Microarray analysis of Ewing’s sarcoma family of tumours reveals characteristic gene expression signatures associated with metastasis and resistance to chemotherapy

2008 ◽  
Vol 44 (5) ◽  
pp. 699-709 ◽  
Author(s):  
Karl-Ludwig Schaefer ◽  
Martin Eisenacher ◽  
Yvonne Braun ◽  
Kristin Brachwitz ◽  
Daniel H. Wai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Microarray Analysis ◽  
Ewing’S Sarcoma ◽  
Ewing's Sarcoma ◽  
Gene Expression Signatures ◽  
Resistance To Chemotherapy

scholarly journals Profiling and functional annotation of mRNA gene expression in pediatric rhabdomyosarcoma and Ewing's sarcoma

2004 ◽  
Vol 110 (5) ◽  
pp. 687-694 ◽  
Author(s):  
Claudia Baer ◽  
Mattias Nees ◽  
Stephen Breit ◽  
Barbara Selle ◽  
Andreas E. Kulozik ◽  
...  
Keyword(s):  
Gene Expression ◽  
Functional Annotation ◽  
Ewing’S Sarcoma ◽  
Ewing's Sarcoma ◽  
Mrna Gene ◽  
Mrna Gene Expression

scholarly journals Microarray Analysis of Lymphatic Tissue Reveals Stage-Specific, Gene Expression Signatures in HIV-1 Infection

2009 ◽  
Vol 183 (3) ◽  
pp. 1975-1982 ◽  
Author(s):  
Qingsheng Li ◽  
Anthony J. Smith ◽  
Timothy W. Schacker ◽  
John V. Carlis ◽  
Lijie Duan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Microarray Analysis ◽  
Specific Gene ◽  
Lymphatic Tissue ◽  
Specific Gene Expression ◽  
Gene Expression Signatures ◽  
Hiv 1

scholarly journals CCT6A, a Novel Prognostic Biomarker for Ewing's Sarcoma

2020 ◽  
Author(s):  
Jie Jiang ◽  
Chong Liu ◽  
Guoyong Xu ◽  
Tuo Liang ◽  
Chaojie Yu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Ewing Sarcoma ◽  
Ewing’S Sarcoma ◽  
Ewing's Sarcoma ◽  
High Expression ◽  
P Value ◽  
Event Free Survival ◽  
Free Survival ◽  
Cox Regression Analysis

Abstract Background: Ewing's sarcoma (ES) is the second most prevalent malignancy among bone tissue tumors, and there is no adequate prognosis biomarker. The protein encoded by CCT6A is a molecular chaperone. Early studies have suggested that CCT6A is involved in the development of many cancers, however, there is no clear evidence of a role for CCT6A in ES.Methods: In this study, we performed a bioinformatics analysis of 32 Ewing sarcoma specimens from the GSE17618 dataset for differences in gene expression and overall survival, event-free survival, and gene expression in different subgroups. Results: After three screenings, we identified CCT6A as highly correlated with Ewing's sarcoma prognosis. Survival analysis showed low overall survival (OS) for CCT6A high expression (P=0.024). On the other hand, Cox regression analysis showed that CCT6A expression, event-free survival (EFS), and age were strongly associated with the prognosis of Ewing sarcoma, identified as independent poor prognostic biomarkers. (CCT6A: P=0.015; Age: P-value=0.026; EFS: P-value=0.001). Conclusion: The expression level of CCT6A is strongly associated with the prognosis of Ewing's sarcoma. High expression of the CCT6A gene may serve as a biomarker for poor prognosis in patients with Ewing's sarcoma.

scholarly journals Functional Interactions in Transcription and Splicing of Ewing’s Sarcoma

ISRN Genetics ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Roumiana Todorova
Keyword(s):  
Gene Expression ◽  
Experimental Data ◽  
Fusion Proteins ◽  
Ewing’S Sarcoma ◽  
Ewing's Sarcoma ◽  
Dna Binding Proteins ◽  
Chromosomal Translocations ◽  
Functional Interactions ◽  
Binding Partners ◽  
Rna And Dna

Ewing’s sarcoma (EWS) protein is a member of the TET (TLS/EWS/TAF15) family of RNA and DNA-binding proteins with unknown cellular role. EWS protein is encoded by the EWS oncogene on chromosome 22q12, a target of chromosomal translocations in Ewing’s sarcoma tumors. The exact mechanism of EWS participation in gene expression and pathogenesis of the resulting cancers is not defined. The binding partners of native EWS and EWS fusion proteins (EFPs) are described schematically in a model, an attempt to link the transcription with the splicing. The experimental data about the partnerships of EWS and EFPs are summarized, which may lead to better understanding of their function.

Abstract 3410: Discovery of prognostic factors in Ewing's sarcoma family of tumors by use of Intercohort co-analysis of public gene expression datasets

2010 ◽  
Author(s):  
Idriss M. Bennani-Baiti ◽  
Elizabeth R. Lawlor ◽  
Aaron Cooper ◽  
Maximilian Kauer ◽  
Jozef Ban ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prognostic Factors ◽  
Ewing’S Sarcoma ◽  
Ewing's Sarcoma

scholarly journals Small-molecule screen identifies modulators of EWS/FLI1 target gene expression and cell survival in Ewing's sarcoma

2012 ◽  
Vol 131 (9) ◽  
pp. 2153-2164 ◽  
Author(s):  
Aleksandar Boro ◽  
Kathya Prêtre ◽  
Florian Rechfeld ◽  
Verena Thalhammer ◽  
Susanne Oesch ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Survival ◽  
Small Molecule ◽  
Target Gene ◽  
Ewing’S Sarcoma ◽  
Ewing's Sarcoma ◽  
Target Gene Expression ◽  
Small Molecule Screen

Cyclin D1 and Ewing's sarcoma/PNET: A microarray analysis

2015 ◽  
Vol 117 (8) ◽  
pp. 824-828 ◽  
Author(s):  
Paolo Fagone ◽  
Ferdinando Nicoletti ◽  
Lucia Salvatorelli ◽  
Giuseppe Musumeci ◽  
Gaetano Magro
Keyword(s):  
Cyclin D1 ◽  
Microarray Analysis ◽  
Ewing’S Sarcoma ◽  
Ewing's Sarcoma

scholarly journals Identification of aberrantly methylated-differentially expressed genes and potential agents for Ewing’s sarcoma

2020 ◽  
Author(s):  
Shijie Gao ◽  
Guowang Li ◽  
Hao Yu ◽  
Shiyang Yuan ◽  
Wenxiang Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Differentially Expressed Genes ◽  
Ewing’S Sarcoma ◽  
Ewing's Sarcoma ◽  
Differentially Expressed ◽  
High Expression ◽  
Hub Genes ◽  
Low Expression

Abstract Background DNA methylation is a common epigenetic regulatory way, and it plays a critical role in various human diseases. However, the potential role of how DNA methylation impacts Ewing’s sarcoma (ES) is not clear. This study aimed to explore the regulatory role of DNA methylation in ES. Methods The microarray data of gene expression and methylation were downloaded from Gene Expression Omnibus (GEO) database, and analyzed via GEO2R. Venn analysis was then applied to identify aberrantly methylated differentially expressed genes (DEGs). Subsequently, Function and pathway enrichment analysis was conducted. Protein-protein interaction (PPI) network was constructed. Hub genes were determined. Besides, a connectivity map (CMap) analysis was performed to screen bioactive compounds for ES treatment. Results A total of 135 hypomethylated high expression genes and 523 hypermethylated low expression genes were identified. The hypomethylated high expression genes were enriched in signal transduction and the apoptosis process. Meanwhile, hypermethylated low expression genes were related to DNA replication and transcription regulation. We next determined 10 hub genes through PPI analysis, among them, C3, TF, and TCEB1 might serve as diagnostic and therapeutic targets. Furthermore, CMap analysis revealed 6 chemicals as potential options for ES treatment. Conclusions For the first time, we jointly analyzed gene profiling and methylation data about ES. The introduction of DNA methylation characteristics over DEGs is helpful to understand the pathogenesis of ES. The identified hub aberrantly methylated DEGs and chemicals might provide some novel insights on ES treatment.

scholarly journals Identification of Aberrantly Methylated-differentially Expressed Genes and Potential Agents for Ewing’s Sarcoma

2021 ◽  
Author(s):  
Shijie Gao ◽  
Guowang Li ◽  
Hao Yu ◽  
Shiyang Yuan ◽  
Wenxiang Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Differentially Expressed Genes ◽  
Ewing’S Sarcoma ◽  
Ewing's Sarcoma ◽  
Differentially Expressed ◽  
High Expression ◽  
Hub Genes ◽  
Low Expression

Abstract Background: DNA methylation is a common epigenetic regulatory way, and it plays a critical role in various human diseases. However, the potential role of how DNA methylation impacts Ewing’s sarcoma (ES) is not clear. This study aimed to explore the regulatory role of DNA methylation in ES.Methods: The microarray data of gene expression and methylation were downloaded from Gene Expression Omnibus (GEO) database, and analyzed via GEO2R. Venn analysis was then applied to identify aberrantly methylated differentially expressed genes (DEGs). Subsequently, Function and pathway enrichment analysis was conducted. Protein-protein interaction (PPI) network was constructed. Hub genes were determined. Besides, a connectivity map (CMap) analysis was performed to screen bioactive compounds for ES treatment.Results: A total of 135 hypomethylated high expression genes and 523 hypermethylated low expression genes were identified. The hypomethylated high expression genes were enriched in signal transduction and the apoptosis process. Meanwhile, hypermethylated low expression genes were related to DNA replication and transcription regulation. We next determined 10 hub genes through PPI analysis, among them, C3, TF, and TCEB1 might serve as diagnostic and therapeutic targets. Furthermore, CMap analysis revealed 6 chemicals as potential options for ES treatment. Conclusions: For the first time, we jointly analyzed gene profiling and methylation data about ES. The introduction of DNA methylation characteristics over DEGs is helpful to understand the pathogenesis of ES. The identified hub aberrantly methylated DEGs and chemicals might provide some novel insights on ES treatment.

Sign in / Sign up

Export Citation Format

Share Document