Dataset of transcriptional signature of the MAPK ERK5 in leiomyosarcoma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE297879 | GEO | 2025/06/19
REPOSITORIES: GEO
Similar Datasets
Project description:Dataset of transcriptional signature of the MAPK ERK5 in leiomyosarcoma
| PRJNA1266661 | ENA
Project description:Sarcomas are a heterogeneous group of tumors in which the role of ERK5 is poorly studied. To clarify the role of this particular MAPK in sarcomatous pathology, we used a murine 3-methyl-cholanthrene (3MC)-induced sarcoma model. Our data show that 3MC induces pleomorphic sarcomas with muscle differentiation, showing an increased expression of ERK5. Indeed, this upregulation was also observed in human sarcomas of muscular origin such as leiomyosarcoma or rhabdomyosarcoma. Moreover, in cell lines derived from these 3MC-induced tumors, abrogation of Mapk7 expression by using specific shRNAs decreased in vitro growth, colony-forming capacity, and caused a marked loss of tumor growth in vivo. Indeed, the transcriptomic profile in ERK5 abrogated cell lines by RNAseq showed a deregulated gene expression pattern for key biological processes such as angiogenesis, migration or motility, among others. Finally, among the various differentially expressed genes, Klf2, a direct target of the ERK5 pathway, is a key mediator of the biological effects of ERK5 in vitro and in vivo, as indicated by its specific interference. Therefore, our data suggest that the ERK5KLF2 signaling axis is an important determinant of 3MC-induced sarcomas and should be further studied in human sarcomas, especially those of muscular origin.
2022-08-03 | GSE199395 | GEO
Project description:In skeletal muscle differentiation, muscle-specific genes are regulated by two groups of transcription factors, the MyoD and MEF2 families, which work together to drive the differentiation process. Here we show that ERK5 regulates muscle cell fusion through Klf transcription factors. The inhibition of ERK5 activity suppresses muscle cell fusion with minimal effects on the expression of MyoD, MEF2, and their target genes. Promoter analysis coupled to microarray assay reveals that Klf-binding motifs are highly enriched in the promoter regions of ERK5-dependent upregulated genes. Remarkably, Klf2 and Klf4 expression are also upregulated during differentiation in an ERK5-dependent manner, and knockdown of Klf2 or Klf4 specifically suppresses muscle cell fusion. Moreover, we show that the Sp1 transcription factor links ERK5 to Klf2/4, and that nephronectin, a Klf transcriptional target, is involved in muscle cell fusion. Therefore, an ERK5/Sp1/Klf module plays a key role in the fusion process during skeletal muscle differentiation.
2011-02-21 | GSE25827 | GEO
Project description:Unlike other members of the MAPK family, ERK5 contains a large C-terminal domain with transcriptional activation capability in addition to an N-terminal canonical kinase domain. Genetic deletion of ERK5 is embryonic lethal and tissue-restricted deletions have profound effects on erythroid development, cardiac function and neurogenesis. In addition, depletion of ERK5 is anti-inflammatory and anti-tumorigenic. Small molecule inhibition of ERK5 has been shown to have promising activity in cell and animal models of inflammation and oncology. Here we report the synthesis and biological characterization of potent, selective ERK5 inhibitors. In contrast to both genetic depletion/deletion of ERK5 and inhibition with previously reported compounds, inhibition of the kinase with the most selective of the new inhibitors had no anti-inflammatory or anti-proliferative activity. The source of efficacy in previously reported ERK5 inhibitors is shown to be off-target activity on bromodomains (BRDs), conserved protein modules involved in recognition of acetyl-lysine residues during transcriptional processes. It is likely that phenotypes reported from genetic deletion or depletion of ERK5 arise from removal of a non-catalytic function of ERK5. The newly reported inhibitors should be useful in determining which of the many reported phenotypes are due to kinase activity, and delineate which can be pharmacologically targeted.
2016-09-09 | GSE86577 | GEO
Project description:Over the past few decades, interest in the role that extracellular signal-regulated kinase 5 (ERK5) plays in various diseases, particularly cancer and inflammation, has grown. Phenotypes observed from genetic knockdown or deletion of ERK5 suggested that targeting ERK5 could have therapeutic potential in various disease settings, motivating the development of potent and selective ATP-competitive ERK5 inhibitors. However, these inhibitors were unable to recapitulate the effects of genetic loss of ERK5, suggesting that ERK5 may have key kinase-independent roles. To investigate potential non-catalytic functions associated with ERK5, we report here the development of INY-06-061, a potent and selective heterobifunctional degrader of ERK5. In contrast to results reported through genetic knockdown of ERK5, INY-06-061-induced ERK5 degradation did not induce anti-proliferative effects in multiple cancer cell lines or suppress inflammatory responses in primary endothelial cells. Thus, we have developed and characterized a chemical tool useful for validating phenotypes reported to be associated with genetic ERK5 ablation and for guiding future ERK5-directed drug discovery efforts.
2022-10-13 | PXD036104 | Pride
Project description:Over the past few decades, interest in the role that extracellular signal-regulated kinase 5 (ERK5) plays in various diseases, particularly cancer and inflammation, has grown. Phenotypes observed from genetic knockdown or deletion of ERK5 suggested that targeting ERK5 could have therapeutic potential in various disease settings, motivating the development of potent and selective ATP-competitive ERK5 inhibitors. However, these inhibitors were unable to recapitulate the effects of genetic loss of ERK5, suggesting that ERK5 may have key kinase-independent roles. To investigate potential non-catalytic functions associated with ERK5, we report here the development of INY-06-061, a potent and selective heterobifunctional degrader of ERK5. In contrast to results reported through genetic knockdown of ERK5, INY-06-061-induced ERK5 degradation did not induce anti-proliferative effects in multiple cancer cell lines or suppress inflammatory responses in primary endothelial cells. Thus, we have developed and characterized a chemical tool useful for validating phenotypes reported to be associated with genetic ERK5 ablation and for guiding future ERK5-directed drug discovery efforts.
2022-10-13 | PXD036105 | Pride
Project description:In skeletal muscle differentiation, muscle-specific genes are regulated by two groups of transcription factors, the MyoD and MEF2 families, which work together to drive the differentiation process. Here we show that ERK5 regulates muscle cell fusion through Klf transcription factors. The inhibition of ERK5 activity suppresses muscle cell fusion with minimal effects on the expression of MyoD, MEF2, and their target genes. Promoter analysis coupled to microarray assay reveals that Klf-binding motifs are highly enriched in the promoter regions of ERK5-dependent upregulated genes. Remarkably, Klf2 and Klf4 expression are also upregulated during differentiation in an ERK5-dependent manner, and knockdown of Klf2 or Klf4 specifically suppresses muscle cell fusion. Moreover, we show that the Sp1 transcription factor links ERK5 to Klf2/4, and that nephronectin, a Klf transcriptional target, is involved in muscle cell fusion. Therefore, an ERK5/Sp1/Klf module plays a key role in the fusion process during skeletal muscle differentiation. To identify those genes whose expression levels are regulated by the ERK5 pathway in differentiating C2C12 cells, we performed genome-wide analysis by using Affymetrix GeneChip oligonucleotide microarrays. We performed two independent experiments. For each experiment, we used five samples: cells in growth medium (0 day), lacZ-infected cells at two time points (2.5 days and 4.5 days of differentiation) and dnMEK5-infected cells at two time points (2.5 days and 4.5 days of differentiation). Each virus was infected at 1 day of differentiation. Total RNA was prepared using the RNeasy Mini Kit (Qiagen) according to the manufacturer’s instructions. The total RNA of each condition was obtained from two independent experiments. Synthesis of cDNA in vitro transcription and biotin labeling cRNA, and hybridization to the Mouse Genome 430 2.0 array (Affymetrix) were performed according to Affymetrix protocols. Hybridized arrays were scanned using an Affymetrix GeneChip Scanner. Scanned Chip images were analyzed with GeneChip operating Software v.1.4 (GCOS) and GeneSpring GX 11.0.2. (Agilent technologies).
2011-02-21 | E-GEOD-25827 | biostudies-arrayexpress
Project description:ERK5 is a dual kinase-transcription factor, which contains an N-terminal kinase domain and transactivation domains in the C-terminal half. Many ERK5 kinase inhibitors have been developed and tested to treat cancer and inflammatory diseases. However, recent data have raised questions regarding the functional role of ERK5 kinase inhibitors. We aimed to investigate how ERK5 reprograms myeloid cells (MC) to the senescence-associated secretory phenotype (SASP), consequently leading to atherosclerosis. We showed that atherosclerosis was inhibited in ERK5 S496A (dephosphorylation mimic) knock-in (KI) mice. Furthermore, ERK5 S496 phosphorylation was required for not only SASP but also senescence-associated cell growth (SACG) observed in the plaque via upregulation of aryl hydrocarbon receptor (AHR). We also discovered a key effect of ERK5 S496 phosphorylation on SUMOylation at a novel site of NRF2 (i.e., K518), which inhibited NRF2 transcriptional activity without affecting ERK5 kinase activity and antagonized oxidized LDL (oxLDL)-induced SASP. Specific ERK5 kinase inhibitors (AX15836 and XMD8-92) both inhibited oxLDL-induced ERK5 S496 phosphorylation, suggesting that ERK5 S496 phosphorylation was involved at least in part of the effects of these inhibitors. We have discovered a novel mechanism, in which ERK5 S496 phosphorylation directly inhibits NRF2 activity by upregulating NRF2 K518 SUMOylation, and induces SACG and atherosclerosis.
2023-06-09 | GSE210949 | GEO
Project description:Objective: The objective of this study was to estimate the accuracy of transcriptome-based classifier in differential diagnosis of uterine leiomyoma and leiomyosarcoma. Methods: We manually selected 114 normal uterine tissue and 31 leiomyosarcoma samples from publicly available transcriptome data in UCSC Xena as training/validation sets. We developed pre-processing procedure and gene selection method to sensitively find genes of larger variance in leiomyosarcoma than normal uterine tissues. Through our method, twenty genes were selected to build transcriptome-based classifier. The prediction accuracies of deep feedforward neural network (DNN), support vector machine (SVM), Random Forest (RF), and Gradient Boosting (GB) models were examined. We interpret the biological functionality of selected genes via network-based analysis using Gene-Mania. To validate the performance of trained model, we additionally collected 35 clinical samples of leiomyosarcoma and leiomyoma as a test set (18 + 17 as 1st and 2nd test sets). Results: We discovered genes expressed in a highly variable way in leiomyosarcoma while these genes are expressed in a conserved way in normal uterine samples. These genes were mainly associated with DNA replication, cell cycle, and DNA damage checkpoint. Among evaluated machine learning classifiers, the DNN had the highest accuracy and average AUC value in training data set. As gene selection and model training were made in leiomyosarcoma and uterine normal tissue, proving discriminant of ability between leiomyosarcoma and leiomyoma is necessary. Thus, further validation of trained model was conducted in newly collected clinical samples of leiomyosarcoma and leiomyoma. The DNN classifier performed AUC of 0.917 and 0.914 supporting that the selected genes in conjunction with DNN classifier are well discriminating the difference between leiomyosarcoma and leiomyoma in clinical sample. Conclusion: The transcriptome-based classifier accurately distinguished uterine leiomyoma from leiomyosarcoma.
2023-12-13 | GSE222045 | GEO
Project description:Global gene expression analysis of inflammatory leiomyosarcoma (ILMS) and conventional leiomyosarcoma (LMS).
2013-05-22 | GSE37992 | GEO