibilidad de los Resultados , Sensibilidad y Especificidad , Método Simple CiegoRESUMEN
Developing improved approaches for diagnosis, treatment, and prevention of diseases is a major goal of biomedical research. Therefore, the discovery of biomarker signatures from high-throughput "omics" data is an active research topic in the field of bioinformatics and systems medicine. A major issue is the low reproducibility and the limited biological interpretability of candidate biomarker signatures identified from high-throughput data. This impedes the use of discovered biomarker signatures into clinical applications. Currently, much focus is placed on developing strategies to improve reproducibility and interpretability. Researchers have fruitfully started to incorporate prior knowledge derived from pathways and molecular networks into the process of biomarker identification. In this chapter, after giving a general introduction to the problem of disease classification and biomarker discovery, we will review two types of network-assisted approaches: (1) approaches inferring activity scores for specific pathways which are subsequently used for classification and (2) approaches identifying subnetworks or modules of molecular networks by differential network analysis which can serve as biomarker signatures.
