Egr1 regulates the coordinated expression of numerous EGF receptor target genes as identified by ChIP-on-chip

UV stimulation of prostate cells causes an apoptotic response that is dependent on the zinc finger transcription factor Egr1; downstream targets of Egr1 in this response were identified

Inhibition of cell growth by EGR-1 in human primary cultures from malignant glioma

BACKGROUND: The aim of this work was to investigate in vitro the putative role of EGR-1 in the growth of glioma cells. EGR-1 expression was examined during the early passages in vitro of 17 primary cell lines grown from 3 grade III and from 14 grade IV malignant astrocytoma explants. The explanted tumors were genetically characterized at the p53, MDM2 and INK4a/ARF loci, and fibronectin expression and growth characteristics were examined. A recombinant adenovirus overexpressing EGR-1 was tested in the primary cell lines. RESULTS: Low levels of EGR-1 protein were found in all primary cultures examined, with lower values present in grade IV tumors and in cultures carrying wild-type copies of p53 gene. The levels of EGR-1 protein were significantly correlated to the amount of intracellular fibronectin, but only in tumors carrying wild-type copies of the p53 gene (R = 0,78, p = 0.0082). Duplication time, plating efficiency, colony formation in agarose, and contact inhibition were also altered in the p53 mutated tumor cultures compared to those carrying wild-type p53. Growth arrest was achieved in both types of tumor within 1–2 weeks following infection with a recombinant adenovirus overexpressing EGR-1 but not with the control adenovirus. CONCLUSIONS: Suppression of EGR-1 is a common event in gliomas and in most cases this is achieved through down-regulation of gene expression. Expression of EGR-1 by recombinant adenovirus infection almost completely abolishes the growth of tumor cells in vitro, regardless of the mutational status of the p53 gene

Comparison of Landuse in the Municipalities of Novo mesto and Mirna Peč based on municipal spatial acts

International audienceEGR1 is an immediate early gene with a wide range of activities as transcription factor, spanning from regulation of cell growth to differentiation. Numerous studies show that EGR1 either promotes the proliferation of stimulated cells or suppresses the tumorigenic growth of transformed cells. Upon interaction with ARF, EGR1 is sumoylated and acquires the ability to bind to specific targets such as PTEN and in turn to regulate cell growth. ARF is mainly localized to the periphery of nucleolus where is able to negatively regulate ribosome biogenesis. Since EGR1 colocalizes with ARF under IGF-1 stimulation we asked the question of whether EGR1 also relocate to the nucleolus to interact with ARF. Here we show that EGR1 colocalizes with nucleolar markers such as fibrillarin and B23 in the presence of ARF. Western analysis of nucleolar extracts from HeLa cells was used to confirm the presence of EGR1 in the nucleolus mainly as the 100 kDa sumoylated form. We also show that the level of the ribosomal RNA precursor 47S is inversely correlated to the level of EGR1 transcripts. The EGR1 iseffective to regulate the synthesis of the 47S rRNA precursor. Then we demonstrated that EGR1 binds to the Upstream Binding Factor (UBF) leading us to hypothesize that the regulating activity of EGR1 is mediated by its interaction within the transcriptional complex of RNA polymerase I. These results confirm the presence of EGR1 in the nucleolus and point to a role for EGR1 in the control of nucleolar metabolism

Prostate Cancer Postoperative Nomogram Scores and Obesity

Nomograms are tools used in clinical practice to predict cancer outcomes and to help make decisions regarding management of disease. Since its conception, utility of the prostate cancer nomogram has more than tripled. Limited information is available on the relation between the nomograms' predicted probabilities and obesity. The purpose of this study was to examine whether the predictions from a validated postoperative prostate cancer nomogram were associated with obesity.We carried out a cross-sectional analysis of 1220 patients who underwent radical prostatectomy (RP) in southern California from 2000 to 2008. Progression-free probabilities (PFPs) were ascertained from the 10-year Kattan postoperative nomogram. Multivariable logistic regression models estimated odds ratios (ORs) and 95% confidence intervals (CIs).In the present study, aggressive prostate cancer (Gleason ≥7), but not advanced stage, was associated with obesity (p = 0.01). After adjusting for age, black race, family history of prostate cancer and current smoking, an inverse association was observed for 10-year progression-free predictions (OR = 0.50; 95% CI = 0.28–0.90) and positive associations were observed for preoperative PSA levels (OR = 1.23; 95% CI = 1.01–1.50) and Gleason >7 (OR = 1.45; 95% CI = 1.11–1.90).Obese RP patients were more likely to have lower PFP values than non-obese patients, suggesting a higher risk of experiencing prostate cancer progression. Identifying men with potentially higher risks due to obesity may improve disease prognosis and treatment decision-making

Associations of prostate cancer risk variants with disease aggressiveness: results of the NCI-SPORE Genetics Working Group analysis of 18,343 cases

Genetic studies have identified single nucleotide polymorphisms (SNPs) associated with the risk of prostate cancer (PC). It remains unclear whether such genetic variants are associated with disease aggressiveness. The NCI-SPORE Genetics Working Group retrospectively collected clinicopathologic information and genotype data for 36 SNPs which at the time had been validated to be associated with PC risk from 25,674 cases with PC. Cases were grouped according to race, Gleason score (Gleason ≤ 6, 7, ≥ 8) and aggressiveness (non-aggressive, intermediate, and aggressive disease). Statistical analyses were used to compare the frequency of the SNPs between different disease cohorts. After adjusting for multiple testing, only PC-risk SNP rs2735839 (G) was significantly and inversely associated with aggressive (OR = 0.77; 95 % CI 0.69-0.87) and high-grade disease (OR = 0.77; 95 % CI 0.68-0.86) in European men. Similar associations with aggressive (OR = 0.72; 95 % CI 0.58-0.89) and high-grade disease (OR = 0.69; 95 % CI 0.54-0.87) were documented in African-American subjects. The G allele of rs2735839 was associated with disease aggressiveness even at low PSA levels (<4.0 ng/mL) in both European and African-American men. Our results provide further support that a PC-risk SNP rs2735839 near the KLK3 gene on chromosome 19q13 may be associated with aggressive and high-grade PC. Future prospectively designed, case-case GWAS are needed to identify additional SNPs associated with PC aggressiveness

A Gradient Boosting Algorithm for Survival Analysis via Direct Optimization of Concordance Index

Survival analysis focuses on modeling and predicting the time to an event of interest. Many statistical models have been proposed for survival analysis. They often impose strong assumptions on hazard functions, which describe how the risk of an event changes over time depending on covariates associated with each individual. In particular, the prevalent proportional hazards model assumes that covariates are multiplicatively related to the hazard. Here we propose a nonparametric model for survival analysis that does not explicitly assume particular forms of hazard functions. Our nonparametric model utilizes an ensemble of regression trees to determine how the hazard function varies according to the associated covariates. The ensemble model is trained using a gradient boosting method to optimize a smoothed approximation of the concordance index, which is one of the most widely used metrics in survival model performance evaluation. We implemented our model in a software package called GBMCI (gradient boosting machine for concordance index) and benchmarked the performance of our model against other popular survival models with a large-scale breast cancer prognosis dataset. Our experiment shows that GBMCI consistently outperforms other methods based on a number of covariate settings. GBMCI is implemented in R and is freely available online

A gradient boosting algorithm for survival analysis via direct optimization of concordance index.

Survival analysis focuses on modeling and predicting the time to an event of interest. Many statistical models have been proposed for survival analysis. They often impose strong assumptions on hazard functions, which describe how the risk of an event changes over time depending on covariates associated with each individual. In particular, the prevalent proportional hazards model assumes that covariates are multiplicatively related to the hazard. Here we propose a nonparametric model for survival analysis that does not explicitly assume particular forms of hazard functions. Our nonparametric model utilizes an ensemble of regression trees to determine how the hazard function varies according to the associated covariates. The ensemble model is trained using a gradient boosting method to optimize a smoothed approximation of the concordance index, which is one of the most widely used metrics in survival model performance evaluation. We implemented our model in a software package called GBMCI (gradient boosting machine for concordance index) and benchmarked the performance of our model against other popular survival models with a large-scale breast cancer prognosis dataset. Our experiment shows that GBMCI consistently outperforms other methods based on a number of covariate settings. GBMCI is implemented in R and is freely available online

The activation of c-Jun NH2-terminal kinase (JNK) by DNA-damaging agents serves to promote drug resistance via activating transcription factor 2 (ATF2)-dependent enhanced DNA repair.

The activating transcription factor 2 (ATF2) is a member of the ATF/cAMP-response element-binding protein family of basic-leucine zipper proteins involved in cellular stress response. The transcription potential of ATF2 is enhanced markedly by NH2-terminal phosphorylation by c-Jun NH2-terminal kinase (JNK) and mediates stress responses including DNA-damaging events. We have observed that four DNA-damaging agents (cisplatin, actinomycin D, MMS, and etoposide), but not the cisplatin isomer, transplatin, which does not readily damage DNA, strongly activate JNK, p38, and extracellular signal-regulated kinase (ERK), and strongly increase phosphorylation and ATF2-dependent transcriptional activity. Selective inhibition studies with PD98059, SB202190, SP600125, and the dominant negative JNK indicate that activation of JNK but not p38 kinase or ERK kinase is required for the phosphorylation and transcriptional activation of ATF2. Stable expression of ATF2 in human breast carcinoma BT474 cells increases transcriptional activity and confers resistance to the four DNA-damaging agents, but not to transplatin. Conversely, stable expression of a dominant negative ATF2 (dnATF2) quantitatively blocks phosphorylation of endogenous ATF2 leading to a marked decrease in transcriptional activity by endogenous ATF2 and a markedly increased sensitivity to the four agents as judged by decreased cell viability. Similarly, application of SB202190 at 50 micro m or SP600125 inhibited JNK activity, blocked transactivation, and sensitized parental cells to the four DNA-damaging drugs. Moreover, the wild type ATF2-expressing clones exhibited rapid DNA repair after treatment with the four DNA-damaging agents but not transplatin. Conversely, expression of dnATF2 quantitatively blocks DNA repair. These results indicate that JNK-dependent phosphorylation of ATF2 plays an important role in the drug resistance phenotype likely by mediating enhanced DNA repair by a p53-independent mechanism. JNK may be a rational target for sensitizing tumor cells to DNA-damaging chemotherapy agents